When the World’s TOM Shifts, Your Business Must Move

CEO

VUCA is back on the table.

Not as a nostalgic acronym from leadership offsites, but as an accurate description of the conditions CEOs are governing within. Volatility, uncertainty, complexity, and ambiguity are no longer occasional disruptions to an otherwise legible environment. They are the environment. Bennett and Lemoine argue that the problem with “VUCA” is not that it is wrong, but that it is often treated as one big blur, when each element requires a different response. (Harvard Business Review)

This matters because VUCA conditions quietly change the CEO’s job.

In calmer times, leadership was largely about direction-setting and optimisation: choose a strategy, align the organisation, execute. Today, the premium is on something more basic and more difficult: converting uncertainty into decisions people trust.

In a world that changes weekly, advantage comes from decision quality, decision speed, and decision credibility. Many organisations can move quickly. Some can make high-quality calls in hindsight. Far fewer can build credibility at scale, particularly when the facts are incomplete and the trade-offs are painful.

Decision credibility is not a slogan. It is a behavioural outcome. You can see it in whether teams commit, or hedge. Whether they build, or wait. Whether they speak plainly about risks, or manage optics. When credibility is high, execution accelerates because people believe decisions are coherent, durable, and fair. When credibility is low, even good decisions fail, because the organisation treats them as temporary announcements rather than changes to reality.

This is where a second narrative becomes useful, especially for CEOs trying to stay level-headed in the noise: the Target Operating Model (TOM) of the world.

Every company has a TOM, even if it is not documented: decision rights, governance, funding, capabilities, metrics, incentives, and the way work actually flows. But the external environment has an operating model too, an implicit logic for how value is created and captured, how risk propagates, where power sits, and what constraints matter most. When that “world TOM” shifts faster than your internal TOM can adapt, your organisation starts running yesterday’s machinery against today’s terrain. Strategy begins to drift, not because the strategy is weak, but because the organisation’s model of reality is out of date.

Karl Weick’s work on sensemaking is helpful here: organisations do not simply respond to reality, they construct meaning and act on the meaning they construct. Under ambiguity, sensemaking becomes the work. (Google Books) If the organisation’s shared interpretation of “how the world works now” is fragmented, every decision will be executed in multiple inconsistent ways, and the CEO will experience it as “resistance” when it is often misalignment.

The practical implication is sharp: in VUCA, the CEO must continuously update the organisation’s shared model of the world, then translate that model into a business operating model that can act with coherence.

This is also why “level-headed decision-making” is emerging as a competitive capability rather than a personality trait. Herbert Simon’s concept of bounded rationality remains a useful anchor. Leaders cannot optimise decisions in complex environments because they do not have complete information, unlimited time, or infinite cognitive capacity. They satisfice, they choose what is good enough under constraints. (Cooperative Individualism) The question is not whether executives are bounded. The question is whether the organisation has disciplines that make bounded decisions credible and executable.

This is where AI enters the conversation, and not in the superficial way most articles treat it.

If you scan current research in AI and finance, a clear emphasis emerges around decision support and risk-relevant applications: keywords commonly cluster around AI, machine learning, fintech, financial markets, decision support systems, risk management, forecasting, deep learning, data mining, and risk assessment. In other words, the centre of gravity is not “cool technology”. It is the industrialisation of judgement under pressure. (Routledge)

That distinction matters for CEOs because AI is often introduced as an efficiency play and then quietly becomes a governance problem. It increases speed, scale, and complexity simultaneously. It can compress decision cycles while expanding the surface area of risk, from model bias to explainability, from cyber exposure to regulatory compliance. The more AI is embedded in operational workflows, the more the CEO’s core obligation becomes trust: trust in outputs, trust in controls, trust in accountability, and trust in the organisation’s ability to challenge the machine when it matters.

This is why the more mature framing is “augmented intelligence” rather than “artificial intelligence”: systems designed to enhance human judgement, not replace it. The academic and practitioner literature increasingly emphasises this human-machine complementarity, including the need for interpretability, oversight, and responsible deployment. (MDPI)

So what does a CEO do, practically, to convert VUCA into decisions people trust, while updating the organisation’s “world TOM” and using AI as an augmentation rather than a substitute?

Five disciplines matter.

First, separate facts from assumptions, and make the assumptions explicit. In VUCA, credibility rises when leaders say what is known, what is unknown, and what is assumed for now, including what evidence would cause a change of course. This reduces corridor speculation and protects the organisation from treating confident language as certainty.

Second, make trade-offs visible. Every decision is a trade, and the organisation senses when leaders pretend otherwise. Naming the sacrifice is not weakness. It is respect for reality. It also makes it easier for teams to execute without inventing their own explanations.

Third, clarify decision rights, then protect them. Ambiguity in decision ownership creates either paralysis or politics. Credible leaders do not centralise everything. They design decision-making so that the right calls are made at the right level, with clear escalation paths, and with finality. If decisions can be reopened informally, trust collapses and execution slows.

Fourth, operationalise decisions, do not merely announce them. A decision becomes real when budgets shift, priorities change, metrics adjust, incentives align, and legacy rules are retired. If the operating model does not change, the decision is theatre. Over time, theatre produces cynicism, and cynicism is the death of transformation.

Fifth, build a visible review rhythm that prevents whiplash. Under uncertainty, some decisions will be wrong. Credibility is not about perfection. It is about correction without chaos. A disciplined review cadence anchored in evidence reduces lobbying, reduces overreaction, and signals that learning is expected but drift is not.

Put together, these disciplines amount to a CEO posture that is simultaneously calm and decisive: calm because it does not pretend uncertainty is solvable by confidence alone, decisive because it creates conditions where the organisation can move as one system.

The headline is simple.

In VUCA, strategy still matters, but it is not enough. The CEO must also keep updating the organisation’s TOM of the world, then reshape the organisation’s TOM to match, with AI increasingly acting as a decision amplifier and risk multiplier at the same time. Those who do this well will look, from the outside, like they have better strategy. Often they simply have better decision credibility.

A final diagnostic question for any CEO is this: when you make a hard call, do people move, or do they wait to see if you mean it?

That gap between announcement and movement is the true measure of decision trust in a changing world.

• Bennett, N. and Lemoine, G.J. (2014). What VUCA Really Means for You. Harvard Business Review. (Harvard Business Review)

• Weick, K.E. (1995). Sensemaking in Organizations. Sage. (Google Books)

• Simon, H.A. (1955). A Behavioral Model of Rational Choice. (Cooperative Individualism)

• Hassani, H. et al. (2020). Artificial Intelligence (AI) or Intelligence Augmentation (IA). MDPI. (MDPI)

• Yadav, A., Alam, M. and Chaudhary, K. (eds.) (2025). AI-Driven Finance in the VUCA World. Routledge/Taylor & Francis. (Routledge)