Upstream oil and gas companies continue to be very reliant on spreadsheets, legacy systems, and manual workflows to manage thousands of wells, compliance filings, and capital decisions. It's labor-intensive, error-prone, and slow. In light of global energy transition moves, operators are now facing ongoing margin pressure, a supply glut, tighter emissions regulations, and a shrinking pool of skilled labor.

Digital solutions to soften the impacts of these pressures too often end up in "pilot hell", with limited results, stalled momentum, and no path to scale. Core systems like SCADA and ERP can't be easily adapted, and the early stage AI tools are often dismissed as too risky, inaccurate, or incompatible with real-world operations. Capital markets frown on any moves that sacrifice short term ROI for the possibility of better results later.

New agentic AI tools look perfectly placed to address these constraints, but getting started is daunting.

In this episode, I speak with AI strategy advisor Jeff McKee who outlines how a handful of upstream operators are now using agentic AI (modular software agents), that augment field teams and automate critical tasks across production, compliance, and finance. Already live across 1,500 wells, these tools have delivered a 3–10% uplift in production, 5–15% profit lift, and >90% reduction in compliance workload. Jeff explains how companies can start small, define just a few key KPIs, and stand up agents in under two months, all without touching core systems. From Sarbanes-Oxley readiness to workover economics, it's a roadmap for scaling AI one agent at a time.

Jeff McKee is the founder of Jeff McKee Consulting and an AI strategy advisor to $100M–$1B+ companies. A former Microsoft leader, he created the PIVOT AI™ framework to help executive teams identify high-impact AI use cases and deliver results fast. In oil and gas, he partners with Mango Bites (Pixie AI) to enable production optimization, profitability, and compliance across upstream field operations.

🌐 Website: jeffmckeeconsulting.com

💼 LinkedIn: linkedin.com/in/jeff-mckee

📧 Email: jeff@jeffmckeeconsulting.com

⚒️ Additional Tools & Resources:

🎬 Go backstage and check out my studio:
👉 https://geoffreycann.com/mystudio/
🎓 Take my one day digital strategy training course for oil and gas:
👉 https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me:

🖥️ Blog series: https://digitaloilgas.substack.com/
🎧 Podcast: https://geoffreycann.com/broadcast/
📇 Linkedin: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🤬 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes:

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Click here 👉 https://geoffreycann.com/contact/

⚠️ Disclaimer:

The views expressed in this podcast are my own and do not constitute professional advice.

The energy industry is rapidly adopting artificial intelligence. Its promises of improved productivity, safety, and operational insight are too good to ignore. But these tools are only as good as the data that feeds them. And therein lies the problem: data across the sector is often incomplete, inconsistent, and scattered.

This historic lack of discipline around data now has consequences. Poor data quality when used in AI undermines any project leveraging AI, exposing companies to greater audit risk, slowing down decision-making, and derailing expensive digital programs. Worse, AI tools amplify these flaws, making unreliable data more visible than ever. In one instance, a company's emissions breach turned out to be a data error that triggered fines, audits, and reputational damage.

Companies struggle to respond, given the scale of the challenge. Getting control of enterprise data often feels like boiling the ocean, compounded by organizational practices that empower every business unit to do things their own way.

In this week's podcast, I speak with Waseem Sinjakli, who knows this challenge well. As the founder and Managing Director of EPM, a Calgary-based consultancy, he's led enterprise-wide transformation programs that put data governance at the center of AI readiness. In this episode, Waseem shares what good governance really looks like, the cultural barriers companies must overcome, and how to turn data from a liability into a high-value asset.

Waseem Sinjakli is the Founder and Managing Director of EPM, a Calgary-based professional services firm focused on complex digital transformations in the energy sector. Building on his lengthy career with leading organizations in professional services, Waseem brings deep expertise in project delivery, change management, and digital enablement. EPM specializes in transformation programs tied to regulatory compliance, operational efficiency, cost optimization, and AI-driven insights.

🔗 LinkedIn: Waseem Sinjakli

🌐 Website: EPM

⚒️ Additional Tools & Resources:

🎬 Go backstage and check out my studio:
👉 https://geoffreycann.com/mystudio/
🎓 Take my one day digital strategy training course for oil and gas:
👉 https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me:

🖥️ Blog series: https://digitaloilgas.substack.com/
🎧 Podcast: https://geoffreycann.com/broadcast/
📇 Linkedin: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🤬 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes:

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Click here 👉 https://geoffreycann.com/contact/

⚠️ Disclaimer:

The views expressed in this podcast are my own and do not constitute professional advice.