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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
Transform your organization’s approach to AI with tested frameworks from global leaders
AI and Innovation: How to Transform Your Business and Outpace the Competition with Generative AI is an expert blueprint on shaping and scaling the AI ecosystem of the future, revealing frameworks already tested and implemented at leading companies including Siemens, GE, and Microsoft. This book contains insight, use cases, tools, and templates to help readers build a brighter future for their organizations based on a fusion of disciplines, new concepts, and foresight thinking.
Written by two transformational business leaders, this AI and Innovation shows readers how to create the future of the innovation engine by connecting the dots between technology, change, and business success. The authors discuss topics including:
- Understanding the core concepts behind AI, including why it matters and what it actually is
- Generating a roadmap of change, then applying concrete tools and methods to kick-start and anticipate transformational change
- Transforming the ways of working, collaborating, and realizing new market opportunities
- Preparing for the future as AI and related technologies continue to progress at a breathtaking pace
AI and Innovation is a timely, essential read for business leaders, innovation and strategy managers, and executives seeking state-of-the-art guidance on AI and proven best practices for implementation.
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Seitenzahl: 332
Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Copyright
Title Page
ABOUT THE AUTHORS
Michael Lewrick (PhD)
Omar Hatamleh (PhD)
OTHER BOOKS BY MICHAEL LEWRICK:
PREFACE
MOTIVATION FOR THE TOPIC
INTRODUCTION TO EXPONENTIAL CHANGE
ADDITIONAL TYPES OF THINKING NEEDED
PERSONAL SELF-ASSESSMENT
New Perspectives
LET’S GET STARTED WITH THE BASICS …
CLEARING UP AI BASICS
HOW DOES AI LEARN AND BECOME MORE INTELLIGENT?
WHAT IS CONVERSATIONAL AI?
HOW CAN AI UNDERSTAND AND CREATE IMAGES?
HOW CAN AI MAKE DECISIONS IN COMPLEX ENVIRONMENTS?
WHAT IS COMING NEXT IN AI ?
WHAT ARE MAJOR BUILDING BLOCKS TO MAXIMIZE THE POTENTIAL OF AI?
KEY TAKEAWAYS
PART 1: Why Ai Matters
IMAGINE THAT…
EVOLVING FIELD OF AI
OVERVIEW UNIMODAL, CV & NLP
BEING AWARE OF TRENDS ON AI APPLICATIONS
EVALUATING BUSINESS IMPACT AND IMPLEMENTATION EASE
AI AS A DRIVER FOR INNOVATION
AI OPPORTUNITIES FOR INDUSTRIES AND NEW BUSINESS ECOSYSTEMS
REALIZING AI MARKET OPPORTUNITIES
WHAT IF …
SHIFTING TOWARD NEW OPERATING MODELS
THE AI TARGET OPERATING MODEL
MASTERING THE BALANCE BETWEEN GUIDANCE, SUPERVISION, AND OWNERSHIP
MINDSET REQUIREMENTS TO HANDLE UNCERTAINTY AND AMBIGUITY
COLLABORATION AND THE FUSION OF DISCIPLINES
IMPACT OF AI: FROM EXPERIMENTS TO VALUE DELIVERY
EXAMPLE INDUSTRY CASES SHOWING IMPACT OF AI ACROSS MANY SECTORS
THE IMPACT OF AI ACROSS MANY SECTORS
AI TRANSFORMING HEALTHCARE
