2024 is the year for scaling AI

The Capgemini RAISE™ framework signifies a new era of advancement and evolution for generative AI. It embraces the fast-evolving and highly experimental development of the technology and adapts to the rapid pace of innovation. RAISE delivers accelerators and learnings to harness the power of AI and generative AI while focusing on sustainability, scalability, and trustworthiness.

Generative AI has emerged as a groundbreaking force, democratizing innovation across industries. Open source and commercial models alike have become widely available, leveling the playing field for those eager to harness their potential.

However, as approachable as generative AI may seem, navigating its complexities is no small feat. Within just a year, the field has seen seismic shifts in paradigms and underlying technologies. Organizations are exploring generative AI, recognizing its value as a catalyst for innovation and revenue growth. The Capgemini Research Institute underscores this trend, revealing that nearly 90% of organizations plan to prioritize AI, including generative AI, in the next 12 to 18 months. The question is: are organizations ready to transition from mere exploration to achieving tangible results?

Generative AI generates new content, ideas, or solutions by learning from vast datasets. This extends from creating realistic images and text to generating code and innovative solutions across various fields.

As generative AI solutions are being constructed, decoupled development has led to redundancy and inefficiency. This disconnected approach gives rise to multiple issues: identical open-source models running on separate GPUs, increasing costs and complexity; commercial APIs used in disparate applications, preventing better vendor deals due to split volumes; and the repeated development of similar applications without performance comparison or monitoring.

The year 2023 was a time for experimentation; 2024 is the year for scaling. To address these challenges and herald a new era of development, we crafted the Capgemini RAISE™ framework to enforce sustainability, reusability, and trustworthiness throughout the code, establishing a robust AI partnership with our clients. The Capgemini RAISE™ framework streamlines the development process, ensuring that generative AI solutions are built on a solid, efficient, and cohesive infrastructure.

Exploring the Capgemini RAISE™ framework

Capgemini RAISE™ is a gateway to a future of trustworthy, scalable, and sustainable AI. While many companies concentrate on solutions, Capgemini RAISE™ shifts the focus to infrastructure – the foundation of both the service and solution layers.

Capgemini RAISE™ is built on modularization. It promotes the development and deployment of reusable components as independent services, covering an array of AI and generative AI models, tools, and data services. This includes both commercial APIs and open-source models.

At the core of the Capgemini RAISE™ framework is a uniform pipeline structure, ensuring cohesion and efficiency throughout development and deployment. It emphasizes efficient deployment of open-source models, leveraging shared GPUs for optimal resource utilization, minimizing environmental impact, and maximizing performance. Its unified management system facilitates easy comparison, efficient deployment, and thorough monitoring of both open-source models and commercial APIs, improving scalability and enabling cost savings as new models emerge.

Adaptability and experimentation are critical, as is embracing a diverse mix of technologies and staying open to future changes. As H. James Harrington noted, “Measurement is the first step that leads to control and eventually to improvement,” highlighting the importance of enforced evaluation. Such processes not only enable rapid comparison of changes in the experiment stage but also ensure smooth transitions to new ideas and models.

Capgemini RAISE™ continually identifies and builds reusable components to enhance trust, efficiency, and performance in AI and generative AI applications. Its current offerings include model cascading for cost savings, prompt optimization for performance improvement, and RAG services for scaling enterprise text retrieving service. The framework is committed to evolving and refining its services, empowering its users to embrace ultramodern technology.

Capgemini RAISE™ provides a path towards:

• Trustworthy AI, through rigorous evaluation, testing, and monitoring
• Scalable AI, by embracing modularization, DataOps, MLOps, DevOps, and governance
• Sustainable AI, focusing on cost optimization, reusability, and efficiency.

Pioneering the future

The Capgemini RAISE™ framework is setting the pace towards a future where AI’s potential is fully unleashed. This next phase in Capgemini RAISE™’s evolution is pioneering tomorrow’s innovations.

Innovative deployment and customization. The future of Capgemini RAISE™ is marked by an even greater emphasis on customization and efficiency. Leveraging the latest advancements in large language models (LLMs), Capgemini RAISE™ is poised to offer an even more refined infrastructure setup. This includes specialized pipelines for deployment, fine-tuning, and data management, designed to streamline the AI development lifecycle from conception to deployment.

Tailored data and model training. A standout feature for Capgemini RAISE™ is its enhanced capability for organizations to craft their own high-quality datasets for training or evaluation purposes. This ensures the data meets the specific needs of each project and also elevates the quality of model training. Coupled with the Capgemini RAISE™ training framework, organizations will have the flexibility to develop custom models, pushing the boundaries of what’s possible with generative AI.

Cost-effective model selection. A novel aspect of the RAISE framework is its intelligent model selection service, designed to optimize resource allocation by matching the most suitable model to each task. This reduces costs and amplifies the effectiveness of AI initiatives.

Leading the way into tomorrow

Capgemini RAISE™ is pioneering innovative solutions that address today’s challenges and anticipate tomorrow’s opportunities. As large models advance in capability, emerging agents face the challenge of dynamically decomposing tasks and choosing the right tools for completion. Capgemini RAISE™ provides these agents with an ever-growing toolbox, incorporating a comprehensive catalog of information and standardized endpoints.

We invite you to reach out. Together, let’s shape the future of AI, leading the charge into uncharted territories of possibility and success.

INNOVATION TAKEAWAYS

MODULARIZATION FOR EFFICIENCY: Break down AI development into reusable components with RAISE, optimizing resources and streamlining processes for enhanced efficiency.

TRUST AND SCALABILITY: Ensure trustworthiness and scalability in AI solutions with RAISE’s evaluation, testing, and monitoring mechanisms.

FUTURE-PROOF INNOVATION: Stay ahead of the curve with RAISE’s commitment to adaptability and customization, empowering organizations to pioneer tomorrow’s AI solutions.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 8 features contribution from leading experts from Capgemini and esteemed partners like Dassault Systèmes, Neo4j, and The Open Group. Delve into a myriad of topics on the concept of virtual twins, climate tech, and a compelling update from our ‘Gen Garage’ Labs, highlighting how data fosters sustainability, diversity, and inclusivity. Embark on a voyage of innovation today. Find all previous Waves here.

Today’s businesses are experiencing a dynamic shift as they eagerly strive to embrace generative AI to stay competitive in an ever-evolving market

Generative AI (Gen AI) is the subset of AI that focuses on the creation of new content, such as text, images, video, audio, and software code autonomously using sophisticated machine learning models called deep learning models. Though traditional AI works through machine learning to complete tasks and learn or make decisions independently, it cannot create new information.

The future of supply chains, fueled by generative AI, will transcend traditional optimization and enter a realm of unprecedented adaptability and resilience. Gen AI’s unique ability to create, simulate, and predict will revolutionize areas like demand forecasting, where it can generate nuanced scenarios based on vast datasets and real-time signals.

Gen AI will be instrumental in achieving self-healing supply chains. While traditional AI can analyze data and identify patterns to predict potential disruptions, Gen AI takes it a step further. It can create and simulate a wide range of scenarios, enabling the supply chain to proactively identify vulnerabilities and generate innovative solutions to mitigate risks before they materialize. Gen AI’s ability to create novel solutions and adapt to changing circumstances is crucial for achieving true self-healing capabilities in supply chains.

Where Gen AI departs from traditional AI

Imagine a supply chain where traditional AI acts like a vigilant guard, constantly scanning for potential threats. It might identify a potential delay in a shipment due to weather conditions, raising an alarm. Gen AI, on the other hand, is a resourceful problem solver. It takes that alarm and springs into action, not just identifying the problem but also brainstorming and generating a multitude of potential solutions. It might propose rerouting the shipment, reallocating resources to expedite other deliveries, or even proactively contacting alternative suppliers to ensure seamless fulfillment. In essence, Gen AI transforms the supply chain from a reactive system to a proactive one, where problems are not just identified but also actively and creatively solved before they disrupt operations.

