Why is AI Crucial for IT Channels?

While India is a bit late to the AI party, experts opine that AI holds the potential to truly transform our lives as individuals and enterprises; however, its growth and adoption are dependent on overcoming challenges like securing right talent and data, and unambiguous policies and guidelines. Read on while we analyze where we stand today in terms of readiness of the ecosystem and overall adoption of AI in India, and why it is crucial for IT channels

By Amit Singh

India has been ranked on the third spot after the US and China in terms of artificial intelligence (AI) implementation, according to a BCG study.

AI is billed as the hottest start-up sector in India with a renewed VC interest and lots of innovation across sectors, especially finance and healthcare. But is the adoption of AI in India as rapid as its western and Asian counterparts?

Large claims

Analysts are staking large claims on the AI market and its effects on the economies including India. According to a recent Accenture analysis, AI has the potential to add $957 billion, or 15 percent of current gross value add (a close approximation of GDP), to India’s economy in 2035 compared with a scenario without AI. The company expects AI to augment labor productivity and innovation while driving growth in at least three important ways: mobilize intelligent automation, empower existing workforces, and drive innovations.

As per IDC, worldwide spending on cognitive and AI systems will reach $19.1 billion in 2018, an increase of more than 54 percent from 2017. The analyst firm expects that every industry and organization would be evaluating AI to see how it will affect their business processes and go-to-market efficiencies.

While the analyst firms are quite audacious on the global AI market, they haven’t yet sized the India AI space.

Is AI more of a buzz-word?

Many experts feel that India has just started experimenting with the technology and unlike other major economies India hasn’t yet spelled out its vision for a future with AI.

So far, only chatbots (conversational AI) have seen good adoption in India in segments like BFSI, retail, travel, e-commerce, and healthcare. Chatbots are becoming quite popular as a virtual agent with a lot of interest among the businesses.

“AI-driven automation and virtual assistants are gradually becoming domain agnostic in its relevance, utility, and implementation. From business solutions to social service and government initiatives chatbots are everywhere,” states Kartik Poddar, Business Head, Haptik Infotech.

“When customers communicate in a natural, conversational way they reveal more about their preferences, opinions, and inclinations. In India, we see a quicker maturity in the chatbot applications,” adds Ravi Shankar, Co-Founder & CEO, Active.Ai.

However, few experts seem to differ and term most of the chatbot adoption as a rub-off effect. “Customers have seen and heard about it and are just willing to adopt the same without getting into the business case and viability of the deployment. In many cases, there is little clarity towards the reasoning behind implementing a chatbot solution,” explains Arup Roy, Vice President, Research, Gartner.

Further, AI applications like machine learning (ML), computer vision and recommendation technologies are yet to see large scale adoption and most of it is in the pilot phase.

ML is quite a new area from the maturity perspective and there is a lot of hype; it’s still early days for ML in India. There are very specific use cases where it is maturing and the real implementation is far and few, highlights Roy.

He adds that the specific use cases where ML is gaining maturity are fraud detection for customer churn and decision making in banks, telecom, and insurance organizations; predictive maintenance in machinery set up; credit risk analysis for loan organizations; dynamic pricing; and anomaly/tumor detection in healthcare.

At the same time, many of the experts are quite optimistic and expect ML, natural language processing (NLP) and recommendation technologies to quickly catch up within 2-3 years.

“In sectors like BFSI and telecom, AI has seen adoption among 20-30 percent of the customers in some form or other. While chatbots are being fairly used, we have seen customized use-cases on applications like fraud detection, cash requirement prediction for ATMs, mobile network optimization, brand loyalty, predictive maintenance, and marketing campaigns,” contends Anand Haridass, Chief Engineer, Cognitive Systems, IBM.

Challenges manifold

India is facing a multitude of challenges when it comes to the adoption of the technology. “In India, many of the senior executives want to use AI in their businesses but do not know where to use and how. Also, the biggest challenge is of experimenting without investment. They fear to invest in building something new,” shares Layak Singh, Founder & CEO, Artivatic Data Labs.

