The weekly download: No 32
Smart thinking about the economic fundamentals and practical implications of disruptive AI change with a great post on the future of enterprise software and what that means for consulting...
It has been a good week for smart people helping clarify and expand my view of the future. So sharing three posts on that theme:
Economic fundamentals of change
Good things are good from Scott Sumner. If you want to understand some fundamental economics this is the post for you. The author explains why the doomsday scenarios - we will all lose our jobs, AI abundance will cause a massive depression and so on - are simply at odds with the way economics actually works.
Keep this for reference. Noise about AI leading to catastrophe will continue for a long time to come. Whatever the obvious newsworthy impacts, the reality will be very different. This article explains why without advocating for some equally unlikely utopia of abundance.
“Don’t take this post as being an exercise in “everything will be fine”. I don’t doubt that AI will create problems, just as other technologies have created problems. I wouldn’t even rule out some sort of AI catastrophe. But overproduction is not the thing we should be worried about. If we ever reach the point where labor is not needed, we’ll all be billionaires—even if it requires a UBI to get there.”
Practical applications of economics to AI
I am an optimist as readers will know. My optimism is grounded and practical. So I loved this note on substack from Rohit Krishnan. He sets out some simple truths that align very well with my view of the world. It’s a two minute read but in case that is too much, a couple of highlights:
“Companies act like companies - whether that’s openai or anthropic - the incentives predict outcomes (eg acceleration) more than vibes or essays”
“AI effects once it gets good enough will be most pronounced on the labor market but individual productivity grows faster than tfp. The real world is incredibly complex and it can’t be easily wrestled into an easily automated form”
“the best safety is in shipping safe products to users. The market demands are far stronger than any alternative.”
How AI changes enterprise software
Getting more practical and more specific, Software is eating the work from Felix Stocker is a thoughtful take on the future.
“The history of enterprise software deployment is now entering a new stage, driven by the falling cost of building software. As this cost falls, the structure of the market changes.”
“Stage 4 is about designing systems that will fully automate tasks currently done by humans, in a way that is truly new.”
The real reason why all those predictions are wrong. The structure of the market and the way we do things are going to change in ways we can’t see yet. AI is not a substitution technology - for people, for software or in any other way.
Note: I enjoyed his stories about BP and Koch Industries - this type of example from real businesses always helps me learn.
He goes on to talk about Jevons Paradox - why lower cost software will drive up both the total volume of software and the total expenditure on software. We can see the outlines of this already in the many use cases that people suggest for AI agents.
The future of consulting
What I really found insightful was his extension of this argument. The cost of AI and business change is not just about software. In large complex organisations, software alone doesn’t change anything.
“In Stage 4, when build costs fall even further, the share of software development cost in enterprise deployment cost will fall. Claude Code will eat the Jevons Paradox: more is different. But that doesn’t mean we’ll see less software development, because, this is only true on the individual project level. I think we’ll see:
Custom software development cost as a % of enterprise deployment cost down
Total cost of each enterprise deployment (at a given level of capability) down
Total number of enterprise software deployments up
Total spend on enterprise software deployment up”
As Felix points out, the companies that succeed in the AI world will be those that manage this change and use it to realise opportunities for growth. He also notes that:
“winners in the real economy will not need software providers as much as they need rollout providers:”
In reality, executing change is some mix of internal capability and capacity with external support. That external support comes from the consulting industry. This is exactly why I believe predictions for the end of consulting are wrong.
My view. Big consultants will deliver much more value and much more change using AI. Their headcount and revenue will not grow as much as the value they deliver but it will still grow. The best shape of the workforce to deliver this will be pretty similar to the current pyramid. Firms that are cutting back on graduate hiring now will regret this in 2-3 years.
Thanks for reading