Approval.

That’s one thing most training has in common. Subject matter experts (SMEs) add requirements, stakeholders sign off and legal gives their blessing.

Often, it doesn’t even matter if the final solution addresses the problem or not; at least the content was risk-free!

But in the artificial intelligence (AI) era, when every employee gets their own version of content, managing risk requires a different approach to governance.

The Promise of Personalization

We’ve talked about personalized learning for years — moving beyond one-size-fits-none training and adapting to individual needs.

AI makes this a reality. Platforms can match people with the right support at the right moment using data from across the workplace. Employees struggling with specific skills automatically receive refreshers while managers are nudged to provide feedback. But personalization is just the beginning.

AI can now take source material and generate unique content for each employee. These tools can determine the right focus, format, language and reading level to suit every worker. A single standard operating procedure (SOP) can instantly become a podcast, step-by-step diagram, reinforcement scenario and interactive coaching session — all with just a few clicks.

Technology is accelerating the shift from personalized to bespoke learning: assets tailored to the individual at scale. It’s also changing the nature of governance. After all, you can’t review every version of AI-generated information moving through your organization.

Does this mean AI is putting your business at risk?

The Illusion of Control

We’re comforted by the notion that all learning and development (L&D) content is “approved.” Each course goes through a review cycle and, as a result, the slides are the right shade of blue and every word aligns with company nomenclature. But how much of the information available to employees actually gets this level of scrutiny?

The truth: very little. Most learning happens outside the official channels. People swap knowledge in email, Teams messages and break room conversations. None of that gets brokered, branded or blessed. Yet, this information drives everyday performance.

This doesn’t mean we should acquiesce control to AI. Moving from static documentation to a dynamic knowledge ecosystem is a big shift. To make this leap, we must first acknowledge an important fact — L&D doesn’t own workplace learning.

Finding the AI Middle Ground

To unlock AI’s full potential, we must loosen our grip. We must redraw the line between corporate information control and a free-flowing, AI-enabled knowledge ecosystem.

Not every topic carries the same level of risk. Customer service skills are much less rigid than financial disclosures and medication handling protocols. Work with key partners to define sensitivity levels for critical subjects. Determine clear boundaries for how content is created, reviewed and shared across every format, including AI-generated materials.

Documenting the rules is only the first step. People still need the awareness and capability to apply them effectively, especially when leaning on AI-generated guidance. L&D plays a vital role in helping employees understand the rules, recognize risk and make sound decisions. Mistakes will happen, but we can’t blame the technology any more than we’d blame a co-worker for bad advice.

AI can also help manage this balance. By embedding guardrails within AI tools, organizations can guide how information is crafted and ensure outputs stay within defined boundaries. Review loops can automatically flag content that deviates from policy, exceeds confidence thresholds or references unverified sources before it ever reaches employees. In this way, AI becomes both a creator and a quality control partner.

The Future of Governance

Trust will shape the evolution of L&D. Bespoke support is now within reach. We finally have the tools to give every employee the help they need, when they need it. The rules aren’t going away (and they shouldn’t), but that can’t stop us from advancing our function. We must leverage AI to reshape governance so it keeps pace with innovation instead of holding it back.