As AI takes over more work, human leadership becomes more important

Artificial intelligence is steadily changing the division of labour between people and machines. The question facing businesses is consequently moving beyond what AI can do towards something potentially more difficult: how organisations should lead the people affected by it. For Don Gregori, Chief Operating Officer of software solutions company First Factory and author of The Emergent Leader: A Guide to Brand Building, Leadership, and Self-Mastery, increasing automation does not diminish the importance of management. Instead, he argues, it makes effective human leadership more consequential.

The reasoning is relatively straightforward. AI can automate elements of a workflow, process information and increasingly perform actions through autonomous or semi-autonomous systems. It cannot, by itself, resolve the uncertainty felt by employees wondering how their jobs will change or what skills they will need next. Recent developments underline how quickly the technology is moving. AI agents are advancing from answering questions towards performing actions within business workflows, although human approval remains an important feature of some implementations.

Against this background, Gregori argues that empathy should no longer be regarded simply as a desirable leadership characteristic. “Real empathy is operational. It means knowing employee capabilities, fears, motivations and what they need from you to move forward, especially in this rapidly changing landscape,” Gregori says. “That’s not a personality trait; that’s a skill you build. And it’s more important than ever.”

There is evidence that organisations have reasons to pay attention to this human dimension. Research reported by Digital Journal in 2026 found a substantial gap between senior executives and other employees in their acceptance of workplace AI. While 74 per cent of surveyed C-suite executives were comfortable sharing workplace documents with AI systems, the proportion among non-management employees was just 20 per cent.

Other research points towards a similarly complicated picture. A Henley Business School study involving 2,900 full-time workers across 29 sectors found 58 per cent were optimistic about workplace AI, yet 61 per cent felt overwhelmed by the pace of change. The research also found that 63 per cent sometimes avoided using AI tools even when they were available.

These findings suggest an important distinction between technological deployment and organisational adoption. Installing an AI system is considerably easier than ensuring employees trust it, understand it and know where human responsibility begins and ends. This is where Gregori sees leadership becoming increasingly important. His argument also challenges the sometimes simplistic assumption that automation principally represents a technology-management problem. The implementation may belong partly to IT and engineering teams, but its organisational consequences extend into training, communication, professional identity and workplace culture.

Leadership in an age of uncertainty

There is another complication. Human oversight is regularly presented as the safeguard for increasingly autonomous technologies, yet merely placing a person somewhere in an automated process does not guarantee effective scrutiny.

Research involving US sales and revenue organisations found that 38.4 per cent favoured a “guided autonomy” model, where AI can recommend or perform actions while people retain oversight and approval authority. However, the research raises a corresponding problem: human supervision is only effective when the person reviewing an AI-assisted decision has sufficient information and judgement to challenge it. This strengthens the case for viewing human capability and AI capability together rather than as competing forces.

It also means organisations need leaders who can decide what should be automated, what should remain principally human and where responsibility sits when the two interact. Gregori develops this theme in The Emergent Leader, published by Torchflame Books in June 2026. According to information supplied for the book, it draws upon his experience of operational transformation and provides 61 short chapters covering six areas of leadership development.

The deliberately concise structure is intended to turn leadership ideas into actions rather than present them solely as management theory. Chapters conclude with a “Take Away” and a practical “Take Action”. Those principles become particularly pertinent when technology is moving faster than conventional organisational change programmes.

Empathy does not mean resisting automation

The human-centred argument should not be mistaken for an anti-technology position. Gregori is himself working within the software industry. His proposition is instead that organisations obtain more value from technology when they understand the people who must use it and the processes it is intended to improve.

In a recent interview, Gregori argues against treating AI adoption as a race and discusses the proposition that some apparent AI failures are actually leadership or organisational failures. This distinction matters. Enterprise experience is already demonstrating that deploying increasingly autonomous AI can introduce problems that do not disappear simply because the technology becomes more capable. One 2026 global survey of senior decision-makers reported that 74 per cent of large enterprises surveyed had rolled back or shut down a customer-facing AI agent following deployment, with data exposure and hallucination or brand risks among the reported concerns.

The lesson is not necessarily that organisations should retreat from AI. Rather, businesses need to recognise that technological capability, organisational readiness and human readiness are different things. Training is part of this equation. One workplace study reported that 67.5 per cent of workers surveyed had received no AI-related training or guidance from their employer, despite around one-third already using AI tools in their jobs. Putting sophisticated technology into an organisation without developing the people expected to use and supervise it risks creating precisely the productivity and governance problems AI is supposed to solve.

The leadership paradox of AI

This leads to an apparent paradox. The more successfully machines absorb routine elements of work, the greater the proportion of human working time that may involve activities that are difficult to reduce to repeatable processes: judgement, creativity, negotiation, accountability, coaching and responding to unexpected events. Leadership therefore does not disappear as automation expands. Its focus changes.

Managers may spend less time supervising the execution of routine tasks and more time helping employees adapt, deciding how technology should be used, identifying where people need additional skills and maintaining confidence while roles are redesigned. Gregori describes The Emergent Leader as a practical reference designed to help managers establish the habits required to build durable organisations.

AI gives that objective fresh urgency. Businesses are understandably investing heavily in what intelligent machines can accomplish. Yet the organisations that navigate the transition successfully may also need to pay equally close attention to something much older: how well human beings lead other human beings.