The report found that 98 per cent of Canada’s financial sector occupations are exposed to AI technologies, much higher than the national average where 56 per cent of the total workforce is exposed to the technology. The report examines which roles in the sector are likely to be augmented by AI versus those at risk of replacement. It finds senior management positions are more likely to be supported by the technology, while a much larger share of jobs, particularly in administration and customer service, face a higher likelihood of being replaced.

While generative AI in the financial sector poses opportunities for augmentation and overall productivity, the report emphasizes that the technology is not well suited for core financial tasks due to risks of inaccuracy. For example, conducting financial analyses, ensuring regulatory compliance, tax calculations, examining financial records, and more, where precision is required and small errors can have significant consequences. AI is not currently well suited to support in these tasks due to reliability concerns.

AI is found to be most effective in areas such as customer service, communications, and routine business support. Based on real-world usage data, AI is increasingly being used for answering customer questions, drafting materials, and internal support rather than for financial analysis.

The report recommends a cautious, targeted approach to adoption, prioritizing low-risk tasks while maintaining strong human oversight, data privacy protections, and regulatory compliance. Adoption should focus on areas where companies can safely improve productivity without introducing significant risk, such as front-line customer service interactions, drafting communications, and summarizing information, rather than core financial activities that require complete accuracy and numeracy.

As companies undergo AI adoption, strong data privacy protections must be upheld, ensuring compliance with regulatory standards and establishing clear accountability for errors or misleading outputs. It also calls for ongoing human oversight, including quality monitoring and safeguards to step in when AI systems fail. Financial institutions are encouraged to avoid overreliance on AI by continuing to develop employee skills and judgment.

Ultimately, generative AI is expected to deliver incremental productivity gains rather than transformative change, with success depending on responsible implementation and workforce adaptation. Read the full Banking on AI full report the Toronto Metropolitan University here.

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Canada’s AI adoption rate sits at just 12 per cent, trailing far behind countries like India, Singapore, and the UAE, where adoption is at or above 50 per cent. To close the gap, AIAI recommends Canada’s strategy focus on five key priorities:

First, invest in applied AI skills. Productivity gains depend on workers across sectors combining domain expertise with accessible AI tools. Canada needs stronger applied training pathways, particularly for SMEs, alongside a strategy that supports both advanced researchers and an AI-ready workforce capable of deploying AI in real-world settings.

Second, the strategy should emphasize supporting adoption through applied research by ensuring access to state-of-the-art infrastructure, incentivising cross-disciplinary R&D aligned with industry strengths, and enabling access to domain-specific datasets. The government should prioritize targeted investments in digital infrastructure, expand industry access, and reduce regulatory barriers to innovation and adoption.

Third, the Canadian government should continue to lead through public sector AI adoption, using strategic procurement, clear departmental roadmaps, and leadership to improve service delivery and stimulate private-sector demand.

Fourth, Canada should modernize and expand incentive frameworks to support applied AI, focusing on investments in fine-tuning, integration, and deployment, and expanding programs to facilitate adoption across SMEs, academic institutions, and public and private sector entities.

Finally, Canada should pursue targeted, interoperable regulation that enables adoption through regulatory clarity, alignment with international standards, and sector-specific approaches for SMEs.

The economic impact of AI depends on diffusion. If the Canadian government prioritizes adoption in its AI strategy, it will translate the country’s AI leadership into productivity growth, better public services, and shared economic prosperity.

Find the full article from AIAI co-founder, Nicole Foster, here.

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The agreement brings together leading frontier AI companies to advance inclusive and responsible artificial intelligence including Amazon, Microsoft, Anthropic, Open AI, Google, Meta, Cohere, BharatGen, Gnani AI, and more. Signatories committed to ensuring the development and deployment of their AI systems are accessible across the Global South by reflecting cultural diversity and real-world needs.

These voluntary commitments include:

1. Advancing understanding of real-world AI usage through anonymized and aggregated insights to inform policymaking on the impact of AI on jobs, skills, productivity, and economic transformation. This research will inform governments and institutions when developing AI strategies to maximize the benefits of major technological change while mitigating risks; and
2. Strengthening multilingual and contextual evaluations to improve the effectiveness of AI systems across languages, cultures, and real-world use. Through collaboration with governments and local organizations, signatories will develop systems that support under-represented languages and cultural contexts, thereby ensuring equitable access to high-quality AI globally.

