Mckinsey Wonders How to Sell AI Apps with No Measurable Benefits

- AI companies of course will try and sell you that you can reduce headcount with AI

- CEO's will parrot this talking point without ever talking a closer look.

- Everyone lower down on the org chart minus the engineers are wondering why the change hasn't started yet.

- Meanwhile engineers are ripping their hair out cause they know that AI in it's current state will likely not replace any workers.

Pretty soon we will have articles like "That time that CEO's thought that AI could replace workers".

Each human can be a bit more productive, I fully believe 10-15% is possible with today's tools if we do it right. But each human has it unique set of experience and knowledge. If I do my job a bit faster, and you do your job a bit faster. But if we are a team of 10, and we do all our job 10% faster, doesn't mean you can let one of us go. It just means, we all do our job 10% faster, which we probably waste by drinking more coffee or taking longer lunch breaks

The quiet part out loud phrase is overused.

Additionally once the AI vendors have locked these companies to their ecosystem, the enshittification will start and the companies who reduced their headcount to bare minimum will start to see why that was a really, really bad idea.

With AI you have a thing you can't quite trust under any circumstance even if it's pretty good at everything.

We will eventually reach a point where people are teaching each other how to perform evaluation. And then we’ll probably realize that it was being avoided because it’s expense to even get to the point where you can take a measurement and perhaps you didn’t want to know the answer.

It doesn't matter. People are convinced it's a miracle technology, so I'm just a backwards luddite resisting progress

I love AI image generation, but many certainly do not enjoy the results. I can see some people skimping on paying artists.

First I thought translators would be hit hard by AI, but you probably still need them as well to be decently sure about correctness.

And it remains true that any creativity produced by AI is basically still just a function of the creativity of other people.

But I'm guessing their growth was linear, and hard fought, after initial success over tools like Atlassian's which are annoying and expensive.

So to get back to hypergrowth, they had to stuff AI in every nook and cranny.

Is your product a search engine? It's AI now. [1][2]

Is it a cache? Actually, it's AI. [3]

A load balancer? Believe it or not, AI. [4]

[1] https://www.elastic.co/

[2] https://vespa.ai/

[3] https://redis.io/

[4] https://www.f5.com/

(And I develop "AI" tools at my day job right now...)

Remember that when they're wrecking your productivity by trying to twist your job into something they can measure in a spreadsheet.

You model it as a fixed %, variable cost and run revenue sensitivities. It either meets your investment criteria or doesn't.

Either

- the execs are leaving a laughably easy 20m on the table McKinsey knew they'd make (how did they know, and why didn't we)

- they're dealing with insider information - especially dangerous if McKinsey is changing dependencies around.

- they're doing some creative accounting

Same reason they ask for "estimates" which they then later try to hold accountable as "quotes" when it suits them. Same reason I 3x my initial estimates.

I'd be surprised if they'd do that for GenAI projects, maybe only for really good clients that pay them 50mln+ a year anyway

I used to love coding, and did it a ton. Then it became less and less part of my job, and I started hating coding. It was so frustrating when I knew exactly what needed to be done in the code, but had to spend the time doing low value stuff like typing syntax, tracing through the code to find the right file to edit, etc when I'm already strapped for time.

LLMs and agentic coding tools have allowed me to not spend time on the low-value tasks of typing, but instead on the high-value tasks of solving problems like you mentioned. Just interesting the different perspectives we have.

What I’d be more interested in is an AI paralegal that works for me, not for the signing tool or the counterparty, where I control its prompt so I can try to focus it on possible ways I can be screwed with this contract, and what recourses I will or won’t have.

Really companies failed to make remote work because it meant giving up a lot of middle-management power and some people realising their job means very little.

Likely, no. In my industry, I see a fraction of ICs using it well, a fraction of leadership using it for absolute dog shit idea generation, and the remainder using it to make their jobs easier in the short run, while incurring debt in the long run since nobody is "learning" from AI summaries and most people don't seem to be reading the generated "AI notes" sent in emails.

By and large, I think AI is going to hurt my workplace based on the current trajectory, but it won't be realized until we are in a hard hole to dig out of.

When I look at top-level decision-makers at my Mag-7 employer, they are smart people. Many of them were go-getters in their earlier career, responsible for driving some very successful initiatives, and that's why they're at the top of the company. And they're very intentional about team structure: being close enough to senior directors and VPs to see some of their thinking, I can tell that they understand exactly who the competent people are, who gets things done, who likes to work on what, and then they put those people at the bottom of the hierarchy with incompetent risk-averse people above them. Then they'll pull them out and have them report directly to a senior person when there's a strategic initiative that needs doing, complete it, and then re-org them back under a middle-manager that ensures nothing gets done.

