Seventeen publications across three report series and our open resource collection. Each one reads in full on this site, and each one downloads as an accessible PDF. Nothing sits behind a paywall, a form, or an account.
17 publications shown.
Six data-grounded reports tracing how artificial intelligence is reshaping access, education, entry-level careers, gender equity, regional opportunity and the older workforce — with a consistent lens on Canadian policy relevance and secondary data from Statistics Canada, the CRTC and the OECD.
Canada closed much of its broadband gap. A faster, sharper AI-adoption gap is opening on top of it — tracked by age, income, education, geography and sector.
78 million net new jobs by 2030 and 39% of skills turning over — why skills-based education, not job-title training, is the evidence-backed strategy.
Recent-graduate unemployment has overtaken the overall rate for the first time in decades. Stanford, Goldman Sachs and Bank of Korea data on where — and whether — AI is the cause.
Traced from access to income: a closing usage gap, a static leadership gap, a Canadian entrepreneurship gap — and a genuine paradox at the very top of organizations.
From fibre to economic development across Northern, rural and remote Canada — the AI adoption gap is inheriting the shape of the broadband gap it followed.
The workforce's fastest-growing group is under-trained, not unwilling — and early data suggests AI has so far been kinder to experienced workers than to entry-level ones.
Five independent briefs on enterprise AI adoption, each grounded in research from McKinsey, BCG, PwC, the World Economic Forum, Gartner, Deloitte, IBM and LinkedIn — with our own read on what the evidence means and where the capability gap actually sits.
88% of organizations use AI and two-thirds are still piloting. Why the next move is building capability, not running another proof of concept.
$2.6–4.4 trillion in annual value, three-quarters of it concentrated in four functions. Treating AI as a governed portfolio of bets, not a pile of disconnected pilots.
Five times the revenue growth and three times the cost reduction. The gap between AI leaders and laggards is compounding, not closing.
The market is sorting into three tiers — 5% future-built, 35% scaling, 60% lagging. When everyone has the same models, advantage shifts to speed and judgment.
Only a quarter of workers say leaders give enough guidance on AI. Training budgets are up; the missing input is coming from further up the org chart.
Longer-form studies on who is included in the AI economy and in the training systems that feed it, using named research and Canadian administrative data.
AI postings have roughly doubled since 2023 and pay more than double the typical role. Women hold 26% of new hires, 20% of Head of AI roles and 13% of AI C-suite seats.
Training decides who advances, not just who is hired. Disabled and racialized workers face compounded, measurable barriers inside the very programs meant to develop them.
Practical tools for evaluators, researchers and community partners doing rigorous work without a dedicated research team. Free to use, with no account, fee, or attribution required.
Theory of change templates, indicator libraries, consent and interview guides, and a reporting outline for small organizations without an evaluator.
Recruitment, consent, session design, and dissemination steps to make a study genuinely accessible to disabled participants and audiences.
Short, plain-language syntheses on questions practitioners keep asking, each with a clear statement of how confident the evidence lets us be.
Practical rules and worked before-and-after examples for turning technical findings into something a busy decision-maker will finish reading.
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