Insights

Sit in on almost any executive meeting today and you will hear two familiar questions: Where can we cut costs? and Where can we move faster? They're common questions. Necessary, even. But they are also incomplete, and increasingly, they may be causing organisations to systematically underinvest in the most valuable dimension of AI entirely.

Work futurist Dom Price offers a useful way to see the gap. His –1, 0, +1 framework cuts through much of the noise around enterprise AI adoption by dividing opportunity into three distinct zones. Simple enough to sketch on a whiteboard in sixty seconds, and consequential enough to reshape how a leadership team allocates its next round of investment.

In practice, most executive teams arrive at AI strategy conversations already oriented toward the first two. The language comes naturally: reduce cost, automate repetitive work, accelerate existing processes. These are legible problems. They come with clear metrics, shorter feedback loops, and business cases that can be modelled, approved, and delivered within existing governance structures.

The third zone, genuinely new capability, tends to get crowded out. Not because leaders lack ambition, but because +1 requires a different posture entirely. It is less predictable, less immediately measurable, and more dependent on rethinking how the organisation actually works. Whether this pattern holds universally is worth interrogating. But the underlying dynamic, that operational frames dominate strategic ones, is well documented in how organisations respond to most disruptive technologies. AI is no exception.

When efficiency becomes the ceiling

The risk is not that organisations focus on –1 and 0. Both are valuable. The risk is that they stop there.

Over time, efficiency-led AI strategies create a particular kind of organisation: faster, but not fundamentally different. Leaner, but not more capable. More automated, but still bounded by the same assumptions. This is where many AI transformations quietly plateau. The organisation improves what already exists, but does not expand what is possible.

That distinction matters because the same tools used to automate your processes are available to your competitors. Efficiency gains are real, but they are also replicable. Margins compress. Differentiation erodes. Organisations that invest seriously in +1 begin to shift the terms of competition entirely.

The business case you already said no to

One of the more revealing exercises is deceptively simple. Ask a leadership team to revisit the past 12 months of rejected business cases: initiatives that were sound in concept but ultimately deemed unviable. Too expensive. Too complex. Too dependent on scarce expertise. Then ask a different question: would we fund this today, given what AI now makes possible?

In many cases, the answer changes. What emerges is not a pipeline of speculative ideas, but a backlog of previously constrained opportunities. Projects that failed not because they lacked merit, but because the organisation lacked the capability to execute them. AI, in this context, is not just an efficiency tool. It is a constraint remover. And that reframes the conversation from optimisation to possibility.

From optimising work to redefining It

The shift from –1 and 0 to +1 is not primarily technical. It is organisational.

–1 asks: What can we stop doing? 0 asks: How do we do this better? +1 asks: What have we been telling ourselves we cannot do?

That third question does not sit comfortably within existing structures. It cuts across functions, challenges role definitions, and changes the relationship between people, data, and decision-making. In practical terms, it often means moving from processing to interpretation, from execution to judgement, from isolated tasks to integrated capability.

This is where many organisations encounter a second-order problem. They deploy AI successfully, but fail to realise its value because the workforce, and the operating model around it, has not been designed to absorb it.

Separating the conversations

One reason the +1 discussion struggles to gain traction is that it is often forced to compete with efficiency conversations. It should not be.

–1 and 0 are operational discussions, about control, optimisation, and delivery. +1 is a strategic discussion, about capability, positioning, and future state. When these conversations are combined, the language of cost and certainty tends to dominate, and the most transformative ideas receive the least attention. Separating them structurally, not just conceptually, is often the first step toward shifting the balance.

The question most organisations are not asking

AI can make an organisation faster, cheaper, and more consistent. A managing director in the pharmaceutical industry recently captured the excitement well: platform development that once took 18 to 24 months can now be delivered in three to six. What followed in that conversation was telling. The instinct was to accelerate everything in the pipeline. The harder question, which took longer to surface, was whether everything in the pipeline deserved to be there. Speed without a strong business case does not reduce risk. It scales it. It reduces the cost of building the wrong thing just enough that organisations begin doing it more often.

The constraint has shifted. The question is no longer whether something can be built. It is whether it should be, and what value it unlocks if it is. This is where many organisations begin to underperform: optimising for delivery while underinvesting in clarity.

The more consequential question is both simpler and harder: what becomes possible now that was not possible before, and how do we ensure we are directing that capability toward the highest-value outcomes?

The –1 and 0 work is necessary. Cleaning up broken processes and sharpening operational execution are legitimate uses of AI investment and legitimate sources of competitive advantage. But they are not, by themselves, a strategy. They are the one-percent changes that keep an organisation moving forwards: incremental, important, and insufficient on their own.

The real question is not how to use AI to do what you already do. It is what AI removes as an obstacle to what you have not yet been able to do. That is a different conversation, and for most organisations, the archive of shelved ideas waiting to be reopened is longer than they think.

AI is not just an efficiency tool. It is a constraint remover. The organisations that grasp that distinction early will not simply outperform their competitors. They will be operating in a different game entirely.

The –1 and 0 work is necessary. Cleaning up broken processes and sharpening operational execution are legitimate uses of AI investment and legitimate sources of competitive advantage. But they are not, by themselves, a strategy. They are the one-percent changes that keep an organisation moving forwards: incremental, important, and insufficient on their own.

Those that ask the harder question, what becomes possible now that was not before, will not simply become more efficient. They will become more deliberate. And in a landscape where capability is rapidly equalising, that distinction may matter more than speed alone.