Currently, 30% of supply chain leaders actively plan to deploy generative AI for supply chain in the next six months.^[i] The projection for increased adoption is driven by Gen AI’s ability to significantly reduce costs, improve efficiency, harness complex data, and increase revenue within business units that deploy the technology. Moreover, a recent Gartner survey of 127 supply chain leaders found that ‘Chief Supply Chain Officers (CSCOs) are dedicating 5.8% of their budget to Gen AI in 2024.’ The mass adoption of this emerging technology is further validated in the same report, with the finding that only ‘2% of respondents say they have no plans to leverage Gen AI.’^[ii]

Capgemini Invent recognizes the vast potential of Gen AI to revolutionize supply chains. While numerous opportunities exist, this perspective focuses on two key areas: scenario modeling and demand planning. In future communications, we will explore additional applications of this transformative technology. Additionally, we will highlight how with the right approach, businesses can unlock and scale the benefits of Gen AI.

“In the world of generative AI, supply chains will evolve from reactive systems to proactive networks, anticipating needs, optimizing resources, and seamlessly adapting to changes in real time.”

Phil Davies – Global Supply Chain leader, Capgemini Invent

Supply chain scenario modeling: a strategic perspective

In an era of unprecedented disruptions, supply chains are under immense pressure. Natural disasters, geopolitical events, pandemics, and even minor internal operational hiccups can trigger cascading effects that lead to production delays, shortages, and financial losses. In the urgent search for solutions, many business leaders are beginning to explore Gen AI’s capabilities as a means to tackle this issue.

The cost of not managing such disruptive supply chain risks effectively is immense, as evidenced by the billions of dollars lost in recent years. A recent Gartner study revealed that ‘75% of supply chain leaders expect an increase in high-impact disruptions compared to the rate of disruptions over the past 5 years.’^[iii] This highlights the urgent need for innovative solutions. For many organizations, Gen AI has proven to be invaluable in this regard.

Gen AI doesn’t just predict the future; it creates it!

Gen AI: the game-changer in scenario modeling

Scenario modeling is a crucial capability of the supply chain, enabling companies to simulate various risk scenarios and prepare appropriate responses. There is a potential for Gen AI to start leveraging models to simulate potential disruptions, companies can gain valuable insights and develop effective contingency plans.

Generative AI in supply chains can revolutionize scenario modeling by creating diverse, novel scenarios beyond historical data, analyzing unstructured sources, such as news and social media. By synergistically combining Gen AI’s generative capabilities with existing AI/ML techniques, supply chain scenario modeling can achieve a new level of sophistication. This powerful combination enables organizations to anticipate disruptions, explore innovative strategies, and make more informed, data-driven decisions, ultimately leading to improved efficiency, resilience, and adaptability in the face of ever-changing market conditions.

Gen AI will exclusively build upon the existing AI and machine learning (ML) capabilities in supply chain scenario modeling to create a more powerful and comprehensive approach. While reinforcement learning (RL), simulation modeling, and agent-based learning provide the foundation for optimizing decision-making, Gen AI is capable of so much more. Unlike traditional AI, Gen AI’s ability to process vast complex data and generate insights facilitates more comprehensive and proactive risk management in today’s supply chains. By modeling the impact of everything from equipment failures and labor shortages to geopolitical events, natural disasters, and cyberattacks, businesses can gain a deeper understanding of their vulnerabilities and develop proactive mitigation strategies.

Gen AI will democratize scenario modeling, enabling leadership to run simulations directly through large language models (LLMs), reducing the need for specialized modelers and tech developers.

The future is what we make it

Despite being its most prominent capability, this transformative technology can unlock benefits far beyond scenario modeling. In fact, Gen AI does not just predict the future; it creates it. Gen AI enables companies to stress-test their supply chains in a virtual environment, experimenting with different scenarios and responses to find the most effective solutions. This ability to “play out” potential disruptions before they occur provides a level of preparedness and resilience that was previously unattainable.

Companies that embrace Gen AI-powered scenario modeling can gain a significant competitive edge. They can achieve the following outcomes:

• Anticipate disruptions: By simulating potential risks, companies can identify weaknesses in their supply chains and take preemptive action to mitigate them.
• Optimize operations: Scenario modeling can help companies optimize inventory levels, allocate resources more effectively, and design more resilient transportation networks.
• Respond faster to crises: When disruptions do occur, companies with Gen AI models can quickly assess the situation, generate alternative scenarios, and choose the best course of action.
• Innovate and adapt: By continuously learning and adapting to new data, Gen AI models can help companies stay ahead of the curve and respond to changing market conditions.

Clearly, there are great potential benefits to integrating Gen AI for scenario and risk modelling!

Demand planning: Bridging the Gaps

Demand planning is a critical component of supply chain management that involves forecasting to ensure a company can meet future customer demand. The future of demand planning is not just about better predictions – it’s about unlocking a new level of understanding. Gen AI is not replacing current AI and ML models; it’s supercharging them. Imagine a demand planning system that does not just crunch numbers, but grasps the nuances of market shifts, consumer behavior, and global events. This is the promise of Gen AI. By synthesizing vast amounts of structured and unstructured data, it creates a dynamic, real-time picture of demand. This is not just about accuracy; it is about adaptability. Supply chains become agile, responding to disruptions with foresight, not hindsight. It is about empowering planners with insights that go beyond numbers, enabling them to make strategic decisions that drive growth and resilience.

These qualities set Gen AI apart from traditional AI capabilities that cannot generate new data or content and are restricted to analyzing existing datasets only. This enables planners to experiment with different scenarios to stress-test their supply chains and formulate optimal strategies for a variety of market conditions.

In today’s market, we are seeing Gen AI-powered demand forecasting systems improve forecast accuracy by up to 10% already by using Gen AI to predict and optimize the forecast. It incorporates market data and signals in addition to historical order and shipment information, employing a library of probabilistic and deep learning models to identify accuracy and reduce bias across product, geography, and time hierarchies.^[iv]

Gen AI presents a powerful opportunity for supply chains leaders to empower their demand planners, who can in turn guard against uncertainty and transform their supply chains in ways that will ensure they thrive despite uncertainty.

Scaling and readiness for Gen AI

As part of the Gen AI revolution, a multitude of use cases have been identified where the technology can potentially drive or unlock significant business value. However, recent research highlights that more than 85% of Proof-of-Concepts (PoCs) for Gen AI have failed to move to production. Therefore, it is crucial to thoroughly assess their feasibility, ascertain their true value, and evaluate their scalability within an organization to fully realize the associated benefits.^[v]

To support this, businesses should look to establish processes and create a shift in mindsets whereby use cases can move beyond ideation to be fully assessed, tested, deployed, and adopted to deliver value. Leaders must move away from traditional, reactive risk management approaches and embrace a proactive, data-driven mindset. Based on our experience, the following guidelines are provided as the core pillars to enable successful Gen AI in supply chain deployment.

GenAI business readiness

• Gen AI Strategizing: organizing dedicated workshops to clearly define your Gen AI strategy and identify use cases that will provide the most benefits.
• Build the right toolkit: Leverage frameworks and toolkits to develop Gen AI solutions from proof of concept to enterprise ready.
• Benefits at scale: Implement the right operating model, people, processes, technology, risk management, and controls to safely scale across the organization.

Finally, leaders in organizations will play a pivotal role in driving the adoption and implementation of Gen AI in supply chain scenario modelling. To succeed, leaders must prioritize the following actions: Championing change, defining a clear vision, and facilitating continuous improvement.

Final thoughts: The future of supply chain management

Whilst addressing two of the many supply chain opportunities in this report, it is clear that Gen AI will make an impact across the End-to End (E2E) chain. With that in mind, here are some parting considerations:

• The future of supply chain management belongs to those who are willing to embrace change and harness the power of AI and Gen AI.
• This is not just a technological challenge; it’s a leadership challenge. The companies that succeed will be those that have the vision, courage, and agility to transform their supply chains for the emerging age of AI.
• This is not just another tech trend; it’s a paradigm shift. Generative AI is democratizing access to sophisticated risk modeling capabilities, enabling even smaller companies to compete on a global scale with unprecedented resilience.