EXPERT POINT OF VIEW
PREPARING THE WORKFORCE FOR GENERATIVE AI AND HUMANS AS A TEAM
KEY TAKEAWAYS
PART 2: HOW TO MAKE A DIFFERENCE WITH AI
WHERE TO PLAY AND HOW TO WIN
INTRODUCTION TO AL STRATEGY, CAPABILITIES, AND ETHICS
HOW TO DESIGN THE AI STRATEGY
EXPERT TIP: APPLYING AI IN STRATEGIC WORK
THE AI OPPORTUNITY MAP
HOW TO IDENTIFY THE OPPORTUNITIES
FOCUSING ON REAL Al OBJECTIVES
PRODUCTIVITY AND EFFICIENCY
LONG-TERM PROFITABILITY OUTLOOK
APPLYING AI IN INNOVATION WORK
STRATEGIC RESPONSE TO SET FOCUS
ADAPTION AND CULTURAL CHANGE TO THRIVE AI
UNLEASHING NEW VALUE ACROSS INDUSTRIES
RISK MANAGEMENT IN AI WORK
MONETIZATION OF AI
HOW TO DEVELOP AI CAPABILITIES
EXAMPLE OF DEVELOPING IT MANAGERS INTO AI PRODUCT MANAGERS
REQUIRED TECHNICAL AI CAPABILITIES
SKILLS AND AI: THE NEW TEAM FORMATION
EXAMPLES OF INDUSTRY CASES ACTIVELY BUILDING NEW CAPABILITIES FOR AI
LEARNING, APPLYING, AND LIVING-UP AI PRINCIPLES
IMPORTANT SKILLS BEYOND AI AND ML
HOW TO ADDRESS AI ETHICS
NAVIGATING BIAS IN AI
HOW TO HANDLE AI AND DATA REGULATIONS
IMPACT OF AI REGULATION ON BUSINESS AND INNOVATION SUCCESS
CREATE TRANSPARENCY ABOUT RISK LEVEL TO INNOVATION TEAMS
CHECKLIST REGULATION
SUMMARY: AI FOR BUSINESS LEADERS
EXPERT POINT OF VIEW
THE FUTURE OF PRIVACY, AI ETHICS, AND RESPONSIBLE AI
RESPONSIBLE AI x GLOBAL
KEY TAKEAWAYS
PART 3: WHAT TOOLS AND METHODS SUPPORT AI ACTIVITIES?
HOW TO LEVERAGE THE AI VALUE CHAIN
THE BASICS OF THE AI VALUE CHAIN
TRANSFORMER MODELS, AGI, AND OTHER BELIEFS
HOW LLM WORKS
LLM X TRANSFORMER
CREATING PROMPTS IN GEMINI, CHATGPT, ERNIE, AND OTHER LANGUAGE MODELS
ACTING AS A (ROLE) PERFORM (TASK) IN (FORMAT)
EXAMPLE OF APPLICATION SCENARIO FOR LARGE LANGUAGE MODELS
(RE)EVOLUTION OF MARKETING
METHODS FOR AI AND INNOVATION
#1 AI LENS: INCREASED EMPLOYEE PRODUCTIVITY
EXAMPLES OF POWERFUL USE CASES
R&D x AI
HOW TO CATEGORIZE PRODUCTIVITY USE CASES
EVALUATING THE POTENTIAL OF DISRUPTION
HOW TO SELECT STANDARD AI APPLICATIONS TO INCREASE PRODUCTIVITY
#2 AI LENS: AI-DRIVEN INNOVATION AND CREATIVITY
KEY ADVANTAGES OF USING AI TO DRIVE INNOVATION AND CREATIVITY
APPLYING AI OVER THE ENTIRE DESIGN CYCLE
UNDERSTANDING THE PROBLEM FIRST
BUILDING UP EMPATHY WITH USERS/CUSTOMERS
EXAMPLE OF TOOLS USED AND APPLIED IN FINDING THE APPROPRIATE PROBLEM TO SOLVE
APPLYING AI FOR IDEATION
AI SUPPORT IN IDEATION
EXAMPLE OF TOOLS APPLIED IN IDEATION, PROTOTYPING, AND TESTING
EXAMPLE OF AI TOOLS USED AND APPLIED IN THE SOLUTION SPACE
EXAMPLE OF AI EXPERT ASSISTANT TOOL OVER THE ENTIRE DESIGN CYCLE
#3 AI LENS: TOP-LINE AND BOTTOM-LINE IMPACT
AI FOR IMPROVING BOTTOMLINE PERFORMANCE
THE NEXT WAVE IN AI ECOSYSTEM CONFIGURATION
GLOBAL AI x ECOSYSTEM
EXPERT POINT OF VIEW
THE RISE OF THE MACHINES … FOR THE BENEFIT OF HUMANITY: PROMPTING INTELLIGENT ADOPTION OF AI
KEY TAKEAWAYS
PART 4: THE FUTURE OF AI AND INNOVATION
WHAT’S NEXT FOR AI
TRENDS ON AI
AI’S INFLUENCE ON DIFFERENT SECTORS
MORE EFFICIENCY OR A TECHNOLOGY EVERY INDUSTRY WILL BUILD ON?
