As learning leaders, we are placed at the forefront of solving skills shortages, predicting future skill needs and evolving the workforce in response to changing technology, strategies, market opportunities and more. It’s a tall order, made all the more complex by rapid shifts in artificial intelligence (AI), hybrid workforces and the push to become skills-based organizations. Put another way, the 2025 training professional needs to master adaptability and agility across their strategy, teams, processes and technology. We must be ready for today while also preparing for an uncertain future.

In discussions with enterprise business, learning and technology leaders, five distinct change areas emerge as key to strengthening organizations’ approach to effective learning.

5 Changes to Strengthen Your Learning Strategy

1. Unlearn to Relearn

In a world where yesterday’s best practices can quickly become obsolete, learning leaders must embrace a mindset of unlearning. This means questioning long-held assumptions about training, skill development and learning delivery. The tactics and technologies that have worked for decades are no longer fit-for-purpose in an era where a single app can change how workforces operate overnight. Indeed, only 12% of learners have applied new skills to their jobs, and 70% feel they lack mastery of the skills needed to complete their work effectively.

Encourage teams to rethink traditional approaches and remain open to experimentation. Have regular “unlearning sessions” where fresh approaches and technologies are explored, tested and discussed. Create a psychologically safe environment for people to suggest fresh approaches, pilot projects and challenge legacy thinking and infrastructure.

2. Adopt AI With Purpose

The buzz around AI in learning reached new heights in 2024, and it’s only going to grow as more organizations explore the potential of AI-powered co-pilots, generative AI, agentic AI and automation. However, AI should be integrated with intention, not just as a trend. Analyst Josh Bersin predicts that companies with AI-augmented workforces will outperform their competitors sixfold.

Learning leaders can start aligning their AI efforts by identifying business objectives and then determining how AI can support them — whether through hyper-personalized learning experiences that adapt in the moment to each learner’s skills, performance and role requirements or real-time coaching and feedback tools. Equally important is staying ahead of AI-related regulations and ethical considerations to ensure compliance and responsible use.

Consider running a small task at scale, rather than a large set of tasks in a small pilot to more accurately predict impact. For example, use an AI agent to manage the enrollment and reminder processes for a large population, rather than implementing a comprehensive system as a test with a small test group.

3. Prioritize Hands-On Learning

As organizations invest in AI and other advanced technologies, one reality remains unchanged: People haven’t truly mastered complex skills until they can apply them. Fundamental skill acquisition is experience-based — whether a toddler learning to walk, a surgeon practicing a new treatment, or a pilot undergoing simulator training. The same applies in the workplace, where high-demand skills such as cybersecurity, AI ethics, compliance, and software proficiency require immersive, hands-on learning environments.

Simulated environments, sandbox experiences and real-world practice are essential for employees to build confidence and competence in technical areas. Creating a safe space for employees to experiment and learn from mistakes accelerates skill development and retention while future-proofing the workforce.

In the past, we’ve been content with letting people attend training and maybe pass a knowledge test, but as AI evolves, human roles will require more sophisticated validation. Skill assessments through on-the-job evaluations or scenario-based testing ensure that employees are not only learning but also demonstrating their ability to apply new skills effectively.

4. Enhance Your Skill Data

Most organizations are moving toward a skills-based model in some way, whether through skill-based hiring, talent marketplaces using skills data or informing upskilling opportunities through existing and needed workforce skills. How confident do you feel in your current skills data?

Many organizations suffer from data fragmentation and trust issues — their data lives in disparate systems, of variable quality and quantity. Managers and other decision-makers aren’t acting on skill insights since they don’t trust the data. Bias may spread due to poor quality data or an overreliance on self-reporting and manager feedback.

It’s a foundational issue that L&D needs to solve if skills-based is to become the norm. Take time to assess your current skills data quality and whether there’s an accurate assessment of someone’s competencies and real-world performance. In the ideal world, everyone will demonstrate that they have a skill and can perform it at work, either through on-the-job assessments or scenario-based testing. This ensures that they are not just learning but applying knowledge effectively. The key is to make skill validation timely and adaptive, so employees can stay current as technology and job roles evolve. Again, try it out on your more critical jobs, like cybersecurity, before expanding to other areas.

5. Build Learning Agility Into Your Strategy

The skills your workforce needs today may not be the same six months from now. The next ChatGPT-level innovation could be just around the corner, and learning strategies must be designed with agility in mind. Rather than relying on static, long-term plans, learning leaders should embed processes and technologies that enable rapid upskilling and reskilling. However, 55% of HR and learning leaders feel that their current technology cannot meet evolving business needs.

As you assess your tech stack this year and consider working with new vendors who may not be committed to their legacy platforms, ask questions about their innovation, product development and updates. It’s worth checking with other learning leaders about their experiences with the vendor, to see if its technology has met expectations and evolved with needs.

Another effective approach is to utilize learning sprints — short, iterative learning cycles where employees will assess their current skills, consume targeted content to build their knowledge, apply that knowledge in hands-on environments, validate their skills with scenarios that match their real-world responsibilities and then repeat the process.

Looking Beyond 2025

It’s exciting to predict and prepare for the future, but as recent years have shown, you cannot be ready for every disruption. Learning strategies must be structured enough to give workforces a clear direction in their upskilling and reskilling but agile enough to respond to the latest changes and opportunities. No matter what comes next, if you challenge yourself and your teams to align, adapt and apply skills, you’ll be better prepared for the future.