The future of supply chain management is here, and it is powered by AI and Gen AI. Leaders must seize this opportunity to transform their supply chains, ensuring they are not only resilient but also capable of thriving in an increasingly unpredictable world.

Capgemini has multiple frameworks and project blueprints to support and accelerate the development, deployment, and operation of Gen AI within supply chain. Contact our experts to learn more:

Neither of us woke up one-day thinking, ‘I want to work in aerospace and defense.’ Yet here we are, passionate advocates for an industry we stumbled into almost by accident. 

One of us started in law, consulting, and even oil and gas. The other moved from a background in telecommunications to A&D. Our journeys, though, share a common thread: the desire to be part of something bigger, something that matters. 

We often forget that idea when crafting the job descriptions, we hope will attract the best and the brightest. We expect candidates to already be passionate about our industry without telling them why they should be.

The problem isn’t the work – it’s how we talk about it. We need to show that A&D isn’t just about hardware; it’s about solving humanity’s biggest challenges.  

An industry at a crossroads 

While so many of us have discovered the hidden gem that is A&D, the industry itself is grappling with a less glittering reality.  

The A&D industry isn’t exactly known for its agility. Don’t get us wrong: aerospace is cutting-edge stuff, but many companies are held back by long development cycles, heavy regulation, and a focus on traditional hardware production. Unlike rapidly evolving sectors like software and services, A&D companies often struggle to integrate the latest innovations quickly. 

This creates a widening chasm between the industry’s talent needs and its ability to attract top candidates. Today’s emerging professionals seek dynamic environments where they can engage with cutting-edge technologies and make a tangible impact. A&D offers these opportunities in abundance yet struggles to communicate this reality to potential recruits effectively. 

The result is a talent pool that often overlooks A&D in favor of industries perceived as more innovative, despite our sector’s critical role in shaping the future. 

Global conflicts and shifting budgets only compound these challenges, highlighting an urgent need for skilled professionals in a rapidly changing landscape. 

But how do we bridge this gap? The answer may lie in one of our most basic, yet overlooked tools: our job postings. 

Our job postings don’t tell the whole story 

Imagine you’re a young professional browsing job posting, seeking a role where you can make a meaningful impact. You come across an A&D listing. Instead of being inspired, you see a dense block of text filled with KPIs, technical jargon, and rigid requirements. It’s hardly the motivational call to action you were hoping for.

The way jobs are advertised doesn’t promote the characteristics of the roles that would attract diverse candidates. Job ads need to evolve to reflect the broader impact and purpose of the roles. Rather than listing qualifications and responsibilities in dry, technical terms, job ads should tell a compelling story about the difference one can make in the industry.  

For example, instead of saying, “Requires proficiency in XYZ software and 5+ years of experience,” a job ad could say, “Join our team and use cutting-edge technology to solve complex problems that safeguard our nation and improve lives. Your expertise in XYZ software will directly contribute to innovations in defense systems that protect millions.” This approach doesn’t discard the important technical requirements but places them within an inspiring narrative. 

By showcasing how roles in A&D contribute to national security, technological advancement, and societal well-being, we can attract individuals motivated by purpose and impact while still ensuring we recruit candidates with the necessary technical skills and experience. 

Crafting new narratives  

Addressing the PR challenge 

Our industry faces a significant PR challenge amidst ongoing geopolitical conflicts and debates around defense spending. It’s no surprise some of the younger generation is hesitant to make the jump. The ethical considerations are complex, and the public perception of our work can be polarizing.  

Yet, beyond these contentious issues, our industry is at the forefront of technological advancement, from developing sustainable aviation solutions to pioneering space exploration.  

The issue isn’t that we’re behind the times – it’s that we’re not telling our story well enough. We need to shine a spotlight on the diverse, impactful work happening across A&D. This includes: 

• Highlighting roles beyond traditional engineering, such as those in environmental sustainability, data science, and digital transformation. 

• Showcasing our commitment to solving complex global challenges, from climate change to national security. 

• Emphasizing the opportunity for individuals to work on projects with far-reaching societal impact. 

• Illustrating the collaborative nature of our work, where diverse teams come together to tackle multifaceted problems. This collaboration extends to both private and public sectors. We also engage in international cooperation, working with allies and partners around the world to drive innovation and address global challenges. 

By refocusing our PR efforts, we can attract individuals who are passionate about making a difference.  

Practical steps for effective storytelling 

Effective storytelling can transform how potential recruits perceive the A&D industry. Here are some practical steps for achieving this: 

• Showcase real-world impact: Move beyond listing technical requirements. Instead, vividly illustrate how roles contribute to addressing critical global challenges. Highlight projects that have tangible effects on national security, space exploration, or environmental sustainability. 

• Appeal to purpose-driven candidates: The next generation of professionals seeks meaningful work. Demonstrate how A&D roles offer opportunities to tackle significant issues, from advancing clean energy technologies to pioneering breakthroughs in artificial intelligence for humanitarian applications. 

• Emphasize innovation and cutting-edge technology: Showcase the industry’s role at the forefront of technological advancement. Describe how A&D professionals work with state-of-the-art tools and technologies, often years ahead of commercial applications. 

• Highlight career growth and diverse opportunities: Illustrate the vast array of career paths within A&D. From engineering to cybersecurity, from project management to research and development, emphasizing the potential for diverse and evolving career trajectories. 

• Share collaborative achievements: Share stories of diverse teams solving complex problems. For instance, describe how interdisciplinary groups develop new sustainable aviation technologies or digital defense systems, showcasing both innovation and collaboration. 

• Connect to global impact: Frame roles within the context of global challenges and opportunities. Whether it’s contributing to climate change mitigation through more efficient aircraft design or enhancing global connectivity through satellite technology, emphasize the far-reaching implications of A&D work. 

Purpose-driven talent: The lifeblood of A&D’s future 

The aerospace and defense industry isn’t just competing for contracts; we’re in a global race for talent. Our future hinges on our ability to attract, retain, and nurture the brightest minds from diverse backgrounds. 

Without effectively communicating our story, we risk losing the next generation of innovators to industries that have mastered the art of self-promotion. Software companies, tech giants, and even gaming industries have captured the imagination of young talent with narratives of innovation, impact, and exciting work environments. 

Yet, the work we do in A&D is critical to global security, technological advancement, and societal progress. If we don’t get that point across, we risk having impressive technology but no one to implement the critical tasks of defending, building, and connecting the nations.  

The question then becomes: How do we craft a narrative that makes the next generation of talent say, “That’s where I want to be”?  

Learn more about Capgemini Aerospace and Defense: 

Digital Continuity in Aerospace 

Digital Twins in Aerospace and Defense 

Intelligent Supply Chain for the Aerospace and Defense Industry  

Lifecycle Optimization for Aerospace and Defense 

The Rise of Total User Experience

In the rapidly evolving world of enterprise service management, the expectations of enterprise users have undergone a significant transformation. The stark reality is that 94% of a website’s first impressions are tied directly to its design, with a preference for simplicity expressed by 41% of customers. The concept of Total User Experience (TUX) has emerged as a pivotal focus area, especially for tools like ServiceNow that are at the forefront of this change. Investing in user experience design is crucial, with studies showing that every dollar invested in UX results in a $100 return, a staggering 9,900% ROI. The modern user demands not just a functionality but an integrated, intuitive, and seamless experience that caters to their every need within a single platform. This shift represents both a challenge and an opportunity for enterprise platforms to redefine service management. 

