Been a management consultant for 20 years.
Made Partner in my 30s.
Led teams of 100+ people.
Run 9-figure client portfolios.
Lived and worked in 4 continents.
Typically, corporate IT investment would follow a common script.
Capital spent on software means a shrinking payroll.
As boards map out their strategies for the coming quarters, they are operating under the comfortable assumption that this way of thinking still holds true for AI.
But I think a fiscal reckoning is brewing there, because within the next few quarters, the current prevailing narrative of AI as a headcount killer (which we all know is vastly exaggerated) will give way to a far more punishing reality.
Instead of a clean capital-for-labor swap, executives are about to watch their IT infrastructure costs and their personnel expenses balloon simultaneously 🚀🚀🚀
It may not be fun.
First, this whole idea that generative AI can operate autonomously will shatter as early deployments attempt to scale.
Because LLMs remain inherently prone to hallucination and error, companies cannot simply fire the analysts; they will be forced to retain them (or hire new talent) to serve as high-vigilance editors.
Furthermore, because AI makes it effortless to generate code, reports, marketing collateral, etc etc organizations will soon find themselves drowning in internal output. Managing, auditing, and securing this massive influx of AI-generated material will require an unprecedented wave of human oversight....
This will ultimately EXPAND corporate bureaucracy rather than trimming it (remember the 'Scaled Agile' saga??).
Even in scenarios where entry-level automation does succeed, the math of headcount reduction will fail to balance out on the ledger.
In the coming quarters, the wage differential of the AI era will trigger *severe* skill inflation.
Replacing 5 mid/entry-level programmers does not result in a net savings of 5 salaries. Instead, it requires hiring a premium-tier AI architect whose single salary frequently eclipses the combined wages of the workers they replaced (plus tokens cost).
Companies will trade high-volume/low-cost labor for scarce/ultra-premium talent, driving TCO UPWARD despite a leaner organizational chart on paper.
Jevons' Paradox again...
AI slashes the time and cost required to draft a legal brief, design a graphic, build a software feature, and therefore executive appetite for those outputs will skyrocket.
Management will demand 10x the volume of data analysis or continuous product iterations. Because the corporate demand for output will scale far faster than the technology's efficiency gains, departments will find themselves forced to expand their human teams just to handle the sheer velocity of these new AI-driven initiatives.
Until AI achieves absolute, unmonitored autonomy (if ever), it will function not as a replacement for human labor, but as a hyper-amplifier of it.
If ungoverned, the corporate balance sheets will show that the AI boom made running the business vastly more expensive.
Micron has crossed $1 trillion in market value for the first time, becoming the 10th most valuable U.S. company.
This milestone is indicative of memory chips' central role in AI infrastructure, also reflects a broader shift in the AI trade as investors seek out companies that can benefit from Big Tech's massive spending plans.
My nephew turned 8 years this Sunday and my cousin organised a grand party. Was confused on what to gift.
I decided to gift him Rs 5100 worth of MF units of a diversified equity fund.
Now u can do it offline also without any demat required..
It’s smooth & more importantly builds financial planning behaviour in the entire family..
Much better than gifting cakes , bouquets and show pieces..
So many calls on how to do it :)
The Rise and Reality of Agentic AI: A Tech Market Analysis. According to recent Gartner predictions, we're about to see a significant shakeout in the agentic AI market, with over 40% of projects expected to fail by 2027. Here's what's really going on and how organizations can avoid becoming part of this statistic, and how to build a successful Agentic AI project/solution.
The Current State: Hype vs. Reality :-
Let's be honest - the market is flooded with what I'd call "fake it till you make it" solutions. Vendors are slapping the "agentic AI" label on everything from basic chatbots to standard RPA tools. It's classic "agent washing," and it's creating a lot of noise in the market.
The bigger problem? :-
Most of these solutions aren't delivering the promised ROI. Current agentic AI just isn't mature enough to handle complex business tasks or follow sophisticated instructions independently. It's like expecting a rookie to perform like a seasoned pro - the potential might be there, but we're not there yet.
The Silver Lining :-
Despite these growing pains, agentic AI isn't just another tech bubble. It represents a genuine leap forward in what AI can do. Think of it as the difference between having a basic calculator and a sophisticated analysis tool - the potential for innovation and efficiency is real, just not as immediate as some vendors claim.
Making Agentic AI Work: Practical Steps :-
Here's what smart organizations are doing right:
1. Being Selective They're only implementing agentic AI where it makes clear business sense. No more tech for tech's sake.
2. Rethinking Processes Instead of forcing AI into existing workflows, successful companies are rebuilding processes from the ground up. It's more work upfront but pays off in the long run.
3. Starting Smart The winning approach seems to be:
1. Using AI agents for decision-making tasks
2. Keeping automation for routine work
3. Limiting AI assistants to simple information retrieval
4. Focusing on Enterprise Impact The real wins are coming from organizations thinking beyond individual productivity gains to enterprise-wide improvements.
The Bottom Line:
Success with agentic AI isn't about jumping on the bandwagon - it's about smart, strategic implementation. Focus on clear value creation through improved costs, quality, speed, and scalability. The technology is promising, but like any major advancement, it needs the right conditions to thrive.
Remember, being part of the 60% of successful projects will depend more on your implementation strategy than the technology itself. Choose your use cases carefully, plan thoroughly, and stay focused on real business value rather than getting caught up in the hype.
BREAKING: McKinsey, the consultancy firm, is nearing a deal with US prosecutors to pay at least $500 million to settle numerous probes into the firm’s past work with opioid makers
Two simple ladies meeting each other at Neelkanth temple near Rishikesh in Uttarakhand....one runs a flower shop outside the temple and the other was there simply to offer her prayers.... though their brothers are amongst the most powerful men in India today, there is absolutely no security present...the shop owner is Shashi Devi.. sister of Yogi Aditynath and the other is Vasantiben... sister of PM Narendra Modi... both lead simple lives of their own... This is the New India....🇮🇳🙏🏻
A friend bought a house for Rs. 1.67 crs in 2015...kept it locked a little, let it out a little. Paid Rs. 3L per annum for 8 years.
Now selling it for Rs. 2.15 crores.
Huge loss...because of the interest paid...Rs. 33L
Good news: No Income tax.
MASSIVE inflows in debt funds in the last few days of March to take advantage of the tax benefits and high prevailing yields.
Corp Bond and Banking PSU Funds have high yields. TMF is popular.
About Rs. 31700 crores in a few days
Image source Value Research.