AI Law - International Review of Artificial Intelligence LawCC BY-NC-SA Commercial Licence ISSN 3035-5451
G. Giappichelli Editore

31/07/2026 - AI Due Diligence in Canada-US M&A: Why “Does It Use AI?” Is No Longer Enough

argument: Notizie/News - Commercial Law

Source: Dentons

Artificial intelligence is embedded across ordinary businesses and now generates legal, contractual and operational risk in a broad range of Canada–US M&A transactions, including targets for which AI is not central. Buyers must move beyond asking whether a target “uses AI” and instead determine whether the target’s AI practices create exposures that could affect valuation, integration costs or post-closing liability; underwriters for representations-and-warranty insurance are already asking AI-specific diligence questions and may decline to cover or expressly exclude AI risk when the diligence record is thin. The piece identifies five recurring categories of AI-related exposure in deals: data provenance and usage rights; privacy and biometric compliance; automated decision-making and transparency obligations; governance, testing and oversight; and accuracy of public AI-related claims.

Cross-border complexity arises because Canadian and US regulatory approaches are diverging. Canada has not enacted a cross-sectoral AI statute—its most significant attempt, the proposed Artificial Intelligence and Data Act (AIDA) in Bill C-27, "died on the Order Paper in early 2025"—but the federal “AI for All, Canada’s National Artificial Intelligence Strategy” signals forthcoming legislation, investment and programs emphasizing trust, opportunity and Canadian sovereignty, plus sectoral investment in health, energy, transport, agriculture and manufacturing/robotics. The Strategy suggests a tightening compliance baseline (including modernized privacy protections, online safety regimes, expanded AI model evaluation and sensitivity to foreign ownership of strategic AI assets), while Canadian law today relies on privacy (PIPEDA and provincial laws), Québec’s automated-decision transparency rules, sectoral regulation and soft-law governance instruments as the operative frameworks that should guide buyer diligence. Part two of the series will offer a practical AI diligence framework and discuss allocating AI risk through representations, interim covenants and indemnities.