The « Answer » Machine
Who are we, once AI handles everything that doesn’t require being fully human?
A recent Guardian long-read follows Peter C. Baker, a teacher trainee, watching students reflexively feed every question into ChatGPT. His deeper anxiety isn’t about cheating. It’s about relevance. If the tool answers faster, more completely, and without ego – what role does wisdom play?
Senior executives are asking themselves the same question. Quietly.
In our CXO programmes, we’re seeing it surface in the margins – in the hallway conversations, in the questions that come after the formal session ends. Decision makers who have built careers on pattern recognition, on knowing the right people, on synthesising complexity faster than the room – are watching AI do all of that in seconds. The existential discomfort is real, even if the boardroom speeches still project confidence.
The anxiety has three faces:
Am I still the smartest person in the room? Probably not, in narrow analytical terms. AI outperforms human judgment on data synthesis, scenario modelling, and risk pattern recognition. Executives who derived authority from those capabilities are right to feel the ground shift.
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Am I still necessary? This is the harder question. Baker observed that students were being funnelled toward AI before they’d even formed a question of their own – Google now routes curiosity directly into chatbots, which are always ready to offer the next step. The same infrastructure surrounds executives: AI-assisted briefings, automated recommendations, algorithmic nudges. The risk isn’t replacement. It’s irrelevance by default – being quietly relegated to the sidelines.
What do I uniquely bring to the table? Here is where the anxiety can become productive. Baker became a teacher because he wanted to honour young people’s thinking with close attention – a deeply human act that no model replicates. The executives who will thrive are those who can name their equivalent: the irreducibly human contribution they bring to decisions under uncertainty.
That contribution is rarely analytical. It lives in the ability to hold ambiguity without collapsing it prematurely. To read a room, a relationship, a moment of organisational resistance. To take responsibility – not just assign it. To make a call when the data runs out and the values have to carry the weight.
The real threat isn’t that AI replaces executives. It’s that executives, unexamined, become the human wrapper around AI outputs – lending authority to decisions they no longer genuinely own.
Executive education has a role here that it hasn’t fully stepped into. Not teaching AI tools. Not building AI literacy as a technical competence. But creating the conditions where leaders can do the real work: understanding what they actually bring, where their judgment is irreplaceable, and how to lead in a world where the machine is always in the room.
At BAI, this is the question at the centre of our graduate and executive programs. Not how do we use AI? – but who are we, once AI handles everything that doesn’t require being fully human?
Baker ends his piece without a resolution. So do most of the executives we work with. That discomfort, held honestly, is probably the beginning of the right answer.
📖 Baker, P.C. (2026). Cheating machine or powerful assistant? The AI anxieties of a trainee teacher. The Guardian, March 3.
