AI will not transform learning through technology alone, warns Gaurav Gupta. For L&D leaders, the real value comes from aligning AI with strategic goals, engaging practitioners in experimentation, and addressing employee fears. Success depends less on the tools themselves and more on the human behaviours, decisions and culture surrounding them.
The race to adopt AI has hit L&D with full force. Organisations are investing heavily in AI-powered platforms, chatbots, and learning management systems. Yet, the return on these investments has thus far been underwhelming. The biggest challenge isn’t the technology itself, but in how L&D leaders are approaching AI in the context of their strategy.
AI is a powerful tool, but it’s still just a tool that should enable your organisational goals
As with any new technology, for AI to truly enable success it must fit within the existing L&D strategy. The critical question isn’t “What’s our AI strategy?” but rather, “How can AI enable our L&D objectives?” AI is a powerful tool, but it’s still just a tool that should enable your organisational goals.
When AI adoption is pursued without clear alignment to broader L&D objectives, it tends to produce fragmented use cases that deliver limited business impact. Instead of unlocking new ways of learning, organisations end up merely fine-tuning existing processes and missing the opportunity for true transformation.
AI adoption is a people and process challenge
Realising true value through AI implementation involves recognising that success depends upon human behaviour. Counter intuitively, getting value out of AI actually requires frequent human decision making. Unlike past technological tools, how a user interacts with the AI tools is a significant determinant of the value it can add.
Hence, the value from AI hinges on employees’ ability to implement it in innovative and purposeful ways. Unlike traditional software with prescribed functions, AI platforms are flexible, with every interaction unique. Give two professionals the same goals and technology, and you’ll likely see dramatically different results, not from skill gaps, but because of how each person leverages the tool’s capabilities. This variability is particularly pronounced with today’s generative AI applications.
For AI to deliver meaningful returns, L&D leaders should focus on cultivating the right mindsets and behaviours around its use. This means making a compelling case for why AI represents a better path to achieving learning objectives and demonstrating its connection to broader talent development goals. When organisations skip this foundational work, AI just becomes another underutilised tool, capable of minor improvements but falling short of fundamentally reshaping how L&D operates.
Employee engagement with AI presents its own set of hurdles. Headlines warning of automation-driven job displacement, paired with mandates to “just use AI” without strategic context, create a climate of uncertainty and resistance. While the intended outcome of AI implementation is to eliminate tedious tasks and boost output, poorly communicated rollouts achieve the opposite. When leaders can only point to nebulous promises of “working smarter,” employees often respond with scepticism and disengagement.
Bridging executive vision with frontline innovation
Making AI work for L&D demands a dual approach: leadership must set the strategic course while practitioners drive hands-on discovery. Executives need to draw clear lines between AI investments and overarching business priorities, ensuring that resources flow toward initiatives that genuinely support talent strategy.
Simultaneously, the emerging nature of AI technology calls for active exploration at the practitioner level. The people delivering training, designing curriculum, and facilitating learning experiences possess invaluable knowledge about pain points and untapped possibilities. Their frontline perspective reveals where AI can make the biggest difference. Smart L&D leaders tap into this expertise by inviting practitioners into planning conversations, implementation teams, and assessment groups.
This dual-engine approach, combining executive clarity on destination with practitioner knowledge of the journey, can create exceptional results. Organisations that ignore grassroots intelligence from their teams leave significant value on the table, unable to fully capitalise on what AI can deliver.
Address fear while highlighting possibility
Strategic clarity alone won’t drive adoption if employees remain apprehensive about what AI means for their roles. Leaders must take deliberate steps to ease concerns while spotlighting the upside. Practical measures like establishing low stakes testing give teams permission to explore AI capabilities firsthand, revealing how these tools can elevate rather than replace their contributions. Watching AI handle repetitive tasks and free up time for strategic work, transforms abstract worry into tangible enthusiasm. Celebrating experimentation further reinforces the behaviours organisations want to see.
AI’s rapid advancement is outpacing the management frameworks most organizations rely on (i.e., structures built for consistency and control, not continuous transformation), forcing L&D leaders from conventional playbooks that prioritise stability over adaptation. This means flattening decision-making hierarchies, assembling agile pilot groups, broadening participation in problem-solving, and fostering lateral knowledge-sharing networks. These methods simultaneously calm fears and channel collective energy toward embracing AI-driven change.
Redefining L&D in the AI Era
AI presents an opportunity to accelerate progress against L&D objectives, but success demands an outcome-focused approach. L&D leaders must connect AI initiatives to strategic objectives, engaging employees as partners in change, and cultivating a culture of adaptability.
At its core, AI implementation succeeds or fails based on human factors rather than technical capabilities. L&D leaders who grasp that this is a cultural shift, not just a software upgrade, will extract real returns from their technology investments and build workforce capabilities that endure.
Gaurav Gupta is Managing Director and Head of R&D at Kotter
