As we approach the era of quantum advantage, where quantum computers outperform classical computers for specific tasks, exploring how we can harness the potential of quantum computing and algorithms for real-world applications becomes crucial.

Among the industries eagerly anticipating the impact of quantum computing, material science and drug discovery hold immense promise. However, transitioning from quantum computational advantage to practical implementation won’t be a walk in the park and will require addressing complementary challenges. Without dedicated research into practical applications, we risk having powerful quantum computers sitting idle while companies are still unprepared to adopt them.

This article will delve into the essential requirements for quantum computers and algorithms to become useful in these fields. It will highlight the significance of focused application research in driving advancements in quantum technology.

Unleashing quantum potential In material science and drug discovery

Material science, at the forefront of innovation, presents abundant opportunities for leveraging quantum computing. By delving into the atomic and molecular levels, material scientists strive to enhance properties and functionalities. Advanced alloys, nanomaterials or topological materials are just a few examples of materials defined by quantum behavior and therefore offer exciting avenues for exploration.

Another promising industry for a quantum advantage is the pharmaceutical industry. The industry faces significant challenges in the drug discovery process, with escalating costs and time requirements. Accelerating the virtual screening of potential drugs in an expanding chemical space is imperative.

Both industries are heavy users of molecular and material simulation. Approximate solutions like density functional theory (DFT) are invaluable for exploring and designing drugs and materials and can model many desired properties. However, other simulating other chemical features can be more challenging. In material science, for example—which approximates solutions of charge transfer processes, photochemical reactions and catalytic reactions—often fails to capture the underlying quantum physics determinative for the material’s behavior. In many cases, these characteristics are defined by electron dynamics and, in some cases, strong many-electron correlations, which is notoriously difficult for classical solvers.

This is where a potential quantum advantage comes in. As we scale up the power of quantum computers, simulating electron dynamics is one area in which scientists hope for a quantum computational advantage.

Still, material scientists and pharmaceuticals aspire to understand higher-level questions such as material behavior and performance or potency and selectivity of candidate drugs. Simulating electron dynamics for small systems alone is insufficient to answer these questions. On the other hand, the genuine quantum effects that determine the behavior of some materials or molecules make quantum computers an attractive tool. Therefore, we’ll likely need a combination of quantum and classical computers and solvers to answer these questions.

The urgent need for application research

To make quantum computers useful, despite all their limitations, we must emphasize the criticality of extensive application research. Applied research goes beyond developing isolated quantum algorithms. It focuses on identifying applications that can genuinely benefit from a quantum approach and integrating quantum technologies into existing computational workflows. Note that this will not be easy. It must deal with complex matters in an interdisciplinary environment of quantum information scientists, domain knowledge experts and business owners. It must deal with the limits of today’s quantum computers while building tomorrow’s applications, all with uncertain specifications and timelines.

However, if done well, it will usher companies into the era of quantum computing. It will allow companies to benefit from quantum computers as soon as they’re available. In the first place, by developing the right capabilities and knowledge. Given the steep and interdisciplinary learning curve, companies should expect several years before becoming quantum-ready.

However, with the high pace of current developments, that time might be now. Benefits go beyond capability and knowledge development, too. Essential technologies must be developed to integrate quantum computing into workflows. Additionally, application research serves as a compass for the quantum industry. By understanding the computational requirements companies face, they can influence the direction of research and guarantee systems support industry requirements.

Conclusion

As we inch closer to quantum advantage, the pressing question arises: How do we make quantum computing truly useful? While numerous companies are exploring quantum computing, the percentage of them publishing their findings remains minimal. This highlights the urgent need for dedicated teams comprised of chemists, material scientists and computational experts to bridge the gap between theoretical advancements and practical applications. If we want to prevent the transformative power of quantum computing from going unused while companies are still getting ready, then initiating application research today is key.

This article first appeared on Forbes.com

A Q&A with Vincent de Montalivet, Principal, Data for Net Zero offer leader, and Christopher Scheefer, Vice President, North American Lead for Intelligent Industry at Capgemini

The world’s manufacturers are more connected than ever, and they simply cannot afford to be at the mercy of unreliable, insecure supply chains. Yet supply chains are among the business operations most vulnerable to outside forces and the cost can be significant, ranging from lost sales and production time to lower brand image and increased difficulty in raising capital.

Insights derived from top-quality data can help manufacturers avoid disruptions in their supply chains – or at least mitigate the effects of climate change – by making these vital operations more sustainable.

