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| | Brought to you by Alex Panas, global leader of industries, & Becca Coggins, global leader of functional practices and growth platforms
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| | | | Companies are using AI across more business functions and deploying a range of tools with the goal of transforming their operations. McKinsey’s latest survey on the state of AI shows that employees say they are more productive, but the share of organizations reporting financial impact from the technology has not changed. At the same time, employees are navigating uncertainty about how AI will reshape their work and careers. This week, we look at how leaders can build higher levels of trust to capture more value from their AI initiatives. | | | |
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| | | AI is compelling leaders to ask their teams to work in fundamentally different ways. Change brings uncertainty, so leaders must earn employees’ trust to encourage them to join their AI journey, say McKinsey’s Aaron De Smet, Bonnie Dowling, Holly Price, and Ignacio Fantaguzzi. “If people are unwilling to engage in this shift, even the most robust AI strategy will struggle to translate technological potential into lasting enterprise value,” they observe. When employees believe AI can enhance their capabilities, not just replace their work, they are more willing to adapt. The authors identify four steps leaders can take to build long-term trust: | | | | | Have a clear plan for creating value with AI and communicate honestly about what is known or unknown and how decisions will be made. | | | | | | | Talk to people across the organization to get a fuller picture of how AI initiatives are unfolding. | | | | | | | Invest in people to help them succeed throughout the transition, including through sustained capability building. | | | | | | | Equip leaders at all levels with the knowledge and skills needed to guide their teams through AI transformation. | | | | |
| | | | That’s the share of surveyed leaders who say their organizations are in the “reinvention” stage of AI adoption, meaning they are redesigning roles, workflows, and operating models, according to a global survey of 750 employees and leaders across industries. McKinsey’s Aaron De Smet, Drew Goldstein, Holly Price, Tanguy Catlin, and their coauthors note that 48 percent of leaders from companies in this cohort report they are realizing enterprise value from AI, compared with 24 percent or less among companies at earlier stages. | | |
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| | | “Traditional change management isn’t enough to spur new ways of working that lead to value from agentic adoption.” | | | McKinsey’s Arne Gast, Ben Fletcher, Karim Thomas, Natacha Catalino, Thibaut Larrat, and Rahul Varma say companies need a more dynamic approach to change as AI transformations redefine how work is shared between humans and machines. “In the agentic era, change leadership should be continuous, behavior-led, and embedded in the work itself,” they say. This approach means leaders should build conviction and trust among their teams, give employees time to commit to joining the AI journey, help people expand their skills, and redesign the company’s entire operating system.
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| Another facet of building trust during AI transformations is ensuring that the technology itself is reliable before allowing agents to work autonomously. Leaders should design AI initiatives for trust first and speed second, McKinsey’s Rich Isenberg says in an episode of The McKinsey Podcast. To generate value, companies need strong AI governance and risk management, including clarity on decision rights, accountability, escalation paths, and controls. “When something goes wrong, customers don’t care that it’s AI. They care that it’s safe, fair, and fixable,” Isenberg says. “If you’re a tech leader, make sure your teams convince you they’ve earned autonomy. Don’t grant it just because agents can do it.”
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| Given how quickly AI continues to advance, how will it shape the future of the business world and, more broadly, humanity? McKinsey’s annual book recommendations from leaders worldwide feature several AI-focused titles that can shed light on this question, including the following: | | | | | A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains by Max Bennett. This book was recommended by economist Daron Acemoglu, who says, “We need to understand how human intelligence differs from artificial intelligence to best work out how to combine AI with human capabilities.” | | | | | | | Human Raised: Nurturing Connection, Curiosity & Lifelong Learning in the Age of AI by Dana Suskind. This book was recommended by organizational psychologist Adam Grant, who says, “It’s a beautiful book about how to preserve our capacities for connection, curiosity, and critical thinking in the age of AI.” | | | | | | | Lead by fostering trust in your AI vision. | | | | | —Edited by Eric Quiñones, senior editor, New Jersey
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| | | | | AI high performers stand out for how they put it to work—and translate adoption into measurable impact. Explore this latest research on coding agents and other agentic AI tools, investment and costs, workforce implications, and the practices that can help turn AI momentum into lasting enterprise value. | | The state of AI in 2026  | | | |
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