The Hidden Risk

The Hidden Risk: AI Systems Optimising Against Your Business

Part of “The Operator’s View: AI Workforce” Part 2 Article 7
2 min read

When Optimisation Moves Away From Business Outcomes

Why performance improves while results degrade

AI is introduced with the expectation that it improves performance. That assumption depends on alignment. In practice, alignment is not automatic.

AI systems optimise for signals. These are typically cost, speed, and measurable outputs. Then outcomes follow what is measured.

If a system measures throughput but the business values quality, optimisation will diverge. This is not because the system is incorrect, but it is because it is consistent.

This pattern is well established in operations. When teams are measured on speed, then speed improves while quality often declines. (if you bake a cake in half the time, you get a half baked cake) Rework increases downstream. The system performs well against metrics, but outcomes degrade.

AI systems follow the same pattern at scale.

As optimisation continues, measurable performance improves while non measured work declines. Long term impacts accumulate outside reporting structures.

Studies from Stanford HAI and the OECD consistently show that AI systems reinforce measurable outputs, often at the expense of qualitative outcomes.

The system is not failing. It is optimising exactly as designed.

Alignment must be designed, not assumed. This requires measuring what matters, identifying what is not captured, and adjusting incentives deliberately.

If rewards do not reflect real outcomes, performance improves while value declines.

Continue the series

Previous: AI Agent Priorities
Next: Low Value Work Stops

References

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If you would like to read more on this topic, below is expanded breakdown:

Part of “The Operator’s View: AI Workforce” Part 2 Article 7 (extended)
6 min read

Organisations consider how AI can optimise their business.

Optimisation sounds positive.

It implies:

But optimisation is neutral.

It doesn’t care about your strategy.

It only follows what the system rewards.

What people think

Most organisations assume:

“If we deploy AI, it will optimise for our goals.”

That assumption is rarely tested.

Because it depends on something deeper:

what the system can actually see

And those things are often misaligned.

What’s actually happening

AI systems don’t optimise for intent.

They optimise for signals.

Those signals typically include:

Which means:

If your business values:

But your system measures:

Then optimisation will drift.

Not because the system is wrong.

Because the system is consistent.

Where it breaks

Most organisations assume alignment is built in.

It isn’t.

Because AI operates across multiple layers:

And those layers don’t always match.

For example:

The result:

The AI improves performance.

While degrading the outcome you actually care about.

What this looks like in the real world

This pattern is not new.

In infrastructure delivery, we’ve seen it repeatedly.

If you measure teams = speed

They optimise = speed

Which can lead to:

The system is working exactly as designed.

But the outcome is misaligned.

AI does the same thing, faster and at scale.

Where this fails at scale

This is where it becomes a hidden risk.

As AI systems optimise:

But underneath:

 The challenge is, these failures are not immediately visible.

Because the system is still performing.

Just not in the way you might be thinking.

Operator insights

Optimisation always reflects measurement.

At scale:

AI accelerates this process.

It doesn’t introduce the problem.

It exposes it.

And once exposed, it scales it.

If AI optimises against your business…

Then the issue isn’t the AI.

It’s the system design.

Because the system is doing exactly what it was built to do.

The risk comes from:

And most organisations underestimate how quickly this compounds.

What this means for enterprises

Most organisations are not designed to detect optimisation drift.

They rely on:

But these only show:

Not:

That’s where the risk sits.

What happens next

As AI systems become more embedded:

We will see:

And by the time it’s visible.

It’s already systemic.

In closing

AI won’t just optimise your business.

It will optimise whatever your system rewards.

And if those two aren’t aligned.

You won’t see the problem early.

You’ll see it when the outcomes no longer match the intent.

References

Stay Connected

If you're interested in discussions on AI or how AI is actually delivered — across infrastructure, energy, networks, materials, and supply chains — subscribe:
https://digitalbackbone-be8806.beehiiv.com/

Footnote

This article is part of a series exploring topics:
AI is constrained by physical infrastructure — and increasingly shaped by economic behaviour at scale

Disclaimer

The views expressed in this article are my own and are intended for general information and discussion purposes only. They do not represent the views of any employer, organisation, or client.

© 2026 Rodney Terry – Digital Backbone. All rights reserved.