Leaping from isolated tools to seamless integration 

Gone are the days when employees were content to navigate through multiple portals to accomplish their tasks. Today, digital transformation has set the stage for a new era where simplicity, efficiency, and convenience are not just preferred but expected. Speaking of convenience, the digital age demands mobile optimization, with 57% of customers avoiding businesses that lack a well-designed mobile site. For ServiceNow and similar platforms, this statistic highlights the urgency of ensuring mobile-friendly interfaces, as 50% of users will abandon a mobile-unfriendly site, even if they are fond of the business. 

One-stop shop for enterprise needs 

Today’s enterprise users are looking for more than just a collection of unrelated tools and platforms; they seek a cohesive, integrated experience that caters to a wide array of needs within a single, accessible interface. This underscores the necessity for platforms like ServiceNow to prioritize design that is not only appealing but straightforward, as 94% of negative feedback is design-related, highlighting the critical role of aesthetics and functionality in user satisfaction.

Raising the bar for seamless enterprise experiences 

Modern enterprise users, accustomed to the seamless experiences offered by consumer applications and platforms, now demand similar standards in their professional tools. They anticipate an ecosystem where diverse functionalities are not only available but are interconnected in an intuitive manner. They seek comprehensive IT service management, not limited to incident reporting but encompassing proactive solutions, predictive maintenance, and tailored IT advice, all within an accessible dashboard. This expectation extends to integrated human resources services, simplifying a range of processes like leave management, performance reviews, and training program participation, without the hassle of juggling multiple systems or paperwork. Additionally, the platform is expected to offer seamless facility and asset management, enabling easy reservations, issue reporting, and real-time tracking of company cars, meeting rooms, and other assets. Users also desire streamlined financial and administrative tasks, including expense reporting, reimbursements, and budget management, all achievable through this singular, integrated portal. This holistic approach aims to eliminate the need for multiple logins and interfaces, offering a comprehensive, frictionless experience across various organizational needs. 

Going a few steps beyond traditional needs 

The one-stop shop model’s ambition goes beyond just streamlining traditional enterprise operations; it envisions a comprehensive platform that encompasses wellness and work-life balance through features supporting mental health resources, wellness programs, and community engagement, all without navigating away from the platform. It aims to promote professional growth with customized learning paths, offering access to a wide array of online courses and opportunities for further education aligned with individual career objectives. Moreover, it seeks to foster a collaborative environment by integrating social tools that facilitate knowledge sharing, project management, and enhanced team interaction. 

Building platforms users love 

Integrating diverse functionalities into a single, user-friendly platform presents a complex challenge for providers like ServiceNow. However, this also opens up unparalleled opportunities to innovate and deliver a superior user experience that sets them apart from the competition. The key lies in developing a transparent yet multifunctional layout that caters to the varied needs of users.

ServiceNow as a pioneer in total user experience 

ServiceNow has been at the forefront of this transformation, reimagining how services are delivered within enterprises. By offering a cohesive platform that addresses the full spectrum of user needs, ServiceNow exemplifies how innovative solutions can meet the high expectations of today’s users, showcasing success stories that highlight the platform’s impact on enhancing enterprise service management. 

Innovations that are changing the game 

Looking ahead, the landscape of user experience is poised for transformation through several key trends. ServiceNow is expected to embrace anticipatory design, utilizing data analytics to predict and meet user needs proactively, thereby boosting efficiency and user satisfaction. A growing emphasis on inclusivity will see the integration of accessibility features, such as screen readers and high-contrast modes, ensuring compliance with standards like the European Accessibility Act and broadening user accessibility. Ethical design principles will play a crucial role in safeguarding privacy and data security, building user trust. Enhancements in user interaction will come through engaging micro-interactions and the adoption of dark mode as a default setting to enhance user comfort. The introduction of 3D designs and immersive AR/VR technologies promises more dynamic and engaging experiences, merging digital with physical realities. The role of UX designers is set to evolve, focusing on creating comprehensive experiences that go beyond the screen. Lastly, a continued shift towards simplified and minimalist interfaces will aim to improve usability and reduce cognitive load, prioritizing essential functionalities. 

The unstoppable march toward a unified user experience 

The drive toward total user experience in enterprise service management is more than a trend; it’s a fundamental shift in how users interact with digital platforms. ServiceNow’s commitment to evolving alongside the trends mentioned above not only showcases its role as a pioneer but also sets a benchmark for what’s possible in creating integrated, efficient, and enjoyable user experiences. As we move forward, the fusion of innovative design principles with technological advancements will continue to redefine the boundaries of enterprise service management, making it an exciting journey for users and providers alike. 

Quantum Computing has the potential to revolutionize many industries by solving complex challenges that classical computers cannot yet solve or that they struggle to solve (*), given the enormous computational requirements and the long time to get the needed results.  

It is important to note that not all challenges will require quantum technology. Quantum computing excels at specific types of calculations, such as optimization, cryptography, and simulating quantum systems. 

Quantum however requires revisiting current approaches to overcome limitations of current models and costly build-and-test cycles. This is the case for example in aerospace (aerodynamics), in energy transition (modelling and simulating energy storage materials, such as Li-ion batteries and fuel cells) or financial services (portfolio optimization). 

With quantum technology rapidly maturing and business benefits becoming clearer, industries now realize that quantum will play an undeniable role in solving todays and tomorrow’s specific challenges in the future.  

This quantum advantage will translate into a competitive advantage, which is why organizations are eager to embrace the quantum adoption paradox: for transformative projects that require quantum capabilities, organizations must now take explicit action towards becoming ‘quantum-ready’ in due time. This includes assessing their organization’s challenges that can be effectively addressed with quantum algorithms and identifying tasks where quantum can offer significant advantage over classical computing methods.  

As we embark organizations on this transformative journey, our preferred partnership with Pasqal, a quantum computing pioneer, is a key asset. Pasqal’s unique approach to constructing quantum processors using ordered neutral atoms in 2D and 3D arrays, a method that leverages Nobel Prize-winning technology, sets them apart in the quantum landscape. These neutral atom quantum processors offer a realistic pathway to near-term quantum advantages and provide exciting opportunity for enterprises to begin developing applications today, making them a game-changer in this technology. 

In 2023, we became a strategic investor in Pasqal through Capgemini Ventures’ CVC fund. Our investment and preferred partnership are built upon a solid collaboration since 2019 which crystallized in the EQUALITY consortium, as part of the EU’s Horizon Europe initiative. 

Capgemini quantum endeavor is fronted by our Quantum Lab focusing on applied quantum research and builds on our internal capabilities ranging from consulting to engineering as well as on interaction with our external partners such as Quantum. All this enables us to integrate world-class quantum hardware and software solutions into quantum-centric supercomputing stacks, giving enterprises a competitive advantage through an unparalleled quantum ecosystem. 

Together with Pasqal, we help organizations realize the full potential of quantum by taking quantum from R&D to production, focusing primarily on augmenting existing high-performance computing workflows. Capgemini’s role in this partnership is to provide strategic guidance and practical implementation support, accelerating the transformation and operationalizing our clients’ adoption of quantum technology.  

Our joint involvement with industry leaders like Airbus and the German Aerospace Center is a good illustration of the multiple exploratory use cases: they include battery and fuel cell design, airfoil aerodynamics, fluid dynamics, space mission optimization, materials design, multidisciplinary optimization as well as space data analysis. 

Our commitment to supporting organizations in adopting the quantum paradox towards achieving quantum value is unwavering. We truly believe that partnerships are the driving force behind innovation quantum adoption. The recently announced partnership between IBM and Pasqal is a significant step forward, and will no doubt contribute to the accelerated adoption of quantum technology. 

_{(*) The promise of unprecedented computing power to solve current intractable problems is a very attractive proposition for quantum computers. But these quantum computers also have the potential to represent a significant threat to the security of many cryptographic systems that we currently use. This issue, referred to as “Y2Q,” is anticipated to require one of the largest global migration programs affecting most of the information and communication systems since Y2K. Read more about this in our report Y2Q: A journey to quantum safe cryptography and in this article from the World Economic Forum.} 

Discover More about Pasqal and our partnership.