Capgemini’s Vincent de Montalivet and Christopher Scheefer talk about how they help manufacturers leverage data to transform their operations. Here, they explain how the sustainable supply chain creates financial and operational advantages even as it reduces environmental impact and mitigates risk.

What is a sustainable supply chain? Is it one that’s environmentally responsible?

Vincent de Montalivet: Environmental excellence is certainly an important part of it. Consumers, investors, and regulators are increasingly concerned about carbon emissions and other environmental issues, and companies must respect and respond to those concerns. Green supply chains are particularly important as companies make net-zero commitments and need to track their emissions across their ecosystem and the life cycle of their products. But sustainability is more than just being green. What we’re really talking about is the transformation of the supply chain beyond its traditional role in which partners work with an enterprise to design and manufacture a product and then bring it to market. The sustainable supply chain encompasses that, but then expands to cover the entire lifecycle of the product in a way that reduces that product’s impact on the environment and minimizes risks to the business. It accounts for how a manufacturer’s decisions and activities impact climate change, but also how climate change impacts the organization – in terms of both financial and organizational risks.

Can you provide an example?

Christopher Scheefer: Sure. A manufacturer buys from a partner in its supply chain that experiences a chemical spill and has to suspend business while it addresses this. From an organizational perspective, the manufacturer needs to find a new source for that chemical so it can continue to operate. But that spill could also negatively impact the manufacturer’s brand because the manufacturer is associated with that supplier. It could also have financial implications – both in terms of sales but also in the form of making it harder to attract capital from investors who are increasingly concerned about environmental, social, and governance (ESG) issues. So it’s absolutely paramount that organizations include sustainable risk analysis in their network.

That’s a greatly expanded role for the traditional supply chain, isn’t it?

Scheefer: Absolutely. A supply chain has traditionally been treated as a means to manage disruptions – for example, those caused by the COVID-19 pandemic or by international conflicts – and, in legacy supply chains, the chief procurement officer would rank members of their network primarily on time, quality, and cost.

de Montalivet: We call those the currencies of a supply chain: they’re the main criteria that companies consider as they make decisions. Now, manufacturers need to add carbon as a currency. We’re witnessing increasing risks to supply chains arising from climate catastrophes and, as we look ahead, extreme weather events are only expected to grow more frequent and more severe. So there’s a real need for companies to make their supply chains more sustainable because that also means making them more resilient.

Scheefer: In the modern business environment,manufacturers must also deal with the rise of the circular economy. Chief procurement officers now must also manage reverse logistics – for example, they must figure out how to bring a product back into the company for reuse, refurbishment, or remanufacture after the customer is finished with it. And once the product has reached its end of life, companies must be able to determine its ultimate waste footprint in order to report on its environmental performance to shareholders, potential investors, and regulators.

Those are significant changes and the supply chain of today must look very different from those of the past. What does today’s supply chain look like?

Scheefer: From a technology perspective, a modern, sustainable supply chain is intelligent and connected. The intelligence provides the manufacturer with the ability to track the priority, the commitment, and the execution of sustainability for all its suppliers, globally, at any given time. In the past that would have been impossible – but now we can apply advanced, data-driven solutions employing artificial intelligence and other leading-edge technologies to the problem. It’s still a challenge – especially for enterprises that rely upon a globe-spanning network of suppliers and sub-suppliers, distributors, and other partners. But data mastery makes it viable.

de Montalivet: Connectivity is also important. It enables the manufacturer to manage the business in a way not previously possible. For example, the supply chain can now be connected to research and development, to ensure new product designs are more sustainable. It can be connected more deeply into manufacturing, where it will have an effect on new methods, new systems, and new machinery. And connectivity enables more sustainable sourcing through marketplaces that provide a true view of the supply chain network and a true view of the organization’s exposure. AI and analytics play huge roles in this because they’re critical technologies for assessing risk on the scale we’re describing. As an aside, it’s why AI is playing an increasingly vital role in the insurance industry as that sector comes to grips with the risks associated with climate change.

Can you provide some examples of how AI enables or enhances the sustainable supply chain?

de Montalivet: The Capgemini Research Institute has identified more than 70 AI-enabled use cases related to climate action. It focused on some of the top use cases for its report, Climate AI: How artificial intelligence can power your climate action strategy. For the manufacturing sector, these include tracking greenhouse gas emissions and tracing GHG leaks at industrial sites, and improving the energy efficiency of manufacturing facilities and industrial processes. Capgemini researchers also cited a number of use cases that have direct implications for the sector’s supply chains – including designing new products that reduce waste and emissions during prototyping, production, and use, improving demand planning, reducing the waste of raw materials, and route optimization and fleet management.

