Making AI Work: Leadership, Lab, and Crowd
Artificial Intelligence is reshaping workāfast. 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 itās writing, coding, customer support, or consulting tasks, AI doesn't just make people fasterāit 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 invisibleĀ to leadership.
Transformational Gains Are On the Table: The biggest surprise? Weāve barely scratched the surface. The performance gains seen so far are just the start. Most organizations are still applying AI superficiallyāwriting emails or summarizing documentsāwhile massive opportunities for deeper, transformational impactĀ remain unexplored.
Companies Arenāt Capturing These Gains: Despite clear upside, organizations are failing to adapt. Thereās 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 AIānot 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 AIābut they need support. Organizations should listen, learn, and amplifyĀ what workers are doing with AI. Crowdsourced innovation can be incredibly effective if you create the right environmentāone that encourages experimentation, shares learnings, and scales what works.
The Lab: Build a Systematic Innovation Engine: The ālabā is not just a physical spaceāitās 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 deployĀ 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?
Itās not just about adding AI to old processesāitās 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.