AI has exposed the biggest knowledge gap in business. Hint: it isn't technical

As $2.5 trillion in AI investments are made by corporations this year, over $1 trillion is allocated to IT services and dedicated software. This significant spending comes at a time when businesses are still trying to understand how AI fits with their operations. Notably, Ford recently brought back experienced engineers after AI systems failed to identify manufacturing issues, highlighting the importance of human expertise in AI implementation.

Meanwhile, new research from Ramp and Revelio Labs found that organizations investing heavily in AI are hiring more people, contradicting the belief that AI reduces reliance on human labor. These findings reveal a critical knowledge gap in business: while AI is changing how work is done, it still heavily depends on experienced employees.

To succeed with AI, companies must first understand the skills people need at individual, team, and organizational levels. Building a skills ontology, a living record of skills across the organization, can help identify where expertise exists and where gaps are. This process can inform workforce planning, internal mobility, and more effective AI deployment.

Once organizations identify their subject matter experts, AI can help maintain this knowledge by surfacing patterns and recommending learning pathways. However, experienced team members remain essential for providing context, explaining processes, and adapting AI to the organization's unique reality. In an era where AI expertise is becoming increasingly valuable, L&D teams have an opportunity to own the upskilling and reskilling agenda, turning expertise into a competitive advantage.

The greatest return on investment in employees and AI comes from identifying, sharing, and scaling existing expertise rather than merely purchasing more software.