The great business system rethink
I was rewatching Jurassic Park with my 9 year old over the weekend, for which she guaranteed she wouldn’t get nightmares about T-Rex’s chasing her (Narrator: She did in fact have nightmares). I was reminded about Jeff Goldblum going on about chaos theory, and how ‘Nature finds a way’ which randomly has triggered me to write about the future of business systems, structures and models in a post-AI apocalypse. As one does.
I want to go through some points about how AI won’t just optimise an existing business structure, it will force us all to dismantle and reassemble our organisations, or die.
Right now we are all prodding AI with a stick, finding out what the gelatinous blob that's washed up on shore is all about - will it bite? What does it eat? Can I eat it?
Most of us are looking at productivity and efficiency gains, trying to find use cases that stand up to the hype. Some are creating a few GPTs and calling AI in their business done. Well brace yourselves cupcakes, you’re in for a wild ride. Trying to simply “upgrade” existing processes with AI is like renovating a house that sits on an eroding cliff. You might be best to rebuild completely in a different place.
AI isn’t a bolt-on tool, it will destabilise existing systems. It accelerates information, decisions, and customer expectations beyond the capacity of those systems to cope. Our usual ways with business strategy assumes control. We predict the market, plan, execute. With AI, control gives way to adaptation. Leaders will need to get comfortable with volatility and there will no longer be a way to plan for any significant length of time.
So back to chaos - these next 2 years or so will feel messy, unpredictable, out of control for all of us. But, chaos is not all disorder, there are patterns we can hold on to. Chaos theory teaches us that beneath the turbulence, fractals emerge, infinitely complex patterns formed by simple rules. The same is true here.
The winners won’t be the ones who fight the chaos, but the ones who see the pattern within it, acknowledge them, and build for it.
Most transformations fail because they underestimate how much unlearning is required, or they try to run the new world inside the structures of the old. The system will eventually make its way back to the original design, whether we like it or not. It requires a break in the system, and an actual business model shift for it to stick longer term. We have to accept that no retro-fitting will work here longer term.
As always, I try to answer the ‘so what can I actually do about it?’ question, or at least what I would do.
The first thing I’d do as leaders in a business is to break my mental models about how the business should operate, and take all previous thinking off the table. Your org chart, processes, cost centres and hierarchies are not sacred. Blank sheet of paper time. Rearchitect.
Rearchitect based on what though?
Well I’d likely start with how your own value to your customers will change in the new world order. They will be impacted equally as much as you are - what are your client’s clients going to want next, and how will you show your value in delivering that when all public knowledge is a commodity? This will be a stripping back of what actual moat you have, and you’re going to need to be honest about this, and soon. AI already can do things for free that were 90% or even 100% the reason a SaaS product existed in the first place. You may need to fundamentally change your business's 'reason to exist'.
Next up, I’d then prioritise building my team’s resilience, adaptability and experimentation. You want to be able to stay adaptive as things in the world keep reorganising itself. Creating capabilities, and small teams of people as fluid, AI-augmented hybrids rather than fixed hierarchies, that can quickly flex and move. No more ‘headcount’ arguments in divisions. The closer we can get to a ‘small nodes in a system’ model the better, in my view.
Leadership will be about looking at chunks of the system, knowing when to increase, move, adjust or remove parts of the system as things evolve. Leaders will also be responsible for reinforcing the ‘why’ much more than usual. When the structures are breaking apart, people cling to clarity. A strong, lived purpose gives employees something steady to hold on to in the turbulence.
Then the timelines need to change. Smaller experiments, parallel experiments, building new things, cutting off old things all needs to happen in no more than 12 week cycles. The biggest leverage a company will have in future will be its ability to create new value that AI can’t. And back to the chaos theory:
A small shift can create massive ripples (the butterfly effect).
Systems in chaos reorganise into new structures rather than dissolving into nothing.
What looks random is often governed by unseen attractors — forces that pull things into new forms of order.
This is what you are looking for, optimising for now. This will be very difficult for those who have gotten where they are through benefitting from the old command and control system. Might be time for those fellas to learn plumbing.
I asked Chat GPT to come up with some scenarios of two companies approaching this whole thing differently, and I’ll put what it came up with below. It’s not completely right (as always) but it is enough to make you think.
I am optimistic we can do what’s needed here. Just this week I have spoken to two leaders who are facing their existential crisis head on, acknowledging they can’t afford to pretend their industry might just be obsolete, and fast. They are asking for help in thinking like this, so I am sure they will have higher odds than most at changing things in time.
So what conversations are you having about this right now? Is it about automation and cost savings? Or is it about how you might rethink your entire business system? I personally embrace the chaos, as inside that chaos is the blueprint or the next era of business.
Two Futures: How a Services Business Might Navigate AI in the Next Two Years
Scenario 1: The Incrementalist (Survival at Risk)
Year 1
Leadership treats AI as a cost-saving tool. They automate reporting, customer comms, and some admin functions.
Efficiency gains are real — costs drop 10–15% — but staff are unsettled. Morale dips because roles feel threatened without clarity on what new opportunities will emerge.
Clients notice faster responses but don’t see meaningful innovation. Competitors start experimenting with AI-powered services that feel more personalised and proactive.
Year 2
With workflows slimmed down, middle management layers start looking redundant. Restructuring begins, creating further instability.
Innovation stalls. The business is “leaner,” but no new value streams have emerged.
Revenue growth flattens; margins are okay short-term but eroding as competitors shift the market.
By end of Year 2, leadership faces a choice: double down and risk disruption, or make painful catch-up investments.
➡️ Outcome: Business survives but weaker. Caught in the trap of doing the same things, just cheaper and faster. Vulnerable to competitors who reimagined instead of retrofitted.
Scenario 2: The Bold Rebuilder (Thriving Through Chaos)
Year 1
Leadership starts by breaking mental models: they see AI not just as automation, but as a chance to redesign the business.
A small AI innovation team is set up to run experiments with real clients — testing new service models, co-piloted staff + AI delivery, hyper-personalised offerings.
Teams are retrained to work with AI, not against it. Some roles shrink, but new ones emerge around client experience, AI governance, and insight generation.
Client delivery gets faster, but more importantly, new value emerges — services that are more predictive, tailored, and outcome-oriented.
Year 2
Parallel operating models start to merge back into the core. A flatter structure develops: fewer middle managers, more empowered hybrid teams.
Leadership rethinks pricing models. Instead of billable hours, they experiment with outcome-based pricing or subscription-style services, enabled by AI’s efficiency.
Employee morale rises as staff see a future for themselves in the new system — they aren’t just being replaced, they’re being up-skilled.
Revenue grows beyond efficiency savings. Client retention improves thanks to differentiated, AI-enabled value.
By end of Year 2, the business looks very different: leaner, faster, more adaptive, with a stronger market position.
➡️ Outcome: Business thrives. By embracing chaos, they find new order — growth, differentiation, and resilience.
⚖️ The Core Difference
Scenario 1 = AI as a tool for the old system → short-term efficiency, long-term decline.
Scenario 2 = AI as a catalyst to rebuild the system → short-term turbulence, long-term growth.
