In Spain, the Madrid Metro uses AI to monitor its network and reduce energy consumption by 25%. In the U.S., a beverage company uses AI to drive sales by analyzing retailers and markets. In Europe, an energy company trains its engineers and managers in a digital twin factory powered by AI. In the Middle East, a telco’s AI-powered virtual assistant speaks to 1.65 million customers every month in different Arab dialects and English.
Undoubtedly, AI is in full adoption around the world, with all industries recognizing it as the next big thing in tech. However, a report from Accenture, assures that 63% of companies using AI are only scratching the surface.
On June 8, 2022, Accenture presented the report The Art of AI Maturity. The report concludes that the majority of organizations using AI are still experimenting with the technology. Only 12% are using it at maturity level.
AI Achievers vs. AI Experimenters
According to Accenture, about 30% of the total revenue of “AI Achievers” is linked to AI. “AI Achievers” also enjoyed 50% greater revenue growth on average during the 2019 pandemic era.
“In 2021, among executives of the world’s 2,000 largest companies (by market capitalization), those who discussed AI on their earnings calls were 40% more likely to see their firms’ share prices increase—up from 23% in 2018,” Accenture says.
In total, Accenture identified four groups: “AI Achievers”, “AI Builders”, “AI Innovators” and “AI Experimenters”. Achievers, Builders and Innovators combined, represent just 37% of surveyed organizations. “AI Experimenters” almost double these numbers.
“AI Achievers” turn AI pilots into production projects to solve business problems in the real world. They also use their metrics and data to take action, for example by measuring and reducing greenhouse gas emissions or consumption of natural resources. Companies leading in AI build their data and AI core instead of buying it. They also have an integral AI strategy and encourage innovation through their culture.
More than half of all surveyed companies using AI are not taking full advantage of the technology. “AI Experimenters”, set at 63% by Accenture, lack the mature AI strategies needed and don’t have the capabilities for AI operations.
Whit Andrews, Gartner distinguished VP analyst, told TechRepublic that while many organizations have chalked up at least one AI project, the challenge they now face is how to drive their digital future through AI.
Gartner agrees that AI has the potential to allow organizations to remain competitive, and reimagine products and services. But IT leaders need to see through the hype that surrounds AI and find how to apply the technology to solve real problems, Gartner says.
Accenture’s new report predicts that companies that master AI will double from 12% to 27% in the next two years. To master AI, companies look beyond data and AI tools, like machine learning. They embrace an AI organizational strategy, invest in talent and infrastructure and build an AI culture.
SEE: Artificial Intelligence Ethics Policy (TechRepublic Premium)
Top and low-ranking industries by AI use
On a scale from 1 to 100, the Accenture report says that the average AI maturity score for all industries is slightly above 35 points. Technology industries are the most advanced with an AI maturity score of 54 that is expected to rise to 60 by 2024. The gap between tech and all other sectors is significant, but Accenture expects this gap to narrow considerably by 2024.
Industries that are excelling in the use of AI include:
Industries that fall below the average include:
- Banking and capital markets,
- Public services
Accenture highlights AI-powered self-driving vehicles in the automotive sector, AI remote and navigation systems developed by aerospace and defense firms and drug development in the life sciences industry, as game-changing trends.
SEE: Metaverse cheat sheet: Everything you need to know (free PDF) (TechRepublic)
The art of mastering AI
Accenture says AI priorities, investments, AI tools, responsible AI use and long and short-term AI strategies are five main points that can help organizations master AI. Companies that excel in AI are not just looking to master one point but combine their strengths to outperform in all.
“AI Achievers” set AI as a priority throughout their entire organizations. Eighty-three percent of “AI Achievers” have full sponsorship from leaders. CEOs are creating a deliberate culture of innovation. Forty-eight percent of Achievers embed innovation in their organizational strategies, while only 33% of Experimenters do the same.
“AI Achievers” are also investing in talent. Seventy-eight percent of Achievers include mandatory AI training for all their workers, from product development to C-suite executives. This creates a strong AI literacy that allows for AI collaboration across the entire company.
The industrialization of AI tools and teams that build an AI core is also a priority for “AI Achievers”. Talent, technology and data environments come together in cloud processes to power migration, scaling and growth, innovation, progress and performance. “AI cores are, in turn, managed by dedicated interdisciplinary teams of machine learning engineers, data scientists, data-domain experts and systems engineers,” Accenture says.
Whit Andrews, VP Analyst of Gartner explains that AI investments should cover various practices. “Examples include formal programs for linking software engineering and AI teams, a plan to hire internal and external talent, and the top-down commitment that all new IT projects and major upgrades should incorporate AI,” Andrews says.
“That means investing resources in doing it in every aspect of their digital operation. They must push experiments toward production. For now, that means central systems. Eventually, those central systems will sink into the overall business,” Andrews adds.
AI responsibility is another differentiator. When an AI project adheres to laws, regulations and ethics from the start, it can empower employees, businesses, and customers, while impacting society.
Long and short-term investments are also top priorities for AI Achievers. Leading in AI requires aggressive investments. AI leaders are getting more from AI, simply because they invest more than other groups. They also understand that AI is a journey that has no peak, and continual investment, research and development are needed.
“AI Achievers are thriving. Across industries, they’ve moved past cloud migration to innovation. They’ve capitalized on the cloud’s scale and computing power to tap into new data sources and AI technologies that are widely available. But AI isn’t their secret to superior performance. It’s how they’re approaching AI that makes them different,” the company behind the report “The Art of AI Maturity” concludes.