Why AI is making the quality of executive team thinking more important, not less.
I recently observed a dynamic in a group executive team session that I suspect we’re going to see a lot more of.
The team had used AI to help with the initial thinking for their business strategy and was pleased with what it had produced. The output was articulate, structured and comprehensive.
It looked like a strategy. It felt like a strategy.
It was only when we started interrogating it that some of the holes became apparent.
What assumptions was it making?
What was missing?
What were the implied choices and trade-offs?
The more we questioned the output, the more its apparent sophistication began to unravel.
Eventually, it became something of an emperor’s new clothes moment. What had initially looked like a compelling strategy was revealed to be a convincing presentation of some surprisingly shallow thinking.
The seductive power of a plausible answer
For much of organisational life, producing answers has been expensive.
It has required research, analysis, expertise and considerable human effort. Executives have spent significant amounts of time gathering information, analysing problems and developing possible solutions.
AI changes those economics.
It can synthesise large amounts of information, identify patterns, construct scenarios and generate plausible courses of action almost instantly.
That is an extraordinary capability. But it also creates a potential risk.
A poorly framed problem can now produce a sophisticated-looking answer very quickly. An untested assumption can become embedded in a strategy. A preferred point of view can be supported by a seemingly compelling argument.
The risk isn’t simply that AI gets things wrong.
It is that the quality of the answer can disguise weaknesses in the thinking that produced it.
As answers become easier to generate, the ability to determine which questions are worth asking, and which answers we should trust, becomes more valuable.
How executive teams think together
The traditional model of executive problem solving has been broadly linear. Define the problem, analyse it, develop solutions and decide a course of action:
AI allows much of the analysis and solution generation to happen extraordinarily quickly.
But that creates the temptation to compress stages that shouldn’t be compressed.
An executive team can move from a loosely framed problem to a sophisticated-looking solution before it has properly examined the assumptions sitting underneath either.
A more useful model for AI-enabled executive teams might be an iterative process of frame, challenge, reframe, generate solutions, interrogate, and then decide:
AI can contribute throughout this process.
It can help challenge an initial problem statement, identify assumptions, generate alternative explanations and argue against a proposed course of action.
Ultimately, however, the executive team still needs to exercise judgment and take responsibility for the decision.
So what might this mean in practice?
I think there are five disciplines that become particularly important.
Strong executive teams don’t necessarily accept the first version of a problem presented to them.
They ask: What problem are we actually trying to solve?
A revenue problem might really be a customer proposition problem. A performance problem might be an accountability problem. A capability problem might actually be an organisational design problem.
AI can be enormously useful in exploring these possibilities.
But the team still needs to determine which framing best reflects what is really happening.
AI makes it relatively easy to generate evidence and arguments that support an existing point of view.
Effective executive teams need to be able to do the opposite.
What assumptions are we making?
What are we missing?
Why might our preferred solution fail?
This requires more than good analytical skills. It requires an environment in which people can challenge an idea without the challenge being interpreted as a challenge to the person who proposed it.
One of the more subtle risks of AI is the confidence created by a polished answer.
An authoritative and comprehensive response can create the impression that a complex problem has been resolved when it hasn’t.
That makes some fairly simple questions increasingly important:
What might we be missing?
What if our original premise is wrong?
What evidence would cause us to change our minds?
If anything, AI may make openness to challenge and a willingness to change our minds more important leadership capabilities.
This is perhaps where executive teams have an advantage that shouldn’t be underestimated.
Each executive brings a different lens, experience and set of assumptions to the table.
The value doesn’t come from everyone quickly reaching the same conclusion. It comes from using those differences to understand the problem more fully and make a better decision.
AI can add another perspective to that conversation. It can challenge the team’s thinking, identify patterns that aren’t immediately obvious and generate alternatives.
But it shouldn’t replace the conversation itself.
The opportunity is to combine the capabilities of AI with the collective judgment of the people around the table.
There is one other distinction that I think matters.
AI can make a recommendation.
It can’t carry accountability for the decision.
Most important executive decisions involve incomplete information, competing stakeholders, difficult trade-offs and consequences that can’t be completely predicted.
There often isn’t a single objectively correct answer.
The role of the executive team is therefore not simply to identify the most persuasive recommendation. It is to make a judgment, make a choice and take responsibility for what follows.
And can they recognise when a polished answer is creating the impression that the difficult thinking has already been done?
These aren’t technology capabilities.
They are executive team capabilities.
And I think AI is making them more consequential.
Better questions, better judgment
AI will continue to make answers faster, cheaper and more sophisticated.
But that doesn’t reduce the importance of executive judgment. It increases it.
The advantage won’t necessarily belong to the teams with the best AI. It will belong to those that know how to think well with it: framing the right problems, asking better questions, challenging plausible answers and knowing when more thinking is required.
Because when answers become cheap, better questions (and better judgment) become more valuable.
From collaboration to collective thinking
This has implications for how we think about executive team development.
Leadership teams have historically spent a lot of time working on collaboration, trust, alignment and communication.
Those capabilities remain important.
But AI introduces another dimension:
How well does the team think together?
Can the team distinguish symptoms from underlying problems?
Can it surface assumptions that have gone unquestioned?
Can they tolerate ambiguity rather than rushing towards premature certainty?
And can they recognise when a polished answer is creating the impression that the difficult thinking has already been done?
These aren’t technology capabilities.
They are executive team capabilities.
And I think AI is making them more consequential.
Better questions, better judgment
AI will continue to make answers faster, cheaper and more sophisticated.
But that doesn’t reduce the importance of executive judgment. It increases it.
The advantage won’t necessarily belong to the teams with the best AI. It will belong to those that know how to think well with it: framing the right problems, asking better questions, challenging plausible answers and knowing when more thinking is required.
Because when answers become cheap, better questions (and better judgment) become more valuable.