Scheefer: AI-derived insights are giving decision makers the information they need to transition manufacturing away from “make to stock,” in which a company creates products and warehouses them on the assumption that a customer, eventually, will want them. It facilitates “make to order,” in which the product isn’t produced until there’s a customer for it. This confers several advantages – including eliminating waste, reducing warehousing space, and making better use of a company’s workers. At the same time, better management allows the organization to reduce water use, energy consumption, and associated emissions. All of this has implications for the supply chain as well.

How are successful companies enabling their supply chains to become more sustainable?

de Montalivet: It may sound obvious, but if an organization can’t see all of the parameters across its supply chains in real time, it’s almost impossible to optimize them in a sustainable manner.So companies that already employ a logistics control tower are off to a good start. The control tower isn’t a new concept – it’s been around for years – but it’s essential to incorporate sustainability data into it.

Scheefer: Successful companies also recognize this is a journey. Once they’ve defined and implemented a sustainable supply chain, they can then start to apply data and analytics to continuously improve it. Capgemini offers solutions that help with this. Our Data for Net Zero solution enables organizations to master data from different sources and suppliers, then share it across their business functions and value chain. Meanwhile, our Sustainable AI solution ensures that employing the computational power of AI is itself accomplished in the most energy efficient, sustainable way possible.

You obviously believe a sustainable supply chain is essential. Why?

Scheefer: We do, because the supply chain is linked to so many other aspects of a business. Well-managed, sustainable supply chains have become a transformational agent and a necessary capability. It’s absolutely essential that a company has a sustainable supply chain strategy. If the chief procurement officer is not making their supply chains more sustainable, they’re losing out. Increasingly, it’s a license to operate and should be a corporate imperative.

Continue the conversation, get in touch with us:

Vincent de Montalivet, Principal, Data for Net Zero Offer Leader

Christopher Scheefer, Vice President, North American Lead for Intelligent Industry at Capgemini

Technologies in the telecommunications industry are evolving at a dizzying speed, driving the need for automation.

From the times of old “physical” network functions (PNFs) that were updated once a year with significant effort and complex procedures, to the VNF/CNFs that are updated monthly or weekly – implementing automated processes is essential for CSPs to remain competitive.

However, the process of implementing automation across multiple functions creates its own problems in the form of costs, incompatibilities between systems, and general disorganization. What’s needed is a strategy for automating that simplifies the setup, operations, deployment, and validation of telecoms networks by introducing automation and CI/CD/CT pipelines into the telecoms world. Like Lego blocks, we need tools that make it possible to quickly construct new solutions built out of solid, proven components, saving time and reducing the risk of error. In this blog, I’ll share my experience with automation in the telecoms world.

The need for simplicity

When we started working in the automation arena, it was a different, largely physical world. When two systems needed to be connected, you could simply grab a cable and connect them. Today, all that’s done virtually. But despite these differences, our goal remains the same: simplification. No one wants a tangle of cables cluttering their office, and a virtual mess is no better. It’s one thing to automate a system; it’s something else entirely to simplify a network setup and operations and save effort and time.

For example, one of our initial projects was as simple as a connectivity setup between different network elements. The solution was to create a user interface where the source and destination IPs were introduced along with the required port. The automation engine identified all the routers and firewalls joining these two points and configured them to allow traffic flow. This wasn’t a complex activity, but we reduced the effort and time for its execution by 70 times – from hours to minutes – and freed the network engineers from a very repetitive task, avoiding many potential errors caused by human intervention.

Today, with the current 5G NF Continuous Deployment and Testing Pipelines we are implementing, we face tasks of far greater complexity. But the basic principles stay the same: analyze the process, identify efficiencies, and implement a structured and maintainable solution reusing as much as possible. That’s what we do.

Solutions should feature cloud-native technology, be based on containers, and be scalable and replicable. They should be able to connect to and include any tool, system, or application that offers an API. This architecture allows us to quickly implement any automation use case.

Beyond time and cost saving, automation brings many benefits: it’s faster than manual execution, provides reliable results, avoids human error, frees our engineers from repetitive tasks, and simplifies network operation.

Any player in the telecoms market who wants to remain competitive should introduce automation into their networks to cope with the herculean effort required to keep networks up-to-date and provide best-in-class, fast services to customers.

