Scale AI is a public–private partnership supported by Innovation, Science and Economic Development Canada (ISED) through the Global Innovation Clusters (GIC) initiative. Based in Montréal, Scale AI supports a national ecosystem of industry leaders, SMEs, researchers, and training institutions to accelerate the integration of artificial intelligence in supply chains and related applications. Through international partnerships, Scale AI positions Canada as a global leader in AI-driven supply chain innovation, fostering collaboration with world-class research institutions and global ecosystem partners. The industry-led cluster focuses on building Canadian-owned IP, fostering cross-sector AI adoption, and developing a skilled workforce.
Scale AI (Canada)
Abstract
Text. The Global Innovation Clusters (GICs) programme, first launched in 2017 as the Innovation Superclusters Initiative and renamed in 2022, aims to enhance Canada’s innovation performance and competitiveness through co-investment with industry in five strategic domains identified by the government as nationally significant: artificial intelligence (AI), digital technologies, protein industries, oceans, and advanced manufacturing.
As a flagship component of Canada’s innovation policy, the GICs are designed to foster industry-led innovation ecosystems that link businesses, research institutions, and other partners to accelerate technology development and adoption. Each cluster defines its own priorities and project focus, while encouraging collaboration between large and small firms within and across sectors.
Scale AI – Canada’s AI-Powered Supply Chains Cluster – is one of the five GICs, dedicated to driving the application and diffusion of AI across Canada’s industrial and service sectors. It bridges the gap between Canada’s world-class AI research and its commercial deployment, supporting collaborative, pre-competitive projects that de-risk innovation and strengthen national capabilities in data infrastructure, supply chain optimisation, and workforce upskilling. Scale AI has delivered significant value that goes beyond conventional supply-chain use cases across diverse industries in sectors such as retail, manufacturing, transportation, infrastructure, healthcare, aerospace, energy, agriculture, and financial services.
Scale AI places a strong emphasis on embedding ‘IP thinking’ into every stage of AI innovation. This means not only creating and owning AI-related intellectual property (IP) such as models, algorithms, and proprietary data, but also implementing robust governance and commercialisation strategies. By integrating IP considerations into business planning, Scale AI ensures that Canadian innovators retain control of their core assets, leverage them for growth, and scale their economic and societal impact within Canada. An overview of key programme characteristics is given in Table 1.
Canada’s broader AI strategy seeks both to strengthen national leadership in responsible AI research and to accelerate the diffusion of AI technologies across the economy. These goals are pursued through complementary initiatives, including the Pan-Canadian Artificial Intelligence Strategy (PCAIS), which supports excellence in AI research and talent development, and Canada’s Digital Ambition, which guides the modernisation of public digital infrastructure and data governance. Within this landscape, the GICs serve as a key policy lever to translate research strengths into commercial and societal impact. By mobilising nationwide ecosystems in strategic industries, the GICs, and particularly Scale AI, enable the development, deployment, and scaling of AI solutions across Canada’s industrial base.
The findings and analysis presented in this case study are based on a combination of 5 interviews and desk research. Between July and August 2025, the OECD TIP Secretariat Team conducted semi-structured interviews of approximately 60 minutes each with a diverse range of stakeholders directly involved in Scale AI, including government representatives, cluster management, small- and medium-sized enterprises (SMEs), large firms, and research organisations. The interviews covered topics such as Scale AI’s governance arrangements, project portfolio and support mechanisms, stakeholder engagement, observed impacts, and approaches to monitoring and evaluation. These interviews provided insights into the perspectives, experiences, and challenges faced by each group within the Scale AI ecosystem. Additionally, desk research was undertaken to review relevant publicly available documents, previous evaluations, and reports on Canada’s GIC initiative. The Secretariat is extremely grateful to the stakeholders in Canada for their time and contributions to the development of this case study.
Background: Scale AI is one of five innovation clusters established under Canada’s Global Innovation Clusters (GIC) programme, a flagship federal initiative launched in 2017 by ISED. The programme aims to strengthen Canada’s global competitiveness in key sectors by fostering collaboration between industry, academia, and government. Through a national competitive selection process, each cluster was chosen to represent an area of strategic economic importance and technological opportunity.
