From fiction to fact

Science fiction films and novels have long painted a future complete with multi-functional robots, “augmented” men and women who enhance their human capabilities, and autonomous machines that take control and govern the world.

 These futures – while often dystopian in nature for dramatic effect – have familiarized us with the idea of a world where smart technology can do everything. That future is now becoming reality.

Yet far from presenting a threat to humans flourishing, new uses of technology are emerging every day that are changing how we live and interact with the world for the better.

Specifically, technology pioneers are focusing unprecedented financial resources towards developments in artificial intelligence (AI).

These developments – such as satnavs that help us navigate from A to B, or apps that recommend a film we might enjoy, or fitness trackers that monitor our health and wellbeing – are designed to enhance our lives, give us more time in our day and liberate us from mundane tasks where we so choose.

We have the power

AI has a long history of theory and research behind it. Yet there have always been computational limitations that have constrained its progress.

We’re now at a point where technology is powerful enough, and accessible enough, to bring 70 years of thinking and ideas about AI to life.

It’s a new age for humankind and for business, turning imagination into reality and opening up all sorts of possibilities.

Over the following pages, we’ll consider:

• Artificial intelligence: from theory to reality – looking at where AI started and how far the developments have come.
• Intelligence for all – the concepts that are driving the widespread adoption of AI.
• An enabler of progress – what we know for certain about AI and its direction of travel.
• Reshaping old models – the opportunity AI brings to change how businesses operate.

Artificial intelligence: from theory to reality

1950 – Alan Turing designed a test of a machine’s ability to “exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.”

1955 – McCarthy, Minsky, Rochester, and Shannon predicated that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”

Therefore, it is clear that AI has a long and respected history. Significant advances have been made possible by a coming together of multiple disciplines – mathematics, statistics, computer science, biology, biotechnology, neuroscience, and cognitive science. After decades of fundamental and applied research, hundreds of billions of dollars of investment and the widespread adoption of computer technology, we are starting to see an “overnight sensation.”

Intelligence for all

AI encompasses many technologies, diverse in their type and nature. Yet common to them all is one aim, to simulate the functions that make us “intelligent”: our abilities to observe, remember, analyze, communicate and act.

We think of these as the “five senses of intelligence” – and we’ll explain how businesses can use them as a framework for adopting AI solutions in a separate article.

Pioneers of progress

The significant computing power now available via the cloud has accelerated the development of real-world AI solutions. Companies can experiment like never before, and process huge data volumes without heavy investment in on-premises IT by renting computer resources “as a service”. This provides them with the agility to fail safely often and learn quickly, adapting and evolving at an extraordinary pace.

The stage is set

Today’s upsurge in AI development can be viewed as decades of ideas and work finally bearing fruit. Thanks to improved communication networks, increased processing power and huge storage capacity, which is more affordable and accessible than ever, we have the ideal conditions for AI to thrive.

An enabler of progress

There are, of course, well-publicized concerns about the increasing adoption of AI by businesses and organizations.

Philosophers, sociologists, anthropologists and many people of influence have been theorizing on the future of work and employment – questioning the role of humans in a world where robots can perform not just simple manual tasks, but more complicated work as well.

AI shouldn’t be seen as a threat, but as an enabler of human progress. Today’s AI technologies are embracing every human activity and helping us rethink how we live our lives for the better.

As budgets rise for AI and robotics research across the globe, we’re seeing the birth of new opportunities. It is shifting the focus from learning and training to imagination and creativity, allowing everyone and anyone (not just the technologists) to contribute valuable ideas that enhance customer experience, employee satisfaction, and people’s lives.

Reshaping old models

Established businesses, in their current form, are the product of a bygone age – and the emergence of AI is bringing about the need for radical change.

Most managerial and organizational models in place today were inherited from the early industrial revolutions.

Despite the tremendous progress made in workplace tools, training and qualifications, these models have remained virtually unchanged and inflexible.

As such, people find it difficult to pursue their own aspirations at work, even when encouraged to be more creative, independent and enthusiastic.

Adapting to a new normal: hyperintelligence

As businesses embrace today’s Artificial Intelligence revolution, there is the

opportunity to reshape organizational models completely.

