Artificial Intelligence is reshaping work—fast. But while individuals are enthusiastically embracing these tools, companies are struggling to keep up. In this insightful article, Ethan Mollick breaks down the disconnect and offers a roadmap for turning potential into performance.
1. Four Key Facts About AI Adoption
AI Boosts Work Performance: Mollick references multiple rigorous studies showing that AI significantly improves performance across a range of knowledge work. Whether it’s writing, coding, customer support, or consulting tasks, AI doesn't just make people faster—it makes them better. The data is unambiguous: AI isn't just hype.
People Are Already Using AI at Work: Despite a lack of formal guidance, employees are turning to AI tools on their own. In some sectors, over 70% of workers have used AI in their jobs. However, this use is often unofficial, uncoordinated, and invisible to leadership.
Transformational Gains Are On the Table: The biggest surprise? We’ve barely scratched the surface. The performance gains seen so far are just the start. Most organizations are still applying AI superficially—writing emails or summarizing documents—while massive opportunities for deeper, transformational impact remain unexplored.
Companies Aren’t Capturing These Gains: Despite clear upside, organizations are failing to adapt. There’s little evidence of structured AI rollouts or strategic planning. Companies lack a coherent approach, often hindered by bureaucracy, fear of risk, or lack of technical knowledge.
2. Winning in AI Requires Three Forces Working Together
To unlock the full value of AI, Mollick proposes a model built on three pillars:
Leadership - Set the Vision: Senior leaders must actively embrace AI—not just as a tool, but as a strategic priority. They should experiment themselves, set bold goals, and remove institutional roadblocks. AI is too important to delegate entirely to IT departments or consultants.
The Crowd: Unlock the Power of Employees: Employees are already exploring AI—but they need support. Organizations should listen, learn, and amplify what workers are doing with AI. Crowdsourced innovation can be incredibly effective if you create the right environment—one that encourages experimentation, shares learnings, and scales what works.
The Lab: Build a Systematic Innovation Engine: The “lab” is not just a physical space—it’s a mindset. Create teams with technical skill, autonomy, and a mandate to explore AI in core business functions. Labs bridge the gap between experimentation and execution. They prototype, test, and deploy AI applications that work.
3. Re-Examining the Organization
Mollick ends with a challenge: what would your organization look like if you were starting fresh with AI from day one?
It’s not just about adding AI to old processes—it’s about rethinking the way you work. Leaders must reimagine job roles, decision-making, training, and even the structure of departments to fully benefit from this transformative technology.