One of the major challenges in India is to collect, validate and access AI-relevant data without compromising privacy and ethics. Data is the bedrock of AI and reliability of AI systems depends primarily on quality and quantity of the data. “For AI to work, having a vast amount of structured clean data is critical. Any AI system is as good as the data provided to it. This poses a great challenge as we still don’t have a well-organized way of stacking, storing, and using the data,” states Roy of Gartner.

Another major challenge corresponds to integration complexity and lack of skills. For most of the businesses, the challenge is to find the right partner with appropriate skills in AI solution design and implementation. “Currently, there is a scarcity of skilled resources and AI experts. Hence, we initiated our Power AI University program last year where we are offering hands-on dedicated industry training to the graduates. We have already tied-up with four large universities in India,” reveals Viswanath Ramaswamy, Director, Systems, IBM India/ South Asia.

Further, Poddar of Haptic highlights that increased competition, lack of concern for regulations, and over-dependence of businesses on chatbots might become future challenges.  “With increasing competition, chatbot developers, in a bid to keep the revenue flowing, might decide to ignore the data protection and utilization regulations and follow unethical practices.”

Hence, the stakeholders expect the government to step in with clear policies and guidelines.

Government is yet to deliver

Although India is a bit late to the AI party, many say that the energy and enthusiasm of the Indian government are at its peak. Right after allocating $480 million to the development of 5th generation technologies like AI, ML, Internet of Things (IoT), 3D printing and blockchain, the government has now geared up to formulate guidelines and policies for the AI utilization in the various industries.

As a first step towards streamlining the AI utilization in the country, the task force constituted by Ministry of Commerce and Industry, Government of India has recently released its report on the adoption of AI in India. The report has suggested building an AI policy with a five-year mission and a targeted investment corpus of $184 million spread across the different initiatives under various government departments.

In addition, a recent NITI Aayog report proposes an umbrella organization to shape and implement India’s AI policies—from stitching global partnerships to picking specialized teams to pursue audacious moonshot projects. It identifies a two-tiered institutional structure — government-led Centre of Research Excellence (CORE) to focus on core research, and private sector-led International Centers of Transformational AI (ICTAI) to focus on application-based AI research. The focus will be on five key sectors— healthcare, agriculture, education, smart cities & infrastructure, and smart mobility & transportation.

To build data ecosystems, the report proposes a National AI Marketplace (NAIM) that will collect and annotate data and evolve deployable models. To tackle AI talent shortage, it suggests a slew of initiatives like re-skilling workforce, modular certification courses and thrust on research with Ph.D. fellowships.

However, it’s better said than done. It looks awesome on paper, but the real challenge is to frame unambiguous policies and guidelines. Looking at the past, the government’s track record has not been so impressive.

“So far, India has suffered from either lack of policy or lack of clarity in the policies. We expect the government to lay down clear guidelines and framework in terms of data, data usage, data security, handling of bias and incentivizing on the usage and adoption of AI. That’s quite a crucial part for the success of AI in India,” emphasizes Roy of Gartner.

AI has only now begun to crop in policy conversations. If India wants to participate in the AI revolution, then it needs a policy that brings together Indian academicians, researchers, labs, private players and investors on the same platform. And if it wants to counter the rise of China and its neighbors in AI, India needs to significantly ramp up its infrastructure as well.

Party has begun for AI start-ups

Large technology vendors and tech giants are investing heavily in the AI opportunity. Vendors like NVIDIA, Microsoft, and Google have set up labs in India for advanced AI-linked work. IT industry body Nasscom is setting up Centre of Excellence (COE) in AI with companies like IBM, Microsoft, NVIDIA, Intel, and AWS. In addition, large enterprises such as Bharti Airtel and Reliance Jio are setting up AI labs and Indian IT services giants like Infosys and Wipro are belatedly investing in the space.

However, it is the AI start-ups which are grabbing most of the limelight. The Indian start-ups are leading several breakthroughs in the field, thanks in part due to high VC interest.