EXAMPLE INDUSTRY CASE ACTIVELY PARTICIPATING IN THE FUTURE OF AI AND INNOVATION
AI, INNOVATION, AND THE SPACE RENAISSANCE
FUTURE OF INNOVATION MANAGEMENT
SINGULARITY AND AI
BUILDING A COMPETITIVE AND ETHICAL AI ECONOMY
EXPERT POINT OF VIEW
SHAPING TOMORROW’S AI: A FOCUS ON DIVERSITY, ETHICS, AND FUTURE CHALLENGES
KEY TAKEAWAYS
CLOSING WORDS
AI-GLOSSARY
SOURCES
INDEX
End User License Agreement
Guide
Cover
Table of Contents
Series Page
Copyright
Title Page
THE EXPONENTIAL CHANGE PARADIGM
ABOUT THE AUTHORS
PREFACE
MOTIVATION FOR THE TOPIC
INTRODUCTION TO EXPONENTIAL CHANGE
NEW PERSPECTIVES
CLEARING UP AI BASICS
KEY TAKEAWAYS
Begin Reading
CLOSING WORDS
AI-GLOSSARY
SOURCES
INDEX
End User License Agreement
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THE EXPONENTIAL CHANGE BOOK SERIES
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Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
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For more information about Wiley products, visit www.wiley.com.
ISBN 9781394254972 (Paperback)
ISBN 9781394254996 (ePDF)
ISBN 9781394254989 (ePub]
Book Design: www.studiohansen.ch
Cover design and illustration: Heike Hansen
MICHAEL LEWRICK
AUTHOR OF INTERNATIONAL BEST-SELLING "DESIGN THINKING PLAYBOOK"
OMAR HATAMLEH
RECOGNIZED AS A TOP 100 THOUGHT LEADER ON AI
AI AND INNOVATION
HOW TO TRANSFORM YOUR BUSINESS AND OUTPACE THE COMPETITION WITH GENERATIVE AI
ABOUT THE AUTHORS
In this age of exponential change and ever-evolving technologies, Michael and Omar’s collaboration on their book presents a unique opportunity. Michael brings a wealth of experience in the field of innovation management, design thinking, and ecosystems design. Omar, on the other hand, possesses deep subject matter expertise within the field of AI. Together, they combine strategic vision with cutting-edge knowledge, creating a powerful synergy that ensures their book re-mains relevant and insightful in a rapidly changing world. This dynamic duo positions their work to be a valuable resource for anyone seeking to understand and leverage the transformative potential of new technologies.
AI IS GOOD FOR DESCRIBING THE WORLD AS IT IS TODAY, WITH ALL ITS BIASES, BUT WHAT WE NEED ARE THE APPROPRIATE MINDSET, TOOLS, AND METHODS TO UNLOCK THE POWER OF INNOVATION WITH IT.
Michael Lewrick (PhD)
is a bestselling author, award-winning design thinking and ecosystem design thought leader, business entrepreneur, and visiting professor at various universities globally. His ideas, books, and company, Lewrick and Company, help mobilize people around the world to better lead innovation and digital transformation in an era of increasingly rapid change. He values the power of human–AI collaboration for solving complex problems.
www.linkedin.com/in/michael-lewrick/
Omar Hatamleh (PhD)
is a global thought leader on AI (top 100 world leader in AI by Thinkers360) and book author about emerging technologies. He holds the position of Chief AI Advisor at NASA, and he is an invited key-note speaker to multiple international events, in-cluding major innovation conferences at G20, United National, Google, IBM, and many others. Omar holds four engineering degrees, speaks four languages and has received numerous prestigious awards.
www.linkedin.com/in/hatamleh
OTHER BOOKS BY MICHAEL LEWRICK:
Book designed by
Heike Hansen is a Swiss-based art director with a passion for human-centered design, storytelling, and emerging technologies. The deep immersion in the topic as well as working in teams are some of her most vital strengths in the field of art, design, and technology. www.studiohansen.ch
PREFACE
Llewellyn King
→ Executive Producer and Host of White House Chronicle on PBS; columnist, InsideSources Syndicate; contributor, Forbes; Energy central commentator, SiriusXM RadioMobile
Leon Trotsky said, “You may not be interested in the dialectic, but the dialectic is interested in you.” So it is with generative ar-tificial intelligence: you may not be interested in it, but it is in-terested in you. It is interested in how we live, work, play, and even think. There will be going forward, if you will, no hiding place. This book at its core says, “Don’t hide from AI, embrace it.” But to do that, individuals and institutions need to embrace exponential thinking. Linear thinking — which is the normal human default setting – will fail individuals and institutions be-cause AI is exponential.
