Your organization prioritized AI adoption, but you actually need AI fluency.

Some departments within your organization are rapidly advancing with artificial intelligence, while others remain stagnant due to lack of formal rollout, governance approval, or guidance. This disparity is widening, necessitating a new operational approach. It is not enough to simply provide access to AI tools; teams must develop AI fluency to truly benefit from them.

Harvard Business School found that workers proficient in AI completed tasks 25% faster and produced results rated over 40% higher in quality. However, performance dropped when employees used AI tools without understanding their appropriate application. Rather than focusing on merely integrating new tools into existing workflows, it is crucial to rethink entire processes.

This requires stepping back and viewing the process anew. An SDR team, for example, initially asked IT to improve sales lead routing. After deeper analysis by IT, they discovered that the data pipeline was overly complex, opening the door to a completely reimagined pipeline with potential for agentic lead follow-ups. Departmental leaders need strategic guidance to help them reimagine work from first principles, not just technical support and software licenses.

AI fluency must be considered from the start, rather than being seen as a table stakes issue. A more effective operating model would pair a central "hub" responsible for platform strategy, governance, and reusable patterns with AI engineers embedded within business departments. These "spokes" would help identify vertical use cases and provide cross-functional visibility.

This approach allows for rapid iteration, as the AI engineer who solved a problem in finance can share their solution with someone facing the same challenge in operations. Over time, departments will develop AI fluency as they learn from these engineers, leading to improved processes and stronger institutional knowledge.