Close Your Workforce's AI Skills Gap by Designing an Adaptive Organization - SPONSOR CONTENT FROM SLALOM

"In the rush to adopt AI, many organizations mistake momentum for progress. Tools roll out, pilots multiply, and confidence rises-but the capabilities necessary to achieve results remain underdeveloped. The dissonance is striking: 68% of leaders and employees surveyed in Slalom's 2026 AI Research Report say they can keep pace with AI, yet 93% report that such workforce barriers as underdeveloped skills and inadequate training limit their progress."

"To overcome this capability gap, organizations must first redesign themselves to adapt at the rate AI demands. However, that level of adaptability doesn't emerge on its own; it's built through a series of deliberate steps to align leadership, talent, and value creation."

"Today's leaders were largely taught to be operators, rewarded for their knowledge, efficiency, and decisiveness. Adaptive organizations need something different: leaders who can think beyond their domain, challenge assumptions, and guide teams with clarity, not control. This requires a new set of leadership muscles that prioritize curiosity over certainty, sense making over jumping to solutions, and co-creation over top-down direction."

While technological disruption is not new, the speed of AI-driven change creates unprecedented adaptation demands for organizations. Many companies confuse momentum with progress, deploying AI tools and pilots without developing necessary capabilities. A significant gap exists between leader confidence and actual workforce readiness: 68% believe they can keep pace with AI, yet 93% cite skill gaps and inadequate training as barriers. Organizations must deliberately redesign themselves through three key steps: developing leaders who prioritize curiosity and exploration over expertise, building workforce capabilities through real-world learning and coaching, and aligning talent with value creation. Traditional leadership models focused on operational efficiency and decisiveness prove insufficient for navigating AI's complexity and uncertainty.

Read at Harvard Business Review