AI is changing what employees need to learn

Artificial intelligence is changing what employees need to learn, and learning and development teams must adapt quickly, according to a report from HRD Connect. The publication spoke with Chloe Bryars, Head of Learning and Enablement at MHR, during the company’s World of Work 2026 event.

Bryars said AI is not simply creating a need for more training. It is changing what employees need to learn and how organizations need to think about development. The technology is changing so quickly that L&D must move beyond teaching basic AI operation.

Critical thinking becomes a core AI skill

MHR provides employees with education around cybersecurity, data awareness, and safe AI use, including how to work with and manage AI agents. But Bryars said the skills conversation is already moving beyond teaching people how to use the technology. Employees need to challenge AI-generated answers rather than simply accepting the first output.

Critical thinking, communication, and judgement could become more important as AI adoption grows. MHR’s learning team applies this principle itself by using an AI agent to support learning content creation and accessibility, while retaining human oversight. Teaching employees how to operate AI may become relatively straightforward, but teaching them when to question it could be much harder.

Protecting time for development

MHR research found that 94% of leaders believe L&D improves performance, yet lack of time remains one of the biggest barriers to learning. To address this, the company has been formally scheduling development time for its consultancy population. Rather than asking employees to find spare time between customer commitments, upskilling time is blocked out in their calendars over the year.

Employees provide feedback on whether they were able to use the time and what prevented them if they could not. Bryars said this approach has increased uptake of development time and reduced blockers. Protecting that time also changes how colleagues perceive it, giving them empowerment to use it for what they need. Learning needs to be treated as a business objective rather than an optional extra.

Measuring impact beyond course completion

Making time for learning is only valuable if it improves performance. For Bryars, measurement needs to begin before a program is designed. MHR’s learning team works with managers to establish what success should look like, then builds training and metrics around that outcome.

MHR gathers feedback immediately after training and then at later stages, including around six weeks and six months afterwards. That moves measurement beyond completion and satisfaction towards whether employees retained what they learned and applied it in their roles. AI can help identify aggregate trends within that feedback, but Bryars stresses that people still need to examine the detail and challenge what the technology produces. It is a tool to support, not for decision-making.

What this means for HR teams

For HR, payroll, and recruiting teams, the shift has practical implications. Recruiters may need to assess candidates for critical thinking and judgement alongside technical AI skills. L&D teams may need to redesign programs to emphasize questioning AI outputs rather than just using tools. Payroll and HR systems may need to track protected learning time and outcome-based metrics.

Bryars also raised a concern about entry-level roles. Junior positions often contain routine tasks that AI can perform, but those jobs have traditionally provided the experience employees need to progress. Removing those opportunities may create short-term efficiencies but contribute to longer-term skills shortages. Organizations need to consider how people will acquire the experience those tasks previously provided.

MHR is working on skills mapping within professional services, building a clearer skills taxonomy that can inform recruitment, L&D, and talent management. This moves L&D away from being primarily a provider of courses towards becoming part of the organization’s wider talent infrastructure. Rules on employee development and AI use vary by jurisdiction, so HR teams should consult local regulations.

Sources: HRD Connect