How Agentic AI in Training Is Shifting HR Oversight in 2026

Agentic AI – autonomous AI tools that act on behalf of users – is reshaping corporate learning, and many HR teams aren’t ready for the impact. In 2026, it’s inviting new questions about how HR oversees training outcomes.

Many employees are already leaning on AI agents to breeze through compliance training and even parts of upskilling programs. On paper, completion rates look healthy. But in reality, the learning isn’t always sticking. 

That gap creates compliance risk and wasted investment. It leaves HR leaders with a critical question: How do you measure and validate real learning when AI is doing the work for employees?

Part of the challenge comes from a fundamental execution gap. Nearly half (44%) of companies don’t use proven learning methods like mentorship, coaching, or peer support – and have no plans to start, according to Absorb Software’s 2025 Inside the State of Upskilling report.

At the same time, approximately one-third lack the necessary tools to make upskilling effective. These gaps make it even harder for HR to track learning beyond simple completion rates.

For HR leaders trying to keep employee training effective in an AI-driven workplace, expert guidance can make all the difference. OB Rashid, Chief Technology Officer at Absorb Software, shares practical strategies for adapting compliance training and upskilling programs so learning actually sticks and delivers real results.

The Problem with AI in Learning

Many employees have treated training as a chore, and some are now using AI to get through it. With GPT-5 and other agentic AI tools, workers can assign bots to finish modules and quizzes in their place. This cuts corners on compliance training – and wastes time and money spent on development programs. 

If this trend continues, HR will struggle to secure buy-in for learning and development (L&D) initiatives and compliance training.

Why Completion Rates Don’t Prove Learning

For years, HR teams have measured training success by one number: completion. The problem is that completion has never guaranteed understanding. 

Now, AI has made that weakness impossible to ignore. An employee can finish compliance training and other courses without retaining, or even reading, any content. 

“Completion rates remain a useful baseline, but they fall short in an AI-driven world where agents can accelerate or even auto-complete certain tasks,” Rashid notes. “What matters most is whether employees are applying new skills – and whether those skills make an impact.”

Instead of just tracking “done,” HR teams should look downstream, he advises. For example, sales teams can track post-training improvements in quoting accuracy or deal cycle times. Customer service teams can monitor call resolution times and shifts in customer sentiment. 

“AI agents can continuously track these signals, spotting where employees excel, where they struggle, and how skills are being applied in context,” Rashid points out. “This creates a smarter feedback loop, giving HR visibility into real outcomes rather than surface-level participation.”

To operationalize this, HR teams can focus on specific measures, such as:

• Scenario-based testing to show decision-making skills
• On-the-job performance indicators tied to the training content, and 
• Follow-up assessments spaced weeks later to measure knowledge retention.

These approaches prove learning in ways that course completions never did.

Designing Training That AI Can’t Fake

Employees often find static slide decks and multiple-choice quizzes tedious, while AI can breeze through them. If employees would rather let AI take training for them, it’s a red flag about the content itself.

One of the biggest risks with agentic AI is disengagement. When AI can complete a task for employees, their incentive to engage disappears unless they understand why the skill matters, Rashid explains. Personalization and context are critical. Training should clearly connect to what employees value most – career mobility, advancement, and staying relevant in a fast-changing market. 

Nearly half of executives believe today’s skills will expire within two years, making continuous learning essential for job security and growth. To make training engaging, Rashid recommends:

• Delivering content in formats employees already consume – short videos, mobile-first modules, interactive simulations, or micro-podcasts that fit naturally into workflows. For frontline workers, this might mean replacing traditional desktop training with mobile content that integrates into their workday.
• Aligning learning with tangible outcomes, like career opportunities or new responsibilities.
• Layering in recognition, such as digital badges, leaderboards, or team shout-outs, to reinforce motivation and progress.

By taking these steps, training becomes something employees want to engage with, not just something to get through, he says.

In addition to making training engaging, HR can also deter AI use as a shortcut by building experiences that are harder to fake and more rewarding to complete, like:  

• Interactive simulations that mimic real-world decisions.
• Role-play exercises requiring live participation.
• Adaptive modules that adjust based on employee responses. 

The more relevant and immersive the training, the less incentive to outsource it to AI.

Rethinking the Role of Agentic AI in Upskilling

Blocking AI tools might seem like the easiest solution. Yet we know how quickly new technology reshapes work, and AI adoption is no exception.

Instead of fighting AI, consider how it can actually support learning. For example, AI agents could act as study partners that quiz employees after training, or generate scenarios for practice conversations. 

When framed this way, agentic AI shifts from a threat to a tool that supports learning. 

Rashid explains that HR teams should think of AI agents not just as tools, but as teammates. They can walk employees through unfamiliar processes and offer support exactly when it’s needed, he said. They also surface the right learning moments without interrupting the flow of work.

He refers to AI agents as “career co-pilots,” emphasizing that an effective agent does more than push content – it learns alongside the employee and provides timely feedback to keep them moving forward. 

Leading AI Agents for Effective Learning

Crucially, employees must learn to lead these AI agents, not just use them, Rashid stresses. That includes:

• Delegating tasks to AI agents
• Directing agent behavior toward learning goals
• Evaluating agent output for quality and accuracy

“Forward-thinking HR teams are already taking this a step further by building knowledge bases of internal policies and connecting them to retrieval-augmented generation (RAG) models,” he added. “That allows employees to ask an AI agent a question like ‘What’s our PTO policy?’ or ‘How do I submit an expense?’ and receive real-time answers.”

This strategy – using AI agents to personalize learning at scale – tailors content to each employee’s role, skill gaps, and preferred learning style, Rashid explained.

Action Steps for HR 

HR leaders can take concrete steps to make employee training more effective, measurable, and engaging.

• Revisit success metrics – Shift KPIs from simple completion rates to demonstrated competence, applied knowledge, and practical outcomes tied to business impact.
• Review compliance and upskilling programs – Identify where employees might take shortcuts or where content may be outdated, irrelevant, or easy for AI agents to bypass.
• Make training more engaging – Use scenario-based exercises, interactive simulations, role-play, and applied-learning activities that encourage active participation and skill retention.
• Leverage AI to support learning – Update programs so agentic AI enhances rather than replaces training — acting as study partners, providing real-time feedback, and personalizing learning experiences.

These steps help HR protect learning investments and build training that employees value and apply in their work. 

3 Forward-Thinking Strategies for an AI-Driven Workplace

Rashid emphasizes three areas HR leaders should focus on to prepare for the evolving role of AI in learning and development:

• Clarity – Define what success looks like beyond course completions. Tie learning efforts to measurable impact, such as faster onboarding, stronger sales performance, or improved compliance.
• Adaptability – Agentic AI allows learning to be personalized at scale, but it only delivers value if content, delivery, and feedback loops can adapt in real time. This requires investing in systems that integrate with business operations so you can monitor outcomes where they actually show up: performance, productivity, and growth. 
• Culture – Create a learning environment where experimentation is encouraged, failure is safe, and growth is expected. When employees see learning as a path to career momentum rather than just a compliance checkbox, the benefits extend far beyond the training itself.

By combining the HR action steps with Rashid’s strategic priorities, HR leaders can keep compliance training relevant, make learning stick, and use agentic AI to support workforce growth rather than undermine it.