My time working in the search field for 13 years, there is always this trend:
Leaders think <buzzy-technique> is a good way to save money, but <buzzy-technique> actually is a thing that requires deeper investment to realize more returns, not a money saver.
> Let’s rip the Band-Aid off immediately: If your underlying business process is a mess, sprinkling "AI dust" on it won’t turn it into gold. It will just speed up the rate at which you generate garbage.
In the world of Business IT, we get seduced by the shiny new toy. Right now, that toy is Artificial Intelligence. Boardrooms are buzzing with buzzwords like LLMs, agentic workflows, and generative reasoning. Executives are frantically asking, "What is our AI strategy?"
But here is the hard truth:
There is no such thing as an AI strategy.
There is only Business Process Optimization (BPO).
This is well-expressed, and almost certainly true for an overwhelming majority of companies.
This should go to all CEOs. They should realize that the real problem AI solves is handling of text and unstructured data. That is the core ability.
But I don't blame them. Process optimization is hard. If a new tool promises more speed, without changing the process, they are ready to pour money at that.
I've seen several serveral introduction of new ERPs in companies, usually they wanted the same processes they had just with the new software, the customizing turned out be a nightmare as the consultants usually accpeted their wishes and the programmers had to bend the ERP-system accordingly, never was in budget or in time
I think there is one counter argument, LLMs are speeding up everything, including the speed of learning, which also implies that companies that might have bad processes would learn and move to good processes as well on the way.
Example, one of many things, in our SDLC process, now we have test cases and documentation which never existed before (coming from a startup).
One of my favorite stories about processes and documentation:
- Work at a hedge fund
- Every evening, the whole firm "cycles" to start the next trading day
- Step 7 of 18 fails
- I document Step 7 and then show it to a bunch of folks
- I end up having a meeting where I say: "Two things are true: 1. You all agree that Step 7 is incorrectly documented. 2. You all DISAGREE on what Step 7 should be doing"
I love this story as it highlights that JUST WRITING DOWN what's happening can be a giant leap forward in terms of getting people to agree on what the process actually IS. If you don't write it down, everyone may go on basing decisions on an incorrect understanding of the system.
A related story:
"As I was writing the documentation on our market data system, multiple people told me 'You don't need to do that, it's not that complicated'. Then they read the final document and said 'Oh, I guess it is pretty complicated' "
I have complicated feelings towards process, especially in large enterprises. In one hand, I know process is how you get good work out of average people - and that has a lot of value in big businesses because statistically, most people are going to be around average.
On the other hand, I have seen process stifle above average people or so called “rockstars”. The thing is, the bigger your reliance on process, the more you need these people to swoop in and fill in the cracks, save the day when things go horribly wrong, and otherwise be the glue that keeps things running (or perhaps oil for the machine is more apt).
I know it’s not “fair”, and certainly not without risk, but the best way I have (personally) seen it work is where the above average people get special permissions such as global admin or exception from the change management process (as examples) to remove some of the friction process brings. These people like to move fast and stay focused, and don’t like being bogged down by petty paperwork, or sitting on a bridge asking permission to do this or that. Even as a manger, I don’t blame them at all, and all things being equal so long as they are not causing problems I think the business would prefer them to operate as they do.
In light of those observations, I have been wrestling a lot with what it says about process itself. Still undecided.
“statistically, most people are going to be around average”
In big corporate environments, ‘around average’ process would be a radical improvement. We are stuck in the reality where standing up a Service Now form is considered great progress.
I have done general process automation work (usually designing new web-based tools) for 20 years now. The underlying idea has always applied, even before AI: if your process is ill-defined and/or nonsensical, trying to "automate" it isn't going to work out.
I have seen a smattering of instances along the way where the act of defining requirements forced companies to define processes better. Usually, though, companies are unwilling to do this and instead will insist on adding flexibility to the automation tooling, to the point where the tool is of no help.
> There is no such thing as an AI strategy. There is only Business Process Optimization (BPO).
Here’s your Ai strategy: every few months re-evaluate agent fitness and start switching over. Remember backstops and canaries.
Details:
Businesses usually assign responsibilities to somewhat flaky employees, with understanding there will be a percentage of errors. This works ok so long as errors don’t fluctuate wildly and don’t amplify through the system. Most business processes are a mess and that works ok.
Once agents become less flaky and there are enough backstops to contain occasional damage business will start switching.
The other nuance is that by definition all of these undocumented workflows are out-of-distribution for the model - so it won't be particularly great at them.
I agree with the article’s core point that placement matters.
The useful framing is not “where can we bolt on AI” but “what does the system look like if AI is a first-class component.” That requires mapping the workflow, identifying the decision points, and separating deterministic steps from judgment calls.
Most teams try to apply AI inside existing org boundaries.
That assumes the current structure is optimal. The better approach is to model the business as a set of subsystems, pick the one with the highest operational cost or latency, and simulate what happens if that subsystem becomes an order of magnitude more efficient. The rest of the architecture tends to reconfigure from that starting point.