Scale AI was designated as Canada’s AI-Powered Supply Chains Cluster, reflecting the government’s recognition that supply chains form a critical backbone of the economy – and a domain where AI could generate broad productivity, resilience, and sustainability gains. By targeting supply chains, Canada sought to create a domestic market for AI innovators, enabling home-grown researchers and firms to deploy and scale AI solutions within key sectors such as manufacturing, transportation and logistics, retail, finance, and health. This approach was designed to anchor a self-sustaining AI ecosystem in Canada, in which domestic innovation could translate into tangible industrial and societal benefits.
Headquartered in Montréal, Québec, the Cluster leverages Canada’s globally recognised AI research strengths, particularly in Montréal and Toronto, to connect research excellence with commercial and industrial application. Its mandate is to bridge academic innovation and industry needs, accelerating the adoption of AI technologies across value chains while supporting talent development and start-up growth.
While DIGITAL, Canada’s Digital Technology Cluster, focuses more broadly on advancing digital transformation and data infrastructure across sectors, Scale AI concentrates on AI-driven optimisation of supply chains and industrial processes. The two clusters are complementary, working at the intersection of AI development and diffusion, one enabling broad digital maturity, the other delivering deep, sector‑specific AI impact, together strengthening Canada’s broader frontier technology ecosystem.
As in other GICs, Scale AI is structured as an industry-led, not-for-profit organisation, with its strategic direction and funding model overseen by ISED. Through the GIC programme, ISED provides core public investment, which is matched by private sector contributions, forming the basis for collaborative R&D funding and talent programmes. In addition to core funding from ISED, the Government of Québec provided complementary co-funding for projects delivered within the province. Over the past seven years, approximately 11.5% of Scale AI’s total public funding came from the Québec government, reinforcing a shared federal–provincial commitment to position Canadian innovators at the forefront of international AI ecosystems. This co-investment model is central to Scale AI’s governance and accountability framework, ensuring alignment with national industrial and innovation priorities while leveraging both private and provincial engagement to maximise impact.
Scale AI is further embedded in Canada’s broader innovation and industrial policy landscape. It aligns closely with the Pan-Canadian Artificial Intelligence Strategy (PCAIS), which supports national leadership in AI research and its responsible use; and Canada’s Digital Ambition, which outlines how the Government of Canada will modernise digital service delivery, enhance data governance, and strengthen digital infrastructure. The Cluster also collaborates with other federal initiatives such as the Strategic Innovation Fund (SIF), which has recently been updated to the Strategic Response Fund (SRF), to support complementary investments in technology adoption, talent development, and scale-up for high-potential firms.
Projects: The following examples highlight how Scale AI supports the application of AI across diverse sectors by enabling real-world, collaborative projects that address specific operational challenges through AI-driven solutions.
Optimisation of Crane Allocation: Led by Guay (adopter) and Vooban (SME partner), this project applies AI to improve crane allocation, by developing an AI-powered platform to streamline and optimise scheduling. In its first phase, the project focused on building an intelligent dispatch system capable of dynamically allocating the most suitable equipment and crew to each service call. This system leverages AI to improve efficiency, maximise daily service capacity, and reduce equipment downtime. The second phase introduces an intelligent service request module, which automates and accelerates the entry of client requests into the system. By doing so, it minimises human error in next-day scheduling and ensures greater responsiveness to shifting operational demands.
Enhancing E-commerce Search (Phases 1 & 2): Being one of the biggest projects of Scale AI, this project, led in partnership with Coveo and IVADO Labs, leverages generative AI and machine learning to improve online product discovery and conversion rates. It develops and deploys advanced AI tools for automating product catalogue enrichment, enabling visual and semantic search, detecting shopper intent, and optimising search result rankings. The goal is to create more personalised and intuitive shopping experiences while providing scalable AI solutions for the broader retail sector.
Galileo Project - Workforce decisions and planning support using AI: Led by the Maritime Employers Association, in partnership with Airudi, Polytechnique of Montreal, and HEC Montréal, this project uses AI to improve labour planning and operational efficiency at the Port of Montréal. By predicting ship arrivals up to 21 days in advance and estimating daily workforce needs based on cargo volume and type, the AI-driven tool enhances supply chain visibility and port performance. The project aims to increase fluidity, reduce delays, and support smarter, data-driven workforce decisions in maritime logistics.