An apocryphal and oft-trotted-out Henry Ford quotation: “If I had asked people what they wanted, they would have said faster horses.” That is linear thinking. AI is different things to different groups of people. To one group, it is something to be wildly feared: a new plague, a glance at the beginning of the end of humanity. To another, it is here and now and frightening but not so frightening that it can’t be harnessed – managed and regulated with legislation, providing so-called guardrails.
These guardrails, they believe, will keep AI from becoming something that could upend society, throwing millions out of work worldwide; taking away privacy; spreading disinformation; interfering in the political process in democracies; and spread-ing bias in data, codifying it as a truth. Yet a group of computer aficionados, a group of elite thinkers, see generative AI as a benefit to humanity.
But it is one for which individuals and institutions must be ready – ready with new ideas and new tools to use AI to sweep in a new age, where the thorniest of human problems can be solved with alacrity, producing huge and unimagined benefits. For example, a life expectancy of 120 years for children born today.
Front and center of this cohort are the authors of this book, Michael Lewrick and Omar Hatamleh, the first in a series to help us get to the glittering future promised by AI: a future where AI solves problems that have plagued humanity for mil-lennia. The first among these is research that can accelerate the finding of cures or therapies for pervasive and even in-tractable and rare diseases.
The authors’ central point in this volume is that AI is exponen-tial, so individuals and institutions must shirk their traditional linear thinking and realign themselves to thinking exponential-ly. Thinking exponentially demands new structures, paradigms, and management concepts that will free the exponential think-ers in an organization to shape it and get the value from AI.
The message for corporations is loud and clear: adapt or lose. Jack Welch, former CEO of General Electric, said, “If the rate of change externally isn’t greater than the rate of change in-ternally, then the end is known.” Welch wasn’t talking about AI, but he might as well have been. What he said then can be taken as an exhortation to institutions to embrace exponential thinking to use AI, or the end is known. That is the vital mes-sage of Hatamleh and Lewrick: if we don’t change our thinking, the end is known. If we do, a new age of human progress is at hand, ready to unfold.
I wish you exciting insights with this book.
MOTIVATION FOR THE TOPIC
The blend of past innovations that have shaped human pro-gress and advanced technologies like artificial intelligence (AI) makes for an incredibly exciting topic. This combination prom-ises to drive change in ways we can hardly imagine.
As a team of authors, we are deeply interested in exponential change because we believe it is one of the most important and impactful forces shaping our world today. Exponential change is happening at an unprecedented pace, and it is having a profound impact on everything from the way we innovate to the way we work. We believe that it is important to understand ex-ponential change and to use the appropriate frameworks in order to be prepared for the challenges and opportunities that it will bring. A key question is how do we move from our usual linear way of thinking to thinking in terms of rapid growth and change? Filling the gap between both elements will ensure humanity and biological intelligence will remain relevant now and into the future. We believe that thinking in terms of rapid growth can help solve some of the world’s toughest problems. New technologies like AI and quantum computing could trans-form healthcare, education, and environmental efforts. Em-bracing an exponential mindset will create a better future for everyone. Creating a synergy between radical innovation and new and evolving technologies can disrupt traditional indus-tries and give birth to new business models, platforms, prod-ucts, and services. These tools will orchestrate a new para-digm shift in rewriting the conventional rules of the game for future innovations.
In this book, we share and reflect on our work with the world’s most innovative companies that have made significant ad-vancements with exponential technologies. These companies have achieved this through a changed mindset, utilizing new tools and methods, and developing a deep understanding of the problems to be solved.
The tools and methods shared in this important book are flexi-ble and meant to inspire innovation during rapid changes. They should be tailored to fit each unique situation.
AI IS THE KEY TO UNLOCKING A BRIGHTER FUTURE FOR HUMANITY. BY HARNESSING ITS POWER RE-SPONSIBLY, WE CAN SOLVE GLOBAL CHALLENGES, IMPROVE LIVES, AND CREATE A MORE PROSPEROUS WORLD FOR ALL.
