When AI Can Answer the Question, What Does Leadership Need to Become?
Liz serves as an Executive Coach and mentor with a unique emphasis on Wellbeing. She is keen to help businesses see that the emphasis on values centred on human needs can not only improve the wellbeing of the people but also foster a successful enterprise. Her mantra is "People first, performance will follow."
A sales director I met recently was not in want of data. He saw in more detail than ever before how the tastes and requirements of his potential clients were changing. He did, however, struggle with the next step, how to convert this information into something that could actually be sold and thus lead to growth.
He put his challenge to me like this, "How do I keep making decisions fast enough to keep the company stable and growing when the information landscape is changing this quickly?"
This is not a question of technology. This is a leadership question. Underneath the exhilaration, and for some, even the anxiety or fear of artificial intelligence (AI), I hear the same worries. In every conversation with managers about AI, I hear some variant of this concern. For the first time, the answer may not be a scarce resource. AI can explore a problem, analyze the data, develop options, challenge assumptions, and increasingly make recommendations.
So, the question for leaders is not what AI can do. It is what AI will require leadership to become.
When intelligence is abundant, judgement is the scarce resource
The prestige of expert knowledge is a very old thing in history. For most of the time, expertise was an important source of authority. Leaders knew more, had seen more, and could gain access to information that others did not have.
AI breaks up that pattern. Now a junior associate can test an idea in advance of the meeting and bring new information that reveals an error in a senior colleague’s way of thinking. A team can try out dozens of strategies without anyone even sitting down.
This does not make experience void, but it makes discernment more important, since more information does not imply better decisions. AI may widen the field of possible solutions, but only leadership can determine which deserve to become realities.
The real problem for the sales director was this, the problem was not the figures, it was the people. The main task was to establish what was important and to translate this into a policy that the employees could understand, believe in, and carry out.
The risk of answers that arrive too easily
Another conversation remained with me in part because of who I talked to. A chief risk officer for a major financial institution told me that he was not so much concerned about whether AI would be able to do the job as he was about what would happen when automation got so good that no one checked the data before it was used in projections and growth models.
That is one of the less visible risks of AI. The danger does not lie only in the possibility that an answer is wrong, it lies also in the fact that it comes to us so glibly, so unavoidably, that we stop asking whether it is true or not.
The better the tool, the weaker the habit of checking it. For the risk specialist, that is where errors stop being caught and are incorporated into forecasts, financial plans, and personnel planning.
This is why the ability to deal with machines does not just mean the ability to use the tools, but also the ability to know when to question them. Where are the assumptions? What data lie beneath? What could be missing? And who is to blame if we act on this information and it is incorrect?
The faster the answers come, the more important the verification process becomes.
When information no longer needs interaction
A third executive brought up something that I believe many boards still fail to see. They were worried about the well-being and cohesiveness of the organization itself. The information that used to circulate between them by means of conversations, check-ins, and face-to-face meetings was now automatically available and accessible at the click of a button.
The benefit is real, and so is the side effect. A unit can acquire knowledge better but be worse as a unit.
Not every exchange in an organization is unproductive. Some serve merely to transfer information, and automation is therefore quite the right thing to do. But others serve a purpose that never comes up for discussion, they build trust, they facilitate informal learning. They expose people to other ways of thinking, give someone the opportunity to challenge an established view of things, and sometimes lead to ideas that no one expected.
So the question is not "Can AI eliminate this meeting?" It is "What was this meeting doing for the organisation?"
Is the answer simply a transfer of information? Then automate it. But if the answer is a matter of trust, learning or collaboration, you had better think twice before you automate. This is not an argument against artificial intelligence (AI). It is an argument for better leadership of AI.
AI adoption is not AI maturity
Many companies measure progress by the degree of take-up, how many employees are making use of AI, how much has been invested in new tools, and how much time has been saved.
Adoption of AI tells you almost nothing about maturity. A mature organization uses AI less, not more. It knows that everything can be automated, but not everything must be, and that productivity is not the only measure of value. It protects the places where relationships, reflection, debate and judgement matter.
It is also a question of not forgetting the human cost of the operation. If every increase in productivity that AI makes possible is simply transformed into an increase in speed, it may result in an organization that is technically advanced but psychologically exhausted.
The question cannot only be "How much more can our people produce?" It should also be "What can our people now do that they never had the time, space or capacity to do before?"
Five questions every leadership team should ask before AI scales
These three conversations came from very different perspectives, from the sales department, from risk management and from organizational well-being. Yet all three have prompted the same questions. If I were to sit down with a management team today, I would not start by asking how much AI they are already using. I would start by asking the following:
What is this process or meeting really doing for us, beyond the output? Separate the transfer of information from the trust, learning and connection that come with it.
Who verifies, and how would we know if they stopped? Build checking into the system, especially for forecasts, financial decisions and workforce planning.
Where must judgement stay human? Decide this deliberately, before the technology decides it for you.
What will we do with the capacity AI creates? If the answer is only "more of the same, faster", look again.
What will we deliberately refuse to optimise? Every organisation has things that are worth protecting precisely because they are not efficient.
These questions lead the conversation beyond the subject of tactics and into that of leadership.
Leading with AI, not like AI
This is not the solution. The more capable AI is at processing information, the more the things it cannot do become important, things such as context, responsibility and human judgement.
It is true that technology can tell us what is possible, but it cannot tell us what is meaningful. It can pick out patterns but cannot tell us how we should feel in a good organization.
This era will bring forth new and different leaders, curious, but not dazzled, knowledgeable about data without becoming dependent on it, open to automation, without assuming it should be applied to everything. They will have a different confidence, not a confidence of having the answers, but a certainty of being able to ask the right questions, and an authority that is based on accountability, not on knowledge.
Thus, the question that will be most useful for managers is not whether AI is good or bad for humanity. Are we using AI to extract more from people, or to create better conditions for them to participate, develop and lead?
When AI is better at answering our questions, the quality of leadership will depend on the questions we ask.
Read more from Liz Emelogu
Liz Emelogu, Executive Strategy & Wellbeing Coach/Mentor
Liz Emelogu works with business leaders to enhance their effectiveness and realise their full potential while protecting their mental and emotional health. She is an award-winning business mentor (received as part of her role in mentoring UK-based Businesses). She is a certified NLP practitioner, certified mental wellbeing coach, and an ILM executive coach. Her approach as a Holistic Business Architect helps leaders create a bespoke framework around strategy, people, and processes, with people at the centre of it. The emphasis on values centred on human needs can not only improve the well-being of the people, but also foster a successful enterprise that is constructed around the lives of both its employees and its customers.
