The Enshittification of the Talent Function
Whenever the stock market is on a bull run – every Investing expert appears to be a genius, every strategy a winner ; but when the bubble burst the one who are left standing are the “real experts” or the lucky ones.
The same logic holds for the talent function. The IT sector in India across the globe has been on an extended bull run for the last 20 years; in fact even the Covid epidemic- gave it a boost !- the world hailing a new paradigm of work from home ! Even Zuck’s Addam Family inspired Metaverse had its moment; Digital was the present and future and the talent function was a the Rolling Stones and Beatles rolled into one and the good times were defined by:
- Talent Acquisition : Talent Acquisition Managers were in greater demand than Baristas in artisan Bistros. Anyone who could mutter Coding, Monetization & Customer Focus in the same breath was hired .
- Engagement- If they come to office pamper them, if they do not come to office- pamper them even more. In fact the attention spotlight was shining so brightly that for a brief period of 2 years , people did not invest in buying awards to showcase on LinkedIn
- DEI- If HR being rock starts was not enough – the DEI initiatives gave them a Halo.
- Compensation – 30-50% jumps for job changes became passe and top performers were given RSU/Stocks out of turn !
- Succession Planning- if you were high potential or gamed the firms online attention game – Money, Consultants, promotions were not a problem
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 about 50,000 middle management folks in financial year 25-26,. By the end of FY 26-27 another 100,000 will be sacked. These are folks in 45-55 age range; with high financial outlays and dependents – old parents and kids.
- Succession planning – I must confess this is easier than earlier- 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!
- Compensation is – Financial year 2026-27 will be the 3rd year when below Inflation level increases will be given to 70- 80% of the population
- DEI- once the orange turd came in power – the lionized or should I say Loinized billionaires showed their true colours combined with the lull in hiring – Diversity has taken the biggest hit, hence proving it was just a prop
- 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- exacerbated by AI & Automation
- Role Profile/JD are made thru AI prompts- the resultant JD is logical, picks the write words, has professional language – but it is the median JD available across the Internet for the role – someone has to fit it to your organisational and functional context and since making the JD has become so “easy” , the task falls to the junior most person in the organsiation- who often lacks understanding of what you need the most- Context, Culture, & Functional Context. Thus- it is a great sounding JD with no reality check.
- The Algorithm negotiates the first Employer / Employee contact. If Amazon ATS system , “trained” to reject women candidates does not jog your memory, try using LinkedIn job posts to get a reality check- the largest platform in the world, owned by Microsoft with a stake in OpenAi- has created a bull shit assembly line. I found so many great candidates in the Rejected bucket that I have turned off the AI. Here is a rule of thumb you may want to use- when the labor supply for a particular role is good- ie- false negatives have no effect on the number of people you are hiring – go ahead and use the AI system, but if you are hiring for a role where false negatives reduce your pipeline by 30% and more- do better or get a better system
- Candidate frustrated by the lack of response and confused by hype of the ATS & AI compliant resume are turning to Automated Resume Builders and even bulk Application systems- thus where you would get 20 relevant profile- you are suddenly getting 200 ( relevant/ doctored) profiles.
- Summarize here is the TA cycle- Make AI make JD >>> No context, no cultural nuance, no functional specifity>>>> 10 AI bots, representing 10,000 candidates and another 1000 candidated directly- find the job interesting- modify their profile thru AI and feed it back to you —- Your selection system crashes because you have capacity to assess- 100, not 2000 >>> instead of figuring out what is wrong – because the system is so farr of the standard deviation … the TA manager declares victory >>> kind of like token maxxing and the talent team is throwing a party in the midst of a slow motion train crash
- Role Profile/JD are made thru AI prompts- the resultant JD is logical, picks the write words, has professional language – but it is the median JD available across the Internet for the role – someone has to fit it to your organisational and functional context and since making the JD has become so “easy” , the task falls to the junior most person in the organsiation- who often lacks understanding of what you need the most- Context, Culture, & Functional Context. Thus- it is a great sounding JD with no reality check.
- Restructuring- People are cynical for a reason – Firing people when you have the cash reserves to retrain , redeploy or just be kind and give more time ,is a symptom of a sickness not business acumen. Companies are eliminating entire functions , or levels and proudly announcing CXO pay raises or Stock buybacks .
- Compensation & Productivity – In India the technology services teams are not even giving inflation adjusted increases to 75-80% of the employees, Campus / Fresher hiring salaries have not budged for almost a decade, and old uncles are screaming about 100 hour work days..
- Engagement – There is a large private bank in India where you are considered worthy of engagement only above a certain hierarchy level- below that everyone is cannon fodder- this is obviously an unwritten rule- Almost every employee knows it , they understand that their Employer is an Equal Opportunity Asshole- there is no discrimination, everyone is treated the same till you hit the Elysium level . I would trust & respect this firm and policy over a firm which goes from providing personalized masseuse services as perks to firing people over a video and announcing to the press that it was done for productivity and only “under-performers” were fired.
- DEI- Trust Science – Diversity has been a proven productivity metric , not only that diverse firms make better long term decisions- but unfortunately DEI cannot be a Talent Acquisition prop , it has to be woven into the fabric of the organisation thru policy and culture for it to have a semblance of chance to succeed
- 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 & Digital Augmented Skills, MLOps, and cloud orchestration