Growing Up: 5 Reasons Why Many Companies Are Still in the "Adolescence of AI"

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Here's what companies can learn from the small group of organizations already using artificial intelligence (AI) for their competitive advantage.

If the biggest companies in the world were people, most would be in their teens when it comes to using artificial intelligence (AI).

According to a new study from Accenture on AI maturity, 63% of 1,200 companies were identified as "experimenters", i.e. companies stuck in the experimentation phase of their lives in AI. They have yet to harness the full potential of technology to innovate and transform their business, and they risk leaving money on the table.

It's money that the most mature AI organizations are already making. While "AI adults" (dubbed Achievers in research) are just a small group - representing 12% of companies - they reap big rewards: by outperforming their peers on AI, they increase growth of their income by 50% on average. How? Because they master key capabilities in the right mix by mastering the technology itself – including data, AI and cloud – as well as their organizational strategy, responsible use of AI, sponsorship of the C suite, talent and culture.

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Unlike individuals, companies do not necessarily grow and reach adulthood in a relatively fixed period. Instead, they hold their development in their own hands. It is therefore crucial to understand what is preventing adolescent AI users from reaching maturity. They generally share the following five characteristics:

1. Their C-suite didn't buy AI's ability to drive growth

Only 56% of experimenters are sponsored by a CEO and senior, compared to 83% of achievers, indicating that AI maturity starts with executive buy-in. Additionally, Achievers are four times more likely than Experimenters to set up platforms that encourage the sharing of ideas and easily ask questions internally. In an example of innovation driven by leadership, a global digital platform is harnessing AI and generative design to create self-contained buildings that fit together like pieces in a LEGO set.

2. They don't invest in their team members

Experimenters are hampered by a shortage of skilled AI workers. Moreover, they have not yet invested in training that helps their employees acquire AI knowledge. While more than three-quarters of Achievers (78%) have mandatory AI training for their engineers up to C-suite executives, the same can be said for only 51% of Experimenters.

To be successful with AI, experimenters need to retrain current team members in the technology. For example, a large oil and gas company in Southeast Asia built a gaming platform to develop the digital literacy of its employees. He then created a cloud-based performance reviewer that assessed a decade of employee data to make recommendations for filling various digital roles. This has reduced the time it takes to fill vacancies and has helped close the digital skills gap.

3. Their use of AI is not integrated across the business

While 75% of all companies analyzed have integrated AI into their business strategies and cloud plans, they lack a foundational AI core. To achieve AI maturity, they need to embed AI across the enterprise while knowing when to leverage external resources.

High achievers are 32% more likely than experimenters to develop custom machine learning applications or work with a partner to...