We bring our eminence and decades of experience to the presented content and frameworks with the objective of creat-ing awareness of exponential change, finding a common lan-guage, and removing the fear associated with ongoing and dynamic transformation. We are cognizant of the fact that AI is a complex and novel concept that brings uncertainty in its wake. These fears are inherent to our human nature. However, it is important to remember that AI is a tool created by humans, for humans, and if we can successfully embrace exponential change, there will be immense opportunities for positive im-pact. Early adopters who take measured risks and proactive action will possess a huge strategic advantage over those who continue along the conventional and reactive path.
We must also highlight that at the current technology level, AI does not possess consciousness or emotions; AI merely mim-ics our cognitive processes based on algorithms and available data. As a result, AI may generate mistakes and experience “hallucinations” due to its inability to understand context nu-ances in ways that humans do.
However, with the introduction of the next level of artificial general intelligence (AGI) systems, AI will be able to do eve-rything that a human brain can do and more. Such impressive capabilities will take us beyond existing boundaries. Genera-tive AI offers a glimpse into a future where the possibilities seem endless, and the need to master the appropriate skills, tools, and methods to better deal with them becomes ever more pressing.
A comprehensive understanding of AI is crucial to allay fears about sentient AI. Promoting and creating a healthy partner-ship and collaboration between AI and humans will spring-board new waves of innovation that would otherwise be unat-tainable. The collective creativity and intelligence that AI and humans bring will propel us into a fertile future of opportunities.
We are confident that the best AI solutions can help solve hu-manity’s greatest problems, especially when AI and humans work harmoniously as a team and build upon their respective strengths regarding fact aggregation and processing speed. To make the most of AI and all the other remarkable technolo-gies, we must guard against the risks and leverage all benefits to create better and more sustainable products, services, and experiences.
We are looking forward to constructive exchanges, exciting discussions at conferences, and our work to implement the tools and methods shared in this book at companies and or-ganizations worldwide.
Your team of authors,
Michael Lewrick Omar Hatamleh
AI AND HUMANS AS A TEAM
INTRODUCTION TO EXPONENTIAL CHANGE
This book from the Exponential Change book series offers methods and frame-works that help to better deal with exponential change. The change is exponential because so many technological advancements – whether in AI, quantum compu-ting, AR/VR, biotech, robotics, or cognition – are occurring simultaneously and rapidly and building on one another across every sector and industry imaginable. Something is not classified as exponential until it breaks the integer barrier. As a result, growth begins to be measured in whole numbers and multiplies from there.
Many factors, such as regulations, technological dependencies, and economic forces, are beyond the control of decision-makers, product owners, and innovation teams. Therefore, the intent of this book series is not to present technology tools but to address the impact of exponential change on future business models, evolving workforce dynamics, strategic consid-erations, and capabilities and future skills to be built. Each book in this series is dedicated to a key topic. This book has a strong focus on AI and innovation: it re-flects best practices and tools to transform industries, create new market opportuni-ties, and solve some of the world’s most significant challenges between AI and hu-mankind. Although not the main focus of this book, we will also touch on the myriad challenges that AI brings, from its potential to perpetuate bias to its capacity to un-dermine security and privacy. Different perspectives from industry experts will be presented throughout each chapter to enrich our discussions.
THE AI REALITY IS HERE, AND DECISIONMAKERS ARE SEEING THE REAL CHALLENGES OF AI INSTEAD OF WHAT THEY ASSUMED THEY WOULD BE. THIS BOOK SERIES WILL HELP ORGANIZATIONS ADDRESS THE PRAGMATIC SIDE OF EXPONENTIAL TECHNOLOGIES.
It is no coincidence that the first book in this series is about AI and innovation, as there is a strong belief that AI will influence everything we design, implement, and scale. With the concepts and frameworks in this book, teams and decision-makers will be equipped with the appropriate toolkit to excel in the age of AI.
The impact that exponential technology will have on each and every one of us is tremendous, as it is possible to imagine a scenario in which machines would do most of the work, and employees would only be responsible for higher-level decision-making and the control and programming of robots and machines.
