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Brain Circuits
5 key steps to scaling AI: Lessons from the best-in-class
Many organizations are discovering that scaling AI is far more difficult than piloting programs. Drawing on data from the world’s largest 300 companies, the IMD AI Maturity Index reveals how the leading companies are responding to the challenge.
Five key lessons in moving from pilot to performance:
1. Plan for scaling early
Consider legal, compliance, and integration issues from the start. Some firms now form dedicated “scale teams” once a pilot shows promise.
2. Match scope to value
Not every tool should reach every business unit: focus on where adoption delivers the highest return.
3. Invest in human capability
Companies such as Unilever, Visa, and Hitachi have trained tens of thousands of employees in AI fluency – a prerequisite for enterprise-wide deployment.
4. Govern transparently
Formal ethics boards (as used, for example, by AXA, Roche, and Volkswagen) build both trust and regulatory readiness.
5. Measure what matters
Beyond usage rates, track operational efficiency, customer satisfaction, employee creativity, and new value creation.
How to embed and scale AI across five dimensions:
AI is not about deploying the newest model but about aligning leadership, people, and technology around a shared purpose. Go through the following checklist to make sure you have everything in place:
Executive support
- Do we have C-suite ownership and clear governance?
Technology and infrastructure
- Do we have scalable data and cloud systems?
Operational excellence
- Is AI integrated into our everyday processes?
Workforce and culture
- Are we prioritizing reskilling, collaboration, and AI fluency?
Ethics and risk management
- Is our use of AI responsible and transparent?
Key takeaways
Scaling AI is as much about managing change as it is about managing code. The most successful firms treat it as a transformation across several dimensions. The message is clear: moving beyond pilots means building maturity. The future belongs not to those who experiment with AI, but to those who trust it, govern it, scale it, and make it work.
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