While speaking at an executive luncheon in Calgary recently, I had an unexpected realization. Nearly 10 years had passed, but I was still having the same conversation with oil and gas leaders: how to move from AI curiosity to AI confidence.
The moment felt familiar because I had seen this challenge before. In 2017, I was leading a software startup that introduced supervised machine learning into the oil and gas industry at a time when AI was still a new concept for many companies.
The organizations willing to explore its potential quickly discovered that AI could deliver measurable business results. Those successes inspired broader adoption and demonstrated that AI could improve performance and create a lasting competitive advantage.
Today, generative AI and autonomous agents have transformed the conversation. The question is no longer whether AI belongs in the enterprise – it’s how to turn growing investment into measurable business impact. That’s where many companies still struggle.
Moving Beyond the Pilot Stage
Research from MIT has found that many enterprise AI initiatives fail to deliver meaningful results. Closing that gap requires applying AI to real operational needs – not technology alone.
For oil and gas operators, the opportunity lies in improving production uptime, increasing field efficiency, strengthening maintenance reliability, enhancing safety, and sharpening cost discipline.
When embedded into daily workflows, AI helps teams identify issues earlier, reduce downtime, and make faster, data-driven decisions. As capabilities continue to advance, success depends on building the processes and ownership needed to turn isolated experiments into trusted ways of working that create lasting operational value.
The Playbook for Turning AI Into Results
The companies making the most progress don’t start big. They start smart.
- Begin with business champions who can build early proof and momentum.
- Focus on one high-value use case and deliver results in weeks, not quarters.
- Measure outcomes that matter—hours saved, production protected, and risk reduced.
- Build momentum within the first 90 days.
- Pair executive sponsorship with accountable business ownership.
Those first wins matter. They replace uncertainty with evidence, helping companies overcome FOMU, prove what’s possible quickly, and build the momentum needed to scale Industrial AI adoption.
SOURCE: Kurt Kemmerly (2026 July 21) From FOMU (Fear of Messing Up) to First Win: The Playbook for AI Adoption. IFS Blog. https://blog.ifs.com/from-fomu-to-first-win-ai-adoption-playbook
