The number of immigration cases filed at the Federal Court has more than quadrupled since 2020, reporting shows: about 6,400 cases in 2020, 9,700 in 2021, more than 28,000 in 2025, and over 6,600 in the first quarter of 2026 (Global News). Some immigration lawyers quoted by Global News link part of the surge to increased use of automation and AI in visa processing; Ottawa lawyer Jacqueline Bonisteel said automated decision tools mean "a human officer isn't spending as much time with the files" (Global News). Immigration, Refugees and Citizenship Canada told The Canadian Press via press secretary Taous Ait that its AI tools "work under human oversight at all times" and that "AI plays no role in decision-making on immigration applications" (Global News).
What happened
The number of immigration cases filed at the Federal Court has more than quadrupled since 2020, according to Global News reporting based on court data: about 6,400 cases in 2020, 9,700 in 2021, more than 28,000 in 2025, and more than 6,600 in the first quarter of 2026. Global News reports that some immigration lawyers link part of the increase to the federal government's use of automation and artificial intelligence in visa processing.
Reported lawyer claims
Ottawa immigration lawyer Jacqueline Bonisteel told Global News, "The use of new technology and automation tools, it just means that a human officer isn't spending as much time with the files as they once did." Bonisteel said refusal decisions increasingly contain "canned lines" and show "no sign of engagement with the evidence," per Global News.
Government response
Per Global News, Taous Ait, press secretary for Immigration Minister Lena Diab, told The Canadian Press that IRCC's AI and advanced analytics tools "work under human oversight at all times" and that "AI plays no role in decision-making on immigration applications. As a matter of fact, all refusal decisions are made by trained officers following a full human review."
Editorial analysis - technical context
Industry-pattern observations: public-sector deployments commonly apply automation for triage, routine-case identification, autogenerated summaries, and chatbots for client queries. Those design patterns raise questions about output quality when throughput pressures increase, because automated triage can push marginal or complex files into faster workflows where template language and reduced officer engagement are more likely.
Editorial analysis - context and significance
Observers of administrative law note that higher volumes of refusals with minimal explanations tend to increase judicial review applications, which can create feedback loops that slow overall case processing. The reported data point to a system-level bottleneck: rising application volumes, automated processing layers, and legal-system capacity together influence backlog growth.
What to watch
Indicators to follow include judicial findings on whether automated processes materially affected the adequacy of reasons given in refusals, IRCC disclosures about the specific tools and oversight mechanisms used, trends in refusal reason quality reported by practitioners, and changes in Federal Court intake and adjudication capacity.
Scoring Rationale #
The story matters to practitioners because it links automated decision tools to measurable legal-system effects and highlights transparency and oversight issues in high-volume public-sector AI use. It is notable but not frontier technical news.
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