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Much of the discussion around AI has focused on how efficiency gains will help employees create new forms of value. But does this hold true in all cases? A new HBR article explores who captures AI’s upside and who absorbs its costs. Based on 18 interviews across two major consulting firms, it finds AI is enabling role elevation at the junior and senior levels, but not in the middle. Junior consultants are moving into work they may not have done as early before, such as joining strategy conversations that were once more likely handled by senior staff. Senior leaders are also expanding the scope of work they can take on. But the middle manager layer is where the pressure seems to be building. Managers are now expected to validate AI outputs, catch what the authors call workslop (AI-generated content that looks professional but lacks substance), coach teams on AI use, and maintain quality standards, while still facing the same delivery pressure and limited formal support. This adds to an existing middle-manager burnout problem, already shaped by leaner structures, layoffs, and broader spans of control. It also raises a longer-term concern: if managers spend more time checking AI-generated work, they may have less capacity for the coaching and apprenticeship that help develop future leaders. While based on a small sample of consultants, the article usefully challenges the simplistic “AI frees everyone up for higher-value work” narrative. Question: When your organization measures AI adoption success, are you tracking what is happening to manager workload and capacity, and the unintended consequences on other important outcomes?