All debates around Gen AI made me realized that the fact that it is creativity that debate circles around (picture generation, texts, sounds, music), i.e. all that we regarded as “human” traits, and that would be the last ones to be automated.

Before that we would replace all “boring jobs”, all routine, etc. Now those jobs seem, in many cases, to be quite difficult actually.

Because they require context, common sense reasoning and often planning. Like cleaning your room. Like driving a car in Lima, Peru or Oslo. Like performing bureaucratic tasks which involves or have to adhere to laws, regulations, etc.

All this made AI to go from “technical” (give me your data and we build a model and run it, update it. full control in all processes) to something that involves language, human communication, creativity and thus sociology started to play a role. And psychology. And even geo-politics become part of the discussion.

Today I had the chance to discuss these topics at the core of Dutch politics, with Barbara Kathmann and Ufuk Esmer in the building of the “Tweede Kamer” (House of Representatives) in Den Haag. One thing we definitely agree on is that it is long overdue that there is a public debate on Artificial Intelligence, benefits, but also its place, its needs and its risks in society.

We will have a more in-depth debate tomorrow at our Capgemini Leidsche Rijn offices on this. Looking forward to it!

(And the state of the public digital services, ref picture from an information stand, really shows the need for a good vision and strategy on digital services).

With the accelerating embrace of Artificial Intelligence, financial services have a once-in-a-generation opportunity to re-imagine customer experiences. This includes hyper-personalizing contact center interactions to engage with customers in new ways. Consider the following story.

Every day since his promotion from customer service representative (CSR) to contact center manager for a global bank, Michael has faced the same challenge: Enabling representatives to deliver personalized customer service despite operating in a communications silo. Like so many financial services offering customer-facing omnichannel experiences, his institution struggles to orchestrate end-to-end experiences that encourage customers to engage in the channel of their choice while providing easy movement between those channels and equipping CSRs with the context from all those interactions.

As a financial services customer himself, Michael has personally experienced the frustration of starting a financial journey at a branch and, later, when he had follow-up questions, explaining the entire situation over the phone multiple times as he was transferred to various CSRs for answers.

As a former agent, Michael knows all too well the limitations imposed by the lack of comprehensive customer visibility. He often found himself wishing for a 360-degree view of the customer, encompassing their previous financial services interactions across various channels—whether in-person visits, phone calls, chatbot conversations, or any other channel utilized by the bank. Without this holistic perspective, Michael and his fellow agents were often forced to transfer customers to other departments or locations, prolonging resolution times and diminishing the overall customer experience.

This lack of visibility not only hampered the efficiency of the customer service process but also prevented agents from providing personalized and proactive assistance to customers, ultimately hindering the bank’s efforts to deliver exceptional service. Moreover, inadequate knowledge retrieval mechanisms and lack of real-time assistance led to delays in obtaining necessary information, resulting in frustrated customers and low satisfaction levels.

Now that Michael is a manager, he’s also thinking about how to develop and retain his team. Staff attrition poses challenges, as it typically takes months of training for a new representative to fully contribute. With contact center attrition still above pre-pandemic norms and the competition for qualified talent remaining strong, minimizing the disruptions caused by turnover is a strategic priority.

In combination, these obstacles not only impact customer satisfaction and the employee experience, but also make it harder for CSRs to offer customers the additional services that drive revenue.

The result? Yet more stress for Michael, who ponders these challenges constantly. How can he help his team overcome the lack of customer insights that prevent delivering the best experiences and address competitive pressures? How can he best engage, coach, and develop his employees?

Increasingly, the path forward is leveraging artificial intelligence for customer engagement channels.

Personalization hurdles hold financial services back

70% of a CSR’s work day is consumed by repetitive manual tasks.

As expectations for hyper-personalized customer experiences (CX) continue to grow and the macroeconomic environment fluctuates, financial services contact centers like Michael’s are increasingly called upon to improve the interactions they deliver.

This imperative is particularly acute for establishing brand loyalty and reducing churn among Gen Z customers. Early in their financial journeys, this personalization-focused generation is becoming a significant banking growth engine worldwide as it will inherit around $30 trillion from their parents through 2030.

Recognizing the importance of building a future-focused customer pipeline, financial services are including contact centers in their digital transformation roadmaps. According to Capgemini’s World Retail Banking Report 2024, 70% of bank CXOs plan to increase digital transformation investments by up to 10% in 2024.

This means tackling challenges such as:

Delivering personalized experiences to each customer: Today’s customer service expectations demand a 360-degree view of each customer, a challenge acknowledged by CSRs. Agents require easy access to comprehensive customer details and history across multiple platforms, including chatbots, apps, and social media. This necessitates robust customer relationship management systems that enable tailoring interactions to everyone’s unique needs and preferences. By empowering agents, a holistic view, financial services can improve service quality, reduce resolution times, and foster stronger customer relationships, positioning themselves as leaders in delivering personalized assistance in the modern era.

Navigating complex questions and interactions: As financial service relationships are frequently complex; CSRs must be adept and agile at rapidly understanding customer questions and answering them succinctly. To do so representatives need readily available data and timely, useful suggestions for guiding conversations. By 2026, conversational artificial intelligence deployments within contact centers will reduce agent labor costs by $80 billion.

Turning massive pools of data into insights: Although siloed customer data is a ubiquitous financial services hurdle, the challenge goes beyond connecting enormous and disparate data pools. The sheer volume of data is too great for humans to review and synthesize quickly enough to turn data into insights. AI provides a path to creating such insights in real time.

Eliminating repetitive manual processes: According to Capgemini’s World Retail Banking Report 2024, repetitive manual tasks consume about 70% of a CSRs workday, leaving only 30% for focusing on customers and just 18% for selling new products and services. Using AI-driven tools to summarize customer interactions increases accuracy and saves time, freeing staff to add value.

Overcoming staff attrition: With all the challenges front line workers face, financial services must do more to reduce turnover-related stresses. Delivering better tools to support customers increases CSR retention, as they enhance the employee experience. Such tools also provide contact center managers with capabilities for directing customer inquiries to the best available representative and enable managers to improve their coaching.

Enhancing fraud detection: Although fraud detection systems continue to improve, the Capgemini World Retail Banking Report 2024 revealed that bank employees are keenly interested in better automation for identifying suspicious data or activities. As AI-driven contact center tools can rapidly sift through multiple data pools, pinpoint anomalous behaviors, surface insights, and make recommendations in real-time, potential fraud can be uncovered early and staff alerted to act.

Ensuring continuous technology evolution: Financial services have a long history of adopting new technologies, only to have them become legacy anvils. For a modern CX solution to be effective, it must constantly evolve to solve next generation demands as they arise. Cloud-based platforms deliver continuous innovation and ensure that financial services can stay up to date with technological advancements.

Unveiling Microsoft Dynamics 365 Contact Center: The artificial intelligence tool transforming customer experience

We are seeing significant interest in and adoption of Microsoft’s contact center solutions by customers in the financial services industry, a testament to our deep investment in AI, including the integration of Nuance into our platform. We are pleased to work with Capgemini to help drive this innovation within our mutual banking, insurance, and capital markets customers.

Jeff Comstock
Corporate Vice President for Microsoft Dynamics 365 Customer Service, Microsoft

Owning massive pools of data is not the same as providing contact center staff with actionable, real-time insights. Solving this challenge requires next-generation technology that non-disruptively layers on top of existing systems to extract data from multiple silos, analyze it, apply predictive modeling, and present actionable, rapidly consumable recommendations to contact center staff. The technology must also continuously learn to hone future results.

Enter Microsoft Copilot, a cutting-edge AI-powered assistant designed to revolutionize productivity and efficiency in the workplace. Copilot leverages advanced AI and machine learning capabilities to automate routine tasks, provide real-time insights, and enhance overall user experience.