Outcomes: Scale AI’s outcomes reflect a step-change growth trajectory, in which ecosystem performance improves through successive phases of mobilisation, deployment, and scale rather than through linear growth. In its early years (2019–2020), the Cluster focused primarily on ecosystem mobilisation and pipeline formation, resulting in a limited number of projects but establishing foundational partnerships across industry, research, and government. This was followed by a period of broad-based deployment (2023–2024), characterised by a rapid expansion in project volume and sectoral coverage. The current phase (2024–2025) reflects a transition towards scale, marked by higher average project values, increased participation of first-time AI adopters, and stronger cumulative impacts.
This progression is reflected in key performance indicators. The number of active projects increased from 8 in the early phase, to 26 during the deployment phase, and to 33 in the most recent period, alongside growth in annual project value from USD 81.4 million (CAD 111 million) to USD 85.8 million (CAD 117 million), and subsequently to USD 104.9 million (CAD 143 million). Over the same period, the share of projects involving first-time AI adopters increased from 69% to 75%, indicating a widening diffusion of AI capabilities beyond early movers. Cumulative project funding rose from USD 538 million to USD 673 million, signalling both scale effects and increasing cluster efficiency.
As of March 2025, the Cluster had supported 162 projects, engaging more than 630 organisations across Canada – including over 425 SMEs, large industrial firms, research institutions, and universities. These collaborations span multiple sectors, such as manufacturing, transportation, retail, healthcare, and logistics, and bring together diverse ecosystem actors across industry, research, and technology development. Scale AI’s 140 member organisations also actively contribute to shaping the Cluster’s strategic direction, helping align investments with real-world business and innovation needs.
The Cluster operates under a co-investment model, with USD 299 million (CAD 409 million) committed by industry partners, contributing to a total portfolio of USD 492 million (CAD 673 million). These investments are expected to generate USD 5.1 billion (CAD 7 billion) in direct economic value by 2030. Scale AI-supported projects have also contributed to building a robust Canadian AI IP base. As of March 2025, 100% of IP created in the first 100 projects was Canadian-owned, and over 95% of this IP had already been commercially deployed by Canadian firms, reinforcing Canada’s competitive position in AI-driven innovation.
Beyond innovation and IP development, Scale AI plays a pivotal role in scaling Canadian ventures and talent. The initiative has supported 500+ ventures and aims to create 9,800 jobs through its funded activities. It also has a strong focus on workforce development, with more than 50,000 individuals trained through its educational partnerships and talent programmes. These results position Scale AI as a key enabler of digital transformation in Canada’s economy and a strategic driver of both national and global AI leadership.
Challenges: Scale AI has demonstrated strong outcomes in project delivery, IP creation, and workforce development. However, it faces several structural and ecosystem-level challenges that are characteristic of initiatives supporting applied AI in real-world settings. One recurring issue is the translation of successful AI pilots into sustained enterprise-wide deployment. While Scale AI’s co-investment model enables experimentation and validation, many SMEs and mid-sized firms struggle to integrate AI solutions at scale due to legacy systems or limited change management capacity. Procurement practices, particularly in sectors like transport, logistics, and healthcare, often lag behind technological capabilities, limiting opportunities for broader commercial uptake. Additionally, although Scale AI operates at a national level, much of the ecosystem’s activity remains concentrated in specific regions, such as Québec and Ontario, making it more difficult to ensure wide geographic diffusion of AI capabilities.
The Cluster also operates in a rapidly evolving regulatory and market environment. As AI technologies mature, expectations around transparency, explainability, and responsible data use are increasing. Scale AI must support firms in navigating evolving standards and ethical considerations while enabling innovation. A further tension lies in managing the role of multinational corporations (MNCs) within the ecosystem. Global firms bring valuable data, infrastructure, and commercial scale, but their involvement raises questions around IP retention, talent pipelines, and long-term benefits for the Canadian AI ecosystem. Ensuring that Canadian firms remain not only participants but leaders in the development and commercialisation of AI-powered supply chain solutions will be a central challenge as the initiative enters its next phase.
Like all of Canada’s GICs, Scale AI operates under a two-tiered governance structure. At the federal level, ISED oversees the programme’s design, funding, and performance monitoring, ensuring coherence with national innovation and industrial strategies. At the cluster level, Scale AI is managed as an independent, industry-led not-for-profit organisation. It is governed by a board of directors composed of leaders from Canada’s AI and supply chain sectors, which provides strategic guidance, sets funding priorities, and ensures alignment with the Cluster’s long-term mission to strengthen Canada’s position in global AI supply chain innovation.