We can be less concerned with who does and knows what, human or machine, in a quest for efficiency. We can focus instead on empowering people to work together with AI. The scale and speed of today’s technology removes the constraints of previous eras, allowing people to bring all sorts of new skills and ideas to the table.

This alliance will move businesses to a state of “hyperintelligence” – where human intelligence, innovation and imagination is liberated and enhanced by technology. Ultimately, this will raise the value and effectiveness of everything a business seeks to do.

In our next article, we’ll demystify AI by introducing a framework that maps and compares its components to the five senses of human intelligence.

This will explain how today’s AI solutions are the simple coming together of different technologies that mimic how humans observe, remember, analyze, communicate, and act.

We’ll look at how a lot of these technologies are already very familiar to us, and therefore how businesses can deploy them easily without deep technical expertise to improve services, enhance customer experiences and transform the workplace.

AI must be made accessible to everyone

Artificial intelligence (AI) brings new opportunities to all areas of an organization.

Capitalizing on it requires a full commitment across all business functions. It must be embraced by everyone, not just technologists.

All too often though, AI is viewed as complex or mysterious.

So, how do you begin building artificial intelligence into your business and engaging with the whole workforce to optimize and release its benefits?

In this article, we outline a simple framework that compares the components of artificial intelligence to five senses of human intelligence – an approach that makes AI accessible to everyone in the business, enabling the organization to release the full value of an intelligence-first approach to transformation.

Creating a framework to facilitate understanding

Inside the brain of a human

As humans, we make sense of the world using a combination of different cognitive functions:

• Attention – the state of observation and alertness that allows awareness of what is happening in the environment (Ballesteros, 2000).
• Memory – the retention of information over time for the purpose of influencing future actions (Sherwood, 1995).
• Language – the production of spoken or written signs that symbolize objects, ideas, etc. (Lecours et al. 1979).
• Praxis – learned motor activity and the generation of volitional movement for the performance of a particular action or towards achieving a goal (NeuronUp).
• Executive functions – required for planning, organizing, guiding, revising, regulating and evaluating behavior necessary to adapt effectively to the environment and to achieve goals (Bauermeister, 2008).

When these cognitive functions interact, we demonstrate human “intelligence.”

Inside the brain of a business

An artificially intelligent business or organization requires similar functions:

• The ability to monitor an environment and activities – i.e., attention.
• The capacity to retain and organize data in the form of knowledge – i.e., memory.
• The ability to communicate and interact – i.e., language.
• The execution of actions and operations – i.e., praxis.
• The capacity to process and analyze knowledge – i.e., executive functions.

We refer to these functions as the “Five Senses of Artificial Intelligence.” When they are combined appropriately, they enable organizations to transform themselves.

Applying the framework to deliver transformation

Applying this concept provides a framework to visualize traditional activities in a completely new way that allows you to reimagine them. It allows innovation and creativity to take advantage of AI technologies by establishing a human metaphor for machine activities.

Stage 1

The first step is to identify activities that will have the greatest benefit to your business. The identification of these activities will help you understand the key differentiators in your business and where there are opportunities for significant competitive advantage.

The objective is not just about reducing cost by applying lean principles to redesign business processes. It is to apply design thinking to deliver better, more effective and efficient outcomes.

What is design thinking? “A human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Tim Brown, CEO, IDEO Design thinking is therefore a method that focuses on the three main elements of a product or solution – people, technology and business – all of which evolve around the customer.

Stage 2

This step is about mapping the people, processes, and technology to the framework. It is also vital to establish why this activity is performed and how improvements will benefit the organization. This creates the basis to allow design thinking.

You should clearly define how you will measure the improved outcomes and their impact on the organization. We’ll revisit this point in a future article.

The five senses framework informs and enables the reimagining of traditional activities.

Stage 3

The final step is about reimagining your activities. You should involve a team of people with a broad mix of seniority and experience. It should include, but not be limited to, knowledge on existing and new technologies, processes, and business needs. This will lead to richer solutions and facilitate unexpected synergies.

