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Closing the AI Training Gap in the Workplace

How HR leaders can turn learning into measurable workforce performance

Artificial intelligence is entering the workplace faster than many organizations anticipated. Employees are experimenting with new tools to write, analyze information, and automate tasks, often before formal training or policies are in place.

Recent reporting from Personnel Today highlights the scale of the challenge. Around 70% of UK employees are experimenting with AI tools at work, while only 19% have received formal training. The result is a workforce that is largely learning through trial and error.

For HR leaders, this creates a familiar challenge. Training programs are being introduced quickly to keep pace with technology, but it is often difficult to answer a simple question: are the messages in the training actually resonating with employees?

Course completion rates and attendance metrics only show that employees participated. They rarely reveal whether people understood the training, felt confident applying it, or believed it was relevant to their work.

As organizations introduce new skills programs, particularly around emerging technologies like AI, understanding how employees interpret and respond to training messages becomes critical.

Understanding how training messages resonate

Training is not just about delivering information. It is about ensuring the message connects with employees in a way that influences behavior and performance.

Employees may complete training but still feel uncertain about how to apply what they have learned. Others may interpret the guidance differently from how it was intended. Without visibility into how training messages are being received, HR teams risk investing in programs that fail to translate into meaningful capability.

This is where the concept of Message Resonance Score™ becomes valuable.

Message Resonance Score™ helps organizations understand how strongly specific messages resonate with an audience by analyzing real language and sentiment. Applied in a workplace context, it can provide insight into how employees respond to training content, communication, and learning initiatives.

Aligning training with employee understanding

Talking Medicines uses Message Resonance Score™ to analyze how people discuss experiences, language, and perceptions at scale. When applied to employee voice data, this approach helps organizations understand how training messages are interpreted across the workforce.

Rather than relying solely on surveys or completion metrics, HR leaders can see whether key learning messages are truly landing with employees.

This enables organizations to:

• Identify where training messages are unclear or misunderstood
• Understand which learning topics resonate most strongly with employees
• Detect confidence gaps in emerging skills areas such as AI
• Align learning programs more closely with real workforce needs

By connecting training content with real employee language and sentiment, organizations gain a clearer view of how learning translates into workplace behavior.

Supporting HR through the AI learning curve

AI will continue to reshape how employees work and how organizations develop skills. For HR leaders, the challenge is not only introducing new training programs but ensuring the messages within those programs are understood and applied.

Using approaches like Message Resonance Score™, organizations can better understand how employees interpret training, where gaps remain, and how learning can more effectively support workforce performance.

If you would like to understand how Talking Medicines can help measure how training messages resonate with employees, get in touch with our team to start the conversation.

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