The board sets strategic direction, evaluates project proposals, and oversees investment decisions. Advisory committees provide additional input on areas such as responsible AI, workforce development, and ecosystem inclusion. This governance model is designed to foster agility, encourage cross-sector collaboration, and maintain a strong industry orientation. Stakeholders interviewed by the OECD noted that Scale AI’s model enables responsiveness to evolving market conditions, particularly in fast-moving sectors such as AI, retail, transport, and healthcare logistics.
In addition to federal support, the Government of Quebec played a role as a co-funder of Scale AI in the early phase of the initiative, recognising the Cluster’s strategic importance in reinforcing Quebec’s ambitions in AI. Quebec’s financial contribution helped fund projects based in the province, particularly those that aligned with provincial economic development priorities. This partnership between federal and provincial governments adds an important layer of alignment between national and regional innovation strategies, while also enhancing Scale AI’s capacity to support firms across Canada.
Scale AI’s strategic focus is shaped by its dual commitment to sector-specific transformation and cross-cutting digital enablement. The Cluster supports AI integration by fostering collaboration across both vertical industries and transversal technology providers, with a structured approach that distinguishes between primary and secondary areas of engagement.
Transversal priorities: Scale AI supports a range of transversal actors who enable AI adoption and innovation across industries.
AI and digital technology providers: These firms bring core technological capabilities, such as data platforms, machine learning tools, and advanced analytics, that power sectoral use cases.
Supply chain solutions providers: Companies that offer specialised systems for logistics, procurement, and warehouse management are key collaborators, helping bridge sector needs with technological capabilities.
Vertical priorities: Scale AI targets several key vertical sectors where supply chain transformation can drive significant economic and productivity gains.
Consumer goods and retail: Where AI helps optimise inventory, demand forecasting, and customer experience.
Industrial goods and manufacturing: Focused on improving production planning, supply chain orchestration, and predictive maintenance.
Transport and logistics: A core focus where AI applications enhance routing, scheduling, and overall efficiency of goods movement.
Intrahospital logistics: Addressing operational and resource allocation challenges in healthcare facilities.
Infrastructure and construction: Exploring AI applications to streamline procurement, delivery, and site operations in large-scale projects.
Scale AI is funded through Canada’s Global Innovation Clusters (GIC) programme, under the stewardship of Innovation, Science and Economic Development Canada (ISED). Like other clusters, Scale AI operates on a five-year funding cycle, designed to ensure performance accountability and strategic adaptability. While this structure enables periodic review and adjustment, it can also constrain longer-term planning – particularly for AI-related initiatives that require sustained deployment, system integration, and workforce transformation over extended time horizons – given that funding is time-limited and renewal is not guaranteed.
In addition to federal support, the Government of Quebec played a significant co-funding role particularly during Phase I, recognising Scale AI’s strategic importance in reinforcing Québec’s leadership in AI and supply chain innovation. Quebec’s contribution supported the development of collaborative R&D and talent initiatives within the province and strengthens regional innovation capacity, particularly in the Montreal-to-Waterloo corridor.
Scale AI follows a co-investment model in which public funding is matched by industry contributions. As of 2025, the total portfolio of Scale AI projects exceeded USD 492 million (CAD 673 million), with USD 299 million (CAD 409 million) coming directly from industry partners. Projects are selected through competitive calls or continuous intake, depending on the nature of the initiative. Calls for Proposals (CFPs) are used selectively for sector-specific priorities where targeted engagement is required. In contrast, horizontal, industry-led projects are generally less suited to CFPs and are better supported through ongoing intake. All projects are evaluated against a set of strategic and operational criteria, including:
Expected productivity and economic impact
Degree of AI integration into supply chain functions
Participation of SMEs and commercial scalability
Creation of Canadian-owned intellectual property
Alignment with national and provincial innovation goals
Project evaluation at Scale AI is overseen by an internal investment committee, supported by external expert reviewers, to ensure technical rigour, market relevance, and ecosystem value. While day-to-day project assessment and refinement are handled operationally, the board plays a critical role in setting strategic priorities, safeguarding balance across adopters, AI service providers, and research actors, and ensuring that funded projects align with Scale AI’s mandate to build Canadian-owned AI capabilities. This governance structure allows Scale AI to combine efficient, demand-driven project selection with strategic oversight, supporting high-potential initiatives while reinforcing Canada’s leadership in applied AI and supply chain modernisation.