I think the reason for this is that if you have a wildly successful company, the last thing you want to do is screw it up. You're on top of the world, money is raking in from your monopoly - and you're in zugzwang. Your best move is not to play, because any substantive shift in your product or marketplace risks moving you to a position where you aren't so advantaged. So CEOs of successful companies have a job to do, and that job is to ensure that nothing happens. But people's natural inclination is to do things, and if they aren't doing things inside your company they will probably be doing things outside your company that risk toppling it. So you put one section of the company to work digging holes, and put the other section to work filling them in, and now everybody is happy and productive and yet there's no net external change to your company's position.

Why even have employees then? Why not just milk your monopoly, keep the team lean, and let everybody involved have a big share of the profits? Some companies do actually function like this, eg. Nintendo and Valve famously run with fairly small employee counts and just milk their profits, some HFT trading shops like RennTech just give huge employee dividends and milk their position.

But the problem is largely politics. For one, owning a monopoly invites scrutiny; there are a lot of things that are illegal, and if you're not very careful, you can end up on the wrong side of them. Two, owning an incredibly lucrative business makes you a target for competition, and for rule-changes or political action that affect your incredibly lucrative business. Perhaps that's why examples of highly-profitable businesses that stay small often involve staying secret (eg. HFT) or being in an industry that everybody else dismisses as inconsequential (eg. gaming or dating).

By having the huge org that does nothing, the CEO can say "Look, I provide jobs. We're not a monopoly because we have an unfair advantage, we compete fairly and just have a lot of people working very hard." And they can devote a bunch of people to that legal compliance and PR to make sure they stay on the right side of the government, and it also gives them the optionality to pull all those talented people out and unmuzzle them when there actually is a competitive threat.

But particularly we're always dealing with IT security "experts" running dumb checklists taking things away and breaking everything and never bothering figure out how we're supposed to use computers to actually get any work done ("hmmm. we didn't think about that... we'll get back to you" is a common response from these certified goons). Apparently the security gods have decided we can't have department file servers anymore because backups are too difficult to protect against ransomware or something so we're all distracted with that pronouncement from the mountain trying to figure out how to get anything done at the moment.

> A successful "AI Transformation" would come in top-down, going after the most expensive headcount first.

This isn't a mistake. McKinsey consultants and their executives at their clients are a part of the same clique. You don't get into either without going to the right schools, being in the right fraternities, and knowing the right people. "Maximize profit" and "cut costs" are to be read as "keep the most money for ourselves in the form of earnings per share and dividends" and "pay fewer people". And since you can convert shares to money by gutting companies, there's no real incentive to remain competitive in the greater marketplace.

Do you still need an "AI Transformation" then? Sounds like just axe the CEO or cut their enormous salary = profit?

I said before but in a pre-2000 world when I worked at a public company I got lectured when my employees timecards utilization were too high because you can't actually utilize people at those levels full time continuously and management wouldn't sign off on incorrect timecards. But the modern world pretends it's fine and is trying to optimize to it and it just won't work. You can't optimize out the key knowledge, and you can't keep the key knowledge and be 80% utilized doing something else.

This is all based on some ideal world that doesn't exist in reality.

I worked in tech support at a big company long ago. Tech support, sales, and engineering used to have a week (for each employee) where we would leave our team and follow the other team around.

It provided incredible efficiency. I now knew what sales was talking about when they called me, they understood how I worked, engineering and I got along so well they used to invite me to their team when they had lunch catered.

Who didn't we need anymore? The middle managers between the groups who brokered what info each group could see, and how we communicated among groups. We solved problems before they started all on our own.

The middle managers won in the end, ending the cross training, too costly they said, but I think they realized that we just didn't need them / weren't engaging them anymore...

> Price levels: How should vendors set price levels when the cost of inferencing is dropping rapidly? How should they balance value capture with scaling adoption?

This is written for B2B target clients as if it's pulling back the veil on pricing strategy and negotiating. Hire McKinsey to get you the BEST™ deal in town.

I also use image generation extensively, but that is for hobby purposes.

I trained some models (RAG) and build some tools, but quickly noticed that is quiet a bit of work even to generate and audit the knowledge base you want to consume. I think it warrants to be a new job position. Problem is that this position needs someone who is very familiar with the processes within a company, so external help here is hard to come by and it would be a longer time investment. If you have success here, I would assume it could boost productivity for workers that aren't that close to AI tech and maybe just used AI for search and questions.

Until now we (only?) have an AI that reads mails and imports the relevant information into our ERP, CRM or general content systems. It queries relevant information about support cases to provide helpful context for case handlers. I think it works quite well, but I cannot imagine it replacing anyone. Exception might be if you specialize on scamming people, that could probably work.