By Sylvain Duranton
& Sumit Sarawgi

Getting palpable value from artificial intelligence (AI) is at the top of the minds of business leaders. However, the widespread excitement does not always translate into a meaningful strategy focused on AI. Adoption of AI across industries from manufacturing to services is imminent. The success of companies will be dependent on the scale at which they adopt AI, and how successfully they are able to transform the business to leverage its benefits. Now the economic activity of most nations is driven by corporates; hence, successful AI adoption by companies will be a critical driver of the competitiveness of nations.

The findings of an Artificial Intelligence Global Executive Study conducted by BCG and MIT Sloan Management Review involving 3,000 executives may be pertinent for India. Twenty per cent of the companies in this survey may be called ‘pioneers’; they are companies who have a significant understanding of AI and have successfully adopted it. Over a period of time’ pioneers’ are likely to increase the gap over even the next group of companies termed as ‘investigators’. ‘Investigators’ are companies who understand AI but have limited adoption. Other groups of companies, classified as ‘experimenters’ and ‘passives’, have limited understanding or adoption of AI. Globally, Chinese companies lead the pack, with 32% of Chinese companies having adopted AI compared to around 20% in the US, France and Germany. While the proportion of Indian companies actively adopting AI may be less than the top ranking countries, India has not been passive about AI. India is among just 20 countries which have a national AI policy. Thanks to Government initiatives, India is among the most data-rich countries in the world. The data and technical infrastructure around biometric identifiers (Aadhaar) and digital payment capability(UPI) are global benchmarks. Select Indian companies in financial services and telecom, and a more limited set of companies in manufacturing, are likely to quality as AI ‘pioneers’. But this number could have been higher.

Unfortunately, certain companies try to ‘signal’ their AI adoption without making any meaningful investment or commitment to AI. The high-point of AI adoption should not be seen as the presence of robots to greet visitors. Many ‘serious’ players are opening labs and hiring data scientists; but business use cases of AI come to some as an afterthought. Often these use cases are not scalable, or form only a peripheral part of an existing process. Some companies busy themselves with an ever-expanding list of Proof of Concepts (POCs). The POCs make for excellent talking points in mushrooming AI forums, but very few of them are meaningfully scaled up. In one of our recent studies we found that 75% of the companies failed to scale up post POC. Such approaches are hardly useful.

To be successful in AI adoption, companies have to respect the golden rule: 10/20/70. BCG GAMMA has continuously tried and tested this law in its missions. Ten per cent of the work involves building the algorithm. But this 10% is critical because the algorithm determines the success of the initiative. The next 20% involves implementation of the algorithm and development of the user-interface. The final 70% consists of structured support and facilitation from the business organization. Under this, work processes may need to be redesigned, teams should be designated to maintain and manage the solution, and measure the adoption rate and the results.

Post the initial excitement of algorithm development, some companies are simply unable to deploy resources for implementation. If the use case is very narrow or peripheral, the benefits don’t justify the implementation cost; sometimes the priority for implementation is lost as the team chases yet another shiny-new-POCs. Even when companies complete stage two, few actually dare to disrupt existing work habits and silos. They attempt to force-fit the new solution to the older process or organization structure, thereby reducing the efficacy of the AI outcome. Such situations lead to disillusionment with AI.

AI pioneers understand that AI is a mission of business transformation.They tend to focus more on leveraging AI to create newer ways of earning revenue, and not just on cost reduction. Senior management should concentrate on two or three high-potential areas such a personalization engine, pricing, and supply chain optimization that are core to their business; and provide support throughout all three phases.

Deceptively prudent strategies such as ‘wait and watch’ may increase the gap between early adopters and late entrants, to the extent that catching up may become difficult. In matters of AI, one needs to dare to have a big vision, take risks and allocate the required resources. Brave and tough decisions will have to be taken. This is the ‘AI or die’ imperative.

Duranton is Sr Partner & leads BCG GAMMA globally
Sarawgi is Partner and leads BCG GAMMA in India