Scale AI supports the development, adoption, and diffusion of AI technologies in supply chain applications by strengthening Canada’s AI ecosystem through co-investment in collaborative projects, integration of diverse industry actors, targeted IP strategies, commercialisation pathways, and workforce development. Its ecosystem-building approach emphasises multi-stakeholder collaboration across vertical and transversal sectors and regions.
Scale AI operates through a co-investment model that funds collaborative AI integration and innovation projects across supply chains. These projects are industry-led and typically involve a mix of partners, including large enterprises, SMEs, startups, research institutions, and academic organisations. The objective is not only to accelerate the development and adoption of AI technologies but also to foster collaborative relationships across sectors and firm sizes.
A notable feature of the model is the strong level of industry participation: as of 2025, industry contributions account for 61% of total project funding, resulting in a higher-than-anticipated co-investment ratio of CAD 1.6 for every CAD 1 of Scale AI funding. This high level of private-sector commitment reflects both the strategic relevance of the Cluster’s focus areas and the strong alignment between public funding priorities and industry needs.
Scale AI engages leading Canadian and international firms as anchor partners, positioning them at the core of its collaborative innovation model. These firms play a crucial role in driving adoption of AI solutions by providing access to real-world use cases, infrastructure, data, and procurement pathways that smaller firms and technology developers can leverage. Through this anchoring function, large firms help de-risk innovation efforts and accelerate the commercialisation of AI technologies developed by SMEs and startups.
The Cluster’s dual orientation – vertical and transversal – fosters cross-sector collaboration, allowing AI innovations developed in one domain, such as dynamic resource scheduling or demand forecasting, to be adapted and scaled in others. For instance, AI tools for workforce planning piloted in the logistics sector can be repurposed for hospital operations or infrastructure maintenance. Scale AI’s platform facilitates these synergies by encouraging project consortia that bring together diverse actors from different parts of the economy, promoting knowledge exchange, capability building, and broader ecosystem integration.
Scale AI aims to foster Canadian-owned and commercially viable IP as a core outcome of its co-investment model. All funded projects are required to develop IP frameworks that ensure clarity on ownership, support equitable benefit-sharing, and maximise opportunities for downstream commercialisation. According to Scale AI’s own reporting, as of March 2025, 100% of the IP generated through its first 100 funded projects was Canadian-owned, and over 95% of this IP had already been commercially deployed by Canadian firms.
Interviews with stakeholders highlighted that Scale AI provides guidance and due diligence during the project design and approval process to ensure that IP arrangements are robust, especially in projects involving SMEs or academic partners. The organisation supports partners in negotiating fair terms that avoid IP fragmentation and enable participating firms, particularly smaller ones, to scale their solutions without becoming locked into unfavourable agreements.
In addition to IP, Scale AI places growing emphasis on the importance of data assets and governance, recognising that access to high-quality, well-managed data is foundational to AI development. Many projects involve multi-party data sharing, particularly in sectors such as logistics, retail, and healthcare, where sensitive or proprietary data must be carefully handled. Scale AI assists project consortia in developing data-sharing agreements and technical protocols that promote interoperability, security, and responsible use, often drawing on emerging best practices in AI ethics and data governance.
These efforts are especially critical in enabling AI models to function across organisational boundaries and systems, thereby expanding their utility and scalability. Several interviewees noted that Scale AI’s support was instrumental in building trust among partners and creating shared understanding around data access, usage rights, and compliance obligations. This has allowed participants to focus more on innovation while maintaining alignment with legal and ethical standards – key conditions for deploying AI in real-world supply chains.
As part of its ecosystem-building mission, Scale AI plays a central role in convening Canada’s AI innovation community. A key platform for this is ALL IN, Canada’s largest AI conference, launched and led by Scale AI in partnership with other ecosystem actors. Held annually in Montréal, ALL IN attracts thousands of participants from across Canada and internationally, including technology leaders, startups, researchers, and government representatives. The event features high-level keynotes, thematic panels, innovation showcases, and networking activities, offering a unique venue to exchange ideas, explore partnerships, and highlight AI adoption in real-world supply chain and industrial settings. In ALL IN 2024, over 4,000 participants and Canada's top 100 AI startups connected with hundreds of investors eager to back the country's next major tech success stories. With 55% of participants being AI adopters and 45% being AI providers, the event provided a unique balance to forge business deals and drive AI adoption across various industries.
