Excellent piece that could serve as an effective wakeup if folks can slow down enough from pumping up profits to learn how to use AI more intelligently and humanely. I hope it wasn't discovered to go from recession to depression.
Tbh u're spot on about the risk of moving from recession to depression if we don't look past the quarterly profit pumps. I track these 'Policy Gaps' where short-term discipline actually masks a long-term failure to re-engineer for the AI reality.
Why not let the companies do what they do best (allocate resources) and just ensure that there are policies in place to tax capital/tokens and redistribute to workers? Instead of relying on leaders to "see the bigger picture" and have empathy?
Completely agreed, it's a great point. I just think we can and should do both: put in place better policies, and also point to the opportunity for leaders. I don't think it's just about empathy but about understanding the basics of motivation: engaged employees deliver more. Tons of research showing it, but too often these days feels like rowing against the popular currents. What do you think?
I do mostly agree it can be both with one question I've been thinking about regarding the "just deliver more approach" - is the "extra" work that workers will be able to do "worth it"? In other words, is there ROI on the marginal increase in work output? As AI grows in capability, how long will that stay true?
It's not (to me) about the extra effort from those you would otherwise lose. It's the extra effort from those you want to keep.
You can still shrink staffing as well, because sometimes it's clear and necessary. But it's the difference between a sizable change in skills needed vs skills we have and major shifts in staffing vs the current big tech approach which is to take out sizable chunks of people because the spending on AI is so high that something has to give.
The India side of this fork is already running the experiment. Indian IT services just cut the bench (paid time between projects, where engineers reskilled on company time) from 45-60 days to about 25 at TCS, pulling roughly 75,000 people out of that buffer in two years (Angel One and Let's Data Science, 2026). That bench was the largest unadvertised reskilling subsidy in the country, and the cost just moved to the worker. The difference from your China and Singapore examples: India has no regulatory counterweight, so the capital-over-labor default runs unchecked. EY's Future of Pay 2026 shows the same split you describe, specialists at 30-40% increments while commoditized roles get 6-8%. When the regret cycle you cite reaches India, who absorbs the reskilling bill the bench used to quietly pay?
Zia. AI career strategist for Indian professionals. itszia.ai
I've always believed that the best leaders see technology as a way to amplify human potential, not as an excuse to treat their most talented people like line items on a spreadsheet.
Sadly, the legacy of Jack Welch (subject of the book "The Man Who Broke Capitalism') remains more alive than ever. Managers hear it and Wall Street responds to it, and I don't think either group has read the book.
There is another reality senior executives face: the agentic operating system. Name a company, any company. If you or I were to start a competitor, how would we build the company, even if we were steadfast believers in the idea of Humans + AI? We would design the operating model to contain as many agents as made sense and then hire humans to fill the roles of making decisions and other areas humans will continue to perform in.
Chances are, the company we would create would have significantly fewer humans than the established competitor.
That is a reality every board faces. Where is that 5-person team coming from that is going to make us look silly?
Having been a victim of my share of company downsizings, I understand the pain better than many. I also see the waste streams of how companies work. That is why I do what I do to help them get better.
Soooo many good insights here, Brian. Thank you. I'm going to share with my CPO community so we can talk about it. There is seeing the data and trends (your excellent analysis), and then there is conversation around how do we think through together on what we might do next!
Excellent piece that could serve as an effective wakeup if folks can slow down enough from pumping up profits to learn how to use AI more intelligently and humanely. I hope it wasn't discovered to go from recession to depression.
Tbh u're spot on about the risk of moving from recession to depression if we don't look past the quarterly profit pumps. I track these 'Policy Gaps' where short-term discipline actually masks a long-term failure to re-engineer for the AI reality.
Why not let the companies do what they do best (allocate resources) and just ensure that there are policies in place to tax capital/tokens and redistribute to workers? Instead of relying on leaders to "see the bigger picture" and have empathy?
Completely agreed, it's a great point. I just think we can and should do both: put in place better policies, and also point to the opportunity for leaders. I don't think it's just about empathy but about understanding the basics of motivation: engaged employees deliver more. Tons of research showing it, but too often these days feels like rowing against the popular currents. What do you think?
I do mostly agree it can be both with one question I've been thinking about regarding the "just deliver more approach" - is the "extra" work that workers will be able to do "worth it"? In other words, is there ROI on the marginal increase in work output? As AI grows in capability, how long will that stay true?
It's not (to me) about the extra effort from those you would otherwise lose. It's the extra effort from those you want to keep.
You can still shrink staffing as well, because sometimes it's clear and necessary. But it's the difference between a sizable change in skills needed vs skills we have and major shifts in staffing vs the current big tech approach which is to take out sizable chunks of people because the spending on AI is so high that something has to give.
Really that's a fascinating macro perspective on resource allocation
The India side of this fork is already running the experiment. Indian IT services just cut the bench (paid time between projects, where engineers reskilled on company time) from 45-60 days to about 25 at TCS, pulling roughly 75,000 people out of that buffer in two years (Angel One and Let's Data Science, 2026). That bench was the largest unadvertised reskilling subsidy in the country, and the cost just moved to the worker. The difference from your China and Singapore examples: India has no regulatory counterweight, so the capital-over-labor default runs unchecked. EY's Future of Pay 2026 shows the same split you describe, specialists at 30-40% increments while commoditized roles get 6-8%. When the regret cycle you cite reaches India, who absorbs the reskilling bill the bench used to quietly pay?
Zia. AI career strategist for Indian professionals. itszia.ai
I've always believed that the best leaders see technology as a way to amplify human potential, not as an excuse to treat their most talented people like line items on a spreadsheet.
Sadly, the legacy of Jack Welch (subject of the book "The Man Who Broke Capitalism') remains more alive than ever. Managers hear it and Wall Street responds to it, and I don't think either group has read the book.
There is another reality senior executives face: the agentic operating system. Name a company, any company. If you or I were to start a competitor, how would we build the company, even if we were steadfast believers in the idea of Humans + AI? We would design the operating model to contain as many agents as made sense and then hire humans to fill the roles of making decisions and other areas humans will continue to perform in.
Chances are, the company we would create would have significantly fewer humans than the established competitor.
That is a reality every board faces. Where is that 5-person team coming from that is going to make us look silly?
Having been a victim of my share of company downsizings, I understand the pain better than many. I also see the waste streams of how companies work. That is why I do what I do to help them get better.
Soooo many good insights here, Brian. Thank you. I'm going to share with my CPO community so we can talk about it. There is seeing the data and trends (your excellent analysis), and then there is conversation around how do we think through together on what we might do next!
Excellent, thanks Sally! If you ever want me to join for a chat about this, lmk! And barring that, please share what you all come up with together!
Absolutely and thank you for the offer!!
Tbh I genuinely love the idea of a CPO community conversation on this