The Risky Business of Using Generic Generative AI for Management Development

As managers face mounting pressures in today's workplace, many are turning to generic generative AI tools for their development and support. While these chatbots offer 24/7 availability and instant responses, they fall critically short of meeting managers' real development needs across five essential dimensions that drive meaningful performance improvement.

These five essential dimensions – personal relevance, time efficiency, synchronized problem-solving, company context, and expert by design, are further explored in our recent blog post.

Generic Responses Miss Personal Context 

While generic AI chatbots can engage in conversation, their attempts at “personalization” lack focus, largely because the chatbots are just that–generic. They indiscriminately try to remember random facts about the user. This might work well for simple things, like remembering that a user loves spicy food for recipe suggestions, but falls flat when it comes to something as complex as being a better manager. 

Further, the generic AI chatbots lack crucial understanding of the individual manager’s capabilities, personality traits, and team dynamics. Without this personal context, their responses remain generic and may require significant “translation” to be useful. This disconnect means managers must spend valuable time adapting AI-generated advice to their specific situation and strengths – assuming they can accurately gauge which parts of the advice are relevant.

Immediate… But Inefficient: The Time Tax of Generic AI 

Yes, generic AI chatbots respond instantly. However, managers often waste considerable time trying to craft the perfect prompt or sifting through irrelevant responses to find useful insights. Instead of getting relevant solutions they can implement immediately, managers receive suposed best practices that don't address their specific challenges or time-sensitive needs. With research showing managers have less than 25 minutes weekly for dedicated learning, this trial-and-error approach to getting valuable advice represents a significant waste of their limited development time.

Disconnected from Company Context 

Perhaps most challenging for managers is generic AI's inability to account for organization-specific policies, procedures, and cultural norms. This can lead to recommendations that directly conflict with company guidelines, processes or values. Further, with the risk of data leakage through managers sharing sensitive information in public AI platforms, this approach could actually create more problems than it solves.

Research Reliability: The Challenge of Unvetted Sources 

While generic AI tools can access vast amounts of management-related content, they lack the ability to distinguish between credible organizational psychology research and unreliable or outdated management theories. This means managers may receive advice based on debunked practices or unproven approaches rather than evidence-based management principles. In an era where 75% of HR leaders report their managers are overwhelmed, providing unreliable guidance or ‘management mythology’ only compounds the challenge.

The Scale Problem: One Size Fits None 

While generic AI is available to everyone, this creates a new problem: inconsistent and potentially harmful advice spreading across your organization. With managers receiving varying (and sometimes conflicting) guidance based on how they phrase their prompts, organizations lose the ability to ensure their leaders are developing in alignment with company goals and values.

“BYO-AI” as a Significant Security Risk 

As managers increasingly turn to generic generative AI tools for workplace guidance, organizations face a growing security challenge. The trend of "bringing your own AI to work" means sensitive company information–from personnel issues to strategic decisions–is being fed into public AI platforms without proper oversight. When managers share specific details about team dynamics, performance issues, or company procedures while seeking AI guidance, they may inadvertently expose confidential information. Organizations must weigh the perceived convenience of these tools against the very real risk of data leakage and potential compliance violations.

In today's complex business environment, where recent data shows employees under ineffective managers are 15 times more likely to be low performers and three times more likely to leave their organizations, the stakes for getting manager development right have never been higher. While generic AI tools may seem like an attractive quick fix, their fundamental limitations make them inadequate as a primary development solution for today's managers.

To learn more about the five essential criteria for modern manager development solutions, read our companion piece: "The Performance Catalyst: 5 Principles to Developing High-Performing Managers."

Ready to transform how your managers perform and grow? Humancore has created the first AI-powered advisor for managers. To learn more about how an AI-powered advisor can transform your organization's approach to manager development, contact us at [email protected].