Architecture

The main features of an automation architecture should include:

• Dynamic GUI to provide a fully customizable graphical user interface that reduces the complexity of the network and automation components, allowing any user, even one without deep network/automation experience, to launch complex tasks and review the results in the same GUI.  
• Centralized logging system that gathers all the logs and information from the network and automation components to analyze and present the relevant KPIs and dashboard in the GUI. This service should be easy to integrate with OSS element(s) present in the target architecture.
• Centralized Notification System able to connect to any communications service (such as email, Teams, Slack, Jira, etc.) that allows the solution to contact users requesting validations, send test reports to the user who launches it, or register an incident in the appropriate system, etc.
• Integration with Traffic Generator and Commercial Testing Tools that allows the triggering and orchestration of testing from the GUI leveraging commercial test tool capabilities.

The architecture must be flexible and highly adaptable, allowing for the addition or replacement of any components according to the target environment and its technological architecture.

High-level architecture and components example

Implementation option

Our recommendation is not about commercial products – that would require a lot of effort in customization and adaptation. Rather, it is an open framework that can be tailored according to the required use case. It will remain an asset that can be maintained and further expanded by the customer. It can be also used as accelerator to launch the automation journey as a base architecture to form the foundations on which to build the automation strategy.

In this sense, different European CSPs are following this open source-based approach to drive 5G Core Network Functions deployment and validation. Pipelines are built to automatically execute the deployment and update of 5GC NFs from different vendors. Our collaboration with several of these CSPs has reduced fourfold the time needed to put an automation framework in place and automate the first NF deployment.

The short term and the long term

Automation is crucial in order to keep up with the fast-paced evolution of telecoms technologies and the increasing complexity of networks. Companies that embrace automation can streamline operations, reduce costs, and stay competitive.

Automation not only saves time and effort it also simplifies network setup and operations.  By automating repetitive tasks, organizations can free up their engineers to focus on more strategic initiatives and avoid potential errors caused by manual intervention. An open cloud-native architecture enables organizations to quickly implement automation use cases and seamlessly integrate with various tools and systems. This scalability and flexibility empower companies to adapt to changing technological environments and efficiently deliver best-in-class services to their customers.

TelcoInsights is a series of posts about the latest trends and opportunities in the telecommunications industry – powered by a community of global industry experts and thought leaders.

The 54th Annual Paris Air Show was a busy week, but a successful one for the global aerospace and defense industry.

It was impressive to see innovation on display across the civil aviation, space, and defense sectors. We witnessed a lot of conversation throughout the week around digital transformation and digital readiness as we look to the future of A&D. As we reflect on our time last week in Paris, we are already looking ahead to another event we are planning for this fall… DSEI 2023 which will be held in London from September 12-15. Digital capabilities are defined in different ways throughout A&D, so I want to take a moment to delve into the importance of a digital culture in the defense sector, why it is crucial to understand the driving forces behind this need for digital transformation, and how organizations can prepare for it.

In today’s interconnected world, relying solely on conventional defense strategies and outdated systems is no longer viable. Embracing a digital culture to better use digital technology has become essential for national and international security, as well as maintaining a competitive edge in the A&D industry.

Navigating a complex geopolitical landscape: the need for advanced defense digital capabilities

The rapidly evolving geopolitical climate has led to increasingly complex threats that, in turn, drive different needs in national and international defense. The frequency of emerging threats and pressures originating from the rising boldness of other countries, the need for consistent maritime deterrence, and the continuous advancement of terrorist abilities and goals add to the rapidly evolving security situation.

We also face challenges in other areas: resource scarcity, sustainability, and the need for efficient delivery are increasingly evident in material supply networks, workforce availability, preparedness, and long-term affordability. Intelligent industry and connectivity are not always paramount in responding to geopolitical shifts.

As a result, defense capabilities, products, and services have had to become more sophisticated, with a $2 trillion push by governments worldwide toward intelligent, connected systems and assets. From sub-surface to geostationary satellites, these systems must deliver accurate decision-making information, optimal asset performance, and availability to meet affordability, sustainability, and availability targets.

The UK government has recognized the need to modernize and integrate defense capabilities by taking a whole-force approach and increasing the use of technology and innovation. The UK Ministry of Defence (MoD) is developing a Digital Strategy for Defense that focuses on a digital backbone, a digital foundry, and an empowered digital culture. This strategy aims to prioritize funding and specialist skills to achieve greater value for money with its £4.4 billion annual digital expenditure.

