Key takeaways
Every day, government leaders navigate the increasing pressure of constrained budgets and cost pressures to deliver digital services that achieve productivity outcomes and support great service experiences. AI and demand for new government service delivery models have further increased this tension and the cost of standing still.
Common tech enablers, interoperable components and repeatable design patterns offer a solution, letting governments effectively create national system-level infrastructure. The results would reduce costs and ensure that even when jurisdictions invest in different technologies, their interoperable pieces still fit.
Doing more with less could start today. In fact, it already has.
Common technology design, tech components, and delivery patterns are all examples of Digital Public Infrastructure (DPI)—the shared digital frameworks that enable digital payments, identification, data exchange, and other foundational systems.
Global case studies demonstrate that common tech components have been successfully implemented as part of DPI in federated environments.
These case studies challenge the assumption that Canada’s federated model is a structural barrier, suggesting that the constraint lies in operating model and execution. Success comes not from centralizing service delivery, but from standardizing shared building blocks—allowing jurisdictions to retain independence while benefiting from common capabilities and interoperability. Here, DPI offers a third way between SaaS and custom software development.
The momentum is real, and recent. In June 2026, the Government of Canada joined the Digital Public Goods Alliance: a multi-stakeholder, UN-endorsed initiative that facilitates the discovery and deployment of Digital Public Goods (DPGs).8 And Canada's DPI efforts to date have been positive and foundational, as illustrated by representative examples in identity, payments, and data exchange.
But these efforts are advancing in isolation, within individual sectors and jurisdictions, reaching a fraction of Canadians. Canada is still behind leading G7 and G20 countries in its progress on executing and integrating DPI. Out of the 44 countries included in the OECD Digital Outlook Government 2026 report, Canada ranks 23rd in “Proactiveness”, 30th in “Data-driven Public sector” and 36th in “Government as a Platform.”9
Privacy requirements, jurisdictional autonomy, governance complexity, procurement models, funding mechanisms, and inconsistent standards can all make sharing harder than building independently. Addressing these barriers is a prerequisite for scaling common components nationally.
Canada has the foundations to build a more coordinated DPI ecosystem—national-scale infrastructure will be built one reusable decision at a time.
To move from individual initiatives to national-scale infrastructure, we recommend:
Canada has just set one of the most ambitious digital agendas in its history: Canada’s National Artificial Intelligence Strategy: AI for All aims to lift business AI adoption to 60% by 2034 and unlock a 3% increase in GDP, largely from productivity gains. But that upside rests on trusted data and public trust.
As shown by the success of India's Aadhaar platform, the foundation on which population-scale AI-enabled services now run, shared digital identity, real-time payments, and secure data exchange will be the connective tissue that lets AI operate on verified data. The DPI Canada builds now will be essential to the next twenty years of AI development.
Deloitte is well positioned to partner across the full DPI journey. Whether you’re already using DPI or just beginning, we offer support from strategy and policy through to pilots, large-scale implementation, and national scale. As a trusted systems integrator, we deliver complex, population-scale platforms across jurisdictions and technologies, while bringing deep expertise in ecosystem governance, sustainable commercial models, and lessons from proven global DPI programs.
We also help clients harness AI and modular, open approaches to enable new service models and model the economic business case for the policies and programs they support.