Recently, Microsoft announced Microsoft Dynamics 365 Contact Center, a Copilot-first contact center solution. This product is a standalone contact center as a service solution (CCaaS) enabling customer service teams to modernize their service experiences with artificial intelligence.

In the context of customer service and contact centers, Microsoft Dynamics 365 Contact Center plays a pivotal role by providing real-time assistance to customer service representatives (CSRs). It enhances interactions through sentiment analysis, intelligent routing, and a 360-degree view of the customer. Integrating with existing CRM systems, it provides a unified and efficient workflow with extensive scalability. By doing so, it not only improves operational efficiency but also elevates customer satisfaction through more personalized and timely responses.

As businesses increasingly adopt AI-driven solutions, Microsoft Copilots stand out as a versatile tool that adapts to various industry needs, offering scalable and customizable features that drive digital transformation and innovation.

70% productivity surge expected from generative Microsoft Copilots

Transforming Contact Centers with Microsoft Copilot: Elevating Customer Experience

In today’s fast-paced, customer-centric world, the transformation of contact centers is pivotal for businesses seeking to deliver superior customer service. Copilot is equipped with large language models (LLMs), sophisticated algorithms, and other machine learning technologies, and offers a comprehensive solution to revolutionize contact center operations. Microsoft Dynamics 365 Contact Center is a Copilot first tool, and this article explores how this can enhance customer interactions, improve efficiency, personalize experiences, and support financial services in providing dynamic solutions to their customers.

Enhanced Customer Interaction

Real-Time Assistance: Providing real-time suggestions and information to Customer Service Representatives (CSRs) during customer interactions. This ensures accurate and timely responses, significantly enhancing the quality of service.

Sentiment Analysis: By analyzing customer tone and sentiment in real-time, the pre-integrated Copilots for digital and voice channels guide CSRs on the best approach to manage conversations, leading to improved customer satisfaction.

Multichannel Support: Assisting in managing interactions across various channels such as phone, chat, email, and social media, providing a unified and consistent customer experience.

Improved Operational Efficiency and Productivity

Automated Routine Tasks: Automating repetitive tasks including data entry, call logging, and customer information retrieval. This allows CSRs to focus on resolving more complex customer issues.

Knowledge Base Integration: With quick access to and retrieval of relevant information from the organization’s knowledge base, this tool helps CSRs resolve queries faster and with greater accuracy.

Workflow Optimization: By analyzing interaction patterns and workflows to create artificial intelligence based real-time reporting, Copilot allows service leaders to enhance operational efficiency across all support teams.

Personalized Customer Experience

Customer Insights: Analyzing historical customer data to provide CSRs with insights into customer preferences, past interactions, and purchase history, enabling a more personalized service approach.

Proactive Engagement: Utilizing predictive analytics, potential issues are identified before they arise and prompts CSRs to take proactive measures, thereby enhancing customer satisfaction. Such conversation tools include sentiment analysis, translation, conversation summary and transcription.

Training and Development

Skill Development: Offers real-time feedback and coaching to CSRs, aiding continuous improvement in their skills and knowledge.

Scenario Simulation: Through the simulation of various customer interaction scenarios, this tool aids in training new CSRs, preparing them effectively for real-life situations.

Data-Driven Decision Making

Performance Analytics: Copilot generates detailed reports and analytics on CSR performance, customer interactions, and overall contact center efficiency, empowering managers to make informed decisions.

Customer Feedback Analysis: By analyzing customer feedback and interaction data, this tool identifies trends and areas for improvement, supporting strategic planning and service enhancement.

An omnichannel contact center powered by artificial intelligence will need a market-centric data layer as its foundation to ensure seamless and interconnected service across all interaction channels. Leveraging Microsoft Dataverse with Copilot will integrate the data and drive both personalized customer experience & operational efficiency.

Chandramouli Venkatesan
Vice President & Head of Customer Experience CoE, Capgemini Financial Services

Enhanced Security and Compliance

Sensitive Data Handling: Ensuring that customer data is handled securely and in compliance with relevant regulations, mitigating the risk of data breaches and compliance violations.

Fraud Detection: Monitoring transactions and interactions, detecting and preventing fraudulent activities, ensuring the security of customer accounts and information.

Application in the Financial Services Sector

For financial services, Copilot offers tailored solutions to enhance customer service:

• Personalized Financial Advice: Leveraging customer data and predictive analytics, assisting CSRs in offering personalized financial advice and product recommendations.
• Loan and Credit Processing: Streamlining loan and credit application processes by automating document verification and providing real-time status updates to customers.
• Fraud Prevention: By analyzing transaction patterns and detecting anomalies, this tool helps financial services prevent fraud and protect customer accounts.
• Regulatory Compliance: Ensuring that all customer interactions and transactions comply with financial services regulations, reducing the risk of non-compliance penalties.

Microsoft Copilots aren’t about replacing people. They’re about empowering contact center staff.

Key Steps for Successful Microsoft Dynamics 365 Contact Center Implementation

Implementing Microsoft Dynamics 365 Contact Center demands a strategic approach to ensure a seamless transition and maximize performance. Here’s a streamlined guide to achieving success:

1. Assessment and Planning
   Evaluate Current Systems and Processes: Conduct a comprehensive review of existing contact center operations, technology infrastructure, and workflows. Identify critical pain points where the pre-integrated Copilots can enhance efficiency.
   
   Define Objectives and KPIs: Of the six most critical AI copilot key performance indicators, the Capgemini World Retail Banking Report 2024 found that less than 6% of financial services have developed, and are tracking, KPIs appropriately. For transformation success, it’s imperative that financial services make KPI development and monitoring a priority. Set clear, measurable goals such as reducing average handle time and boosting customer satisfaction. Establish key performance indicators (KPIs) to track progress and success.
   
   
2. Stakeholder Engagement
   Secure Executive Buy-In: Gain executive support by articulating the benefits of Copilot, securing necessary budgets and resources.
   
   Engage Frontline Staff: Involve customer service representatives (CSRs) and managers early on to gather their input and address any concerns, ensuring their commitment to the implementation.
   
   
3. Customization and Integration
   Tailor Features: Customize pre-integrated Copilots for digital and voice channels to address the specific needs of your contact center by configuring use cases and integrating with existing CRM systems or custom apps.
   
   Seamless Integration: Ensure Copilots integrates smoothly with existing tools, minimizing disruption and maintaining workflow continuity.
   
   
4. Training and Onboarding
   Comprehensive Training Programs: Develop detailed training programs for CSRs and managers, incorporating hands-on sessions, user manuals, and support resources.
   
   Pilot Programs: Initiate a pilot implementation with a select group of users to test and refine features before a full-scale rollout.
   
   
5. Monitoring and Optimization
   Continuous Monitoring: Regularly assess Microsoft Dynamics 365 Contact Center performance using predefined KPIs, analyzing data to gauge its impact on efficiency and customer satisfaction.
   
   Feedback Loops: Establish feedback channels for CSRs to share their experiences and suggestions, using this input to make necessary adjustments and enhancements.
   
   
6. Scalability and Expansion
   Scale Gradually: Based on pilot results, progressively expand the implementation across the contact center, ensuring each phase is meticulously managed and supported.
   
   Future proofing: Stay updated with Microsoft’s latest features and advancements in AI, continuously enhancing contact center operations.
   
   
7. Security and Compliance
   Data Security: Ensure the implementation complies with data security standards, safeguarding customer data and handling sensitive information securely.
   
   Regulatory Compliance: Adhere strictly to industry regulations and compliance requirements, ensuring the ethical use of AI in customer interactions.

92% of financial services lag in developing KPIs to gauge the actual performance and accuracy of AI solutions

In the dynamic landscape of financial services, where digital disruption and evolving client expectations reign supreme, personalization is no longer a fad, but a necessity to survive and thrive. Just like a complex puzzle, each client problem represents a unique piece demanding meticulous attention to unlock optimal engagement.

