News & Analysis

Only 12% of Enterprises Using AI are Gaining an Edge

A recent survey by Accenture indicates that that the AI Maturity levels in companies continue to be a low level as most businesses are still experimenting with it

Artificial Intelligence (AI) became the buzzword for business efficiencies some years ago, but new research suggests that most enterprises using the technology are still experimenting with it and just about 12% of them have reached a maturity level that results in a strong competitive advantage. 

Global research from Accenture titled “The Art of AI Maturity: Advancing from Practice to Performance” says AI maturity is considered the degree to which organizations outperform their peers in a combination of AI-related foundational and differentiating capabilities. 

The report uncovers strategies for AI success through a holistic framework, which includes a new index to express company AI maturity on a 0-100 scale. These capabilities include the technology — data, AI, cloud — as well as organizational strategy, Responsible AI, C-suite sponsorship, talent and culture.


The three level of achievers

The research puts the median AI maturity of organizations at a moderate score of 36, revealing most companies have significant opportunities to generate greater value with AI. The research highlights a small group (12%) of organizations that already use AI to outpace their competitors. This group is dubbed AI Achievers, with a score of 64 on the maturity scale, almost doubling that of others and correlating with 50% higher revenue growth than their peers.

The analysis further shows that most companies (63%) are AI Experimenters, barely scratching the surface of AI’s potential with an AI maturity score of 29. AI Innovators (13%), scoring 50, and AI Builders (12%), at 44, are somewhat advanced in their level of AI maturity, but are still leaving the full value of AI untapped.

“We believe every part of every business must be transformed by technology, data and AI, in some cases resulting in total enterprise reinvention,” said Sanjeev Vohra, global lead for Applied Intelligence at Accenture. 

“AI Achievers are showing their peers what’s possible when you release the full potential of talent and technology, working in tandem, supported by a clear vision and commitment to change. But even this most mature group has plenty of room for growth. And while most industries have AI Achievers, they vary greatly in how AI-mature they are overall and the leaps they will make,” Vohra says. 


The Hare and the Tortoise

The study points out that Tech firms  already have a high AI maturity score of 54, which will rise moderately to 60 in 2024, but still position them at the pinnacle of AI maturity across all industries. In contrast, carmakers and suppliers will leap from a moderate 39 today to 57 in two years — betting on a significant surge in sales of AI-powered self-driving vehicles.

Similarly, retail companies will evolve in their AI Maturity from 38 today to 54 in 2024. Notably, many retail companies show a deeper commitment to AI transformation than other industries. Walgreens Boots, as part of its efforts to create a more data-driven organization that can offer customers highly personalized digital service, migrated from legacy databases to advanced cloud databases and analytics. The company also built more than 100 high-value AI products that create detailed customer profiles and help it better optimize inventory and prices.

“AI adoption rapidly matured during the pandemic, yet to create more value with AI and use it to reinvent the enterprise, companies require a clear leadership vision combined with effective change management and human capital reinvention,” said Piyush N Singh, India Business Lead at Accenture.

“To successfully scale the use of AI, the companies need to industrialize AI tools and teams and also nurture a culture of responsible AI design. But most importantly, they must invest in talent,” said Prithvijit Roy, Managing Director, Applied Intelligence, Accenture in India. Besides hiring for multidisciplinary AI-related skills, it is imperative to create data and AI fluency across the workforce through skilling and reskilling for a majority of employees.

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