5 Key Takeaways from ALL IN 2026

Between the strengthened partnership with Germany, the investment in LawZero, and the national AI literacy initiative, five major workstreams emerged from the conference, outlining the conditions required to industrialize AI across your organization.

1. Sovereignty Is Shaping the Next Phase of Execution

The enhanced partnership between Canada and Germany goes far beyond diplomatic symbolism. As the Minister of Artificial Intelligence, Evan Solomon noted,“No country can build alone.” The two nations signed a joint declaration on AI and launched the Sovereign Technology Alliance, with the goal of reducing technological dependencies while building shared capabilities in research, commercialization, and infrastructure.

That commitment was reinforced through direct investments in LawZero, the Montreal-based organization founded by Yoshua Bengio. Canada is contributing CAD $150 million, while Germany is investing €100 million. The funding will support LawZero’s Scientist AI approach, an advanced AI designed to be safe, transparent, and verifiable, while also strengthening sovereign computing capabilities within Canada. In practical terms, the objective is to develop world-class AI without relying entirely on foreign models.

2. Trust Remains a Prerequisite for Adoption

“AI is not a goal, it’s a means,” reminded Isabelle Turcotte, co-founder of ALL IN, during the conference opening. Minister Evan Solomon echoed the same principle: technology must serve people, not the other way around. Montreal Mayor Soraya Martinez Ferrada reinforced the message: “Trust cannot be decreed; it must be built. Fear must not prevent us from innovating.”

The reminder comes at a time of growing public skepticism, as anti-AI demonstrations continue to gain visibility, including in Montreal during the event itself. In response, the federal government will launch a national AI literacy initiative this fall in partnership with the Alberta Machine Intelligence Institute. The program will target students, educators, workers, and communities, helping citizens recognize bias, misinformation, and privacy risks associated with AI technologies.

3. Security Can No Longer Be an Afterthought

Organizations are not lacking AI ideas. What they often lack is the methodology, time, and governance needed to build security into systems from the outset. Under pressure to move quickly, cybersecurity is still too often postponed, even as increasingly autonomous systems introduce new risks, from data exposure and flawed decision-making to deepfakes and vendor dependency.

At ALL IN, responsibility for addressing these challenges was framed as a collective effort rather than an individual one. Beyond LawZero, several announcements focused on enterprise data security and governance. Canada has placed democratic protection and technological sovereignty at the center of its national AI strategy, signaling that security is no longer solely an IT concern. It is a shared responsibility across governments, businesses, and citizens.

4. Execution Capacity Is Becoming the Real Bottleneck

AI use cases are everywhere, and experimentation continues to accelerate. Yet human factors often enter the conversation too late: workforce training, employee engagement, change management, and process redesign. As a result, AI transformation frequently reaches a ceiling determined by an organization’s ability to absorb change at scale. An example shared by Alberta Minister of Technology and Innovation Nate Glubish highlighted the gap between traditional operating models and modern capabilities. A conventional public procurement process originally projected to take four years would likely have become obsolete before implementation. By adopting new approaches to talent mobilization and project delivery, the initiative was completed in just 12 months for approximately $2 million. As Glubish noted, it was “95% faster, 95% cheaper.” AI may accelerate technical capabilities, but procurement, governance, and organizational structures must evolve at the same pace.

5. Corporate Memory Will Shape the Future of AI Agents

To truly support day-to-day work, AI agents must understand multiple layers of context: the user’s history, team knowledge, departmental processes, and the broader organizational memory. Without that depth, they remain transactional assistants. With it, they become powerful tools for continuity, knowledge retention, and operational effectiveness.

That corporate memory also raises important governance questions. Which data can be accessed? By whom? Under what controls? AI agents will only be valuable if they rely on relevant organizational knowledge, and they will only be viable if that knowledge is governed responsibly. One of the next major challenges for organizations will be moving from AI that simply responds to AI that genuinely understands organizational context, without compromising privacy or security.

The Shift to Execution

After years focused on demonstrating AI’s potential, the technology is entering its execution phase. Canada possesses significant strengths, from world-renowned research and Montreal’s innovation ecosystem to international partnerships. Going forward, success will be measured by AI’s ability to create lasting, tangible transformation across organizations and society while keeping people at the center of progress.