Defense products are evolving to address new threats and mission priorities, becoming more sophisticated and complex than ever before. Advanced metalwork and cutting-edge carbon structures are the foundation for top-notch digital platforms.

The growing demand for connected and insight-driven services necessitates a transformation across all tiers of the defense supply chain. Embracing new internal capabilities and competencies that bridge the gap between the physical and digital worlds is essential for maintaining a competitive edge in an increasingly complex and technologically advanced landscape.

The convergence of OT and IT

Information abounds as we become more data-centric, and so it is crucial to integrate across various domains, from supply chain to battlefield. The convergence of operational technology (OT) and information technology (IT) is becoming increasingly evident, opening up new opportunities and enhancing defense capabilities.

According to a 2022 GlobalData research paper titled ‘Internet of Military Things‘ (IoMT), real-time information sharing is critical between military sectors. The report provides an overview of the market by considering the global IoT market and identifying civilian solutions that can be adapted for defense environments. These include wearables, electro-optical/infrared systems, and command, control, communications, computers, intelligence, surveillance, and reconnaissance (C4ISR) systems and infrastructure. Though estimating the market size of IoMT is challenging due to the sensitive nature of the research and development, the IoMT market was valued at $439 billion in 2019, rose to $486 billion in 2020, and is projected to grow to $807 billion by 2025, with a compound annual growth rate of 11% over the period.

As the linkages between OT and IT become more pronounced, innovative solutions emerge, enabling defense organizations to leverage the latest technological advancements.One such example is the use of digital twins, virtual replicas of a physical system, or process, that can monitor, analyze, and optimize the physical world. In a recent Capgemini Research Institute (CRI) report, researchers found 73% of A&D organizations now have a long-term roadmap for digital twin technology, and investment is ramping up, being projected to increase 40% from the previous year.

The implications of integrating IT and OT in the defense sector are far-reaching. For instance, the use of digital twins and connected systems can enable predictive maintenance, reducing equipment downtime and ensuring optimal performance. Additionally, the integration of IT and OT can enhance situational awareness and decision-making capabilities, allowing military organizations to respond more effectively to emerging threats and challenges.

As author Will Roper put it in a paper released in 2020 in line with a new digital push, this is a paradigm shift for military tech dominance: “In design, engineering, software, manufacturing, testing, and sustainment, Matrix-like simulation realism is happening: components and processes rendered so realistically they become digital twins of reality.”

Adoption and change management: defining a digital culture

The defense sector faces specific challenges when it comes to adopting new technologies and embracing change, due to its inherently slow-moving nature, security concerns, budget limitations, and general conservative outlook. However, the shift from a “need to know” to a “need to share” mindset is becoming increasingly important as the industry seeks to leverage the benefits of integrating IT and OT.

Private industries, such as Formula One, have been quicker to adopt digital technologies and engage in the digital journey. These organizations prioritize data-driven decision-making over anecdotal information, recognizing the value of real-time insights to drive performance and innovation.

For the defense industry to undergo a similar transformation, it is crucial to build trust in data and promote its adoption across all levels of the organization. When personnel understand the importance of data and rely on it for decision-making, they are more likely to actively contribute to and extract information from connected systems. Whether in new capability introduction, service or disposal, businesses must be as effective and integrated, if not more so, than the products and services their customers and end-users need. And keeping your digital culture current will attract the best new talent on the market.

As leaders and experts in the defense sector, it is essential to continuously develop our own skill sets and adapt the organizational culture to embrace digital innovation. For instance, a Chief Information Officer (CIO) might consider taking on the role of a Chief Digital Officer, driving digital transformation across the organization. Similarly, Chief Engineers and Operations Directors should incorporate digital innovation, experimentation, and development into their delivery plans, ensuring that the organization remains at the forefront of technological advancements.

By developing the necessary skills and fostering a culture of innovation and collaboration, defense organizations can overcome the unique challenges they face and maintain their dominance in an ever-evolving landscape.

Final thoughts on the Paris Air Show, and on to DSEI

Powering your digital capabilities and defining your digital culture are essential activities to stay ahead in our interconnected world, enabling the defense industry to overcome challenges, adapt to emerging threats, and remain at the forefront of innovation.

This message was prominent throughout the Paris Air Show last week, and we look forward to continuing discussions with our clients after the Paris Air Show comes to a close. We will next be present at DSEI in London from September 12-15 where our themes of connected defense and digital technology will once more be front and center. We will be at booth H1-456 and we would be honored to have to come by for a visit! We welcome the opportunity to share our views in more detail.

