Turkish President Recep Tayyip Erdoğan has described COP31, being hosted in his country, as the “implementation COP,” emphasizing the need to translate climate commitments into action.
The urgency is mounting. In September, the latest United Nations Environment Programme report concluded that limiting global warming to 1.5 C, or even slightly exceeding that threshold, is no longer achievable.
Although returning below 1.5 C later this century remains possible, it would require rapid, substantial emissions reductions. Meanwhile, continued warming increases the risks of severe and irreversible climate impacts, making effective action critical.
Given this urgency, artificial intelligence (AI) is attracting attention for its potential to deepen our understanding of climate risks and inform our responses. This growing interest is reflected in COP31’s Antalya AI Pledge.
But realizing this potential raises an important question: Do the professionals working on climate adaptation have the knowledge, skills and support to use these technologies effectively and responsibly?
AI and climate monitoring
A 2023 national survey of Canadian professionals found that many do not feel adequately equipped to apply adaptation tools or make the case for adaptation measures.
This points to a gap between understanding climate risks and having the capabilities to address them. Canada’s National Adaptation Strategy sets a target for 70 per cent of relevant professionals to have these capabilities by 2027.
Canada uses AI to improve weather forecasting, and Canadian researchers use it to assess flood risks. Emerging applications include infrastructure and adaptation planning, such as flood-risk modelling in Vancouver. Yet better information does not necessarily lead to better decisions.
As AI enters climate risk assessment and adaptation planning, it adds to the challenges professionals already face as they grapple with difficult decisions about infrastructure, public safety, ecosystems and community resilience.
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AI skills for a climate workforce
The challenge goes beyond learning to use AI. Front-line climate action professionals need to understand how AI-generated information is produced, assess its reliability and limitations, and decide when and how to use it alongside other evidence and knowledge.
Consider a coastal community facing rising flood risk. AI-supported modelling might identify vulnerable roads, homes and public facilities. But deciding whether to reinforce a shoreline, restore wetlands, restrict development or consider relocation involves more than comparing projected risks.
These choices affect livelihoods, ecosystems and relationships to place. They also involve competing priorities and values, Indigenous rights and jurisdiction and questions about whose knowledge informs decisions and who has the authority to act.
Many of the competencies required to navigate these challenges are already recognized in climate adaptation practice. At the ResilienceByDesign Lab at Royal Roads University, we’ve developed a Climate Action Competency Framework that identifies systems thinking, critical assessment of information, collaboration, communication and ethical leadership as essential to effective climate action.
These capabilities remain relevant as AI enters adaptation practice, but they are insufficient on their own. Professionals also need to understand how AI systems work, recognize potential biases and gaps in the data they use, assess the reliability of AI-generated recommendations and navigate questions of transparency and accountability.
This does not mean every planner, engineer, emergency manager or public health professional needs to become an AI specialist. Instead, they need enough AI literacy to ask informed questions, recognize when additional expertise is required and exercise professional judgment rather than simply accepting what the AI produces.
From competence to professional practice
Identifying these capabilities is only part of the challenge. They must also be reflected in professional standards, education, ongoing training and the organizational conditions that shape adaptation decisions.
The Professions Advancing Adaptation Competencies initiative offers a Canadian example. By examining how the Climate Action Competency Framework aligns with the standards and practices of engineering, planning, accounting and landscape architecture, the initiative identified shared competencies and profession-specific needs.
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Similar work could examine how AI is reshaping adaptation practice across professions, what existing competencies remain relevant and where additional capabilities are needed. This would strengthen workforce readiness by identifying the competencies professionals need to use emerging technologies effectively, rather than assuming that access to AI alone will automatically improve climate action.
If COP31 is to deliver on its promise to move from commitments to implementation, preparing the workforce responsible for adaptation must be a priority. Governments, professional associations and educators must ensure professionals have the competencies, resources and institutional support to use these technologies responsibly and translate climate knowledge into action.
AI can improve our understanding of climate risks, but turning that knowledge into effective, equitable action will still depend on people and the decisions they are equipped to make.
Robin Cox has previously received research funding from the Social Sciences and Humanities Research Council of Canada and Natural Resources Canada.