The key lies in understanding the nuances of individual client needs and preferences, from their behaviors and aspirations to their pain points. To truly resonate, financial institutions must embark on a journey of discovery, piecing together a comprehensive personalization strategy that fosters deeper connections and drives meaningful engagement. However, building such a strategy requires a robust foundation.

Three crucial aspects underpin this approach, acting as those elements that work together to form the bigger picture: technology and data, the right operating model, and a culture of experimentation.

Putting together the corner pieces: User research

The initial step in crafting a robust personalization strategy begins with in-depth user research. Just as assembling a puzzle begins with finding the corner to establish a framework, developing a strategy encompassing both quantitative and qualitative inputs to thoroughly understand the users’ needs, wants, and aspirations provides the framework for the personalization strategy. Quantitative research, like customer surveys and website analytics, acts like those corner puzzle pieces, providing the basic framework. It reveals trends in demographics, preferences, and behaviors, allowing you to grasp the “what” of your customer base. However, to truly understand the “why” behind the numbers and create a personalized experience that resonates, qualitative research becomes the essential edge piece. Through in-depth interviews, focus groups, and user testing, you gain invaluable insights into your customers’ emotions, motivations, and aspirations.

Discovering the unique pieces: Identifying distinct client archetypes

Creating distinct client archetypes (personas) can refine the personalization process, by providing a clear understanding of various aspects such as target audiences, investment preferences, risk tolerance, and financial goals. This approach adds depth and dimension to the framework, akin to finding unique puzzle shapes that fit together perfectly. For example, a young professional saving for a first home will have different needs and expectations compared to a retiree managing their nest egg. Aligning your user research with these personas ensures that your strategy resonates with each distinct segment of your target audience.

Revealing the bigger picture: Creating personalization concepts based on customer needs and wants

With the blueprint of client archetypes, financial service providers enter the phase of crafting personalized experiences. This stage mirrors placing puzzle pieces strategically, each aligning with the bigger picture to form a complete image. Here, the focus shifts from understanding to action, translating research insights into tangible personalization concepts. These concepts should address the specific needs and desires of each customer segment. Designing bespoke puzzle pieces for each archetype ensures they seamlessly fit into the overall picture while adding a unique touch that resonates with individual preferences. For instance, a young professional saving for their first home might benefit from personalized savings tools and educational resources on mortgage options, while a retired investor might appreciate tailored investment recommendations and wealth management strategies. By creating such targeted concepts, financial institutions cater to the specific puzzle pieces representing each customer’s unique financial journey.

The 3 crucial elements: Technology and data, operating model, and a culture of experimentation

To unlock the power of hyper-personalization at scale, three crucial elements demand your attention: technology and data, the right operating model, and a culture of experimentation. By focusing on these core elements financial institutions can build a strong foundation for their personalization journey. Technology and data empower financial institutions to gather deep client insights, enabling them to tailor experiences and offerings. Conducting a tech and data assessment is akin to sorting your puzzle pieces. It helps identify the strengths and weaknesses in your content, decision-making tools, cross-channel orchestration, and overall data strategy. Similarly, the right operating model acts as the glue that binds the puzzle pieces together. To achieve a truly personalized experience at scale, the operating model of an organization should be holistically aligned to a customer-centric approach. Finally, a culture of experimentation is akin to having a diverse pool of puzzle pieces. It encourages exploring new ideas, testing different strategies, and iterating based on results.

Piecing the complete puzzle together: Change management and value realization

Crafting a winning personalization strategy involves meticulous implementation of concepts, effective change management, and value realization. This entails comprehensive rollout plans, clear communication, and ongoing support for successful adoption. Change management ensures stakeholders embrace the new approach, akin to a coordinated team assembling a puzzle. Yet, the journey doesn’t end there. Consistent measurement and value realization are crucial for unlocking personalization’s true potential. Organizations should develop a value realization framework that is aligned with their key business objectives. Monitoring and analyzing these metrics ensure ongoing value delivery and enhanced customer experiences. By methodically addressing each aspect of the puzzle, you can create a comprehensive personalization strategy that not only meets but also exceeds client expectations. This way, your organization can become more customer-centric, foster deeper connections, and ultimately, unlock the true potential of personalization in today’s dynamic financial landscape.

Traditional asset management is technology-challenged

Traditional asset management investments and opportunities rely on traditional technology solutions to support them – but the asset management industry has to move forward, evolution to meet changing investor expectations and needs is an imperative. There are now increasing opportunities to adopt new technology to solve for many inherent traditional challenges:

• Inefficient processes: Traditional asset management involves manual, time-consuming processes such as paperwork or regulatory compliance
• Limited transparency: Asset ownership, performance, and valuation is often opaque.
• Restricted transferability: Traditional assets can be subject to restrictions on transferability.
• Limited access to larger investor pools: Investor pools are often limited to high-net-worth individuals.
• Illiquidity: these types of Traditional types of assets are owned by smaller pools of investors and are often difficult to turn into liquid assets.

New standards in technology and the adoption of modern technology solutions can support improved efficiency, increase transparency, streamline the transfer process, and increase the pool of investors in asset management.

Tokenization solutions support the evolution of asset management

Advancements in technology and growing demand for more accessible, transparent, and efficient investment solutions is driving the evolution of asset management. The digitization of assets through tokenization is a key factor driving this transformation and enables even more new opportunities for investments. To support this transformation, several technological solutions have emerged, including blockchain and smart contracts. These technologies work together with the application infrastructure to create an integrated ecosystem.

Key considerations for technology behind tokenization

The move to web3 technologies to support digital asset management involves many of the typical considerations already present in modern, cloud-based, and regulated environments; some new elements are important, too. Consider the following:

• Security: Ensuring the security and integrity of digital assets and transactions is a top priority in tokenization.
• Scalability: As tokenization gains traction, the volume of digital assets and transactions will grow, and technology solutions should be able to scale seamlessly without compromising performance or security.
• Interoperability and Integration: The ability to interact with different systems, platforms, and protocols is essential to adopt tokenized asset management. Technology solutions should support interoperability, enabling cross-platform communication and data exchange.
• Compliance: Compliance with laws and regulations is critical when implementing tokenization technologies. Solutions should enable automation of compliance processes and provide features that facilitate adherence to regulatory requirements.
• Confidential compute: For these workloads, it is important to adopt compute infrastructure which can be trusted to maintain security throughout the execution of the workload’s functionality.

These requirements should be evaluated and incorporated in the definition of the tokenization architecture to ensure successful implementation and adoption.

Critical elements for successful tokenization solutions

Given critical architectural considerations, what key components should be adopted to achieve optimal tokenization outcomes?

Blockchain

Blockchain provides advantages over traditional solutions for ledgers and the tokenization of assets: it can reduce the need for traditional custodial services, promote greater transparency and trust, streamline operations of investment funds, and reduce commission and intermediary costs. Two major benefits of utilizing blockchain as a core technology for tokenization are the possibility of decentralized consensus mechanisms and cryptographic hashing:

• By decentralizing consensus mechanisms, transparency and trust is increased because the transactions are recorded in the ledger, and multiple parties are involved in the settlement of transactions.
• Cryptographic hashing is valuable in this digitization process because it provides a tamper-proof digital representation of the asset, enabling fractional ownership, liquidity, and interoperability.

Smart contracts

Smart contracts are a valuable component of a tokenization solution because they can be used to execute intelligent automation within a blockchain transaction for the assets that have been tokenized. Such automation can support multiple capabilities and may include dividend payments, interest calculations, compliance, reporting, and other operational functions.

These smart contracts can improve operational inefficiency by automating workflows, standardizing information sharing, streamlining asset servicing, and reducing or eliminating the need for dealer intermediaries.

Leverage Microsoft technologies to support tokenization solutions

Microsoft technology solutions support the transition to tokenization within asset management. We provide a full range of world-class infrastructure solutions – from identity and access management to security to trusted compute. Several of these capabilities are summarized below.

