Artificial intelligence is no longer an emerging technology for Canada’s oil and gas sector - it is becoming a defining factor in how energy is produced, optimized, and decarbonized.  Across the value chain, AI is reshaping decision-making, driving operational efficiency, and enabling greater emissions transparency. In an increasingly competitive global market, these capabilities are no longer optional; they are key differentiators for Canadian energy players seeking to compete on reliability, cost, and environmental performance.

Recent KPMG research highlights how AI has moved beyond experimentation into core operations across the energy sector. While the findings shown in Accelerating Canada’s climate progress with AI span the broader energy ecosystem, they carry particularly important implications for oil and gas leaders who are navigating rising cost pressures, tightening emissions expectations, and growing demand for reliable power.

AI is delivering value

For oil and gas operators, the shift from AI in the back office to being embedded into business‑critical processes is already visible in day‑to‑day operations. Predictive maintenance and advanced analytics are reducing unplanned downtime, extending asset life, and lowering energy waste. These improvements translate directly into stronger cost performance and reduced emissions intensity, which are outcomes that matter to regulators, investors, and customers.

The research also points to specific AI applications delivering measurable emissions and operational benefits. These include carbon accounting with real‑time emissions tracking, real‑time demand response and load forecasting, smart grid optimization, and energy price forecasting. These use cases are gaining traction because they improve operational resilience while strengthening emissions visibility, without forcing organizations to choose between the two.

The role AI can play to deliver positive emissions and operations

Better data is becoming a competitive necessity

Emissions data quality is becoming increasingly important and can drive cost savings. Real‑time emissions tracking and carbon analytics are emerging as priority AI applications with the potential to deliver vast impact. Rather than relying solely on retrospective reporting, organizations are using AI to gain continuous insight into emissions performance.

For oil and gas operators, this capability supports stronger operational control and regulatory readiness. It also enables clearer communication with investors and downstream buyers who increasingly expect transparent, verifiable performance data. The shift underway is from compliance‑driven reporting toward decision‑grade emissions intelligence.

The dual challenge: AI enables decarbonization and drives energy demand

The findings surface a critical tension shaping the next phase of the energy transition. Sixty‑eight percent of respondents believe AI will have a net positive impact on climate outcomes over the next three years. At the same time, energy use associated with AI and computing is expected to increase significantly.

For oil and gas operators, the implications are immediate. As data centres, hyperscalers, and digital infrastructure expand across Canada, system reliability becomes more important, not less. Grid constraints, permitting delays, and uneven renewable access are emerging as material execution risks across the energy system.

In this context, the role of oil and gas is being reframed. Natural gas, particularly if it can be paired with carbon capture and efficiency improvements, remains central to balancing variable renewable supply and supporting AI‑driven load growth. Ensuring grid resilience and access to reliable power is increasingly inseparable from broader decarbonization objectives.

What the findings mean for oil and gas leaders

Beyond individual use cases, the research offers clear guidance for Canadian energy leaders. Executives emphasize prioritizing AI applications that deliver both cost savings and emissions reductions, investing in robust data architecture, and engaging early with utilities and regulators on power access and permitting.

Speed of execution also matters. Seventy‑five percent of respondents agree that without AI, achieving net‑zero objectives will take longer. Organizations that translate insight into action fastest will be better positioned to manage risk, improve performance, and maintain credibility in an increasingly data‑driven energy transition.

Learn more about what energy leaders are saying on AI's role in sustainability in KPMG's new report: Accelerating Canada’s climate progress with AI

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