There is a consensus among technology experts that exponential change is beneficial to society in general, as technology can solve many of society’s problems and act as an empowering force. However, this also requires social and corporate responsibility on how to deal with technologies such as AI. Governments can no long-er continue their slow and bureaucratic processes, where it takes years for changes to become visible. In fact, the process of exponential change will soon leave behind those who cannot keep up with the changes and proactively shape the future. At the same time, companies must also transform in an environment without clear guidelines because the strategies, processes, and approaches of the past no longer serve them.
This series of books aims to help decision-makers and managers adapt to an increasingly dynamic and disruptive business environment. This means that digital transformation approaches and AI frameworks must be applied to support this continuous and ongoing transformation process. However, it is important to distinguish which parts contribute to the longer-term goals and strategy and what needs to be adapted quickly and flexibly to realize and monetize the corresponding market opportunities. In addition to the impact of emerging technologies, organizational cultures will also require a phase of evolution and transformation to create the most efficient and enabling business landscapes for future success.
Many decision-makers are aware of the pace of change, but a lingering question remains: how must we approach it? As a first step, it is important to under-stand and leverage the power of new disruptive technologies and business models. The first steps often refer to the transformation toward agile and adaptive organizations. In this way, organizations can be ready for the exponential leaps that come next to achieve exponential results. The path of exponential transformation is an iterative process that goes through the phases of imagining, exploring, prototyping, testing, adapting, and scaling. The important factor here is to start actively trans-forming; simply being aware of exponential technologies does not lead to transformation.
In the context of this book, exponential change is best holistically addressed and embedded in a broader innovation and strategy framework. Often, the bulk of the value from innovation lies outside of the products, services, or experiences offered – whether in a profit/business model or at the customer engagement level. As such, we encourage expanding the utilization of exponential technologies (and other re-sources) for purposes beyond mere products and processes.
Corporate practice shows that companies are most successful when leadership teams have the courage to embrace change, allocate resources, invest in new technologies, and take risks. Proactive decision-makers provide the resources for technology development and implementation – as well as the timeline to address obstacles, both large and small – and clearly articulate the design principles and mission for adoption to ensure cultural fit. In the current technological era, there is no room for reactive cultures. Only proactive cultures will survive. Here, the focus of empowerment is on the individual and team members so that each can reach their full potential. This implies that developing an exponential mindset requires bold, engaged, and thoughtful leadership. By understanding the characteristics of the exponential change paradigm, organizations can better prepare themselves for the challenges and opportunities of the future.
BE AWARE OF SOME KEY CHARACTERISTICS ASSOCIATED WITH THE EXPONENTIAL CHANGE PARADIGM:
Change is accelerating.
The pace of change is increasing at an exponential rate. This is due to numerous factors, including technological advances, globalization, and the increasing complexity of the world.
Small changes can have a big impact
. Small changes can have a disproportionately large impact over time. This is because exponential growth is multiplicative, not additive.
→ The Exponential Change Paradigm implies a new way of thinking about how we collaborate and realize new market opportunities.
The future is uncertain.
The future is more uncertain than ever before. This is because the pace of change is so rapid that it is difficult to predict what the future will hold.
Adaptive culture is at the forefront.
Without a properly enabled and empowered culture, technology transformation will not succeed. Ensure a proper alignment to achieve best results.
Start to prepare for change
. It will be of paramount importance to think creatively and innovatively, and the entire organization should be able to adapt to new situations.
LINEAR GROWTH VS. EXPONENTIAL GROWTH
Humans have evolved to think in linear terms; we were hunters, farmers, and crafters, and our environments changed very slowly. We must embrace a new ex-ponential way of thinking to remain relevant in this new exponential landscape.
The Exponential Change Paradigm is a way of thinking about the world that recog-nizes that change is not linear but exponential; this means that small changes can have a disproportionately large impact over time. For example, if a technology dou-bles in power every year, then in 10 years, it will be 1,024 times as powerful as it was to begin with.
The illustration below depicts how technology trends and growth are deceptively slow at first and appear to be decimal progress, just a dot on the horizon that no one really cares about. For example, generative AI became exponential by 2018 and accelerated in 2022 with broader use cases related to language processing. → see page 33
→ The following outline of examples will help you to understand how exponential change is impacting the world today. As this paradigm continues to unfold, it is important to be prepared for the challenges and opportunities that it will bring.