Adopt an AI-first approach that explores and investigates new technologies mapped to the five senses. As an example, watch how intelligent automation is radically transforming traditional finance operations like procure-to-pay and credit-to-cash.

During this step, it’s important to test how your new technologies interact with each other, and with people and processes, to deliver better outcomes. Connecting each of the senses creates the intelligence!

Using design thinking and AI-first principles will deliver exciting outcomes.

AI is part of our everyday lives

This example of an in-car navigation system shows how the five senses are already working together in technology that we use every day. Such is the accuracy, convenience and intuitive nature of satnavs today, very few people navigate using maps anymore.

There is no time to waste

The satnav is just one example of how AI is improving our lives. The rapid pace of development in solutions underpinned by artificial intelligence will soon completely eclipse the performance of those that are not.

Intelligent organizations will take full advantage of the opportunities that AI enables by involving all of their workforce in transforming their business.

In our next article, we’ll look in detail at the impact AI is having on people in a business by considering new organization designs and the changing roles of managers and workers.

Bringing people and technology together

In the first article of our hyperintelligence series, we looked at the history, development, and progress of artificial intelligence (AI) – and how it is creating new opportunities for organizations.

In article two, we introduced a simple framework to make AI more accessible to all of the individuals within an organization by comparing AI to the five senses of human intelligence.

In this article, we will consider how AI technologies are also creating new opportunities for individuals in the workplace.

In the age of hyperintelligence, it is not just about what activities people can complete based on their own knowledge – it is also about how they use their skills and experience to access and apply knowledge available on their organization’s intranet or the global internet to create value.

This is leading to a fundamental shift in the roles of individuals and managers that suggests organizations should consider transforming their operating models to match the “Five Senses of Artificial Intelligence.”

Enhancing the role of the individual

A powerful new alliance is emerging between the individual and technology. Machine intelligence is augmenting human intelligence and expanding the limits of what individuals can achieve. This is liberating people’s time and allowing for more choice and creativity in the workplace.

Machines can do certain activities quicker and more accurately than people – such as processing and analyzing data. This revolution is less about doing the same things cheaper or completing activities faster, and more about freeing people from tasks better suited to machines. It enables people to augment their skills and knowledge and to rebalance their workload – such as taking more time to focus on driving insight and determining the next best action, rather than populating and manipulating spreadsheets.

The era of the “Google worker”

Until recently, people have generally required personal knowledge to generate value for the business – or been reliant on the willingness of managers to share their skills and experiences.

Knowledge is now more open and accessible to everyone. We all use the likes of Wikipedia, online dictionaries, and YouTube to develop new skills and tackle new challenges with confidence. We no longer need to hold knowledge in our memory, but to understand the relevance of the information we find. Improvements in connectivity are also creating networks that facilitate closer collaboration with different people, which is broadening our effective knowledge.

As such, people at work are becoming less concerned about what they know, and more interested in developing new skills to identify opportunities and solutions that will deliver value. Traditional workplace boundaries are disappearing. Individuals are resetting their expectations for what they are able to achieve. Individual knowledge is less of a differentiator when it is stored in a database and readily accessible through a search engine. There are fewer limitations and far more opportunities. As long as they are delivering value, people can apply their creativity and act on their ambitions like never before.

Across all industries and services, we are going to see a new generation of Google workers emerge – people who proactively use AI tools to enhance and augment their skills and knowledge. Established training and education will need to change radically to enable and encourage this release of potential. Managers will need to adopt a new approach to support their teams, and organizations will need to consider new operating models.

Rethinking the role of managers

In the age of hyperintelligence, where the role of the individual has changed significantly, it follows that the way they are managed and measured must also be revised.

Managers of the future will continue to be valued for their own individual contribution and that of their team. However, the measures of that contribution will change to include things like:

• Value added to the organization and its customers
• Behaviors exhibited (more creativity and innovation)
• Leadership demonstrated to drive change

They will have to embrace the age of the Google worker to create synergies within teams and juxtapose different skills to create differentiation.

The role of the manager will be about encouraging, supporting, and enabling individuals, exploring new ways to engage them and helping identify the greater contributions they can make to the business.

