How AI Cuts Employee Training Time and Boosts Proficiency
13 Oct 2025
Discover how AI transforms employee training, reducing time to proficiency and enhancing skill development across industries.
The rapid integration of AI into business operations is no longer an abstract concept - it is a reality reshaping how companies train, manage, and support their teams. In today’s fiercely competitive industries, particularly for founder-led SMEs in the United Kingdom, understanding the transformative power of AI in employee training can be the difference between stagnation and exponential growth.
This article delves into practical insights and strategies shared by Judy Stone, Group Vice President and Chief Learning Officer at TEK, a global customer experience leader. Stone recounts her organisation's journey to revolutionise employee training with AI, from reducing the time it takes employees to reach proficiency to building a more adaptive, engaging, and results-driven learning environment.
The Training Challenge: Why Traditional Methods Are Failing
For decades, training programmes have followed the same formula: static courses, PowerPoint presentations, and passive learning environments. While these legacy methods may have served businesses in the past, they are no longer effective in engaging modern learners, particularly in fast-paced industries where time and attention spans are at a premium.
Judy Stone explains that many organisations continue to rely on outdated approaches to training, even with AI technology at their fingertips. "Companies are using AI to do what they already do - just faster", she notes. "That’s not enough. To truly unlock AI’s potential, we need to think beyond efficiency and reimagine what training could look like."
How AI is Revolutionising Learning and Development (L&D)
1. AI-Powered Simulations for Real-Time Practice
The cornerstone of Stone’s initiative was embedding AI-driven chatbots into the training curriculum. These chatbots simulate real-life scenarios, allowing employees to practise their skills in a safe, judgement-free environment. Whether it’s handling customer service calls, diagnosing technical issues, or closing a sale, employees can practise as many times as needed until they build confidence and proficiency.
This approach addresses a critical gap in traditional training: the lack of hands-on application. "Learning doesn’t happen by passively sitting and listening", Stone emphasises. "You need to apply it, practise it, and receive feedback." The AI-powered role-play bots not only provide instant feedback but also allow employees to refine their skills without fear of embarrassment.
2. Accelerating Time to Proficiency
One of the most significant metrics in employee training is "time to proficiency" - how quickly a new hire can perform their role at a competent level. By integrating AI, TEK reduced this time by measurable margins, enabling employees to contribute effectively sooner. For industries with high turnover rates or complex onboarding processes, such as customer service and tech support, this capability is a game-changer.
3. Personalised and Adaptive Learning
Gone are the days of one-size-fits-all training. AI enables tailored learning experiences that adapt to each employee’s strengths, weaknesses, and pace. For example, an AI system can identify specific skills an employee needs to work on - such as improving empathy during customer calls - and provide targeted practice scenarios designed to develop that skill.
4. AI Coaches in Leadership Development
While much of the initial focus was on frontline roles, TEK has extended its AI applications to leadership development. AI-powered coaching platforms analyse performance data and identify behaviours that drive successful outcomes. For example, a team leader struggling with time management might receive tailored recommendations and simulations to refine their skills.
Leadership development is particularly critical for SMEs looking to scale, as strong leaders cascade knowledge effectively across teams. Stone observes, "It’s a hard time to be a leader, and they need all the help they can get."
Overcoming Barriers: The Mindset Shift Required for AI Adoption
For many organisations, the biggest hurdle in adopting AI isn’t the technology itself - it’s the cultural and mindset shift. Stone highlights two critical challenges:
1. Moving Beyond Incremental Improvements
Many companies adopt AI with the aim of making existing processes faster or more efficient. While this approach has value, it misses the larger opportunity to reimagine processes entirely. Stone advises businesses to start with a "holy grail ambition" - a bold vision for what training could look like if there were no constraints.
For example, instead of focusing on how to make traditional training shorter, organisations should ask: "What would it take to deliver a fully immersive, hands-on learning experience that ensures proficiency from day one?"
2. Embracing Constant Change
Change management is no longer a linear process with a defined endpoint. With technology evolving daily, organisations must train their teams to adapt to continuous change rather than seeking stability. Stone argues that this new paradigm offers freedom: "It takes away the notion that you have to get to perfection. You just need to keep iterating, learning, and improving."
Building the Foundations for AI-Enabled Training
For SMEs ready to embark on their AI journey, Stone offers several practical steps:
Create Dedicated Teams for Innovation: Successful AI adoption requires focus. TEK employs a small but specialised team, led by a PhD in neuroscience, to evaluate the latest AI tools and pilot them internally. This ensures the organisation stays ahead of the curve without overburdening day-to-day operations.
Redefine Roles and Competencies: Traditional roles in L&D, such as instructional designers, must evolve. The new learning experience designer role combines technical expertise with a deep understanding of evidence-based learning principles, extending their influence beyond the classroom to real-world performance outcomes.
Invest in Skills Taxonomies: TEK has developed bespoke taxonomies that map specific skills and behaviours to performance metrics. These taxonomies guide both human and AI coaches in delivering targeted feedback and training, ensuring measurable results.
Pilot, Test, Iterate: AI tools vary widely in quality and capabilities. Stone’s team conducts rigorous head-to-head evaluations of AI solutions, ensuring they only adopt platforms that align with their evidence-based learning standards.
Looking Ahead: The Future of AI in Training
The potential of AI in learning and development extends far beyond what most organisations have realised. In the coming years, expect to see:
Hyper-Personalised Learning: AI systems that not only adapt to an individual’s needs but also anticipate them, offering just-in-time training based on real-time performance.
Seamless Integration with Workflows: Learning will no longer be a separate activity but will occur in the flow of work, aided by tools like AI coaches and sentiment analysis during live interactions.
Redefining ROI for Training: With AI, measuring the true return on investment for training initiatives - with clear financial impact - is becoming more feasible than ever.
For United Kingdom-based SMEs, which often juggle limited resources with ambitious growth goals, embracing AI in training isn’t just a competitive advantage - it’s a necessity.
Key Takeaways
AI-Powered Simulations: Enable employees to practise real-life scenarios in a pressure-free environment, accelerating learning and building confidence.
Reduced Time to Proficiency: AI can significantly shorten the time it takes new hires to perform competently, saving time and resources.
Customised Learning Paths: Adaptive AI systems personalise training to address individual skills gaps, enhancing outcomes for every learner.
Leadership Support: AI-driven coaching tools are improving leadership development, helping leaders better support their teams.
Cultural Transformation: Organisations must shift from a fixed mindset to an agile, iterative approach to change and learning.
Dedicated Innovation Teams: A focused team for exploring and testing AI tools is crucial to staying ahead in a rapidly evolving landscape.
Skills Taxonomies: Bespoke taxonomies link specific skills to performance outcomes, guiding targeted coaching and training strategies.
Future Focus: The integration of AI into workflows and hyper-personalised learning is shaping the future of L&D.
AI is not just a tool for efficiency - it’s a catalyst for transformation. By harnessing its potential, SMEs in the UK can not only streamline training but also create more engaged, productive, and adaptable workforces. The question is no longer whether to adopt AI, but how far you’re willing to take it.
Source: "How to Use AI to Cut Employee Training Time by 20% (and Boost Proficiency)" - HR Leaders - Shaping the future of work., YouTube, Aug 11, 2025 - https://www.youtube.com/watch?v=omRGBDqBLQA
Use: Embedded for reference. Brief quotes used for commentary/review.