A LOOK IN THE REARVIEW MIRROR REVEALS EXPONENTIAL CHANGES IN TODAY’S WORLD
The growth of the internet. The internet has grown exponentially since its incep-tion in the 1960s. In 1993, there were only 1 million websites. In 2024, there were already over 1.7 billion websites.
The growth of gene editing. Gene editing is a technology that is capable of re-writing DNA. This technology is still in its early stages, but it has the potential to rev-olutionize medicine.
The growth of artificial intelligence. AI is another area that is experiencing ex-ponential growth. In 2012, there were only 16 billion AI parameters. In 2022 there were already over 175 billion AI parameters.
In the utilization of market opportunities and the way we will shape them together, we need to discuss new developments, ideas, and technologies and decide how to shape the future. One of the most important dimensions is the fact that AI will sur-pass human intellect in every domain at a certain point, which will transform all so-cieties and economies globally.
At the same time, each technological advancement will fuel further innovation, cre-ating a cycle of exponential growth that speeds up the rate of progress. Technolo-gies of high relevance include AI, quantum, nanotechnologies, additive manufac-turing, and many others. All of them will transform traditional economic constraints and provide the opportunity to shape new business ecosystems and communities of a post-scarcity society.
With this book about AI and innovation and the entire book series, we would like to contribute to the perception of exponential change and reach a point beyond un-certainty where the pace of change exceeds our capacities to foresee and under-stand future developments. However, we are aware of the risks of these technolo-gies. Our ambition must be that the changes positively contribute to humanity in all possible aspects. Notably, integrating advanced technologies with human biological systems could easily redefine humanity based on migrating minds and beyond.
ADDITIONAL TYPES OF THINKING NEEDED
To successfully manage exponential change, organizations must master two other crucial mindsets besides exponential thinking: design thinking and systems thinking. Both require an effort to fundamentally rethink the existing mindset and work atti-tude. These mindsets shift how employees and managers look at problems and so-lutions, allowing them to reimagine how they create, deliver, and capture value – not just to survive but thrive and meet proactively the transformative challenges of the coming decades.
Building capabilities in all three domains is part of the minimum skillset needed to actively shape the future, explore it in a structured way, and anticipate new devel-opments. The different approaches have proven to be very useful in identifying and exploring challenges that arise from the multiple signals and drivers of change that shape the future. Many of the world’s most innovative companies use the three mindsets to develop strategic options in a context full of unknowns. In this way, new market opportunities, business segments, or entire business ecosystems emerge that are new to the customer and unique to the market.
This mindset includes active scouting and monitoring of trends and megatrends. Methods from the foresight toolbox help identify signals, patterns, and paradigm shifts. The associated tools and methods help organizations build future capability through exploration, orientation, visioning, strategy, and innovation. The application of scenario planning is compelling in outlining different possible futures and creating easy-to-understand stories to educate decision-makers and other relevant stake-holders.
These methods and tools also help sharpen the common understanding and dia-logue between all stakeholders, assist them in philosophizing about the future, and help them understand what they can do here and now.
In addition, decision-makers should not neglect the ecological component associ-ated with how behavior can be changed alongside customer needs, the long-term view of systems, and the use of exponential technologies. This view heralds a shift from human-centered design to design thinking for humanity.
THE FUTURE OF BUSINESS MUST WORK BEYOND THE FAMILIAR BOXES. THE CLEVER COMBINATION OF NEW TECHNOLOGIES AND HUMAN THINKING LEADS TO BETTER RESULTS.
PERSONAL SELF-ASSESSMENT
You might feel unsure about navigating the whirlwind of exponential change and growth, especially with AI and innovation at the forefront. The self-assessment model introduced below can help you assess how confident you are to handle exponential change and technologies. We’ve used it successfully in count-less personal coaching sessions to prepare executives, leaders, and teams for this very scenario. The model focuses on four core layers of skills and capabilities: cognitive (critical thinking, communication, strategic planning), interpersonal (mobilizing systems, relationship building, teamwork), self-leadership (self-awareness, management, achieving goals), and digital literacy (fluency, citizenship, software use, understanding digital systems). By evaluating yourself across these four layers, you can identify areas of strength and opportunities for growth, ensuring you’re well equipped to lead and thrive in a rapidly changing world.
