6 Research-Backed Strategies to Modernize Training Programs

Generative AI has been transforming the learning space since 2022, and for good reason.
According to LinkedIn’s 2024 Workplace Learning Report, 52% of organizations say AI is speeding up skill development, while 68% have adopted personalized learning paths powered by AI. Even more telling, organizations using AI in learning are seeing tangible business impact and measurable returns.

But that doesn’t mean relying solely on ChatGPT. Today, there are AI-powered platforms built specifically for corporate L&D that can turn internal materials — documents, podcasts, interviews, even YouTube videos — into training quickly and efficiently.

The output goes beyond plain text, too. These tools can generate interactive content like quizzes, case studies and task-based exercises, plus get detailed reports to track progress and guide decision-making.
These platforms can help build courses on anything from product features and company workflows to role-specific training for project managers, client teams, factory workers or methodologists.

1. Leverage Platforms for Corporate Learning

When it comes to AI and upskilling, generative AI is usually the first thing that comes to mind, but what’s often overlooked is AI’s power to spot real skills gaps before the training even begins.

For example, federal agencies are using AI tools to evaluate the skills their workers have and the skills they’re missing. A 2024 Pluralsight survey found that 64% of agencies have already run skills checks and used the results to upskill roles most impacted by AI, like data analysts and cybersecurity specialists.
Pinpointing real skills gaps is one of the smartest actions to take before building an AI training program. What do employees actually need to learn? Industry experts keep coming back to this. The takeaway is to not just throw AI-generated training at employees but start with clear needs.

In practice, this may look like AI pulling data from performance reviews, training records, job descriptions and surveys to build skill profiles for each employee. These profiles are then matched against current and future role requirements. Companies can also use AI-powered skill assessments and simulations, helping target training where it’s most needed.

2. Start Smart: Identify Skills Gaps First

Evaluating the gaps first is part of a wider shift toward personalized AI-learning. In the US, especially in knowledge and service sectors, adaptive platforms are now tailoring training to each employee. They use machine learning and real-time feedback to adjust the content so it fits employees’ needs, not just a one-size-fits-all plan.

Accenture’s LearnVantage is a good example of personalized AI learning in action, tailoring upskilling by first assessing each employee’s performance, skills and career goals. For example, aspiring managers are served leadership development modules, while technical experts are guided toward advanced certifications.
It’s about delivering the right learning at the right time, in the right format and in a sequence that makes sense.

3. Deliver Personalized Learning Programs

Despite living in a hyper-connected, globalized world, upskilling still isn’t reaching everyone equally. Pew Research found that only 36–39% of U.S. blue-collar workers have taken a class or received training in the past year to improve their job skills. This leads to lower job satisfaction and higher turnover, and more people out of work due to automation and digital skills gaps.

AI upskilling programs could help close these gaps, but only if they’re built with real people in mind. That means keeping them simple, accessible and mobile-friendly, with clear visuals and support for multiple languages. For example, Augmentir’s AI platform for food production workers identifies individual skills gaps and delivers short, tailored video guides straight to employees’ phones. The content adjusts based on performance, so if a technician struggles with a task, the AI offers more targeted support.

4. Design Inclusive Programs for Front-Line and Blue-Collar Workers

Another powerful way companies can close digital skills gaps is through reverse mentoring, pairing employees with different experiences and perspectives for skill transfer. When applied to emerging technologies such as AI, reverse mentoring allows employees who are early adopters of new tools to share insights with colleagues who may bring deeper institutional knowledge or leadership experience. This two-way exchange strengthens both digital fluency and leadership capability, while also boosting engagement by valuing diverse expertise across the workforce.

5. Bridge Skills Gaps Through Reverse Mentoring

Mental health inequities cost the U.S. $477.5 billion in 2024 alone, with $116 billion lost just from reduced productivity. It’s no surprise that more and more companies are weaving well-being into their L&D strategies, recognizing it’s not just good for people, but for performance too.

Forward-thinking organizations are embedding wellness into their training strategies. This might mean integrating breaks for mindfulness or movement, offering workshops on recognizing stress and building resilience, or partnering with experts to provide mental health literacy programs.

For example, fashion retailer Kate Spade partners with the National Council for Mental Wellbeing to offer Mental Health First Aid at Work training for nearly 1,000 store leaders. Such initiatives not only improve employee experience but also strengthen long-term organizational performance.

6. Integrate Well-Being Into Your Learning Strategy

AI and other emerging tools are creating new opportunities for L&D leaders to design programs that are smarter, more personalized and more human-centered. By identifying skill gaps, embracing inclusivity, fostering mentorship and supporting employee well-being, organizations can build learning strategies that keep pace with change and with employee expectations.

Final Thoughts