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AI and Leadership: How executives can boost productivity through human-AI collaboration

AI and Leadership: How executives can boost productivity through human-AI collaboration

AI is reshaping how organisations plan, make decisions, and perform. For senior leaders and L&D directors, the challenge is not whether to adopt AI. It is how to integrate it into leadership capability that strengthens performance and people development.

26/01/2026 Back to all articles

Rather than replacing leadership, AI is acting as a partner. When used well, it enhances human judgement, frees up leadership capacity, and enables a greater focus on coaching, mentoring, and long-term capability building.

This evolving relationship can be understood as the AI-Human Continuum, where value is created through the interaction between technology and human skill.

Human skills are now the primary currency of the modern workplace. The future of leadership belongs to those who use AI to work faster, so they can lead more humanely. People who use AI will replace people who don’t.

Leadership behaviours needed in an AI-enabled world

As AI becomes embedded across businesses, leaders need a mix of capabilities to remain effective. Research from the Microsoft Work Trend Index reveals that 71% of leaders say they’d rather hire a less experienced candidate with AI skills than a more experienced candidate without them. And 66% of leaders say they wouldn’t hire someone without AI skills.

For leadership, a baseline level of AI and data literacy is essential. Leaders do not need to be technical specialists, but they must understand:

  • How AI systems generate insights
  • How to question outputs
  • How to recognise limitations, bias, or gaps in data. 

Taken together, successful AI-era leadership rests on core behaviours:

AI and data literacy

Successful leaders move beyond seeing AI as a black box and start asking questions. This involves understanding what AI can achieve versus the hype and knowing how to interpret data to make evidence-based decisions. Without this capability, AI can become either underused or over-relied upon.

Agility and decision-making in fast-changing environments

Agility remains a defining leadership behaviour. Organisations that prioritise agility and resilience are more likely to achieve their business outcomes. Agility is about more than speed; it is about navigating ambiguity.

The pace of AI development is exponential. Leaders must now make confident, high-stakes decisions even when the technological landscape is shifting beneath their feet and the correct path is unclear. Strategies become obsolete. Leaders must pivot and unlearn old business models. They need to experiment in a culture where learning from fast failures is accepted.

Responsible leadership, ethics, and AI governance

AI brings risks about bias, privacy, and transparency. A leader's role is to implement frameworks that ensure AI is used responsibly, maintaining transparency with clients and teams about how automated decisions are made.

These behaviours matter because AI is already changing what leaders spend their time on.

Putting the human into AI

At the same time, human leadership skills are becoming more important, not less. Analytical thinking, judgement, storytelling, and ethical reasoning are critical when translating AI-driven insight into decisions. AI can surface options, but leaders must apply context, values, and experience.

As AI takes over analytical and repetitive tasks, human skills become the ultimate premium. Think emotional intelligence (EQ), coaching, and inspiration. High-level leadership is today about managing the anxiety that AI causes in the workforce. Leaders must help their teams transition by identifying human-plus-AI roles rather than AI-instead-of-human roles.

What AI can and can’t replace at leadership level

AI already supports a range of executive tasks, from data analysis and reporting to scenario modelling and forecasting. A Harvard Business School and BCG study found that consultants using AI were able to complete 12.2% more tasks on average and performed tasks 25.1% more quickly.

These capabilities reduce the time leaders spend on operational and administrative work. Yet, AI does not replace the human elements of leadership.

  • Building trust
  • Managing complex stakeholder dynamics
  • Developing people
  • Making judgement calls in sensitive situations

These all remain human responsibilities. Recent research from McKinsey (January 2026) suggests that while AI handles the inference, leaders must provide aspiration and judgement.

For senior leaders, the real opportunity lies in how reclaimed time is reinvested. AI can create capacity to focus on coaching, mentoring, and leadership development activities that support organisational resilience and succession planning.

Redefining the leadership workload

AI is absorbing process-driven executive tasks, such as scenario modelling, initial budget drafting, and performance data synthesis.

DDI’s Global Leadership Forecast 2025 shows 71% of leaders are under increased stress, causing 40% to consider leaving their jobs. But could AI be the ‘relief valve’ that can automate routine administrative tasks?

What happens to that reclaimed time? The most effective leaders are reinvesting this found time into high-impact human activities:

  • Coaching and mentoring: Moving from being a "message relay" to a developer of talent.
  • Deep strategy: Focusing on long-term "non-linear" outcomes that AI cannot predict.
  • Building culture: Strengthening the "psychological safety" needed for teams to experiment with AI

Refocusing leadership

As AI takes on more process-driven work, leadership roles are more people-centred. This places more emphasis on skills such as empathy, communication, and the ability to develop others.

LinkedIn’s 2024 Workplace Learning Report notes that 91% of L&D professionals believe that human skills (soft skills) are more important than ever. Leaders who use their time to strengthen leadership capability across the organisation are more likely to see performance gains.

Assessing and closing the AI skills gap

To partner with AI, organisations need clarity on where their leadership capability stands today. This starts with defining which AI-related skills are needed at different leadership levels. These may include:

  • Data literacy: Understanding how to interpret and challenge AI outputs.
  • Ethical decision-making: Navigating the bias and privacy risks of automated systems.
  • Change leadership: Guiding teams through the transition to AI-augmented workflows.

Assessment is a critical step. By evaluating leaders against these capabilities, organisations can identify skills gaps and prioritise development. This could be AI-first leadership journeys that combine technical training with soft skills such as empathy and communication. Targeted learning, coaching, and practical application then support skills growth in a way that aligns with the business.

AI as a partner to leadership success

The organisations that benefit most from AI will be those that adopt it thoughtfully. When positioned as a partner rather than a replacement, AI enhances human capability. Leaders can then focus on judgement, coaching, and strategic direction.

By offloading the analytical tasks to AI, leaders are freed to focus on the 'softer' side of leadership. These elements drive engagement, retention, and long-term resilience.

For senior leaders and L&D directors, the goal is not to reduce the human element of leadership, but to strengthen it. The future of leadership will be shaped by how organisations navigate the AI-human continuum. Combining technology with human skill to build capability, confidence, and long-term performance.

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