Cognitive
Related to critical thinking, communication, planning and ways of working, mental flexibility
Interpersonal
Related to mobilizing systems, developing relationships within and outside of the organization, teamwork effectiveness
Self-leadership
Related to self-awareness, self-management, entrepreneurship/intrapreneurship, achieving objectives and key results
Digital literacy
Related to digital fluency, citizenship, software use and development, understand existing and future digital system
New Perspectives
The mindsets, tools, and methods presented in this book series have one significant objective: solving problems better. Metaphorically, our idea of problem- solving should be viewed as a magic cube that uses different technologies and varying states of mind to find better solutions for existing and future problems. Most important is to adopt a perspective shift that allows new enabler technologies to realize the corresponding market opportunities
To benefit from exponential change and growth, we also need strategies, tactics, and metrics that help us position the elements of the Magic Cube so that technology can flourish in the best possible way. In particular, combining different elements can also help gain a solid competitive advantage.
Specific capabilities can be learned to better deal with exponential change. These capabilities include understanding the advantages and limitations of emerging technologies and their implications and establishing mindsets that help identify the problem and enable radical collaboration among interdisciplinary teams while being open to fast adaptation and change.
Characteristics such as patience, mindfulness, visualization skills, robust and tested algorithms, and a culture of experimentation and failure are essential for prob-lem-solving and realizing innovations.
There are many possible options and combinations to solve problems. According to “God’s Number,” the theoretical minimum number of moves required to solve a Rubik’s Cube, there are 43,252,003,274,489,856,000 possible combinations for solving a Rubik’s Cube. This number is so enormous that solving the Cube by ran-domly turning the faces is impossible.
Highly skilled humans can tackle a Rubik’s Cube in roughly fifty moves, but AI can solve the cube in less than twenty moves, which is the minimum number of steps possible in most scenarios. To highlight its power, AI will already be done with the task before any human has attempted to solve it.
Similar to the opportunities and options in an exponentially changing world, we need guidance, methods, and frameworks to help us create, capture, and deliver value. This book strongly focuses on specific elements of our imaginary magic cube: the power of AI and Innovation.
To start the journey of AI and innovation, we provide on pages 30 and 31 an over-view of the AI layers, and clearing-up AI basics is on page 32. AI can be divided into infrastructure, perception, cognitive, and decision-making layers, which are the ba-sis for the applications, reaching from conversational AI to applied computer vision.
LET’S GET STARTED WITH THE BASICS …
In our daily lives, we experience the benefits of AI through user-friendly applications. Whether it’s getting personalized recommendations or receiving better healthcare with AI-aided medical diagnoses, these applications are the tip of the iceberg. While the application layer makes interacting with AI feel seamless, it’s supported by complex underlying layers – from the powerful hardware infrastructure to the algorithms that make decisions – that work together to power these intelligent systems.
AI is a product of a beautiful marriage between human minds and scientific disciplines as displaced in the onion graph below. From conceptualizing the problems AI can solve to designing the algorithms and building the necessary infrastructure, it’s this melding of minds and sciences that allows us to develop intelligent decision and support systems that are constantly evolving alongside our world.
CLEARING UP AI BASICS
In the first pages of this book, you will find a variety of AI terminology. For many of us, these terms are part of our daily language; for others, they raise questions that require a brief answer. For this reason, we have compiled a simple guide on the following eight pages to help you better understand AI basics.
→ A more detailed glos-sary with key terms can be found on page 248 et sqq.
HOW DOES AI LEARN AND BECOME MORE INTELLIGENT?
AI refers to the development of computer systems and algorithms that can perform tasks typically requiring human intelligence, such as learning, problem-solving, and decision-making. The cornerstone of machine learning (ML), a subset of AI, is a process called training. A computer program is given a large amount of data during this process. This kind of data comes with labels explaining the data and a series of instructions. The prompt might be something like “Find all the pictures that contain a traffic light” or “Categorize the sounds of a typical city.” The program then looks for patterns in the given data to achieve these goals. It may need a few hints along the way, such as “That’s not a traffic light, it’s a streetlight” or “These two sounds are different; one is a fire siren and the other is a police siren.” What the program receives and learns from the data be-comes the AI model. The quality and quantity of the training material ultimately de-termine its capabilities.
