The Enshittification of the Talent Function
Whenever the stock market is on a bull run, every investing expert appears to be a genius and every strategy a winner — but when the bubble bursts, the ones left standing are the “real experts,” or the lucky ones.
The same logic holds for the talent function. The IT sector has been on an extended bull run for the last 20 years; in fact, the COVID pandemic gave it a boost, with the world hailing a new paradigm of digitization and work from home. Easy capital spawned a startup frenzy, with fintech, B2C e-commerce, and SaaS firms scaling up — and the talent function was at the core of this growth:
Talent Acquisition — Firms racing to create the digital future were hiring anyone who could mutter coding, monetization, and customer focus in the same breath. Consequently, talent acquisition managers were in greater demand than baristas in artisan cafes.
Engagement — If they come to the office, pamper them. If they do not come to the office, pamper them even more. The attention spotlight was shining so brightly that for a brief period of two years, people did not invest in buying awards to showcase on LinkedIn.
DEI — The focus and celebration of DEI initiatives gave the talent function a halo. Campuses across the globe prayed to the saints of do-good and be-good capitalism.
Compensation — 30–50% jumps for job changes became passé, and top performers were handed out RSUs and stock at the expense of peers and, sometimes, reporting managers.
Succession Planning — Succession planning became hot, because if you didn’t share the future vision with your high-potential associates, another company would come up with a better crystal ball.
Successful Talent heads were Infinity Stones – sought by anyone seeking glory.
Then the market corrected. Here are some facts to appreciate the new reality.
The Indian IT services sector sacked roughly 50,000 middle managers in FY25–26. By the end of FY26–27, another 100,000 will be sacked. These are typically people in the 45–55 age range, with high financial outlays and dependents — old parents and kids in college.
Succession planning — I must confess this is easier now than before: instead of doing long and complicated succession planning exercises, some firms are just firing a layer, and the ones below are promoted — or at least get the feeling of promotion.
in Compensation — FY2026–27 will be the third year that 70–80% of IT employees in India will get salary increases below inflation.
DEI — Once the orange turd came into power, the lionized — or should I say loinized — billionaires showed their true colours. Combined with the lull in hiring, diversity has taken its biggest hit since the subprime crisis, proving once again that DEI was a TA prop for most firms.
Engagement — If you have a job, you are suitably engaged! I am not being cynical — this is a sentence being used quite frequently.
The pain is not over. The AI bubble is yet to burst – here are some numbers from Prof G media substack- “Investment in AI has grown astronomically. Big Tech is now spending more on AI Capex annually than the U.S. spent on the Apollo program on an inflation-adjusted basis. Earning a return on this investment, according to The Economist, would require revenues of roughly $2.5 trillion per year. The cumulative revenue from AI today is about $150 billion.”
Indian tech is not invested so much in the AI market- but the snowball effect will be inescapable- like the subprime crisis which had a 2 year drag on the Indian market.
For the talent function to be taken seriously again, it needs to solve the following problems:
Talent Acquisition has an industrial-scale trust gap:
- Role profiles and JDs are made through AI prompts. The resultant JD is logical and sounds professional, but it is the median JD available across the internet for the role — someone has to fit it to your organizational and functional context. Since making the JD has become so “easy,” the task falls to the most junior person in the talent acquisition function, who often lacks understanding of what you need most: context, culture, and functional specificity. The result is a great-sounding JD with no reality check.
- The algorithm negotiates the first employer/employee contact. Try using LinkedIn job posts for a reality check: the largest platform in the world, owned by Microsoft with a stake in OpenAI, has created a bullshit assembly line.
- I found so many great candidates automatically tagged as “Not a Fit” that I turned off the AI. Here’s a rule of thumb: when the labor supply for a particular role is good — i.e., false negatives have no effect on the number of people you’re hiring — go ahead and use the AI system. But if you’re hiring for a role where false negatives reduce your pipeline by 30% or more, do better, or get a better system.
- Candidates frustrated by the lack of response, and confused by the hype around ATS- and AI-compliant resumes, are turning to automated resume builders and bulk application systems. The only “human-sounding” responses on the internet are from fraudsters — some are just bait-and-switch schemes for automated resume platforms or training companies, but others are evil, building professional-looking websites and extorting money from the desperate and gullible.
- A lot of times, the TA cycle looks like this: AI generates the JD → no context, no cultural nuance, no functional specificity → job applications come through 10 AI platforms representing 10,000 candidates, plus another 1,000 applying directly → your selection system crashes because you have the capacity to assess 100, not 2,000 → instead of doing a root-cause analysis, the TA manager declares victory. Same logic as token-maxxing: the wrong variables are being measured instead of the outcomes that matter.
Compensation & Productivity — If you’ve made savings by sacking people, at least give inflation-adjusted increases to the remaining employees. Campus and fresher hiring salaries haven’t budged in almost a decade, while old uncles scream about 100-hour workweeks.
Engagement — There is a large private bank in India where you’re considered “human” only above a certain level; below that, everyone is cannon fodder. This is, of course, an unwritten rule — every employee knows their employer is an equal-opportunity asshole. There is no discrimination; everyone is treated the same until you hit the Elysium level. I would trust and respect this bank and its talent team more than a firm that goes from providing personalized masseuse services as perks to firing people over a video call and telling the press it was done for productivity, with only “underperformers” let go.
DEI — Trust the science: diversity has been a proven productivity metric, and diverse firms make better long-term decisions. For DEI to succeed, it has to be woven into the fabric of the organization through policy and culture.
Training & Development — Traditional IT delivery models built around manual coding, routine maintenance, and legacy testing are shrinking. IT majors face a massive reskilling hurdle to transition millions of employees to AI and digitally augmented skills, MLOps, and cloud orchestration.
People are cynical for a reason. Firing people when you have the cash reserves to retrain and redeploy them is a symptom of a sickness, not business acumen. Companies are eliminating entire functions or levels while simultaneously announcing CXO pay raises and stock buybacks.
Omar Farooq