About this episode
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. ? About the Guest 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. ?
