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UltraTech Cement, operating across 80-plus plant locations as part of the Aditya Birla Group, is building its AI adoption strategy around psychological safety and deliberate failure rather than top-down mandates. CHRO Chandrashekhar Chavan, speaking at Tech HR Pulse Mumbai, frames the company’s workforce AI approach around pull-based adoption, where employees see tangible value before the organization scales. Current use cases include AI-assessed performance documentation, video analytics for safety, and prompt literacy workshops with HR teams across manufacturing sites.
What this means for your business
The scale math here is what makes UltraTech’s caution credible rather than timid. Chavan’s point that a mistake replicates 80 times across 80 plants is a structural argument, not a cultural one, and it lands differently depending on where your organization sits. A distributed, asset-heavy workforce with embedded legacy processes faces compounding failure risk that a single-site or knowledge-worker business simply doesn’t. If your workforce looks like UltraTech’s, the question isn’t whether to move fast, it’s whether your error-correction loops are fast enough to survive moving fast.
The most interesting operational bet buried in this interview is treating prompt literacy, the ability to write effective instructions for AI tools and critically evaluate their outputs, as a formal HR competency rather than a personal productivity habit. UltraTech is already running prompt workshops and exploring whether AI literacy should influence hiring and promotion criteria. That’s a meaningful shift. Most enterprises are still treating AI fluency as a nice-to-have soft skill. Encoding it into succession planning and job architecture, as UltraTech appears to be doing, changes the talent market signal an organization sends and who it attracts.
Chavan’s framing of ROI as autonomy and reduced supervision dependence, not just cost savings, is the right frame and also the harder one to defend in a budget conversation. CHROs who adopt this argument need a measurement counterpart: if autonomy is the outcome, you need engagement data, span-of-control metrics, or manager-to-IC ratios that move over time, otherwise the CFO reclassifies it as a soft benefit and the program gets cut in the next cycle. The falsification condition for this whole approach is whether UltraTech can show retention or performance lift at scale in 18 months, not just anecdotal ownership from prompt workshops.
Based on reporting from “Failing is important in the age of AI”: Chandrashekar, UltraTech Cement, originally published 2026-07-02 03:00:00.
