How to Really Make AI Work in Your Organization
Discover why AI doesn't automatically lead to better performance—and what your organization needs to do to make it happen.
Reading time: 3 minutes
The Promise of AI: Big, but Still Unfulfilled
AI is often presented as the technology that makes organizations smarter, faster, and more efficient. And there’s evidence to support that. Research shows that employees experience AI as a productivity booster—think reports being generated three times faster or research conducted in minutes instead of hours. Yet this personal gain rarely translates into organization-wide success. Why? Because AI is not a technical challenge—it’s an organizational one.
The Real Problem: Organizations Lack Innovation Power
Many companies use AI on an individual level: a marketer drafts content faster, a lawyer speeds up their analysis. But without a structural redesign of processes, incentives, and workflows, the impact and scalability remain limited. Organizations simply aren’t used to fundamentally rethinking their ways of working. Instead, they rely on external consultants and out-of-the-box software—solutions that rarely match their unique dynamics.
The Key to Success: ‘Leadership’, ‘Lab’, and ‘Crowd’
According to Professor Ethan Mollick, an expert in AI and organizational change, three factors determine AI success:
- Leadership: Leaders must articulate a clear and credible vision of the future. What does AI mean for the organization? Is it about growth or cost savings? And more importantly: what does it mean for employees? Only when these questions are openly addressed can buy-in emerge.
- Lab: This is the organization’s experimental core. It’s where new AI workflows are designed, tested, and improved. Think of building benchmarks, proof-of-concepts, or even provocative demos that spark curiosity.
- Crowd: Employees who discover how AI helps them are crucial. They bring domain knowledge and practical experience. But their insights must be made visible and shareable—without fear of rejection or reprimand.
This triangle is powerful because it not only generates ideas but also ensures adoption, buy-in, and continuous learning.
Source: Oneusefulthing.org
What Can You Do Today?
- Define your organization’s AI objective
Start the conversation: Do we want to work more efficiently or tap into new markets? The answer fundamentally shapes your AI strategy.
- Create a safe space for experimentation
Allow employees to experiment with AI in clearly defined contexts. Provide room for failure—and celebrate successes.
- Launch an internal AI lab
Gather enthusiastic users, let them test and develop practical applications, and actively share their outcomes with the rest of the company.
- Recognize and support silent AI users
Many employees already use AI quietly. By fostering openness and appreciation, you activate hidden potential. Read more in our blog on Shadow AI.
- Build your own benchmark
What does “successful AI use” mean in your organization? Measure not just output, but also process improvement, collaboration, and motivation.
Conclusion: AI Requires a Learning Strategy, Not Just a Software License
AI is not a ‘tool’ you simply implement. It’s a new way of working that demands constant adaptation. Successful organizations treat AI as a learning process—with space for experimentation, vision, and human involvement. In this fast-changing world, it’s not about who knows the most, but who learns the fastest.
🔍 Curious how your organization can learn faster and use AI strategically? Get in touch and discover what AI can mean for your team.