G7 Industry, Digital and Technology Ministerial Statement on the SME AI Adoption Blueprint

Montréal, Canada

Background and Context

1. We, the G7 Industry, Digital and Technology (IDT) ministers, met in Montréal, Quebec, Canada, to explore practical measures to accelerate the use of secure, responsible and trustworthy artificial intelligence (AI) by small and medium-sized enterprises (SMEs) in our respective economies. Responding to commitments in the June 2025, G7 Leaders' Statement on AI for Prosperity, we present concrete actions that businesses, business associations and policymakers can broadly implement to create the conditions for SMEs—including micro-enterprises—to access, adopt, and leverage AI in ways that drive value and productivity.
2. We recognize AI as a transformative general-purpose technology with the potential to significantly benefit economies and societies. While we remain committed to mitigating negative externalities, respecting personal data protection and intellectual property rights and strengthening security, AI's widespread adoption, especially by SMEs, is key to realizing this potential. Although AI use by SMEs is rapidly increasing, they are adopting it at a slower pace than large enterprises as they face distinct barriers that call for targeted measures. Efforts by governments, businesses and other organizations to overcome SME barriers will accelerate the technology's positive impact.
3. In addition to widespread AI diffusion across and within sectors, we highlight that achieving productivity gains at the company level is necessary to deliver on AI's potential. We recognize the importance of supporting SMEs' efforts to integrate AI in their business strategies and core and support functions, and of involving and empowering the broader workforce to effectively use, interact and innovate with AI models and systems across a breadth of applications.
4. We regard as beneficial the development of dynamic, self-sustaining and resilient AI adoption ecosystems that integrate SMEs across AI value chains and bolster SME AI innovation. We will spearhead this effort in collaboration with private sector leaders. SMEs can play a defining role in building and shaping these ecosystems, including by being early adopters of AI and sharing lessons learned, by addressing market gaps with new AI products and services and by championing collaborative AI adoption and commercialization efforts within their sectors and industries. Startups, in particular, can play a vital role in building dynamic and SME-friendly ecosystems and by delivering targeted AI solutions that align with SME needs.
5. We acknowledge that SME needs and profiles vary greatly, including by region, industry, size, digital maturity and growth aspirations. SMEs' AI adoption journeys can, therefore, range widely in complexity and ambition, from acquiring off-the-shelf generative AI products to customizing AI models for business needs; from building foundational AI literacy to sustaining extended internal capabilities and skills; and from piloting targeted-use cases to deploying AI holistically across business functions. The G7 OECD Discussion Paper: AI adoption by SMEs provides information on diffusion patterns and enablers of AI adoption as well as tools, such as the taxonomy of AI adopters, which can help governments tailor policy measures to specific SME profiles. We encourage active communication and collaboration between governments and SMEs, to address the wide scope of SME needs and enable effective implementation.
6. We welcome the SME AI Adoption Blueprint, developed by the Canadian Presidency with input from G7 partners. It presents high-impact policy actions and provides concrete examples of AI adoption use cases from across the G7 to better inform governmental and SME choices. We believe that this resource can help lower barriers faced by SMEs in adopting and commercializing AI.
7. Our work to advance SME AI adoption builds on the 2024 Italian G7 Presidency report Driving factors and challenges of AI Adoption and Development among companies, especially micro and small enterprises. We welcomed the contributions of the Organisation for Economic Co-operation and Development (OECD) and Canada's three National AI Institutes (Amii, Mila, and the Vector Institute), to inform development of the Blueprint. We also appreciate insights from the AI and Small Business workshop in May 2025, hosted by the Government of Newfoundland and Labrador, the Newfoundland and Labrador Association of the Community Business Development Corporation and the OECD.

