Collecting, curating, connecting, and correlating data to make the data AI-ready is the core to unleashing and excelling the true power of AI. Similarly, AI helps connect and unearth millions of known and unknown relationships from the data signals. Today, there is no dearth of data; on the other hand, the AI domain is witnessing ground-breaking innovations.

With this background, we talked with Sunil Senan, Senior Vice President and Business Head, Data and Analytics at Infosys, to understand why we're yet to see large-scale adoption despite the power of both data and AI available. Further, we tried to deep dive and understand the trends that will dominate in 2022 and beyond.

With a humongous volume of data at our fingertips, still, we can feel the dearth of data-driven decision-making by Indian companies. What, according to you, is holding us back? 

There are certain reasons that are holding companies back from incorporating data-driven decision-making:

• First, AI and analytics initiatives need exponential initial investment but with returns in the long term. This is the primary reason enterprises hold back or postpone such initiatives. 
• Second, AI or analytics is only as good as the data that you feed it. Unfortunately, many firms believe they are not in good shape in terms of data quality to allow a machine to generate valuable insights or recommendations.
• Third, AI is a black box, i.e., unlike traditional stats, there aren't equations that a human can comprehend to understand why an AI output or recommendation changed from what it was the last time. This leads to a perception of loss of control and increased risk in following insights or recommendations generated through AI. 
• Lastly, 85% of AI projects have stayed at the POC stages, as per a report by a leading consulting firm. This would make the typical Indian firm feel afraid of investing in AI. This is not true for most AI projects done by large technology companies since they do get productized, but this low percentage has become well known. They would rather wait for proven products than buy such products. For example, there are Indian banks whose chatbots on their websites do use AI and customer past data, etc., to interact with the user. 

How is Infosys playing its part in removing these bottlenecks for companies in India?  

Infosys works with both government departments as well as Indian corporates as clients. The work ranges from data and analytics to AI to identify patterns in large data and make decisions from that. We have convinced clients through results that AI can pay for itself and more, thus leading clients to trust it further and make further investments. However, we can do that only with clients who take the first leap of investment in data-driven decision initiatives. After that, we create roadmaps that target low-hanging fruits to deliver and demonstrate benefits and go after the long-term exponential returns. It's a journey, and the bottlenecks get eased out as we proceed since we have done it globally for many years.  

We are accelerating our innovations and bringing in the best of the ecosystems like hyperscalers, data partners, startups, and our data and AI solution assets to launch Industry Intelligent Clouds powered by data and AI. We have already launched a couple of such in life science, CPG and retail.

Data-driven enterprises are expected to reap their true potential. Can you share with us three solid reasons behind this?

Firstly, data is the foundation for enterprises to accelerate their growth, amplify their value and realise the true potential of their digital investments. Leaders who helped their organisations reap their true potential have always relied on data-driven decisions. Since business decisions are a balance of risk and reward, data reduces the unknown and hence, reduces the risk. Companies that do this consistently will reap higher or safer rewards.   

Secondly, the first wave of digital transformation is more toward moving the utility of business-like commerce and customer service into digital space. The second wave will be of open commerce and banking and is going to be how we unlock the actual value by orchestrating the business ecosystem that comprises their suppliers, partners, customers, and competitors with data. Again, the marketplaces that we see evolving here are great examples. In India, for example, what UPI laid, is the foundation for transforming the utility of payment.  

Thirdly, the future of business will be data if the business needs to stay relevant. For example, Metaverse, Web 3.0, etc., will drive an experience-driven economy for which understanding one's behaviour is key. Data and AI are the fulcrum of such an economy. For example, you can look at how Nike is relooking at their experience by bringing NikeiD (now called "Nike by You"), which lets the customers personalise their shoes with Nike's co-creation service, helping them further understand customer behaviour. In India, we see a similar experience-driven economy that will be powered through marketplaces. As more companies invest in this, those that don't will effectively be flying blind. 

With such a long experience in this domain, can you share the data and analytics trend in 2022 and beyond?  

The macro trend that has been going on is that of moving from enterprise data to a data ecosystem with immediate partners to a data economy where data is available from a myriad of sources and through marketplaces and consolidators. Similarly, AI is moving from input-output systems that generate recommendations to systems of automation that automate specific tasks and to systems that conduct business themselves.

Similarly, we have seen a trend of higher adoption of industry platforms. For example, a healthcare platform with pre-built models typically used in healthcare has proven very useful for healthcare industry firms, rather than each firm having to build its models and workflows, etc.  

We also expect 5G and edge computing to catalyse AI-driven business transactions and operations in consumer industries, banking and investment, telecom and entertainment, manufacturing, mining, and oil field services. 

Sustainability (ESG) is another area that is seeing increasing investment, and this will likely become one of the fastest growing investment areas very soon. For example, AI and analytics can help optimise routes not only for cost but for carbon footprint, some retailers are collaborating to leverage load optimisation to utilise container space better on long-distance shipments, and AI can orient solar panels to the best angle, not reactively but proactive; we have even helped adjust wind-based power generator's blades as per the wind direction for one of our clients.