Harvard Business Review

Senior leaders invest heavily in building engaged organizations. Yet new research, involving more than 4,300 managers and employees, found a hidden cost eroding those returns. When unexpected work arises (the kind that wasn’t on anyone’s radar but needs to get done), managers systematically turn to their most intrinsically motivated employees, assigning them nearly 70% of additional tasks. Why? They assume these employees will enjoy the extra work and won’t burn out from it. Both assumptions are wrong. Over time, this disproportionate allocation reduces job satisfaction and increases turnover intentions among the very employees organizations work hardest to recruit and retain. The research identifies three low-cost interventions to assign work more equitably.

Leaders often struggle to assess whether their employees are using AI successfully. Often, they default to measuring what’s easily observable: how much they’re using AI tools. To get a clearer picture, researchers partnered with KPMG and observed how 2,500 employees used LLMs over an eight-month period. They identified certain patterns that indicated sophisticated use: specific prompting strategies, clear and ambitious requests, and a level of comfort with the tools. They used these signals to better understand what set sophisticated users apart and found that top users: were ambitious with how they approached AI, treated it as a reasoning partner, delegated complex tasks with clear objectives, and treated AI as a general cognitive tool rather than a mere productivity tool. KPMG then used these findings to help the company advance from its already high adoption rate for AI to patterns of sophisticated use.

At American firms, accent bias can quietly shape whose ideas gain traction at work by depressing attention and engagement for speakers with nonnative English accents. Drawing on an analysis of 5,000+ English-language TED Talks, research finds a consistent “accent penalty” in views and likes that persists even after accounting for topic, speaker expertise, visibility, and other indicators of content quality. A follow-up experiment with 1,300+ U.S. adults helps explain why, showing that accented speech increases cognitive effort and reduces perceived warmth and trust, which in turn lowers interest and willingness to share. Because attention functions as a form of organizational currency, these dynamics can distort recognition, influence, and learning in global teams. Leaders can mitigate the effect by redesigning meetings and evaluations and by raising awareness of processing fluency–driven bias.

Employees today experience far more organizational change than in the past, yet their willingness to support it has sharply declined. To help employees thrive through continuous transformation, executives must move beyond top-down mandates by creating channels for employee ideas, fostering safe-to-fail cultures, and ensuring managers can clearly explain why each change matters.

AI is reshaping online search in ways that reduce friction for consumers while increasing it for businesses. Large language models such as ChatGPT and Copilot now function as answer engines, synthesizing information into a single response. AI-powered summaries like Google Overviews further reduce click-through rates, delivering answers without requiring visits to branded websites and compressing the customer journey. This shift creates three strategic imperatives. First, branding is moving from paid persuasion to AI-mediated recommendation. As consumers increasingly trust algorithmic guidance, firms must ensure their ideas, data, and distinctive concepts are clearly associated with their brand. Second, traditional SEO is losing its edge. Companies must shift from optimizing pages for clicks to engineering recall inside AI systems—publishing original data, naming proprietary frameworks, and attaching credentialed experts to insights. Third, marketing must target a new audience: machine algorithms. Structured content, consistent positioning, and third-party validation now shape visibility. Winners will design their brands to be cited, remembered, and recommended by machines.

Today’s uncertain environment—marked by economic instability, tough competition, and growing demands related to AI—has prompted many board members to take on more operational roles, which can be disruptive to the leadership teams executing the work. Leaders who diagnose what’s driving the board’s overreaching behavior, rebuild clarity with their own teams, and put simple communication structures in place can stop drift before it becomes dysfunction. When everyone is clear on their role, the board shifts from bottleneck to strategic partner, freeing the leadership team to lead with confidence, focus, and speed.

There’s been much speculation (but little evidence) regarding AI’s potential to eliminate jobs and radically alter the labor market in the U.S. and abroad. A new study sheds some early light on how the new technology has impacted the U.S. market: in it, researchers find evidence that generative AI is reshaping, not uniformly erasing, white-collar work. Analyzing nearly all U.S. job postings from 2019–March 2025, the study shows that openings for routine, automation-prone roles fell 13% after ChatGPT’s debut, while demand for more analytical, technical, and creative jobs grew 20%. The study argues that firms’ choices—especially around reskilling and integrating AI as an augmentation tool—will determine whether workers face displacement or new opportunity ahead.

Senior leaders often decide how fully to engage in meetings based on whether a topic sounds interesting—and multitasking or disengaging during more routine meet ups. But a new study found that this decision-making may be flawed: people systematically underestimate how engaging and valuable “boring” discussions become once they participate. The research found that while passive alternatives—listening to recordings or reading summaries—felt as dull as people expected, real-time interaction on topics rated “boring” consistently proved more engaging than people expected—and participants were much more likely to desire a follow-up conversation than they had anticipated at the outset. By reframing expectations and investing attention—especially in non-discretionary meetings—executives can unlock hidden value in mundane exchanges, build trust with their employees, and avoid the costly blind spots caused by inattention.

A conversation with the University of Utah’s Jay Barney about how leaders who successfully drive cultural change communicate through authentic, compelling stories.

Many leaders believe candid negative feedback improves performance, but when criticism feels belittling or humiliating, it often produces the opposite effect. Research drawing on employees’ firsthand accounts shows that destructive criticism—especially when it attacks character, lacks guidance, or occurs publicly—undermines confidence, suppresses learning and innovation, and drives disengagement and turnover. Leaders can prevent these outcomes by setting clear guardrails for feedback, focusing criticism on specific behaviors and next steps, and repairing trust quickly when feedback causes harm.

Our relationships at work matter. They make us happier, more productive, and more engaged. They help us weather tough times and celebrate good ones. And they’re built through thousands of small interactions, many of them messy, awkward, and imperfect. But what happens when we start handing those interactions over to AI or allow AI to intermediate them? There are costs to bringing AI into our work relationships. We are not just saving time or reducing friction. We’re outsourcing the very moments that create connection. Here are guidelines for how to navigate when and how to use AI to solve problems with other people along with recommendations for how to be more intentional about when and how we use it, especially when it comes to relationships with colleagues.

Historically, the CEO’s role has been to guide their employees through challenging shared experiences. But today, times have changed, and executives are facing backlash against this form of empathetic leadership. In this issue of the HBR Executive Agenda, editor at large Adi Ignatius speaks with Harvard Business School’s Bill George about purpose-driven leadership, and asks the question: Have today’s leaders become too cautious?

When an organization faces turbulence like leadership turnover, political infighting, or broken processes, it instinctively leans on its most competent people to restore stability. These leaders become the unofficial shock absorbers: fixing what’s broken, mediating conflict, and maintaining performance when others are distracted or disengaged. The most reliable leaders rarely notice when the system starts leaning on them too heavily. It begins with trust—“We know you’ll handle it”—then turns into dependence—“We can’t do this without you.” Over-reliance on competent leaders may keep an organization afloat, but it hinders its ability to adapt. To keep your competence from becoming a liability, 1) stop buffering your team and reflect the system back; 2) stop fixing everything and build capacity; and 3) stop translating everything and clarify what’s yours.

AI’s greatest economic impact will come not from automating tasks but from dramatically lowering the “translation” costs that keep teams, tools, and data from working together. By extracting structure from messy, fragmented inputs and continuously reconciling them, AI makes it possible to coordinate complex projects without forcing everyone onto common standards or platforms. This shift enables new strategies and new forms of competition, which in turn will reconfigure how value is created and captured across ecosystems.

A conversation with psychology professor Jamil Zaki about the negative consequences of a cynical mindset.