AI Is Restructuring Value
3 min read
I spent time recently with a CEO and CTO of a £2bn revenue enterprise, who showed me something that genuinely shifted my perspective. Downstream, I can see my world needing to adapt as we see a shift in engineering culture and business decisions over the next year. I think we are underestimating what is actually happening.
AI in 12 months has significantly evolved, which is shown across global SIs, MSPs and SaaS share prices. Regardless of performance, this is about sentiment too!
This is not just about faster coding. It is about the compression of time, cost and complexity in building software.
When one capable developer, using Claude Code and modern AI tooling, can take a blank repository and produce an almost production ready SaaS platform in roughly 16 hours, that is not incremental improvement, it is structural disruption.
For years, the assumption has been that building robust software required large teams, layered governance, long backlogs and significant capital. That model underpins global systems integrators. It underpins offshore delivery factories and supports parts of the SaaS valuation story itself.
So when markets react to companies like TCS or Monday.com, or when investors start questioning the long term defensibility of certain SaaS models, it is not irrational. If AI meaningfully reduces the effort required to build and iterate software, then parts of the value chain inevitably become commoditised.
The uncomfortable question is if software production becomes dramatically cheaper and faster, where does scarcity move?
It likely shifts away from pure coding capacity and towards:
Problem definition
Product judgement
Data advantage
Distribution
Trust and brand
Leadership able to reconfigure organisations at pace
AI can write code but it does not decide which problems are commercially worth solving. It does not align a board behind a new operating model. It does not restructure incentives so experimentation is rewarded rather than punished.
What I am seeing, from inside boardrooms and leadership hiring conversations, is a widening gap between organisations that recognise this inflection point and those still budgeting and hiring as if nothing fundamental has changed.
Some CEOs are asking how to reduce cost. The more interesting ones are asking how to redeploy capacity. If a team can build in 16 hours what used to take months, what new products, features or revenue models become viable? What legacy constraints disappear?
The winners will not simply be the companies that use AI tools. The winners will be the ones that redesign how decisions are made, how teams are structured and how value is created.
There will be winners and losers and large scale labour arbitrage models face pressure. SaaS businesses that relied on technical complexity may find their secret sauce no longer unique. Mid level technical roles may feel squeezed as leverage increases.
The change agents are already visible with CTOs who think like product owners and CEOs who protect experimentation time. Innovative CFOs are reinventing themselves as Chief Future Officers, with a solid understanding of where investment budgets should be allocated and backing the risks while recognising value Investors across PE and Institutions who back speed over headcount. Importantly, we then have the Developers who are comfortable orchestrating AI rather than competing with it.
Time will ultimately determine the shape of the landscape. But it is clear we are moving from an era where building software was the bottleneck to an era where imagination, judgement and leadership are the constraints.
From a talent perspective, that changes everything. With 17 years in Executive Search and supplying niche technical capabilities, the question is no longer… can we hire enough engineers?
It is… are we hiring the kind of leaders who understand what this shift really means?