These commitments align with the AI Adoption Initiative’s calls for collaboration between the public and private sector to improve access to AI, ultimately enabling adoption comparisons across countries.

AIAI looks forward to seeing the progress made by signatories in the lead up to the 2027 Global AI Summit in Switzerland.

Find the Government of India’s press release here.

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The workshops will explore how AI is reshaping the workplace and what organizations, educators, and policymakers can do to strengthen productivity and workforce readiness in a changing economy.

Participants will examine the skills needed to use, deploy, and advance AI technologies. The workshops will bring together members of the global AI adoption policy community for panels, fireside conversations, and breakout sessions focused on upskilling the workforce.

To confirm your attendance please register here. For more details, please email info@adopt-ai.org.

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Nadella warned that without meaningful uptake beyond large technology firms, today’s AI momentum risks becoming a speculative bubble. While investment in AI infrastructure and models has surged, he emphasized that sustained economic growth will only materialize if AI is embedded into everyday workflows—across public services, traditional industries, and small and medium-sized enterprises.

Nadella framed AI not as a standalone sector, but as a general-purpose technology, comparable to electricity or the internet. Its true value will be realized when it is deployed to improve productivity, service delivery, and decision-making at scale in sectors like healthcare, education, manufacturing, and public sector.

Microsoft’s message from Davos reinforces the core focus of the AI Adoption Initiative: moving the global conversation beyond hype to real-world implementation. As AI investment accelerates, the real economic and social value will only be unlocked if governments, small businesses, and public institutions have the tools, skills, and frameworks to adopt AI at scale.

Hear Nadella’s full remarks here.

Join us 

AI adoption is a global challenge, and it will take collaboration to succeed. AIAI will continue to bring together voices from around the world to ensure AI becomes a tool for opportunity and growth.

Learn more and get involved: www.adopt-ai.org.

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The report looked at how AI, specifically Claude, is currently being used, the types of tasks where it delivers the greatest productivity gains, and how adoption differs across countries and occupations. Anthropic’s report reinforces that that the economic benefits of AI are contingent upon adoption, which varies widely across industries, skill levels, and economic contexts.

Using a framework of five “economic primitives”, Anthropic looked at the use and impact of AI by assessing task complexity, skill level, purpose, AI autonomy, and success. Using these metrics to assess the economic impacts of AI, the report found that AI delivers the largest productivity gains for tasks that require higher levels of human capital. As a result, it sees adoption rates the highest amongst white-collar professions. The tasks best supported by Claude are those that require more education compared to the overall economy-wide average, suggesting AI is augmenting higher-skilled work rather than replacing it.

In 2025, Anthropic’s adoption data found roughly 36 per cent of jobs used Claude for at least a quarter of their tasks. Compared to one year later, the figure has grown to 49 per cent of jobs. AI tools are increasingly supporting a growing share of everyday work across occupations and enhancing productivity.

However, AI adoption and use vary significantly across countries. Countries with higher GDP per capita are adopting AI more widely and tend to use the technology for work, personal productivity, and leisure. Those leading in Claude usage include the U.S., India, Japan, the U.K., and South Korea. In contrast, lower-income countries are not adopting AI at the same rate and tend to use the technology more for education, coursework, and learning support.

Artificial intelligence has the potential to transform economies, enhance productivity, and become the next industrial revolution. Earlier research from Anthropic estimated that widespread AI adoption could increase U.S. labour productivity growth by 1.8 percentage points annually over the next decade, roughly double the current rate. When the probability that AI will complete a task successfully is considered, the number falls to 1.2 percentage points, and 1.0 percentage points for more challenging tasks. Even on the lower end of these rates, AI still has the potential to see the U.S. return to growth rates not seen since the late 1990s and early 2000s.

Despite its impact on economies and productivity, global AI adoption remains uneven, with higher-income economies adopting the technology at a faster pace. As the world enters a period of rapid technological change, Anthropic’s report provides data and analysis to assess the real-world impacts of AI adoption on workers, industries, and regions at large.

With the launch of The Anthropic Institute, a new initiative focused on researching the economic, legal, and societal impacts of AI, the AI Adoption Initiative looks forward to continued insights from Anthropic. Its research will help inform the technological transition of economies and support the responsible adoption of AI.

Find Anthropic’s full report on the New Building Blocks for Understanding AI Use here.

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