Six leadership skills you need to make the most of AI

Artificial intelligence (AI) is impacting almost every industry. According to research by Forbes more than half of business owners currently use it for cybersecurity and fraud management, and nearly half (46 per cent) for internal communications.

Those organisations that have yet to adopt it are likely to do so in the coming months and years. However, they would do well to recognise the challenges and risks associated with doing so.

The 2023 AI Study by Forbes found a disparity between the willingness of C-suite executives and employees to embrace AI, with only 52 per cent of employees keen to make use of it.

This can create difficulties when rolling out technology across a business.

Other concerns relate to data privacy and security, the risk of relying too heavily on AI to make important decisions, and the potential for it to disrupt traditional workplace roles and dynamics.

Leaders have an important role to play in ensuring businesses can use AI effectively and responsibly.

To do this, they must adopt six complementary leadership capabilities – and ensure their teams have the required skills in each area – to harness the potential of AI, while mitigating risks and promoting the wellbeing of their employees.

1 The experimenter

Embracing AI requires a mindset and approach that emphasises experimentation and learning. Leaders must integrate AI into their individual and organisational management practices.

There are examples of organisations that have successfully developed their offering using AI based on a strategy built around experimentation.

Under Co-founder and Executive Chair Reed Hastings, Netflix has used AI and experimentation extensively to personalise content recommendations for its users.

Amazon deploys it in areas such as product recommendations, supply chain optimisation, and customer service. IBM’s Watson AI platform develops personalised treatment for patients.

None of these businesses would have been able to do so without the culture of experimentation at the top of the organisation.

2 The empathetic leader

AI generates a significant amount of unease for employees. A survey by Warwick Business School suggests that more than 50 per cent of its Global Online MBA students, particularly those in the 35-44 age group, believe their company will replace employee-led roles and responsibilities with AI within the next year.

This has the potential to impact engagement levels, and cause issues around wellbeing and mental health. Leaders need to acknowledge this fear and reassure employees where possible.

A good example of this is Satya Nadella’s stint as CEO of Microsoft, where the company’s strategy focused around using AI to augment human capabilities rather than replace them.

Discussions around the use of AI involved a sense of empathy, collaboration and ethical responsibility, and bringing employees onboard and ensuring a financially successful project. Leaders need to ensure they listen to employees, take onboard their concerns and minimise any negative impact.

3 The ethical leader

Ethical leadership is vital for any AI implementation, and leaders need to demonstrate strong ethical values and apply these to potential use cases.

An example here is Emma Dickison, President and CEO of US Home Helpers, a private care service for old people, who stressed that any AI usage in the field of home-monitoring technology must be cost-effective and respect the privacy of its customers.

Other organisations have looked to implement top-down ethical positions. Japanese tech firm Fujitsu formed an international AI ethics research team, which sought to prevent bias that could potentially cause gender or racial discrimination being included in any AI models or dataset.

IBM has created the IBM AI Ethics Board and the IBM Principles for Trust and Transparency in AI, which seek to ensure transparency, explainability, fairness and accountability in any project.

Leaders need to understand ethical considerations and responsible AI practices, and undergo training in topics such as bias, fairness, privacy and transparency so they understand the risks.

4 The collaborator

When developing and implementing any AI application, collaboration with other disciplines and business functions is essential to ensure a successful roll-out.

This is something Jonathan Lerner, CEO of US IT frim InterVision Systems, has highlighted, stressing the role this can play in overcoming any ethical issues and risks that may come up.

According to the Forbes 2023 AI Study, three-quarters (75 per cent) of CEOs say members of their C-suite mention cross-functional collaboration when setting their AI strategy.

Leaders need to take a holistic approach to projects, and include roles such as CEO, chief technical officer, chief financial officer and chief marketing officer in planning and execution.

5 The data-savvy leader

AI, almost by definition, requires a huge amount of data to make inferences and decisions.

Leaders need to be able to make sense of this data and understand how to include data-driven insights in their own strategic decision-making, as well as supporting others in the organisation to do the same. Again, training may be required here.

Susan Wojcicki, the CEO of YouTube, is known for her data-driven approach to leadership. Under her tenure, YouTube has heavily relied on analytics to understand user behaviour, optimise content delivery, and drive platform growth.

Wojcicki’s focus on leveraging data to inform decisions has been pivotal in maintaining YouTube’s status as the leading video-sharing platform.

6 The pragmatist

Alongside all the work involved in implementing an AI strategy, organisations need to add value to customers as they always have.

This means leaders must be pragmatic, balancing the experimentation required for innovation and future success with meeting the needs and expectations of stakeholders today.

Leaders must be able to multi-task and combine short-term focus with longer-term aspirations.

Amazon founder and former CEO Jeff Bezos is a quintessential pragmatist. His leadership style is marked by a relentless focus on practicality and efficiency.

Bezos’ pragmatic approach can be seen in Amazon’s operational innovations, such as the development of the world’s most advanced logistics and distribution systems. His ability to balance long-term vision with practical execution has been a key factor in Amazon’s success.

The six leadership characteristics outlined above require very different skillsets, so leaders must accept that no individual can do everything. They must draw on the strengths of others.

Through collaboration with other C-suite members leaders can create an AI strategy that aligns with broader organisational goals and objectives. This will also ensure a diverse range of perspectives and experiences related to different areas of responsibility, which can lead to well-rounded AI strategies with less risk of unforeseen issues.

AI leadership capabilities should also be developed among executives, managers, and team leaders to create a culture of collaboration and experimentation, as well as empathy and ethics.

Leaders who can successfully build organisations with these capabilities stand to reap the benefits that AI can bring in terms of efficiency and innovation, while reducing the attendant risks and taking their employees with them on the journey.

Further reading:

Working on the jagged frontier: How managers should use generative AI

Are managers going to be replaced by AI?

No shortcut to upskilling: Managers can't rely on Gen Z on generative AI

How to reduce AI bias

Dimitrios Spyridonidis is Associate Professor in the Entrepreneurship & Innovation Group, at Warwick Business School. He teaches Leadership and Strategic Leadership Development on the Executive MBA and Global Online MBA. He also teaches Leadership Plus on the Full Time MBA.

Learn more about Developing Executive Leadership on the four-day Executive Education course at WBS London at The Shard.

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