Growing AI adoption in India, but still some way to go: Romal Shetty, Deloitte India

Source: Economic Times, Apr 01, 2021

While financial services, Hi Tech, telecom, oil and gas, FMCG verticals in India are ahead of the curve in AI adoption, there is huge potential to be tapped in large parts of transport/logistics, retail, education, government, said Romal Shetty, President Consulting, Deloitte India in an interview regarding Deloitte- CII’s recent report titled ‘The Age of with: Humans and Machines’. Edited excerpts:

Are you witnessing trends in AI adoption across certain industries more so than others? If so, what are the key industries where you see major AI adoption?
India is a major developer of AI solutions, and has seen its analytics industry move from dashboards and data warehouses, to advanced industrial and services applications of AI. Across industries, companies are trying to reap the benefits of AI. While financial services, Hi Tech, telecom, oil and gas, FMCG verticals in in India are ahead of the curve in AI adoption, there is huge potential to be tapped in large parts of transport/logistics, retail, education, government, etc.

To democratize AI usage, the Indian Government’s policy think tank, NITI Aayog has been actively working on the #AIforAll program. As part of the Digital India initiative, the Government also intends to leverage AI in healthcare, agriculture and e-governance. Today, solutions are being developed from India for both the domestic and global market.

How have Indian organizations fared in terms of AI adoption when compared to other nations?Indian companies both big and small (Indian MNCs and family-run businesses) have responded at speed to the opportunities that have been thrown up in the past year due to the pandemic disruption – specifically more so in customer facing and manufacturing areas, but also in virtualization of various parts of the enterprise, given the new normal of work, workplace and workforce.

AI has come to be used in the customer facing (sales and marketing, customer experience), operations (supply chain, logistics, manufacturing) as well as support (HR, IT, finance) functions. While a lot of companies have initiated on this journey, there is still some way to go before all of these would be used at scale enterprise wide.

As far as AI is concerned, while India is still behind developed countries, we are seeing a drive towards this direction – India-centric innovation (for India from India). This has increased significantly as lift-and-shift models haven’t really worked given Indian realities.

What type of governance and policy problems occur with increasing AI adoption? Furthermore, could you elaborate on Deloitte’s framework to tackle this?
Despite wide adoption, organizations count ethical risks as one of their top challenges in implementing AI initiatives. Concerns include lack of explainability and transparency in AI-derived decisions, using AI to manipulate people’s thinking and behavior. A well-established governance and ethical model guides organizations to adopt AI more efficiently.

Deloitte’s Trustworthy AI framework is an effective tool in diagnosing the ethical health of AI while maintaining customer privacy and abiding by relevant policies. The key features of the framework put an emphasis on privacy, on AI being fair and impartial, transparent and explainable, the organisational policies being responsible and accountable, keeping systems and stakeholders safe and secure, and AI-driven output being robust and reliable.

Historically, have investors and stakeholders responded positively to companies adopting AI?Companies that are adopting AI are forward looking and ready for change. This has typically been appreciated by investors, all else being equal. For example, we were working with an EPC company which is looking to use AI-driven forecasts in order to look at bid values and walk-away prices for infrastructure bids. Strategic, as well as institutional/retail investors, have looked upon this company with a lens that they will be on another level compared to their peers in delivering shareholder value.

The PE/VC community already has a clear view that AI-driven solutions are valued better, in fact there is a joke that any company AI-driven will necessarily be funded.

Having said that, the story is not the same with all stakeholders. Some  employees have been a bit apprehensive of being shown that machines can potentially do a better job than them, especially in areas where there are long years of experience. It is a potential classical “Deep Blue beats Garry Kasparov” moment, where machines pitted against humans can show better results in many fields (for example, even cancer detection from visual inspection apparently can be done better by AI algorithms than expert doctors).  Also, in many countries, regulators and governments have sought to regulate the usage of AI – whether it is purely AI-driven decision making, for instance for credit card approvals (which may bring in biases), autonomous cars, conversation-AI enabled digital voice assistants answering first line calls at call centres, etc, which can risk bringing up various socio-legal issues as well as create an unfair playing field. Overall, the march of AI like any other technology will have supporters and detractors. However, the technology itself is a revolutionary one, and mankind has to figure out the right ways to use it in a meaningful and positive fashion to improve the lives of citizens and consumers.

Lastly, how can the fear of AI replacing human jobs be remedied? As we call it the “Age of With” where humans and machines together bring disproportionate value, not one or the other. Human creativity, judgement and intelligence is as vital a component as machine intelligence, and therefore we will have both co-exist.  We at Deloitte, looking at Technology Trends, observe three stages towards achieving full utilization of AI. First being assisted intelligence – e.g. a car warning a driver when they change lanes. Second, augmented intelligence – e.g. a car warning a driver when they change lanes and if they do not act in time, it takes the decision on the driver’s behalf. Last, autonomous intelligence – e.g. a car driving itself from source to destination point. While autonomous intelligence forms the holy grail that everyone would want to get to, we believe that most of the AI that assists in decision support on core business issues would fall in the first or second category. That is where AI will not replace humans, but assist and augment the intelligence of humans. It will be humans who will make the decisions based on their judgements.

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