Expert perspectives

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Generation Z. Gen Z. “Zoomers”. Born between the late 1990s and early 2010s, Gen Z grew-up alongside smartphones, social media, and constant connectivity. They are the first digital-native generation, and they expect a consistent, seamless digital experience in every aspect of their lives. This has created a generational gap where technology is concerned, particularly with the “Baby Boomer” generation (born between 1946-1964), who are beginning to retire out of the market.

Lifestyle Spending and Saving Habits

Technological upbringing isn’t the only thing that sets them apart. Gen Z favors lifestyle spending, or “soft saving”, over aggressive saving goals. This is in marked contrast with Millennials who prefer “FIRE” (Financial Independence, Retire Early) trends in saving. Going further, the “Zoomer” generation gravitates towards immediate gratification and, particularly, “Buy now, pay later” services.

Innovative intentions, inexperienced implementation

Gen Z is also beset by a very tumultuous financial world. Macroeconomic trends like inflated real estate and education prices form a tight market. When combined with their “soft saving” habits, this uncertainty creates a lack of confidence in terms of wealth and inheritance. This has, in turn, pushed Gen Z into entirely new avenues of finance.

Increased digitalization and the expectations for personalized engagements are the foundation for the innovations that Gen Z is driving. They prefer mobile apps and online solutions rather than traditional cash or card payments. Online success stories have bolstered Zoomer’s faith in cryptocurrency and “meme stocks”, or social media fueled investment campaigns. While innovative, this reveals Gen Z’s limited knowledge of financial products.

“Gen Z respondents averaged the lowest (43%) in answering finance-related questions correctly”
– TIAA Institute and the Global Financial Literacy Excellence Center at the George Washington University School of Business.

Moreover, by 2030, it is estimated that Gen Z will inherit around $30 trillion from their parents and grandparents. This incredible sum underlines them as a vital demographic for wealth management firms and banks.

Winning Over Gen Z: Strategies for Wealth Management Firms

Education and guidance

Gen Z will need trustworthy and agile financial advisors to help them manage their inheritance. Wealth management firms must offer educational resources that cover financial literacy, investment strategies, and responsible financial practices – and deliver all these articles, videos, webinars, and workshops in a way that connects and relates to Gen Z.

Financial planning for major life events

Pursuing higher education, starting careers, buying homes, and getting married are the kinds of life decisions that necessitate financial planning for major life events. Wealth managers play a crucial role by bridging the gap between Gen Z’s dreams and their financial reality.

Impact Investing and values-based decisions

Gen Z is a socially active generation. 92% believe that helping others in need is important and prefer to associate with brands that align with their beliefs. Wealth management firms will need to adapt and offer sustainable investing options, ESG-focused portfolios, and make ethical considerations a center-point of their overall strategy.

Digital natives require digital solutions

As the first digital-native generation, Gen Z expects personalized digital solutions, user-friendly interfaces, and digital offers that cater to their expectations and preferences.

Innovation and partnerships with FinTech

Fresh approaches are necessary to meet the unique demands of this generation. They expect continual innovation and settle only for leading-edge solutions. Wealth management firms and banks must differentiate themselves if they hope to capture Gen Z’s attention. Collaboration with FinTech and embracing new business models is an imperative.

What comes next?

It’s nothing new to suggest that every generation brings with them fresh ideas, new horizons, and changing expectations. Gen Z is no exception. This new generation of clients is just beginning their financial journeys, navigating a complex world, and bringing their values with them. Understanding this, wealth management firms and banks stand to not only form valuable partnerships but drive transformation across the industry.

What Gen Z need are trusted, experienced advisors that understand finance while bringing digital solutions to the table. Looking to the future, this is a trend that will only amplify with future generations as digitalization and enhanced personalization continues to develop and branch into ever-changing digital trends. Staying ahead, maintaining a fresh approach, and providing an open-minded network of support will ensure Gen Z’s loyalty for decades to come.

I was fascinated reading the insights from Capgemini’s new edition of #innovation publication, Data-powered Innovation Review – Wave VI.

Data makes us collaborate to better understand and act on market trends, consumer behavior, and business performance.

AI augments our abilities by helping us analyze vast amounts of data, make better predictions, and automate routine tasks.

Then there’s the continuous quest to activate data for #sustainability and building a better #society.

Download the report now and deep-dive into the fascinating world of data-powered innovation, where the possibilities are as vast and diverse as the coral reefs of the ocean.