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.

Have you ever given thought to the possibility that the suppliers of your core business technology, brands like Microsoft, Oracle, and SAP, might simply turn you off with no warning?

It sounds fanciful, absurd, a black swan event so far beyond any reasonable risk matrix as to be unworthy of consideration.

Yet it happened this year, 2025, to a major oil company in the world's most populous country.

What was once unimaginable is now here, and with it, lessons for every oil and gas organization, indeed every company, about the new risks in the digital landscape.

⚒️ 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.

Most large enterprises rely on a handful of expansive technology platform solutions to run their business, and the most prominent and widely deployed in oil and gas is SAP. As I've outlined in my books, enterprise solutions such as SAP are also migrating to digital technologies, which triggers a major question: what is the optimal upgrade path for an SAP customer, or any enterprise technology, to adopt?

Broadly speaking, there are two strategies to this vexxing question: a brownfield migration or "lift and shift" and a greenfield re-implementation or "start afresh". The problem is that brownfield upgrades rarely deliver any ROI while greenfield is seen as too risky, costly, or complex to execut, especially at the global scale one encounters among the oil and gas majors.

Is there a third path, where organizations can preserve their historical data, stay compliant, and still deliver tangible business outcomes?

In this episode I speak with Don Mahoney, Global Head of Products and Innovation at SNP Group about a new approach, coined 'bluefield'. Bluefield lets companies dial in just the right amount of transformation, one that preserves key data, avoids excessive risk, and achieves a positive ROI. I'm very interested in how Bluefield works, how it supports AI training strategies, when to use it, and why it's becoming an attractive model for SAP S/4HANA transitions, and indeed all major platform solution transformations.

👤 About the Guest

Don Mahoney is the Global Head of Products and Innovation at SNP Group, where he leads strategy for the company's transformative deployment technologies, including its flagship Bluefield methodology. Don brings over 30 years of experience across process industries, enterprise software, and solution management. He previously held senior roles at SAP, overseeing strategic accounts like ExxonMobil and leading SAP's global chemical industry business unit.

🔗 LinkedIn: Don Mahoney

🌐 Website: SNP Group

⚒️ 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.

Motors are the quiet workhorses of industry. They drive pumps, fans, compressors, and heaters, and they consume more than sixty percent of the power in most industrial operations. When operators need to control motor speed, they historically relied on mechanical adjustments or trial-and-error testing to keep processes stable and safe.

As motors get larger and drive trains more complex, traditional testing approaches no longer work. Bringing every component together for a full string test adds months of delay and millions of dollars in logistics. The industry is conservative and reference driven, which makes it hard for operators to trust new configurations without seeing them proven first.

This is where simulations shine.

In this episode, I speak with Anand Jha, Vice President of Global Sales for ABB System Drive – Process Industries, about simulation twins that let operators model the entire system before it's built. These "virtual plants" replicate the grid, the drives, the motors, and the compressor.

With software-in-loop and hardware-in-loop tools, operators can validate performance, tune configurations, and eliminate expensive string tests. The result is faster execution, lower cost, deeper system insight, better training, and continuous improvement across the plant lifecycle.

Anand Jha is the Vice President of Global Sales for ABB System Drive – Process Industries. With over 20 years of experience in the Oil & Gas and other Process industries, Anand has held various roles from commissioning engineer to sales leader. He is also an accomplished author, having written two books. Anand holds an MBA from the University of Alberta in Canada and a B.Tech in Electronics and Instrumentation.

• 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

• 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

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

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

Canada's energy sector has long struggled with low productivity on the front line, as indeed the entire Canadian economy. Despite heroic efforts by tradespeople, their effectiveness is hamstrung by badly dated processes, old disconnected systems, and paper-based workflows.

The problem isn't the workers. It's that they're too often sent out with the wrong drawings, the wrong tools, the wrong permits, or even to the wrong location. Multiply that by a hundreds of thousands of jobs, and you've got a national productivity drag.

One company, MSCP Heat Management Solutions, set out to build a completely paperless, digitally connected operation, starting at the job site. By linking trades, materials, safety workflows, and quality processes into a seamless digital flow, MSCP has achieved something few believe is possible: cutting required manpower by 40% to 45% on major jobs.

In this episode, I speak with Chris Maki, MSCP's founder and CEO, on lessons he took from Fort McMurray's distant job sites and turned them into a blueprint for frontline innovation, cross-trade productivity, and system-level change. We talk technology, training, and trust, and why it's not about buying a platform, but building a mindset.

👤 About the Guest

Chris Maki is the President and CEO of MSCP Heat Management Solutions, based in Sherwood Park, Alberta. A former frontline tradesman with deep experience in Fort McMurray turnarounds and major projects, Chris launched MSCP in 2011 with a simple belief: there has to be a better way. Today, MSCP operates as a fully digital contractor, combining electrical, insulation, rope access, material handling, and fabrication into a unified and highly productive system of work. Chris is a vocal advocate for trades-focused innovation, continuous improvement, and the future of work in energy.

🔗 Website: http://www.mscpltd.ca/

🛠 Additional Tools & Resources

🎥 Go backstage and check out my studio:

https://geoffreycann.com/mystudio/

📚 Take my one-day digital strategy training course:

https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🌐 Connect with Me

📝 Blog series: Digital Oil and Gas

🎙 Podcast

🔗 LinkedIn

🐦 X (Twitter)

🎤 Contact for Lectures and Keynotes

I speak regularly on these and other topics. Book a call for your upcoming event:

⚠️ Disclaimer

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