This is a summary of a book titled “Creativity in the Age of AI: Toolkits for the Modern Mind” written by Jerry (Yoram) Wind, Mukul Pandya and Deborah Yao and published by De Gruyter in 2025. Recommendation. This book examines creativity as a disciplined capability rather than a sporadic or innate talent, situating it within the contemporary context of artificial intelligence. The authors contend that creativity has become a central requirement for organizational effectiveness and long‑term competitiveness, particularly as AI technologies alter how problems are framed, explored, and solved. Their central claim is not that AI supplants human creativity, but that it can extend and reinforce it when integrated into established cognitive, organizational, and analytical frameworks.

The book begins by establishing creativity as an essential component of business performance. Empirical research demonstrates a strong relationship between creative capability and outcomes such as revenue growth and market share, yet many organizations struggle to translate creativity into systematic practice. This gap, the authors argue, stems from persistent misconceptions: creativity is often treated as an unpredictable spark rather than as a process that can be deliberately cultivated. Drawing on longstanding research, the authors emphasize that creativity requires both novelty and usefulness, and that ideas only become creative when they are developed into practical and effective solutions.

To clarify how creativity functions, the authors revisit foundational models that remain relevant in the age of AI. Graham Wallas’s four‑stage framework—preparation, incubation, illumination, and verification—illustrates creativity as a progression from problem definition to refinement and implementation. Teresa Amabile’s componential theory further expands this view by identifying the interacting elements that support creativity: domain‑specific expertise, cognitive processes that enable creative thinking, intrinsic motivation, and an environment that encourages exploration and risk‑taking. Together, these models reinforce the authors’ view that creativity is the result of sustained effort shaped by both individual and contextual factors.

Advances in neuroscience provide additional support for this perspective. Research shows that creativity is supported by the interaction of three neural networks: the default mode network, which generates ideas; the executive control network, which evaluates and refines them; and the salience network, which mediates between exploration and judgment. Creativity depends on maintaining balance among these systems, a balance influenced by factors such as cognitive flexibility, intrinsic motivation, and psychological safety. Environmental conditions also matter. Spaces characterized by coherence, fascination, or comfort can support different phases of creative work, suggesting that creativity is shaped not only by mental processes but also by physical and social contexts.

Within this human-centered framework, AI is introduced as a complementary resource rather than a disruptive replacement. The authors position AI as an assistant and collaborator that can support creativity across execution, idea generation, and evaluation. By handling routine tasks, generating unconventional combinations, and providing analytical feedback, AI can expand the range of possibilities considered while allowing humans to focus on judgment and meaning. The example of Airbus’s use of generative design illustrates this dynamic: AI explored vast design spaces beyond human capacity, while engineers defined constraints and evaluated outcomes. The result was a solution that combined biological inspiration with engineering requirements, demonstrating how AI can augment, rather than diminish, human creative agency.

The authors also address the organizational challenges associated with adopting AI for creative work. Resistance to change, fear of failure, and limited resources can all impede progress. Rather than dismissing these concerns, the authors recommend examining their underlying causes and addressing them explicitly. Techniques such as pre‑mortem analysis can reduce uncertainty, while reframing obstacles as opportunities for reconsideration can help organizations move beyond entrenched habits. Creativity, in this view, requires not only tools but also cultural conditions that tolerate experimentation and learning.

A significant portion of the book is devoted to the role of mental models in shaping creative outcomes. Unexamined assumptions can constrain perception and limit the range of solutions considered. The authors argue that creativity depends on the continual reassessment of these models through techniques such as assumption reversal, analogical reasoning, and exposure to diverse perspectives. General‑purpose AI tools can assist by making implicit assumptions visible and by generating alternative ways of framing problems, thereby supporting paradigm shifts that enable more fundamental forms of innovation.

To support complex problem‑solving, the authors outline structured approaches including morphological analysis, analogical thinking, and benchmarking. Morphological analysis is particularly effective for problems involving multiple variables and stakeholders, as it systematically explores combinations that might otherwise be overlooked. Analogies and benchmarking extend the search for solutions beyond familiar domains, while AI accelerates these processes by identifying patterns, generating combinations, and visualizing implications across large datasets.

Interdisciplinary collaboration and open innovation further expand creative capacity. By integrating insights from different fields and engaging contributors beyond organizational boundaries, teams can access perspectives that would otherwise remain unavailable. AI can support this work by synthesizing knowledge across domains or simulating expert viewpoints, reinforcing the authors’ argument that creativity benefits from structured diversity rather than isolated insight.

In its later chapters, the book turns to trend analysis, experimentation, and iteration. AI’s ability to detect emerging patterns and intersections among trends can inform strategic foresight, though the authors caution against uncritical reliance on algorithmic outputs. Ultimately, creative ideas must be tested, refined, and validated through experimentation. Tools such as digital twins illustrate how AI can accelerate this process by enabling low‑risk simulation before real‑world implementation.

The book concludes by emphasizing curiosity and imagination as the foundations of creativity. Leaders play a critical role in fostering environments that support both directed inquiry and open exploration. Emerging technologies, including immersive environments, further extend the contexts in which creativity can occur, with AI serving as an integrative layer across these tools. Rather than prescribing a single method, the authors encourage readers to assemble a personalized toolkit of creative strategies, selected and refined through experimentation. Creativity, they argue, is sustained not by novelty alone, but by disciplined practice, reflection, and persistence over time.