How Gen AI Could Change the Value of Expertise

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How Gen AI Could Change the Value of Expertise

By Joseph Fuller et al., | Harvard Business Review | March 10, 2025

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3 key takeaways 

  1. The gen AI revolution is changing not just what but also how we learn. Traditional learning curves are being redrawn, creating new paradigms for skill acquisition and career advancement. This shift demands a fundamental rethinking of how businesses approach talent management and how individuals navigate their careers.
  2. The authors’ analysis suggests that, in the next few years, the better part of 50 million jobs will be affected one way or the other. The extent of those changes will compel companies to reshape their organizational structures and rethink their talent-management strategies in profound ways. The implications will be far-reaching, not only for industries but also for individuals and society. Firms that respond adroitly will be best positioned to harness gen AI’s productivity-boosting potential while mitigating the risk posed by talent shortages.
  3. The organizations that thrive will be those that embrace the fluid nature of AI-augmented learning curves. They will view each curve as not a fixed trajectory but a dynamic path that can be reshaped and optimized with the right strategies and tools.

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(Copyright lies with the publisher)

Topics:  AI and Learning, AI and Jobs, AI and Strategy, AI and Organizational Structure

AI will open doors for some workers while closing them for others.  Approximately 12% of U.S. workers are currently in occupations where gen AI is likely to automate away a significant proportion of the tasks associated with entry-level jobs. That, ineluctably, will lead to a reduction in entry-level hires. It’s already happening: With the advent of Microsoft’s gen AI–powered Copilot, hiring into entry-level software engineering jobs has largely stalled. Conversely, about 19% of workers are in fields where gen AI is likely to take on tasks that demand technical knowledge today, thereby opening up more opportunities to those without hard skills.

The authors’ analysis suggests that, in the next few years, the better part of 50 million jobs will be affected one way or the other. The extent of those changes will compel companies to reshape their organizational structures and rethink their talent-management strategies in profound ways. The implications will be far-reaching, not only for industries but also for individuals and society. Firms that respond adroitly will be best positioned to harness gen AI’s productivity-boosting potential while mitigating the risk posed by talent shortages.

With gen AI reshaping the landscape of work, businesses face a new reality that demands strategic adaptation. The parallel impact of raised and lowered barriers across different occupations will require a fundamental rethinking of organizational structures and talent strategies. Businesses will have to grapple, in particular, with the implications in the following areas.

  1. Organizational structure.  New opportunities and challenges will emerge as gen AI reshapes organizational pyramids in some parts of the firm into more rectangular or diamond-like structures. Such structures may facilitate faster information exchange and more direct communication between organizational levels, allowing more agile decision-making and execution. They may also enable businesses to deploy smaller, more-agile teams.
  2. Talent strategy.  Evolving organizational hierarchies will require companies to rethink how they handle recruitment and career development. Companies will probably focus recruiting efforts on fewer skills providers. Talent-acquisition teams will need to become significantly more agile to access talent pools that align with rapidly evolving technological demands.
  3. Training models.  Once gen AI becomes widely integrated into the workplace, that will mean identifying and then investing in the skills that will be increasingly important to each role—and that keep those who are most experienced at the top of their game. Diamond-shaped organizations will need to restructure learning paths to facilitate the lateral transfer of experienced workers from other fields and workers whose careers may be disrupted by AI.
  4. Company-specific knowledge.  As gen AI automates more-generalized skills, company-specific knowledge is likely to become an increasingly important factor in unlocking worker productivity. Companies will want to focus on identifying and cultivating this knowledge, and on whether and how to build infrastructure to make it more accessible to workers. This will involve decisions about the creation of new knowledge management systems, such as internal wikis and AI-powered learning platforms. Organizations will need to consider how much of a barrier they want company-specific knowledge to be and how to balance the benefits of specialization with the need for workforce flexibility.