Less supervision, more trust

The relationship between manager and individual will change too. Rather than instructing people how to work and looking over their shoulder to ensure they have remembered, managers will need to let go and trust them to find their own answers. They will still need to hold people to account for their performance, but the focus will be on outcomes achieved, rather than traditional metrics such as attendance and efficiency.

As people adopt AI technologies to augment their performance, the organization will start to depend on more valuable contributions from them. Therefore, the fundamental purpose of a manager will evolve to be the enabler of change, as well as stability, within their environment.

Shaping the organization around the “Five Senses of Artificial Intelligence”

Legacy businesses are traditionally organized around core functions such as customer services, finance, HR, and supply chain, with tasks and data managed in silos. However, by adopting a new operating model that’s organized around the five senses of AI, better connections can be formed within and between those functions to create a hyperintelligent enterprise.

As we have seen, knowledge is key to hyperintelligence. It needs to be consolidated into one central function, rather than being spread across different teams. Improvements in ownership and accountability lead to clearer governance and control, resulting in enhanced integrity and quality of knowledge, enabling better and quicker decisions. This is the approach that “native” AI companies such as Amazon and Google take.

Native AI companies also employ various monitoring functions that track their employees’ use of knowledge as well the demand, questions, and feedback from their customers. An example is the use of HTTP cookies, which track browsing activity and provide companies with a greater understanding of what people are looking at over time to enrich their knowledge base.

This knowledge is then fed into models that analyze customer activity and predict future purchasing decisions. This insight may result in communication with the customer to recommend a combination of relevant, complementary, and substitute products or services.

If this leads to an order, it will be routed to the relevant supplier and fulfillment partner to act appropriately to meet the customer’s requirements.

AI at work – demand-driven knowledge At Capgemini, we are using a corporate knowledgebase to support 15,000 associates who deliver Finance & Accounting services. This has benefits for people, managers, and overall business outcomes: Individuals can complete their tasks with reliable knowledge and are no longer constrained by their ability to remember or their manager’s willingness to share the right training. Work instructions are easy to locate and rated for their ease of understanding, allowing individuals to explore new areas and learn faster. Managers have increased confidence knowing that their teams have reliable information, and they also benefit from clear visibility on what their people don’t know. Seeing what questions are trending and the root cause of those trends allows managers to create effective training interventions and identify latent problems in performance or disruption in the client environment. The organization has increased confidence that the right knowledge is being deployed effectively, and that knowledge is no longer dependent on specific people. Better management of knowledge leads to improved client satisfaction and new services.

Hyperintelligence – step by step

Although it is unrealistic for most legacy companies to transform overnight into a native AI company, they can take a step-by-step approach to hyperintelligence that will help them stay competitive. This could start with the formation of a single function responsible for all of the knowledge in the organization.

For example, we’ve worked with a leading biotech company to put stronger governance around all of its master data. This ensured that critical knowledge was firstly cleansed and is now managed and enriched centrally, improving completeness, relevance and quality. There is now an organizational trust in the integrity of the corporate knowledge platform that allows timely, informed and aligned decisions to be made with confidence.

Keeping it simple

Organizations in the initial phase of transformation can learn simple lessons from the early adopters as they go about reshaping their operating models to support hyperintelligence:

• Think technology and people – AI is bringing benefits to all areas of business, and is transforming (rather than replacing) the role of people. Consider how technology will shift the skills your people need.
• Be inclusive – involve a broad group of stakeholders as you start your AI journey, so you can factor in all the different implications for people, managers and organizational functions.
• Measure impact – thanks to the reducing cost of automation technologies, you can start valuing people on metrics such as customer satisfaction, rather than attendance and efficiency.

In our next article, we’ll look at the flexible infrastructure that underpins AI and how it is widely accessible today, enabling businesses to implement their own solutions quickly and without deep technical expertise.

Hyperintelligence awaits

As progress in technology infrastructure marches rapidly on, more and more businesses are embracing artificial intelligence (AI) to enhance their competitiveness.

Improvements in connectivity, storage capacity and processing power at lower costs are enabling this revolution.

New developments in cloud, wireless networks, the Internet of Things, Application Programming Interfaces (APIs), quantum computing, and microservices – to name just a few – are working together to build the hyperintelligent enterprise.