Policy Recommendations

8. Access to adequate infrastructure is essential to supporting AI development and deployment. Connectivity, compute and storage and high-quality datasets are some of the key elements. However, we note that the infrastructure currently on offer does not always meet SMEs' access and affordability needs. We therefore see value in:
   • Continuing public and private investments in reliable, high-speed broadband infrastructure with a specific focus on building infrastructure in communities that either lack or have inadequate coverage, notably by increasing internet speed, improving connection quality and lowering prices, to help spur and improve opportunities for AI adoption and participation in the broader digital transformation.
   • Accelerating public and private investments in AI compute and cloud infrastructure, including shared infrastructure, with a particular focus on increasing affordability, availability and competition. This will improve availability of compute and cloud resources on terms and costs better suited to SME constraints and budgets and promote the emergence of offerings that unlock SME growth while promoting healthy competition.
   • Increasing the availability of high-quality, privacy-preserving, intellectual property-respecting datasets, including sector-specific datasets, that are essential for training AI models and can help drive SMEs' AI adoption and innovation. Access to sector-specific datasets—offering, where relevant, de-identified and anonymized datasets—is particularly critical for supporting high-risk domains, such as healthcare, finance and critical infrastructure, where accuracy, reliability, confidentiality and privacy are essential. To help achieve these objectives, it is important to build and invest in public-private collaborations where needs are identified.
   • Exploring how open-source and open-weight AI models and systems can help lower barriers and administrative burden to adoption and experimentation by SMEs, including by drawing on a wider pool of developer talent and making it easier to adapt and reuse solutions in new settings, and while noting that standardized solutions can help support these objectives. We also affirm the need for these models and systems, as well as the ecosystems supporting them, to be responsibly managed and appropriately maintained, to promote their continuing relevance.
9. Successful AI adoption at the company level requires awareness of AI and its opportunities, strong leadership, coherent planning and alignment with a company's overall business strategy. We therefore encourage businesses and business associations to invest in AI—and data—literacy across the organization, including among leadership, to facilitate multifaceted decision-making, involve and empower employees and their representatives, build change readiness and strengthen return on investment projections. We note that AI adoption roadmaps (including sector-specific roadmaps) can guide value-driven adoption and alignment with business goals, and that pilots and phased rollouts can help mitigate risks and support scaling. We emphasize the value of fostering a conducive business culture that embraces AI experimentation and collaboration across business functions, supported by effective change management and evaluation. We also recognize the importance of raising awareness about the benefits of AI use cases among SMEs, while fostering open and transparent conversations to overcome the obstacles and financial considerations involved. We also highlight that ecosystem activities, such as peer-learning, workshops, conferences and events can spread best practices among SMEs and startups.
10. Upskilling, reskilling and talent development are essential for SMEs to effectively and responsibly integrate AI. It is crucial to equip employees with the knowledge and confidence to responsibly deploy AI, adapt their roles and drive innovation across workflows. The rapid pace of AI innovation has surfaced a wealth of high-quality learning opportunities. We underline the importance of supporting programs that combine foundational learning and role-specific training, including the unique operational and technical needs of specific sectors and populations, as well as programs that connect SMEs to universities and research centres, notably by embedding AI talent directly within the company. We emphasize the value, for SMEs, of fostering a culture of continuous learning and actively involving employees in shaping AI implementation in the workplace, so they are empowered—not displaced—in the age of AI. We recognize the value of ensuring equal opportunity by encouraging women and communities left behind by globalization to be involved in this process. We also encourage public entities, businesses and business associations to create shared spaces that connect SMEs with the most relevant training, tailored to their specific needs.
11. Expanding mechanisms for financial support to SMEs, including public-private partnerships, is important to addressing the barriers to access capital that they face when adopting AI. Governments, businesses and business associations should collaborate to promote the development of, and competitive markets for, innovative AI-based products and services that meet SME needs, including through support for research and development and SME-focused innovation hubs. We encourage sector initiatives and networks, when implemented consistently with applicable legislation, that can pool SME resources to create economies of scale, for instance, through shared services models, collaborative procurement, learning, joint purchases of AI licenses and cloud infrastructure access, or joint hiring of specialized expertise. Finally, we see value in leveraging trusted intermediaries, such as chambers of commerce, research and innovation centres, industry and sectoral associations, credit unions and local development banks, to help SMEs navigate the AI ecosystem and promote uptake, for instance by bundling financial support with advisory services.
12. A pro-innovation environment, combined with clear and practical guidance on regulatory and governance matters is essential for a level playing field and enables effective and responsible AI adoption by SMEs. When concerns around legal and reputational risks are unaddressed, they can prevent businesses from fully taking advantage of AI and lead to the deployment of AI in inappropriate ways. As SMEs face these risks with fewer resources, we support the development of SME-friendly toolkits and guidance informed by best practices, such as those recognized through the Hiroshima AI Process. Governments and regulators may wish to promote frameworks and support standards development accounting for SME operational realities. Enhancing compatibility in AI governance frameworks across borders can also promote clarity and reduce compliance burden for SMEs.