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Most large enterprises are flying blind on talent, and Mahesh Balasubramanian of Korn Ferry makes the structural case for why. Assessment data, skills inventories, succession records, and workforce plans sit in separate systems, updated on different schedules, and connected to no shared definition of business priority. The result isn’t just an HR inefficiency problem. It’s a strategy execution problem: fragmented talent decisions delay transformations, misdirect development spending, and leave internal capability invisible precisely when AI is accelerating the pace at which roles and requirements change.
What this means for your business
The organizations most exposed here aren’t the ones with the weakest HR functions. They’re the ones that have grown fast enough to accumulate large, diverse internal talent pools but haven’t built the data infrastructure to see across them. Indian enterprises scaling global capability centres are the explicit example, but any multinational that runs talent reviews by business unit rather than across the enterprise faces the same blind spot. If your succession planning and your workforce planning happen in different rooms with different data, you’re not doing integrated talent management, you’re doing coordinated guessing.
The argument Balasubramanian makes, coming from a firm whose commercial interest is selling exactly the integrated assessment and intelligence products being prescribed here, still holds on its internal logic. The bias to watch is the implied timeline: the piece treats “connected talent intelligence” as an achievable near-term state rather than a multi-year data integration project with real organizational politics attached. Connecting fragmented people data across business units requires not just technology but agreement on whose definitions of “readiness” and “capability” govern, and large enterprises have historically failed that governance problem repeatedly. The AI layer on top is only as clean as the data underneath, and the article’s brisk “build an enterprise talent-intelligence foundation” instruction skips the hardest part.
The sharpest reframe buried in this piece is the sequencing argument. Strategy first, then people implications, was the old model. The claim here is that business decisions and talent decisions now need to run in parallel, not in series, because AI is changing role requirements faster than annual cycles can track. If that’s right, the CHRO’s budget conversation shifts: the case for real-time talent intelligence isn’t about HR modernization, it’s about not discovering capability gaps after a transformation has already started executing. I’d revisit this view if enterprise AI adoption plateaued and the pace of role change slowed enough that annual reviews recovered their accuracy, but that’s not the trajectory any indicator currently supports.
Based on reporting from The Business Cost of Fragmented Talent Decisions, ETHRWorld, originally published 2026-10-14 02:21:00.