In this chapter, we’ll look at the infrastructure approach needed for success.

The story so far

Digital technology has changed nearly every facet of our lives – but what’s enabling it?

Behind all of the solutions that recognize our faces, that tell us what and whom we are going to like, that provide instant search results and real-time electronic payments, lies the infrastructure of intelligence.

In the past, the mainframe was the mainstay of the infrastructure landscape. While that era should be long gone, many industries still rely on large, monolithic solutions running on infrastructures that are costly to maintain, rigid in their architecture, and too restrictive for the new digital age.

Hyperintelligent organizations are transitioning to an infrastructure that delivers the speed, responsiveness, and reliability modern consumers and employees expect – an infrastructure that can receive, store, and instantly recall the ever-increasing quantities of data that today’s AI solutions rely on.

The new landscape is characterized not by monoliths, but by nimble, modular technology. By adopting a “building block” architecture that supports continuous development and dynamic adjustment, resources can be added and removed quickly and affordably. This enables organizations to embrace intelligent solutions today, whilst future-proofing their infrastructure for the developments of tomorrow.\

The new age

Most businesses now use Software-as-a-Service (SaaS) solutions, hosted in the cloud. This has become the standard mode of software distribution, replacing on-premises installations using CD-ROMs and floppy disks.

However, there is a major difference between subscribing to SaaS applications and completely redesigning your infrastructure around what the cloud can offer.

Organizations that choose to go “native” with cloud can achieve a broader range of benefits and help transition to an AI-first future.  That’s because of the range of functionality that is now available on the cloud in the form of web services and microservices. 

Building block architecture

Constructing a complete business process or application can be as simple as selecting functional modules from a catalogue and assembling them in the same way you would put together Lego blocks.

These independent building blocks communicate with each other using APIs. Many APIs are freely available on the market, in an open and standardized format – enabling you to link to new applications easily and affordably. You can also use them to incorporate new microservices into an existing application chain, to get more value out of your existing enterprise solutions.

Microservices and APIs give confidence in the ability of constantly evolving solutions to continue to thrive in a constantly evolving ecosystem.

Continuous development

APIs eliminate the need to recode and retest a microservice every time it gets updated or replaced.
In fact, it can take as little as 15 seconds to initiate the production of a microservice or to execute an application update in a building block architecture.

Compare this to a traditional legacy environment, where it could take as much as 12 months of development and testing to update a core in-house business application.

Digital businesses update their critical applications millions of times each year using the modular flexibility of microservices and APIs.

 

Such dramatic shortening of production cycles allows for more frequent – even real-time – application development. This helps ensure key systems meet the evolving requirements of the business, the changing expectations of customers, and the latest technological advances.

Dynamic adjustment

A further benefit of the cloud and microservice-based architectures is the ability to procure dynamically physical resources based on exact workloads.

Today, most businesses still over-resource each application to ensure uptime. They clone their production environments to respond to a potential peak in demand. If that peak never happens, they are paying for unused resources. However, that has to be balanced against the risk that if demand exceeds the predicted maximum level, the core applications could fail – causing untold reputational damage and lost revenue.

Alternatively, microservice-based applications operate in their own independent software container, which determines the resources required for its own execution. When demand peaks, the required microservices are replicated automatically to take up the load. When the peak has passed, the duplicates are destroyed, and the resources are made available to other applications.

Today’s leading e-commerce and streaming sites use dynamic adjustment techniques for instantaneous load balancing to keep their services online even at peak times.

Don’t forget the data

When thinking about new forms of infrastructure, it’s important to remember that we are in a new age of technology, where data quality and security is everything.

Data becomes knowledge that provides valuable insight into business operations. Acting effectively on that insight can help an organization differentiate itself and create new value.

Data, knowledge, and insight are not static, but are constantly in flux. Any organization that is rethinking its infrastructure design must also consider how it will collect, process, exploit, and circulate them in a secure and effective way.

In the next article, we’ll explore how the use of AI allows organizations to shift their focus from efficiency to effectiveness, leading to far richer user experiences and better business outcomes.