Digital Transformation Canada: Why I'm In Favour

Yesterday the Government of Canada announced a change I have wanted to see for a long time. Digital Transformation Canada (DTC) brings Shared Services Canada, the Canadian Digital Service, and selected digital functions from the Treasury Board of Canada Secretariat, Public Services and Procurement Canada, and Employment and Social Development Canada into a single organization, led by CEO Patrick Pichette and reporting to Minister Joël Lightbound ^[1]. Its mission: use digital solutions, including AI, to make government services easier to access and more reliable, and to use federal purchasing power to help Canadian technology companies grow at home ^[1].

I do not write about this as an observer. Before Microsoft, I spent two decades doing organizational IT innovation in the Government of Canada, including work with Shared Services Canada and the Treasury Board Secretariat. I have seen these systems from the inside: what fragmentation costs, what consolidation achieves, and where the last attempt fell short. So let me say it plainly: I am in favour of this. Here is why, and here is what I will be watching.

Consolidation was never the hard part

The Government of Canada created Shared Services Canada in 2011 for good reason. Before SSC, departments ran their IT infrastructure independently: 63 separate email systems, more than 500 data centres, and 50 wide area networks, at a cost of roughly $2 billion a year ^[2]. Centralizing that was necessary, and it delivered real savings and reliability gains ^[2].

But consolidating infrastructure was never sufficient. An organization that runs networks and data centres well is not automatically one that designs services people find easy to use, buys technology smartly, or helps departments adopt new ways of working. Those capabilities lived in different departments, with different cultures, budgets, and incentives. The result was a government that owned the pipes but struggled to deliver the experience.

DTC is the first attempt to put infrastructure scale, user-centred service design, policy, and buying power into one accountable organization ^[1]. That is the part that gives me confidence, because it targets the actual failure mode: not too much consolidation, but too much separation between running technology, designing services, and buying capability.

The anchor-customer turn is the real Canadian AI story

Canada's AI strategy, AI for All, launched in June 2026 with an ambitious target: raise business AI adoption from just over 12% to 60% by 2034, contributing $200 billion in growth and 250,000 AI jobs ^[3]. Strategy targets are only as good as their delivery mechanisms, and this one is explicit: the federal government will use procurement as a strategic anchor customer for Canadian AI companies ^[3].

DTC makes that operational. Its third priority is using the Government of Canada's purchasing power more strategically so Canadian digital and AI companies can test, scale, and commercialize new technologies at home before competing globally ^[1]. Government is the largest buyer in the country. A demanding, fair, early customer at home is exactly what Canadian AI firms lack today, and it is how a domestic ecosystem grows instead of exporting its best companies early. Procurement as industrial policy, applied to AI: this is overdue, and DTC is the vehicle that could actually deliver it.

The fellowship model builds judgment, not dependence

DTC will also establish a fellowship model to bring specialized private-sector expertise into government for short-term assignments, including in advanced AI, with an explicit focus on knowledge transfer: building the public service's own technical capacity and its ability to evaluate, procure, and deploy new technologies responsibly ^[1].

This is the right instinct. The public service does not need to build every system itself, but it does need enough internal judgment to be a smart buyer: to know what good looks like, to evaluate vendor claims, and to turn pilots into programs rather than shelfware. Fellowships that rotate real expertise in, with a transfer mandate, build that muscle without hollowing out the institution. Application details are not yet published as of this writing; the design will matter as much as the idea.

The largest workforce in the country gets modern tools

DTC's other priorities are about the public servants themselves: equip them with more modern, secure tools, reduce administrative burden, and let departments focus on core programs and services ^[1]. Having worked inside these organizations, I know how much daily capacity is lost to dated tools and manual process. The federal public service is the largest workforce in the country. Small per-person productivity gains there are national gains, and AI applied to real workflows, translation, navigation, casework, is how those gains arrive. This is adoption work, not technology work, which is precisely the part most organizations underestimate.

Where I would be careful

I am in favour, not naive. Reorganizations fail when they move boxes instead of changing how work gets done, and this one carries real risks. If procurement rules and risk appetite do not actually change, DTC becomes a new nameplate on old behaviour. Private-sector leadership is a bet, and while Pichette's record is formidable, public service delivery is not scaling Google; success will depend on respecting public service culture and its accountability rules ^[1]. And consolidation has a human cost: transitions of this size take years and cannot be rushed for optics. The 2011 SSC experience taught the system what disruption looks like; the question is whether this round pairs change with support.

Five markers I will be watching

1. Procurement speed. Time from pilot to contract, and whether outcomes-based, flexible vehicles actually appear.
2. Anchor-customer deals. The first announced Canadian AI contracts under DTC, and whether they are real scale opportunities or pilot-sized gestures.
3. Fellowship design. Transparent intake, genuine knowledge-transfer mandates, and assignments that end with capability left behind.
4. Tool adoption. Whether public servants get modern tools and actually use them, not merely license them.
5. Outcomes for Canadians. Measurable improvements in how people experience federal services: faster, clearer, more accessible.

The leadership position

Canada has world-class AI research and one of the slowest business adoption rates in the G7, a gap AI for All names directly ^[3]. The federal government has now committed to lead by example in responsible AI adoption ^[3], and DTC is the largest single test of that commitment: the country's biggest organization attempting what every large organization struggles to do, turning AI access into everyday capability, with procurement deliberately pointed at Canadian companies.

That is why I support it as a former public servant, and why Beyond 2.0 supports it as a company. Practical AI adoption, workforce enablement, and change that sticks are the work we do every day. If the Government of Canada has made that the official job of a new organization, with Canadian AI companies as the intended beneficiaries, it is a mission worth getting behind, and a test worth watching closely.

Sources

1. Prime Minister of Canada — "Prime Minister Carney launches Digital Transformation Canada to deliver better, faster, more reliable government services to Canadians" (Sep 3, 2026) — https://pm.gc.ca/en/news/news-releases/2026/09/03/prime-minister-carney-launches-digital-transformation-canada-deliver
2. Shared Services Canada — "Overview of Shared Services Canada" (Canada.ca briefing material) — https://www.canada.ca/en/shared-services/corporate/about-us/transparency/briefing-documents/ministerial-briefing-book/overview-shared-services-canada.html
3. Prime Minister of Canada — "Prime Minister Carney launches AI for All: Canada's new national artificial intelligence strategy" (Jun 4, 2026) — https://pm.gc.ca/en/news/news-releases/2026/06/04/prime-minister-carney-launches-ai-all-canadas-new-national-artificial