For example, in insurance (just an illustration, not a claim about any specific firm), underwriting, sales, and support dominate cost. If underwriting throughput improves by an order of magnitude, the downstream constraints shift: pricing cycles compress, risk models refresh faster, and the human-in-the-loop boundary moves. That’s the level where AI changes the system shape and acts beyond the local workflow.
This lens seems more productive than incremental insertion into existing silos.
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[ 2.7 ms ] story [ 50.8 ms ] thread>Processes that rely on unstructured data are usually unstructured processes.
I appreciate someone succinctly summing up this idea.
Leaders think <buzzy-technique> is a good way to save money, but <buzzy-technique> actually is a thing that requires deeper investment to realize more returns, not a money saver.
In the world of Business IT, we get seduced by the shiny new toy. Right now, that toy is Artificial Intelligence. Boardrooms are buzzing with buzzwords like LLMs, agentic workflows, and generative reasoning. Executives are frantically asking, "What is our AI strategy?"
But here is the hard truth:
There is no such thing as an AI strategy. There is only Business Process Optimization (BPO).
This is well-expressed, and almost certainly true for an overwhelming majority of companies.
But I don't blame them. Process optimization is hard. If a new tool promises more speed, without changing the process, they are ready to pour money at that.
Example, one of many things, in our SDLC process, now we have test cases and documentation which never existed before (coming from a startup).
- Work at a hedge fund
- Every evening, the whole firm "cycles" to start the next trading day
- Step 7 of 18 fails
- I document Step 7 and then show it to a bunch of folks
- I end up having a meeting where I say: "Two things are true: 1. You all agree that Step 7 is incorrectly documented. 2. You all DISAGREE on what Step 7 should be doing"
I love this story as it highlights that JUST WRITING DOWN what's happening can be a giant leap forward in terms of getting people to agree on what the process actually IS. If you don't write it down, everyone may go on basing decisions on an incorrect understanding of the system.
A related story:
"As I was writing the documentation on our market data system, multiple people told me 'You don't need to do that, it's not that complicated'. Then they read the final document and said 'Oh, I guess it is pretty complicated' "
Write down the problem. Think very hard. Write down the solution.
On the other hand, I have seen process stifle above average people or so called “rockstars”. The thing is, the bigger your reliance on process, the more you need these people to swoop in and fill in the cracks, save the day when things go horribly wrong, and otherwise be the glue that keeps things running (or perhaps oil for the machine is more apt).
I know it’s not “fair”, and certainly not without risk, but the best way I have (personally) seen it work is where the above average people get special permissions such as global admin or exception from the change management process (as examples) to remove some of the friction process brings. These people like to move fast and stay focused, and don’t like being bogged down by petty paperwork, or sitting on a bridge asking permission to do this or that. Even as a manger, I don’t blame them at all, and all things being equal so long as they are not causing problems I think the business would prefer them to operate as they do.
In light of those observations, I have been wrestling a lot with what it says about process itself. Still undecided.
In big corporate environments, ‘around average’ process would be a radical improvement. We are stuck in the reality where standing up a Service Now form is considered great progress.
What does it bring?
What's the prompt for that one? ;)
I have seen a smattering of instances along the way where the act of defining requirements forced companies to define processes better. Usually, though, companies are unwilling to do this and instead will insist on adding flexibility to the automation tooling, to the point where the tool is of no help.
Here’s your Ai strategy: every few months re-evaluate agent fitness and start switching over. Remember backstops and canaries.
Details:
Businesses usually assign responsibilities to somewhat flaky employees, with understanding there will be a percentage of errors. This works ok so long as errors don’t fluctuate wildly and don’t amplify through the system. Most business processes are a mess and that works ok.
Once agents become less flaky and there are enough backstops to contain occasional damage business will start switching.
The useful framing is not “where can we bolt on AI” but “what does the system look like if AI is a first-class component.” That requires mapping the workflow, identifying the decision points, and separating deterministic steps from judgment calls.
Most teams try to apply AI inside existing org boundaries.
That assumes the current structure is optimal. The better approach is to model the business as a set of subsystems, pick the one with the highest operational cost or latency, and simulate what happens if that subsystem becomes an order of magnitude more efficient. The rest of the architecture tends to reconfigure from that starting point.
For example, in insurance (just an illustration, not a claim about any specific firm), underwriting, sales, and support dominate cost. If underwriting throughput improves by an order of magnitude, the downstream constraints shift: pricing cycles compress, risk models refresh faster, and the human-in-the-loop boundary moves. That’s the level where AI changes the system shape and acts beyond the local workflow.
This lens seems more productive than incremental insertion into existing silos.
I have learned to be careful of "too much process", but I find that the need for structure never disappears.
AI deals well with structure. You can adjust your structure to accept less-structured data, but you still need the structure, for after that.
Just maybe not too much structure[0].
[0] https://littlegreenviper.com/various/concrete-galoshes/
There is only Business Process Optimization (BPO)."
Exactly, that's the fundamental truth. The shiny tool of the day doesn't change it at all