AI is reshaping business and redefining competitive advantage. Leaders need to adapt their mindsets and strategies to compete and collaborate in ecosystems driven by algorithms.

Instill tight feedback loops and information flows for continuously observing impacts, drawing insights, and immediately applying the learning by publishing findings and altering strategies. The pace of AI-infused environments necessitates agility, learning, and willingness to self-disrupt. Never stand still.

Cultivating Organizational Learning and Adaptability

<ul><li>Build teams encompassing a diversity of AI-related skills including computer science, mathematics, ethics, design thinking, business strategy, change management and more. </li><li>AI progress requires technical prowess combined with humanistic perspectives to produce well-rounded solutions.</li></ul>

Developing Multidisciplinary AI Talent and Know-How

Instill and operationalize strong humanistic guardrails around ethics, fairness, transparency, accountability and control to ensure the development and application of AI technologies ultimately serve and benefit humanity, rather than threaten it. Technological progress and humanistic progress must advance hand-in-hand.

Prioritizing Humanistic Values and Concerns

In environments where value is produced via networks, leverage platform business models that efficiently and intelligently match producers and consumers of value, while also capturing a share of that value for the platform via fees, data accumulation, or other means.

Leveraging Platform Business Model Advantages

<ul><li>In ecosystems of increasingly intelligent and interconnected machines, value is driven less by individual firms and more by the broader networks they participate in. </li><li>Adopt network-focused thinking, in which success stems from efficiently orchestrating platform-based ecosystems of producers and consumers. </li><li>Move from controlling internal resources to harnessing external networks.</li></ul>

Adopting a Network-Focused Mindset

Success requires continuously hypothesizing, building, testing, analyzing, and refining AI-powered prototypes and business models at speed. Fail fast, adapt, and iterate. The availability of massive datasets and progress in machine learning vastly accelerate the pace and viability of experiments a company can run.

Competing Through Rapid, Intelligent Experimentation

<ul><li>Responsibly monitor jobs at high risk of automation displacement. </li><li>Provide transition support, reskilling/upskilling, severance, and alternative role paths for workers affected. </li><li>Manage societal and enterprise impacts simultaneously.</li></ul>

Proactively Managing AI's Impacts on Jobs

AI's implications for business extend far beyond simply automating repetitive tasks. Applied thoughtfully, AI also enables vastly expanded leverage of data, personalization and customization at scale, superior prediction capabilities, and deep integration across platforms and ecosystems. Business leaders across functions must radically adapt their mindsets and strategies beyond isolated automation use cases to compete in an environment increasingly defined by intelligent and interconnected machines.

Understanding AI's Multifaceted Business Impacts

In Competing in the Age of AI, Iansiti and Lakhani provide frameworks for business strategy, leadership, and organization in an age increasingly driven by AI, platforms, and networks. They advise on navigating ecosystem-driven disruption.

"a provocative new book" — The New York TimesAI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions.When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani:<ul><li>Present a framework for rethinking business and operating models<li>Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models<li>Explain the opportunities and risks created by digital firms<li>Describe the new challenges and responsibilities for the leaders of both digital and traditional firms</ul>Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.