Why The CEO Must Be The Company’s Primary AI Leader

Long thought of as a tool to increase efficiency and save costs, AI has now proven to be an innovation driver that enables business growth. According to our latest Accenture research on AI among 1,200 global companies, “AI Achievers”—those companies that are the most AI-mature—enjoy 50% greater revenue growth, clearly outpacing their competitors.

Why, then, are most organizations (63%) stuck in the experimentation phase with AI? Because AI initiatives are often led with timidity and are hampered by “pilot-itis,” a fixation on pilot projects at the expense of scale. Speaking to a select group of CEOs as part of the research revealed an opportunity—and the need—for companies’ most senior leaders to increase their AI expertise. Many wondered about scaling AI, its impact on the operating model, and how to embed the technology in their organizations.

Our research suggests four actions CEOs can take to follow the AI Achievers’ playbook and become AI-first companies:

1. Internalizing and evangelizing data and AI know-how: Better, more frequent training on AI literacy can reduce the knowledge gap. For example, a media company in India created a data and analytics center to better predict viewership for its programs. Its Chief Digital Officer realized these AI transformation efforts were more likely to succeed if his leadership had a stronger grasp of AI tools. He organized formal and informal opportunities, such as workshops and “gamified” trainings, to learn about image recognition, predictive analysis and metadata tagging. Today, the company’s C-Suite leaders use AI to make decisions up to 90% faster.

2. Aligning data and AI strategy with business goals: CEOs should ensure their organization has effective strategies in place to capture, store and process the data that fuel AI. These are crucial to delivering on AI’s potential, better understanding customers’ needs and improving decision-making.

The best AI strategies are often the boldest. “In the last five years, we started to use AI as one of the main drivers in the business,” said the CEO of automotive parts for a German equipment manufacturer. The following example shows that having a clear vision for data and AI’s value to the business can yield impressive results: A refinery in France created an AI-powered “digital factory” that encouraged collaboration between its data scientists, software developers and other digital experts. This hub is expected to improve the firm’s revenue by $1.5 billion annually by 2025.

3. Invest aggressively in capabilities that support the company’s AI strategy: All leaders need to increase their investments in AI or risk being left on the sidelines. By 2024, we project nearly half of the companies (49%) will devote at least 30% of their technology budgets to AI, up from 19% in 2021. Efforts to invest in data and AI platforms, such as an AI engine, can accelerate enterprise-wide transformation. Built for the future and managed by a diverse team of machine learning engineers and data scientists, AI engines balance experimentation and execution with AI.

CEOs must also recognize that the greatest risk to AI-driven transformation is not building clear governance on top. They should ensure this and signal leadership buy-in by appointing a C-suite level AI champion tasked with leading AI strategy, execution and embedding AI into the company’s operations. For instance, 83% of Achievers have C-suite sponsorship in AI, compared to 56% of Experimenters.

4. Keep humans in charge of who decides: AI should help companies achieve their goals without ceding control to machines. Like other technologies, AI has its limitations, such as recommendations being only as good as the data and assumptions on which they’re based. Considering that, CEOs should encourage their teams to design AI responsibly from the start. This is essential to building trust with customers, employees, businesses and society at large. Take a page from a central bank that partnered with the financial industry to create the first practical methodology and toolkit that offers detailed guidance on using AI to leverage fair, ethical, accountable and transparent principles.

By adopting these practices, CEOs can set their companies on the path to AI success and the growth opportunity that comes with it, rather than being locked into permanent pilot mode. This bold transformation will require a long-term embrace of and investment in technology across every part of every business, sometimes resulting in total enterprise reinvention. A clear sign of what’s to come? Forty-six percent of CEOs already mentioned AI in their earnings calls last year, and this is just the beginning.