Adopting AI

The People-first Approach

De: Paul Gibbons, James Healy

Narrado por: Virtual Voice

"Few books so artfully blend the optimism of Kurzweil with the caution of Bostrom with the pragmatism of Mollick." (Linus Caldwell, Alphaverse Capital)

"While AI technologies have transformative potential, their value is realized only when they are widely adopted and integrated” is the sort of trivial insight often presented as a profundity by management gurus. Few thinkers address the deeper question: What makes AI adoption different from prior technologies like cloud or CRM platforms? And given humanity’s centuries of experience with technological change, beginning with the Industrial Revolution, and decades of experience with IT adoption, will traditional change management approaches deliver AI’s transformative potential?

2025 is a pivotal year for AI. In the words of CIO magazine, “…playtime is over.” Businesses are moving beyond experimentation and PoC to deployment – with tangible returns expected. Adopting AI focuses on the "how."
In a book written for executives, technology leaders, project managers, and consultants on the frontlines of AI deployment, authors Healy and Gibbons propose a three-fold answer: Workforce, Culture, and Ethics & Governance.

The authors, both techno-optimists and business ethicists, begin with a fulsome account of why claims like Google’s Sundar Pichai’s assertion that AI is “more profound than fire and electricity” are not hyperbole but might even understate AI’s potential. They provide an up-to-the-minute overview of the latest AI applications as of mid-2025, including an in-depth exploration of AI agents and their implications for businesses, arguing that AI agents are capable of autonomously managing workflows, analyzing data, and making decisions, and thus could redefine the boundaries of what organizations and individuals achieve.

Turning to Workforce and Culture, Healy and Gibbons outline why a People First strategy is essential for successful AI adoption and what leaders must do differently to make this approach work. Unlike prior waves of technology, AI demands not just adoption but rethinking organizational DNA, in other words, systemic change that requires leaders to balance organizational restructuring, process redesign, workforce adaptation, culture change, and unprecedented ethical challenges. Drawing on their experience at firms like Deloitte, Morgan Stanley, IBM, and PwC, they offer practical insights for navigating these complex challenges.

In the final section, the authors take a cautionary tone. Unlike prior technologies such as the internet or cloud computing, AI places immense ethical strains on leadership. From existential risks to day-to-day challenges like bias, transparency, privacy, and accountability, AI presents ethical dilemmas more profound than any prior human innovation. Healy and Gibbons conclude with concrete guidance for navigating AI legislation, managing risks, and adopting governance strategies that align with this unparalleled technological revolution.

Adopting AI studiously avoids reprising anything previously written on AI – inviting those at the coalface of adoption to consider ideas not found in other books that have, as the authors put it, “done a search and replace” on what has been written about previous transformational technologies.