AI (artificial intelligence) has captured the collective imagination, thanks to the breakthroughs of large language models (LLMs), such as ChatGPT, and generative AI. However, in the latest EY Global Board Risk Survey, 43% of respondents cited that the pace of technological change and disruption, including AI, is likely to have a severe impact on organisations over the next 12 months.

As designers of corporate strategy, boards must ensure their organisation treads with confidence into this new world, fully understanding the opportunities of digital advancements while developing appropriate risk frameworks. There are three board-level priorities to consider in the current AI craze.

Brave new world

The first is to build confidence in the outcomes and operations of AI. Confidence will be the top differentiator between companies that fully harness AI and those that fall behind.

The technology is nascent, and key constituencies—such as software companies, regulators, governments, enterprises and citizens—need time to settle on and agree standards. The EU is aiming to set risk parameters, but it will take time to strike the right balance for all parties.

At the recent Global AI Safety summit held in the UK, 28 governments in attendance—including the US, China, and the EU—agreed to collaborate to i) identify and understand risks of shared concern, and ii) build multilateral policies to mitigate those risks.

In addition, major AI tech companies joined several (but not all) governments in signing a non-binding agreement to collaborate on testing AI models against a range of potentially harmful capabilities, including critical national security, safety, and societal harm. Confidence in AI will hinge not only on regulation, but also on reliable and safe outputs, based on the right controls and the quality of data, processes, technology platforms, security, governance and skills.

The second theme to consider is exponential value creation. The potential of AI comes not just from isolated use cases but unlocking new operating models and sources of growth. Companies rightly often start with AI experiments focused on efficiency, “learning by doing” such as automating manual processes.

However, the bigger opportunity lies in enterprise-wide transformation. Is AI opening up new markets and channels? Is it feasible to reinvent the product portfolio? Can you reimagine the customer and employee experiences? How will AI transform talent development, career paths, and workflows? Should internal policies be revisited? Can you make more accurate financial forecasts, or think differently about supply chain management? These are examples of just a few crucial questions companies should consider.

When measuring the potential value of AI for your business, there are two main angles. The first is productivity and efficiency gains. We are seeing significant savings in areas like software development costs. AI is about doing more with the same resources, not about replacing jobs, and productivity gains can be measured and achieved relatively quickly.

The second gain is revenue growth. AI can bring new sources of income, clients, and products, and quicken time to market. Generative AI alone could drive a 7% increase in global GDP and boost global productivity by 1.5% over a ten-year period. This is pushing the market to the next S curve, bringing a proliferation of new business models.

Power of the people

The third, and perhaps most exciting aspect of AI, is its ability to augment and unlock human potential. EY teams prefer to talk about ‘augmented’ rather than ‘artificial’ intelligence, because we view AI not as a replacement for people, but as a collaborator. Consider AI as a ‘co-pilot’, which can amplify expertise in specialised domains like finance, risk management and treasury.

These AI advisers allow an organisation to capture the knowledge of its top performers and extend it across the workforce. Just as a personal tutor helps a student excel, AI augmentation can customise training to the individual to help employees reach new heights and enable scalable talent development.

In this future scenario, human judgement will be increasingly important, as technology is probabilistic, not deterministic. The same question will not always elicit the same answer.

Looked at through the prism of these three themes—confidence, value creation and people potential—there are several steps boards can consider in order to drive successful AI adoption.

1. Benchmark. Know your starting point in terms of workflows, data, security and applications. A thorough audit of digital and data maturity can help focus attention on the most fruitful, data-rich domains for AI, and the key risks and blind spots.

2. Learn by doing. While trepidation is warranted when tinkering with a powerful new capability, companies can only understand the risks and benefits through initial hands-on experimentation. A governance framework, as part of an AI roadmap, can help firms deploy responsibly.

3. Have a broad transformation mindset focusing on the long term, about enterprise-wide value and transformation opportunities, not just AI point use cases. At EY, we have taken a strategic approach through a holistic transformation pivoting around three vectors: transform clients, transform EY and transform the world. We’ve collected more than 100 contemporary AI applications and aligned them to metrics including time to productivity, employee experience, and growth.

The market is getting better at identifying the right key performance indicators to start measuring value. Boards need to embrace AI as a tool for productivity, growth and talent. The efficiency gains are more immediate, but revenue potential is huge too. With the right metrics, companies can make data-driven decisions and measure the impact.

4. The talent agenda will need to transform as companies adopt AI. Tutors and co-pilots can learn from analysing best practices and behaviours, constantly improve, and provide tailored recommendations to each employee, which has huge potential to augment people skills. However, personal judgement is still essential in all aspects of the workforce.

Companies should strive to strike a balance between AI and employee oversight, acknowledging both the potential of AI to unlock the workforce’s potential through personalised support, while ensuring human input remains central. With this framing, AI can support your talent development strategy.

The race to deploy AI is understandably becoming a competitive pressure for boards, but as they see the risk and regulatory landscape evolve, they are understandably cautious about deployment at scale. Through taking a careful, iterative approach, and by connecting AI to wider business transformation objectives, boards can steer their enterprises safely into a new era of digital innovation.

Beatriz Sanz Sáiz is EY global consulting data and AI leader