Three-quarters of C-level executives believe if they don’t move beyond experimentation to aggressively deploy artificial intelligence (AI) across their organisations they risk going out of business by 2025, according to a newly released study from Accenture.

The report, titled “AI: Built to Scale” and produced by Accenture Strategy and Accenture Applied Intelligence, is based on a global survey of 1,500 C-level executives across 16 industries designed to understand how companies are implementing AI across their organisations.

The research found 84 per cent of C-level executives believe they won’t achieve their business strategy without scaling AI, yet only 16 per cent have made the shift from mere experimentation to creating an organisation powered by robust AI capabilities.

As a result, this small group of top performers is achieving nearly three times the return from AI investments as their lower-performing counterparts.

The report reveals the secret to success for these top performers centers around three key elements: a strong data foundation; multiple dedicated AI teams; and a C-suite-led commitment to strategic, organisation-wide AI deployment.

These companies demonstrate their deep commitment by scaling AI at a much higher rate — conducting nearly twice as many pilots than other companies. But this commitment to AI does not necessarily translate to higher spend, with top performers reporting lower investment levels on their AI implementations — pilots and full-scale deployments — than lower performers.

“It’s clear that companies of all sizes, and across all industries, know they need to scale AI not just to grow, but to merely stay relevant today,” said Athena Reilly, a managing director in Accenture Strategy.

“However, the vast majority are still struggling with how to do it successfully, in a way that will generate the most ROI and bolster competitive agility. What we’ve seen with our clients is that it has to start with the basics: the right data, the right strategy and the right people.”

Data regime key to scaling AI

According to the report, nearly all companies (95 per cent) agree on the importance of data as the foundation to scaling AI, but the top performers are more intentional and focused on ensuring that the right, relevant data assets are in place to underpin their AI efforts.

They are more adept at structuring and managing data, with 61 per cent wielding a large, accurate data set and more than two-thirds (67 per cent) effectively integrating both internal and external data sets.

Beyond the ability to glean the right insights from the right data assets using the right tools, most top performers (71 per cent) have a clearly defined AI strategy and operating model in place, from the onset, for their scaling efforts.

Further, more than two-thirds (67 per cent) have flexible business processes in place and integrate AI applications into the broader ecosystem, which provides the necessary agility needed to achieve lasting growth.

“This connection between strategy and success might seem like common sense, but the pursuit of AI with intention is what truly sets these top performers apart, who are piloting and scaling with intention,” said Dr. Athina Kanioura, chief analytics officer and global lead for Accenture Applied Intelligence.

“Being specific about the business problem they aim to solve helps inform the most effective way to achieve those goals. For example, we see fewer instances of testing a conversational agent to see if it will work in their specific environment, and a push toward strategic thinking upfront to determine whether that’s even the right AI tool to use in the first place.”

This strategic approach is further bolstered by another key characteristic of top performers — assembling the right talent to drive results. Instead of relying on a single AI champion, 92 per cent have strategically embedded multi-disciplinary teams throughout their organisations.

This cross-functional approach also helps ensure diversity of thinking which, in addition to having tangible benefits for considerations like Responsible AI, can also maximise the value an organisation sees from their AI deployments.

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