Accenture Study: Failure to Scale AI could risk 80% of Indian Organizations Out of Business
Nearly eighty percent of C-level executives in India believe if they don’t move beyond experimentation to aggressively deploy artificial intelligence (AI) across their organizations they risk going out of business by 2025, according to a newly released study from Accenture (NYSE: ACN).
The research, titled “AI: Built to Scale” and produced by Accenture Strategy and Accenture Applied Intelligence, found that while 79 percent of C-level executives in India believe they won’t achieve their business strategy without scaling AI, only a few have made the shift from mere experimentation to creating an organization 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.
“Over the years, the use of AI has permeated various functions demonstrating its true transformative potential. Most companies now also recognize that they need to scale AI for growth and relevance, yet they are unable to do so. Those who push through the barriers to embed AI more deeply in their organization, are seeing a return on their AI investment of 70 percent or more,” said Anindya Basu, geographic unit and country senior managing director, Accenture in India. “Indian businesses need to step on the pedal and learn from the leaders. They need to make strategic investments to scale AI as that’s the only way to realize its true business value.”
The report reveals that the secret to success for top performers centers around three key elements: a strong data foundation; multiple dedicated AI teams; and a C-suite-led commitment to strategic, organization-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. However, 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.
According to the report, nearly all global respondents (95 percent) 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 percent wielding a large, accurate data set and more than two-thirds (67 percent) effectively integrating both internal and external data sets.
“A key barrier to the successful scaling of AI is the lack of the right people strategy. Companies need to ensure their employees understand both what AI is and how it applies to their day-to-day role. While the top leadership team can serve as the champions responsible for scaling AI initiatives, embedding teams with AI across the entire organization is not only a powerful signal about the strategic intent of the effort, but will also enable faster culture and behavioural changes,” said Saurabh Kumar Sahu, managing director and lead for Applied Intelligence, Accenture in India.
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 percent have strategically embedded multi-disciplinary teams throughout their organizations. This cross-functional approach also helps ensure diversity of thinking which, in addition to having tangible benefits for considerations like Responsible AI, can also maximize the value an organization sees from their AI deployments.
