Sun Life, Scotiabank, Telus, and Toronto-based Lightworks have formed a Canadian AI consortium aimed at accelerating the development of compliant AI systems. The group, which includes 30 engineers from all four member companies, processes 2 trillion data points monthly. John Painter, founder of Lightworks, said the initiative began as a collaboration between Lightworks and Telus but expanded after recognizing shared challenges in AI governance. The consortium’s formation is a result of over a year of planning, with Painter stating that progress would be significantly accelerated with the addition of more companies.
Collaboration Driven by Common Needs
Industry leaders emphasized that regulatory requirements in finance, insurance, and telecom often overlap. Painter noted that most AI standards across sectors are similar, making joint development efficient. Sun Life’s Laura Money described the partnership as necessary, highlighting urgency in addressing AI compliance. They are working on a system to monitor and manage AI models in real time. This system enables organizations to coordinate AI resources without relying on external vendors. “It’s not a competitive advantage to control AI,” Money added. “They are solving a common problem together.” The consortium’s shared ownership model allows members to retain control over intellectual property, avoiding dependency on third-party systems. This approach also enables companies to have control over AI sovereignty, giving them the ability to make decisions about their AI systems without being forced to rely on vendors.
The diversity of AI platforms and standards makes governance and compliance difficult, but the group brings companies together to jointly develop AI systems they would otherwise have had to build separately. According to Painter, about 80% of the standards and technologies used in AI systems are the same across financial services, insurance, and telecommunications. This similarity in standards makes it efficient for companies to work together to develop compliant AI systems. The consortium’s first project is an agentic decision-making system that helps companies manage the different AI models and agents they use. This system monitors what AI models are doing in real time, allows staff to check its work, and ensures that companies can stop AI processes when they need to.
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Expanding the Initiative
The group plans to develop an AI operations center to track performance metrics for members. Scotiabank and Telus have already joined, with Sun Life and Lightworks following. Money said the consortium is open to new members, including insurance firms and brokerages. “They want to accelerate AI use in Canada,” she said. The addition of new members will bring new expertise and perspectives, further accelerating the development of compliant AI systems. The consortium’s open membership approach also allows companies to join and contribute to the development of AI systems, while also retaining rights to the systems they help develop.
Members split costs and expertise, with no obligation to remain in the consortium long-term. Even if a company exits, it retains rights to systems it helped build. Painter compared the collaboration to office productivity tools, which are essential for any organization. The consortium’s approach to shared ownership and collaboration could set a precedent for other industries, demonstrating the benefits of working together to develop compliant AI systems. As the consortium continues to grow and develop new projects, its impact on the Canadian AI setting is likely to be significant.
They are working to address these challenges. The consortium’s efforts to develop compliant AI systems will help to ensure that companies can use AI in a safe and responsible manner. By working together, companies can share knowledge, expertise, and resources, ultimately accelerating the development of AI systems that meet regulatory requirements. The consortium’s success will depend on its ability to balance the needs and contributions of its members, while also ensuring that the development of AI systems is done in a way that is transparent, accountable, and beneficial to all parties involved.
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