ALL IN has quickly become a landmark event in Canada’s innovation calendar, helping Scale AI catalyse new collaborations, increase visibility for Canadian AI solutions, and align stakeholders around shared priorities. It also reinforces Canada’s global position as a hub for responsible, applied AI innovation. In addition to ALL IN, Scale AI regularly hosts sector-specific events, international delegations, and ecosystem roundtables to further deepen its engagement across the country and beyond.
Recognising that AI integration is only as effective as the workforce that enables it, Scale AI has made workforce development a core pillar of its mandate. As of 2025, over 50,000 individuals have participated in training and upskilling activities supported by the Cluster. These efforts aim to equip both current and future workers with the knowledge and skills needed to harness AI in practical, industry-relevant ways.
Scale AI works closely with Canadian universities, polytechnics, research centres, and private training providers to co-develop educational offerings tailored to the evolving demands of AI-enabled supply chains and business operations. These programmes range from short-term, micro-credential courses to more extensive certifications and degree-integrated modules, covering topics such as:
Applied data science and machine learning
AI system deployment in logistics and manufacturing
Ethical and responsible AI use
AI-driven decision-making in supply chains
AI policy, regulation, and risk management
In addition to technical training, leadership and executive education initiatives help business leaders and decision-makers better understand AI adoption from a strategic perspective. Scale AI also supports internship and placement programmes, particularly those targeting underrepresented groups, early-career talent, and SMEs, helping ensure that AI expertise is distributed across regions and sectors.
The Cluster’s talent programmes are designed not only to build technical capacity but to bridge the gap between AI development and industry deployment, helping companies of all sizes develop internal capabilities, reduce reliance on external consultants, and sustain AI adoption beyond initial pilots.
ALL IN: Scale AI’s flagship event and Canada’s largest gathering focused on AI. It brings together industry leaders, researchers, policymakers, and startups to showcase AI innovations, discuss emerging trends, and foster collaboration across sectors.
Canada’s Digital Ambition: A federal strategy that outlines how the Government of Canada will modernise digital service delivery, enhance data governance, and strengthen digital infrastructure. It sets priorities for improving citizen services, enabling secure and interoperable systems, and fostering a digitally skilled public service to support innovation and resilience in the digital age.
Global Innovation Clusters (GIC): Launched in 2017 (formerly Innovation Superclusters Initiative), Industry-led sectoral clusters that bring together businesses, researchers, and government to drive innovation in five key areas: Advanced Manufacturing, Digital Technology, Protein Industries, AI (Scale AI), and Oceans.
Innovation, Science and Economic Development Canada (ISED): A federal department of the Government of Canada responsible for fostering a growing, competitive, and knowledge-based economy. ISED designs and administers policies and programmes to support innovation, scientific research, business growth, and regional development across Canada. It oversees national initiatives such as the Global Innovation Clusters programme, which includes clusters like Scale AI and DIGITAL.
Pan Canadian Artificial Intelligence Strategy (PCAIS): Canada’s national strategy in AI launched in 2023 focusing on research and innovation by supporting talent development, research, and the application of AI technologies.
Strategic Innovation Fund (SIF) : Canadian government programme that provides funding to drive large-scale, transformative projects across critical sectors like advanced manufacturing, clean technology, health, and digital industries through support for research and development, business expansion, foreign investment attraction, and collaborative technology projects.
Strategic Response Fund (SRF): Replacing and building on the earlier SIF, the SRF is a new Canadian federal programme, managed by ISED, that provides large-scale investments to help industries innovate, adapt and compete in a changing global economy by strengthening domestic capacity, managing trade and tariff pressures, and supporting transformative projects in strategic sectors.
References
[4] ISED (2024), IP in Action, https://ised-isde.canada.ca/site/global-innovation-clusters/en/success-stories/ip-action?utm_source=chatgpt.com.
[1] Scale AI (2025), 2024-25 Annual Report, https://www.scaleai.ca/wp-content/uploads/2025/12/SCALE-AI_Annual-Report_2024-2025.pdf.
[2] Scale AI (2024), 2023-2024 Annual Report, https://www.scaleai.ca/wp-content/uploads/2024/09/scaleai_annual-report_2023-2024_eng.pdf.
[3] Scale AI (2020), Strategic Plan, https://scaleai.activ.is/wp-content/uploads/2020/05/scale-ai_strategic-plan_en.pdf.
This case study was developed in the context of the Working Party on Innovation and Technology Policy (TIP) project “Frontier technology development and diffusion” and with the support of Innovation, Science and Economic Development, Canada.
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