Microsoft Entra Verified ID

Microsoft Entra Verified ID is a managed verifiable credentials service. It is an extension of open standards for identity verification, enabling privacy-protected interactions between organizations and users. Because tokenization solutions require interoperability and reusability, these identities are an excellent technology selection. Identities that are onboarded to Microsoft Entra Verified ID are digitally verified to ensure trustworthy self-service and faster onboarding

Azure Confidential Ledger

Azure Confidential Ledger utilizes the Azure Confidential Computing platform, coupled with the Confidential Consortium Framework, to provide a high integrity solution that is tamper protected. It runs on hardware-backed secure enclaves, which is a heavily monitored and isolated runtime environment.

Security tools

Security services are crucial to any successful infrastructure and software solution. From application configuration secrets to encryption to cyber protection to security monitoring, there are numerous services that can help enable cybersecurity health.

• Azure Key Vault is a cloud service for securely storing and managing cryptographic keys, secrets, and certificates. It helps to safeguard private information used in the software solutions that are produced to service tokenization.
• Azure Confidential Computing enables data protection through the use of hardware-based trusted execution environments. Software that is executed on Azure Confidential Computing resources is performed in a secure and isolated environment, which prevents unauthorized access to the data while it is being processed.
• Azure Security Center is a comprehensive security management and threat protection service enabling security posture evaluation and strengthening. Additionally, security assessments, advanced threat detection, and security alerts can be configured for Azure resources.

Reference architecture

Cloud service providers have revolutionized the management, utilization, and operation of infrastructure on demand. Companies across the financial services industry have made major strides in adopting this technology to improve the scalability, security, resiliency, high availability, and predictability of technology solutions. Microsoft has several service offerings that support the implementation of next-generation tokenization of assets.

Figure 1. Conceptual diagram representing infrastructure utilizing Azure services

A solution built on Microsoft Azure infrastructure is able to support multi-party implementation for node operators. It can incorporate numerous critical aspects needed to meet the demands of a modern digital asset management solution; these include global presence and availability; a secure hub; a scalable, reliable, and resilient core; and a flexible supporting cast of services for connectivity, security, interoperability, and storage of data.

• In this reference architecture, infrastructure is deployed to Azure to support the software operations. The global entry point for the infrastructure is using Azure Front Door which is a highly available, low latency, scalable, and secure solution as a secure perimeter across the globe. Web Application Firewall policies can be applied to secure OWASP vulnerabilities.
• Once the traffic has reached the private network, it is further filtered via secure hub leveraging Azure Firewall. Azure Firewall provides Layer 3 to Layer 7 traffic filtering and threat intelligence feeds from Microsoft Cyber Security.
• The reference architecture also has a core infrastructure tailored to the tokenization solution leveraging Azure Kubernetes Service (AKS); this is a managed solution that can be deployed within Azure to reduce complexity and operational overhead of self-managed clusters. AKS is Cloud Native Computing Foundation (CNCF) certified and Service Organization Control (SOC), International Organization for Standardization (ISO), and Payment Card Industry Data Security Standard (PCI DSS) compliant.
• In addition to AKS, additional services can be flexibly integrated into the reference architecture. For tokenization, a valuable service to incorporate is Azure Storage for Blobs and utilizing Write Once, Read Many (WORM). Another service that is crucial for security is Azure Key Vault, for the storing keys, secrets, and certificates.

The architecture can serve as a foundation for building advanced tokenization solutions leveraging secure, scalable, compliant, interoperable solutions on blockchain using smart contracts.

It’s time for next-gen tokenization in asset management

The use of new technologies is essential to the development of a complete and successful strategy for digital asset management: blockchain, smart contracts, and other web3 technologies accelerate the adoption of digital asset management solutions, including tokenization. Microsoft Azure can help accelerate innovative use cases across the asset management industry: now is the time to explore what makes best sense for your organization.

As July approaches, our excitement is building for the upcoming Farnborough International Airshow (FIA). Once again, Capgemini eagerly anticipates participating in this premier event. With our longstanding involvement in the A&D industry, we view these airshows as invaluable opportunities to engage with clients, network with industry peers, and gain insight into the latest advancements shaping the future of the industry.

The headline for this year’s show is “the apex of aviation” which is a timely theme. The future may seem daunting to some as a myriad of challenges confront us, but we also have more tools and technologies than ever to tackle those challenges. This year’s airshow is an opportunity to assess where we are, how far we’ve come, and where we’re going.

The industry continues to emerge from the impact of the pandemic, faced with ongoing issues impacting production and supply chains. In addition, there are increasing environmental and regulatory pressures to address. Thankfully, with challenges come opportunities. FIA allows the industry to come together and share knowledge, best practices, and innovations that can help A&D leaders shape the future as a community.

As we thought about our presence this year, we recognized that collaboration is at the heart of how we engage with our clients. Through collaboration, we can ideate, brainstorm, share best practices, and look for collective solutions. We can even debate and compete, allowing for standards to be set and surpassed. Collaboration accelerates innovation, leading all of us within the industry to strive for solutions of the highest of standards that benefit our collective future.

We recognize that organizations need to innovate and collaborate to remain competitive in today’s complex ecosystem. We need to deliver cheaper, faster, and more sustainably. At FIA, we will be focused on six areas that we believe are the top priorities for today’s organizations.

Artificial Intelligence

Real intelligence drives artificial intelligence. Behind every AI system are the experts who design and refine the technology. It is only as effective as the people that power it and use it. Today’s organizations can benefit greatly from the power of AI but only when implemented ethically and securely.

Connected Aerospace and Defense

Connecting systems and programs for the transfer of data may seem intuitive, but it takes strategic thinking and collaboration across the business. Being “connected” means you are joined, attached, and united. It takes collective thinking to develop and implement a connected A&D strategy. We help enable seamless connections and facilitate the exchange of insights among people and ecosystems, laying the groundwork for innovation and a successful strategy for the future. We also tap into our network of partners to identify technologies, from Cloud to AI to 5G, to deliver optimal solutions.

Digital Continuity in Aerospace and Defense

Organizations are looking to implement digital continuity principles to achieve a consistent process and a reliable source of data that can be shared across the organization. Unified data throughout the product, process, and resource lifecycle can trigger predictive and prescriptive services, giving organizations access to innovative and more flexible business models to conquer new markets. Digital continuity is not just a single process, however. It is an enterprise-wide transformation that requires communication and connectivity throughout the organization.

Net-Zero and Circular Economy

There has never been more urgency around sustainability for A&D than there is today. We work with organizations to identify the most pressing issues impacting the path to an effective sustainability strategy. We recognize all aspects can’t be addressed at once, so we focus on specific issues that are at the core of your sustainability strategy. Implementing even the smallest change can lead to a positive impact.

Production Ramp-Up and Supply Chain

Many industries continue to face supply chain issues post-pandemic, the A&D industry was probably hit the hardest. It has been a lesson in the critical role of the supply chain as a strategic asset. Our industry needs to accelerate production and synchronize the entire value chain due to unprecedented demand. An advanced supply chain architecture, what we call an ‘ intelligent supply chain’, can play a crucial role in meeting the increasing demand for aerospace and defense products while supporting ambitious environmental targets.

Talent

The industry is evolving at a rapid pace, not just technologies but the people who develop and implement them. Today’s talent, and especially tomorrow’s new hires, need to be vested in their careers and their organizations. That means providing the tools they need to be ready on day 1, and the learning and development needed to enhance the existing workforce. Technology doesn’t run companies, people do.

We exist in a time when we have access to the ingenuity, innovation, and technologies to transform operations, build resilience, and embrace new and creative ways of addressing A&D’s biggest challenges. At Capgemini, we’re able to help organizations collaborate internally by connecting strategy, with technology, and delivery.

Learn more:

Digital Twins in Aerospace and Defense

Intelligent Supply Chain for the Aerospace and Defense Industry

Lifecycle Optimization for Aerospace and Defense