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Part 2: Understanding the AI Hype vs. Reality for Today’s Leaders

Greater use of digital data and increased automation has been a workplace reality for decades, often complementing human capabilities. However, the current wave of AI, fuelled by advances in data analysis, computing power, and machine learning, is more disruptive. AI excels at tasks traditionally associated with leadership, such as data analysis, scenario planning, and communication. This has led to anxieties about the potential obsolescence of human leadership. Discover the impact of AI on leadership – Part 2.

In this second part of our 3-part series on the impact of AI on leadership past, present, and future of leadership, we dive deeper into the core characteristics of AI and explore the hype surrounding its capabilities. We emphasise defining the role of leadership today, we recommend that every leader gains a meaningful understanding of the opportunities and threats provided by the current wave of AI and the data analysis and advanced automation on which it is built. This new wave brings significant changes and challenges traditional notions of human judgment and decision-making. Above all, leaders must appreciate that AI works through machine learning (ML) and data analysis. AI excels at tasks such as processing large amounts of information, analysing complex scenarios, and synchronising multiple streams of communication, offering significant benefits in support of a more agile style of leadership that automation is not new, and while it can displace some jobs, it also creates new ones and will be an essential tool in enhancing human capabilities.

However, leaders must also recognise AI’s limitations. AI currently struggles with understanding human behaviour, is limited in how it supports creativity and requires careful management to ensure ethical decision-making. Leaders must be aware of these limitations to leverage AI effectively.

The Essence of AI

Automation in the workplace is not a new phenomenon. Historically, the introduction of new technologies has always spurred anxieties about job displacement and the future of work. However, these concerns often overlook the broader picture. While automation has undoubtedly displaced some jobs, it has also created new ones and, critically, has often complemented and enhanced the capabilities of human workers.

Yet, we live in a confusing world. Technologically speaking, we have entered a period where advances in “intelligent” systems and “smart” digital products and services are all around us. Often, they are out in the open where they can be seen, such as your bank’s mobile app or the devices you buy for the home to play music, turn on the lights, and control the heating. However, more and more we see these capabilities buried inside almost all the products and services we’ve been using for some time: From TV and washing machines to the clothes we wear.

However, there is much more to digital transformation than just new product features. More fundamentally, the advances we see are based on using data to predict future needs and automate tasks, changing how we interact with the world. This creates new business opportunities, improves efficiency, and enhances product quality. But even more importantly, it blurs the lines between human and machine decision-making.

The excitement surrounding these digital solutions is justified. After two decades of digitisation, advancements in data analysis, data access, connectivity, and computing power are finally coming together. This powerful combination is accelerating the design and delivery of digital solutions, impacting everything from government services to private businesses.

While stricter and more robust definitions exist, most people now describe these broad capabilities to be part of the new wave of Artificial Intelligence (AI) systems. Generally, AI refers to any system capable of mimicking tasks traditionally requiring human intelligence. To achieve this, most AI systems rely on machine learning (ML), a technique that utilises vast amounts of data and computing power to build and validate decision-making logic. This logic forms the core of an AI model. The AI system then feeds new data into this model, which generates human-like decisions based on the learned patterns.

In one typical scenario, more and more data is gathered from a variety of sensors contained in internet-connected devices. This could be from many sources including domestic devices in the home, environmental sensors on the street, performance metrics in the workplace, or physical monitoring equipment in a factory. By collecting this data, analysis is possible to explore the data to look for patterns. That is the creation of algorithms that recognise common situations or anomalies and solve problems by learning from earlier experiences to apply that knowledge in unfamiliar contexts.

The impact of AI on leadership

As a result, AI systems excel at many tasks typically considered core to the role of leadership: Processing lots of information, analysing a variety of possible future scenarios, recognising shifts in market conditions, communicating efficiently across large teams, and so on. All of these can bring huge benefits to leaders as they adopt more data-driven approaches to decision making and seek greater agility in taking action.

Recognising these benefits, AI is no longer seen as purely a technology issue to be addressed by the IT team. It is firmly on the radar of leaders at all levels in the organisation. McKinsey’s “state of AI” survey in 2023 found that nearly a quarter of C-suite executives are personally using generative AI tools, and over a quarter of companies using AI already have gen AI on their board’s agenda. This rising interest is leading to increased investment, with 40% planning to boost their AI budget due to gen AI’s potential.

However, managing the risks of gen AI is still in its early stages. Less than half of those surveyed are actively mitigating even the most common risk: inaccuracy. Companies with established AI capabilities are leading the charge in exploring gen AI, and those excelling in traditional AI (those McKinsey calls “AI high performers”) are already outpacing others in adopting these new tools.

Navigating the Path to AI

However, taking advantage of AIs’ capabilities is far from straightforward. Leaders today face the challenge of integrating AI capabilities effectively into their organisation, realising its potential while ensuring it complements, not replaces, human leadership. How can they get the balance right? This requires a clear understanding of where AI can add value and where human expertise remains irreplaceable.

Hence, it is essential to be clear on what are AI’s strengths and weaknesses as seen in current products. Today, AI excels in areas such as:

  • Data analysis and pattern recognition: AI can analyse vast amounts of data to identify trends and insights that might escape human awareness, informing decision-making processes.
  • Automating routine tasks: By taking over repetitive tasks, AI frees up valuable human time and resources for more strategic endeavours.
  • Personalised learning and development: AI-powered platforms can deliver tailored learning experiences to individuals, enhancing employee development and upskilling efforts.

However, AI currently struggles with:

  • Understanding the nuances of human behaviour: The complexities of human interaction, including emotions, motivations, and cultural differences, are often beyond the capabilities of current AI systems.
  • Creativity and critical thinking: While AI can generate new ideas based on existing data, it lacks the ability to think truly creatively or critically analyse complex situations.
  • Ethical decision-making: The ethical implications of AI decision-making, particularly in areas like hiring and employee performance evaluation, require careful consideration and human oversight.

Key Lessons for Leaders

Today’s leaders must navigate the complexities of integrating AI into their organisation’s ways of working, ensuring it enhances rather than replaces human leadership. This involves recognising AI’s strengths in data analysis, task automation, and personalised learning, while also acknowledging its current limitations in understanding human behaviour, creativity, critical thinking, and ethical decision-making. Achieving the right balance necessitates a clear understanding of where AI can add value and where human expertise remains indispensable.

Consequently, it is now a priority that today’s leaders acknowledge the role that AI will play:

  • Understand the strengths and weaknesses of AI to leverage it effectively.
  • Explore how AI excels at data analysis and automation, freeing up time for strategic endeavours.
  • Increase awareness of AI’s limitations in areas like human behaviour and ethics to expand your understanding of how to adopt it appropriately.

Watch Part 2

Learn more from the video interview with Professor Alan Brown as he examines the impact of AI on leadership, including its current effects and implications for the future of organisational leadership.

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