AI’s success depends on ensuring that AI expansion is matched by rapid, clean-energy infrastructure development.
Artificial intelligence (AI) has become both a mixed blessing and a mixed blessing regarding climate change. UNEP calls attention to its ability to detect patterns in data and uses historical knowledge to predict future outcomes, for example, to accurately predict weather. CAN Adapt sees it as bringing capacity to confront climate issues by predicting disasters such as hurricanes, floods, droughts, and wildfires, enabling modeling and proactive disaster risk management, and simplifying information to engage the public and decision-makers (with chatbots and natural language processors). AI’s ability to process vast amounts of data and adapt to changing conditions makes it particularly suited to navigating the uncertainties of a changing climate.
Canada’s Innovation Science Ministry uses AI technologies to improve the quality of life and grow the economy through health care, precision agriculture, supply chains, scientific discoveries, new smart products, and language processing technologies, including translation and text-to-speech tools. Last year, Carney established Canada’s first-ever Ministry of Artificial Intelligence and Digital Innovations to create the “economy of the future,” incentivize businesses to adopt AI, and build the infrastructure and regulations to support it. Public consultation results released earlier in February 2026 highlight the need to balance AI adoption with standards for safety, privacy, and environmental considerations.
The UNFCCC affirms that AI helps minimize energy waste and decarbonize heavy industry processes by identifying emission hotspots. AI-powered energy management systems can improve grid efficiency, forecast power demand, and optimize renewable energy deployment. Similarly, AI tools can analyze transportation data to optimize traffic flow and route planning, to reduce fuel consumption and emissions. AI-driven urban resilience planning can help identify infrastructure vulnerabilities and optimize land use. When combined with satellite imagery, AI supports biodiversity conservation, sustainable water use, and land restoration efforts.
However, AI relies on massive amounts of energy to power data centers, on water for cooling, and on critical minerals and resource extraction. The rapid obsolescence of AI hardware contributes to e-waste. UNEP points out some unintended possible consequences, such as AI-powered self-driving cars could cause more people to drive, pushing up emissions, or be used to generate misinformation about climate change, downplaying its threat. “Governments are racing to develop national AI strategies, but rarely do they take the environment and sustainability into account.” Therefore, tradeoffs are needed between AI’s benefits and constraints to reduce its emissions impact.
The Canadian Climate Institute (CCI) notes Canadian governments are courting data centers, with electricity as the selling point. Data centre electricity use is rising rapidly — adding uncertainty to forecasts of future electricity demand and planning. Traditional data centres typically draw 5-10 MW of electricity; demand from modern AI facilities typically exceeds 100 MW, raising concerns about electricity affordability and reliability. The timing and magnitude of future efficiency improvements depend on technological developments that are difficult to predict. With rising electricity demand driven by population growth and the accelerating energy transition, supply surpluses are diminishing, and new infrastructure demands entail large new capital costs. Some regions have data centres pay more of their share of new infrastructure costs and take on more risk in case demand changes in the future. In Alberta, if planned data centres go forward using natural gas power, the province’s electricity emissions will roughly double, wiping out any emissions savings from recent years.
A recent University of Ottawa paper argues that Canada should focus more on ethical and sustainable development. Guidelines include:
- Creating a public cloud Crown corporation,
- Regulating AI in housing and labour markets,
- Prioritizing renewable-energy data-centre corridors, and
- Establishing clear rules for algorithmic use in policing and defense.
Sustainability in the Digital Age, a Concordia University think tank, has argued that AI’s success depends on ensuring that AI expansion is matched by rapid, clean-energy infrastructure development. Data Centre News just last month highlighted the same for AI to remain a net positive for Canada’s climate goals, alongside strict, sustainable operational standards.
Also, a global AI Impact Summit, held in New Delhi (February 16–21, 2026), concluded with the New Delhi Declaration (88 signatories), which positions AI as a shared global responsibility aimed at economic growth, societal welfare, and safety. Another emphasis was on “Frugal AI,” making technology practical, energy-efficient, and accessible rather than just high-cost. In Canada, that could involve data centers in colder regions using renewable energy and projects like the University of Waterloo’s reuse of waste heat for district heating.
This Post was submitted by Diane Szoller, Climate Scorecard Canada Country Manager.