There is no doubt that the amount being invested in India has grown exponentially and a lot of start-ups have spawned on the back of these investments. Ratan Tata backed Niki.ai, Staqu, Braina, Morph.ai, Formcept, Haptik.ai are just a few that were set up in the recent years.

In addition, Niki.ai, launched in 2015 received funding from Unilazer; SigTuple, launched in July 2015, received seed funding from Flipkart founders Sachin Bansal and Binny Bansal; and vPhrase Analytics raised an undisclosed amount from Venture Catalysts.

By some estimates, there are 300-plus start-ups in India developing or deploying AI-related technologies.

Moreover, many of the technology giants are acquiring start-ups to strengthen their AI offerings. Companies like Amazon, Google, Microsoft, and Uber have done a slew of acquisitions of AI start-ups over the last few years. On the other hand, almost all of the technology vendors are partnering with start-ups to leverage their deep AI skills and niche solutions for specific segments.

“We are identifying a distinct ecosystem of AI solution providers, which have deep skills in processes and algorithm development for specific segments. We are complementing them with our best-of-the-class Power AI systems to reduce the time required to train the machine,” elaborates Ramaswamy of IBM.

In fact, technology giants’ collaboration with start-ups is proving to be a successful strategy for universalization of AI in India. For instance, Bengaluru-based Niki.ai, with its chatbot solution, is working with several organizations like Paytm, Ola, and Uber.

In addition, Uncanny Vision, Active.ai, Arya.ai, Boxx.ai, Cuddle.ai, Embibe, Edge Networks, Haptik, Zenatix, Tricog are few of the start-ups adding value to various segments in India.

Why is AI crucial for IT channels?

As per IDC, 40 percent of digital transformation initiatives are expected to use AI by 2019. From predictions, recommendations, and advice to automated customer service agents and intelligent process automation, AI will change the face of how we interact with computer systems. This is the reason why system integrators and solution providers need to reinvent themselves as AI experts and address the need of the new technology buyer — the LOB.

However, the IT system integrators and solution providers seem to have missed the bus so far. “The traditional IT partners are yet to skill themselves on AI frameworks, understanding of processes, and the algorithms. A major challenge for them is to amend the algorithms to better train the hardware for optimum results. Hence most of the traditional IT partners have a long way to go in the AI space,” highlights Ramaswamy of IBM.

He, however, adds that it’s not the end of the story for IT channel. They must approach the AI start-ups to jointly build and offer the AI solutions to their customers. Since the new generation of AI partners is not skilled enough in hardware; system integrators can complement them with their core hardware and solution designing skills.

Further, IT channel can simultaneously develop their skills in AI. “AI platforms have hundreds of prebuilt models that do the heavy lifting, essentially automating machine learning. Hence, for channel partners, it is about prepping the data, and making sure they understand the business needs rather than diving deep into data science,” explains Tanuj Vohra, Senior Vice President and Head, India Technology Center, CA Technologies.

Road ahead

Many of the Indian start-ups have indicated that Indian B2B customers are not mature enough in comparison to their western counterparts. This has forced many early-stage technology companies to scout for their target market outside India. However, as the Indian enterprises have shown readiness to adopt AI solutions, the scenario is expected to take a 180-degree turn.

With over 36 percent of large financial establishments investing in AI-driven technologies and 70 percent planning to embrace it, India is well poised for an AI-led economic transformation, according to a recent PwC India and Assocham report.

Experts opine that AI holds the potential to truly transform our lives as individuals and enterprises; however, its growth and adoption are wholly dependent on overcoming challenges related to reducing costs, securing the right talent and data, and addressing the data crunch.

With the Indian government’s recent push towards the adoption of AI, certainly, the sector will get heated up further. But unless the suggested guidelines are implemented and executed with the proper measure, the road will stay long for the Indian AI market.

Many of the experts believe that it will take another 3-5 years for enterprises and SMBs to mainstream AI in the business processes. But for that, government impetus in the form of funding, research, and infrastructure is crucial.