other
Training and reskilling the workforce for AI
0.22% to 3.1% of the quarter’s revenue
Incremental total: counts at zero at the point and in full at the high end, with no traced baseline.
our inferencedisclosure: withdrawn· motive: narrative-defensive· before LLMs: expanded
Training hours were given on the last call before coverage, in the quarter ended 2025-11-30 (anchor claim acn-anchor-c37), and on the prior call, in Q2 FY2026; this quarter's call, release and 10-Q do not give them, nor the course completions or the count of AI and data professionals given a quarter earlier (, ). A metric given in consecutive quarters up to and including Q2 FY2026, counting the reference quarter, and absent now meets the definition of withdrawn, applied by the same rule as advanced AI revenue; no stop was announced, and the rule does not ask for one. The state steps from quantified to withdrawn. The CFO speaks of continuing to invest to strengthen relevance in the age of AI (claim c32). The size is the ledger's own, , carrying the hours stated on the prior call with a wider range.
Evidence: 2 quotes, 4 figures, 2 confounds, 4 from before coverage
What the company spends to train its people for AI work: training hours, an agentic AI curriculum built with a university, and the build-out of its AI and data workforce. The cost sits in Cost of services as learning and professional development and as the paid time of the people trained; the filing does not separate it.
Why this motive
Carried. The performance-evaluation requirement of Q2 FY2026 is neither repeated nor withdrawn; this quarter's only words are the CFO's, investing to strengthen relevance in the age of AI for long-term leadership (claim c32), which read alone would be exploratory. A change of motive is not taken from an omission.
Before LLMs: expanded
Learning and professional development was in fiscal 2024 for training hours, about an hour, and the annual report attributed that year's rise in hours predominantly to generative AI training; the company had said it was investing in AI over three years. The budget existed before LLMs; its size in a quarter before them is not in the anchor, so no baseline figure is registered. The size is the whole of an activity that existed before.
“We are progressing towards our goal of doubling our deeply skilled data and AI practitioners from 40,000 to 80,000, with an additional 5,000 practitioners as of Q1.”
“With our digital learning platform, we delivered approximately 44 million training hours, an increase of 10% compared with fiscal 2023, predominantly due to generative AI training.”
“As you know, we are investing $3 billion in AI over three years.”
“We have nearly reached our goal of 80,000 AI and data professionals, and our people participated in approximately eight million training hours this quarter, with a significant focus on building advanced AI technology and industry skills.”
Figures
- Training hours, quarter ended 2025-11-30, approximate · 2025-CQ4
- Training hours completed in the quarter · 2026-CQ1
- People who completed the Agentic AI Fundamentals program · as-of 2026-02-28
- AI and data professionals, lower bound · as-of 2026-02-28
What else could explain it
- line composition: Training hours cover every subject; the share that is AI training is the ledger's assumption.
- other: No hours, course completions or headcount of AI and data professionals are given this quarter; the size carries the prior quarter's stated hours.
Quotes
“In closing, we remain focused on executing our business and capturing new opportunities for growth while continuing to invest to strengthen our relevance in the age of AI for long-term market leadership.”
“Cost of services and the related gross margin may be impacted by several factors, including contract profitability, which includes the pricing on the work that we sell, as well as by the investments we make in our business, such as research and development to build assets, platforms and industry and functional solutions and strategic acquisitions, as well as in our people, such as total rewards and learning and professional development.”
By quarter
- Q1 2026quantified · our inference · narrative-defensive · $65mn to $585mn
- Q2 2026withdrawn · our inference · narrative-defensive · $41mn to $585mn