Illustration by Eliot Wyatt
On September 8, 2026, Meta launched Muse, a personal AI agent designed to act on a user’s behalf: filling out forms, negotiating, booking travel, and making purchases. Twelve days later, Amazon blocked Muse from shopping on its site, arguing that third-party agents should identify themselves and obtain a retailer’s permission before transacting on behalf of its customers.
Illustration by Jason Ford
Generative AI has produced two competing views about which workers will benefit most. One view is that AI will narrow performance gaps by giving lower performers templates, answers, and coaching directly in their workflow. The other is that AI will widen those gaps by eliminating routine but necessary work, which will allow top performers to spend more time on higher-value activities where they already have an advantage. At the individual task level, high and low performers may both benefit, but the more important question is which effect dominates on net in real jobs, where workers perform bundles of activities. The answer matters for how firms hire, train, organize teams, and adjust practices built for their current talent mix.
AI is advancing so quickly that companies can’t afford to treat it as simply another productivity tool; it is fundamentally reshaping strategy. In this final episode of our special four-part series on how AI is changing leadership, Wharton professor and AI expert Ethan Mollick explains why leaders need to rethink what their organizations are designed to do—and how work gets done. He discusses how AI agents are changing the role of managers, why companies need to experiment rather than wait for proven playbooks, and how leaders can create competitive advantage when everyone has access to the same frontier models. Mollick is author of the forthcoming book Co-Existence: The Next Phase of AI.
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In case you missed it, you can find the rest of our AI series below.
How AI Is Changing Innovation: Why Speed Alone Isn’t a Strategy
How AI Is Changing Communication: Weighing Efficiency with Efficacy
How AI Is Changing Talent, Not Just Tasks: Rethinking Where Human Judgment Matters Most
is a senior director analyst in the Gartner HR practice. They support CHROs and HR leaders to understand and prepare for AI’s impact on the workforce and shape work for the human-AI era. CV engages with clients and speaks on topics including AI’s impact on headcount and roles, AI’s impact on skills, AI literacy, building AI-readiness across the workforce, and the intersection of inclusion and AI.
October 6, 2026
In this week’s The Insider newsletter, technology editor Tom Stackpole shares a story from MIT’s Christian Catalini, who argues that when execution is cheap due to AI, verification
The Insider is a weekly, subscriber-only newsletter, where our managing editor curates HBR stories, research, and ideas that senior leaders shouldn’t miss.
Read more on AI and machine learning or related topics Generative AI, Technology and analytics, Data management, Organizational transformation and Digital transformation
Illustration by Mandy Tsou
Organizations today need to simultaneously perform (run the business reliably for today) and transforming (change the business for tomorrow). The challenge is that most organizations are much
Most companies are transforming for AI faster than their cultures can keep up.
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Somewhere in your company today, an expert rejected a perfectly plausible answer. A controller caught a revenue figure that counted deferred bookings. A security engineer blocked a release that passed every test but would have handed an AI agent write access to the production database. That override, escalation, or reversal is the most valuable data your firm produces. If you record enough of those moments and use them, alongside everything else your firm knows and measures, to train an AI model that learns from each correction, you could, in theory, eliminate the need for managers to route information and coordinate action. In doing so, execution gets turbocharged by automation. You might even be able to eliminate hierarchy altogether.
Leadership|The Mindsets Leaders Need as AI Accelerates the Pace of Business
Illustration by Klawe Rzeczy
AI is changing not only what leaders need to know, but how they need to think. Yet many are struggling to adapt to the speed, uncertainty, and emotional complexity of an
AI is accelerating business transformation at an unprecedented pace. Leaders aren’t keeping up.
Read more on Leadership or related topics Managing yourself and AI and machine learning
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The cybersecurity outlook for small and medium-sized businesses can seem dire. Cybercriminal and nation-state cyberattacks appear to be on the rise, especially against utilities and small businesses. At the same time, there are new AI-enabled cyber risks, including AI agents from frontier labs breaching confinement and attacking other companies. Generative AI and machine-learning models have also streamlined traditional attack vectors. Phishing lures are now hyper-personalized, vulnerability discovery is exponentially faster, and ransomware operations are automated and ubiquitous.
AI is making it faster and cheaper than ever to turn ideas into prototypes, products, and businesses—but that abundance creates new challenges for leaders. In episode 3 of a special four-part series on how AI is changing leadership, we look at the ways industry leaders are using AI to truly gain a competitive edge and innovate for the future. Cisco Chief Product Officer Jeetu Patel explains how AI is changing the pace and nature of innovation, why human judgment and taste become more important when everyone has access to the same tools, and how companies can use AI to tackle problems they couldn’t have solved before. He also discusses the risks of AI agents, why organizations need new approaches to security and oversight, and how leaders can build a culture that embraces experimentation without sacrificing rigor or accountability.
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