Leaders today are operating in an environment characterised by too much information, increasing complexity, greater uncertainty and limited time to make consequential decisions. AI is changing that environment further, not simply by providing access to more information, but by changing how leaders process information, explore possibilities and prepare for decisions.
Further up the ladder, AI is also reshaping leadership approaches, shifting from just another support tool to an active partner. Deloitte’s 2026 Global Human Capital Trends reported that 60% of executives regularly use AI to support decisions, while Gartner predicted that by 2027, 50% of business decisions will be augmented or automated by AI agents
These are not insignificant numbers. They reflect the role intelligent systems play in a modern enterprise.
Critical to leveraging AI as part of a leader’s decision making is its positioning as an enabler, rather than an outright replacement for human input. To understand this, leaders need to think carefully about their relationship with technology and how this fits into their own styles.
Reframe the question, receive a better answer There is a lot to be said about the opportunities AI technologies offer leaders. Yet, a lot can also be said about the risks. Of course, there is an incentive at play.
Operating in ever-more complicated business environments, leaders now have to absorb larger volumes of information and respond to high-pressure, high-stakes situations. AI helps them do all of that, but it can also become a crutch, confirming existing biases or leading them to become over-reliant on it.
Embracing AI means reshaping the fundamentals. Proposed models such as the Anticipatory-Predictive Leadership Capability Model (APLCM) provides a conceptual lens for considering how anticipatory thinking, predictive thinking, strategic foresight and decision-making quality can operate in an AI-enabled environment. This positions AI to help leaders while keeping their judgement at the centre of the decision-making process. APLCM offers significant benefits in organisations where leaders have to identify early indicators and predict long-term consequences1, challenges that AI has shown real value in assisting with.
Instead of asking “What should I do?”, leaders must reframe the question. What outcomes am I not seeing? What assumptions am I making? What evidence contradicts my assumptions? What processes am I ignoring? What are the unintended consequences? These questions better contextualise and inform the output systems give them. They let leaders interrogate answers that sound confident but may be wrong. Remember, confidence is no guarantee of correctness. AI should invite interrogation, not obedience. AI can provide a recommendation, but it cannot carry accountability for the decision.
What happens to the time?
AI’s value cannot simply be measured by the time it saves. Leaders also need to consider what happens to the capacity that AI creates. If AI saves an employee four hours a week, simply filling those four hours with more work does not necessarily constitute transformation. That capacity could
instead be redirected towards learning, innovation, customer value, strategic work or improving the employee experience. For HR, this makes AI more than a technology conversation. It becomes a conversation about work design, skills, roles, performance and the future workforce. AI can create the capacity, but leadership has to decide what that capacity is worth.
Working with a black box Business leadership is where AI’s ‘black box problem’, the inability of users to view or understand the decision-making paths that systems take to deliver outcomes, is most apparent. How can AI contribute to organisational decisions when leaders don’t know the rationale behind those contributions? How can I trust the decisions being made when those decisions aren’t transparent? The black box problem raises a fundamental leadership question: if a system contributes to a decision, can the recommendation be understood, challenged and explained, and WHO remains accountable for the outcome?
Given the pace at which tech is advancing, it’s difficult to answer these questions. But that doesn’t mean leaders cannot be critical of the outcomes that systems and applications give them. Leaders are still responsible for the decisions they make regardless of whether they outsourced the thinking process to AI.
This begs the question: what does the future of leadership look like with the power of AI?
The future leader is not someone who knows everything. It is the person who knows what to ask AI, when to challenge it, when to trust it and when human judgement must override it.
Many organisations have responded to the need for AI leadership by creating dedicated roles, such as Chief AI Officers (CAIOs), or have expanded existing roles to help integrate AI capabilities into their structures.2Going forward, a leader’s relationship to AI will be an important marker of their performance, efficacy, and success. There is also a growing emphasis on accountability and whether decisions from the top were the result of a reinforced thought process. And that’s all it comes down to: AI should not make leaders think less. It should enable them to think further.
- Jarmaine Lawrence-Manho, Senior Human Resources Business Partner at Canon South Africa
