Arvind Thakur, Vice Chairman and Managing Director, NIIT Technologies Ltd.

The IT services industry has long been labor-based, priced on time and material. Over the years, service providers have built or used commercially available tools and preconfigured solutions to automate service delivery, especially high-volume routine tasks like data migration and testing. Current trends encompass automation across more tasks. The advent of artificial intelligence (AI) has enabled the automation of higher order knowledge work, reducing labor inputs significantly, and taking efficiency gains to the next level. Automation with AI or Intelligent Automation is fundamentally changing how businesses operate across all sectors, extending the power of IT to tasks traditionally performed by humans.

Large-scale intelligent automation threatens the labor arbitrage model which has been the mainstay of our industry, forcing service providers to change their business model from being labor-centric to providing technology arbitrage, thereby also decoupling labor hours from pricing. Outsourcing contracts reconfigured with intelligent automation are 20–30 percent more cost-effective than traditional labor-based contracts. Gartner proposes that through 2021, the majority of service providers will use intelligent automation service techniques, thus lowering cost of commodity services by 15–25 percent annually. Application of automation with AI essentially falls into three main categories.

Product applications. These embed AI technology in a product or service to provide end-customer benefits. They transform customer experiences by largely focusing on helping customers ideate to serve customers. Use of bots, virtual agents, or conversational AI platforms obviates the need for the user to be tech savvy to perform business transactions.

Process applications embed the technology in an organization’s workflow to improve operations. General AI platforms now available are able to perform human functions of learning, understanding, and solving. These platforms leverage real life experts for learning, and their knowledge is converted to knowledge items. Environmental understanding and knowledge items are linked through semantic maps to cover enterprise data/services, which respond to a dynamically changing environment, whereby they deduce and induce response to known and unknown problems. This is particularly useful in managing computing and network infrastructure.

Insight applications. These applications help differentiate product offerings and largely depend on access to rich data sets. It gives companies the opportunity to offer customers personalized service.

Advancements in AI have been inspired by biological nervous systems or neural networks which essentially perform tasks like clustering, classification, and pattern recognition. Deep learning is a method of machine learning based on learning data representations accomplished through application of algorithms to large amount of data using powerful processing capability. Machine learning works best with data science since the process involves learning from data over time. Data science allows AI to find appropriate and meaningful information from large pools of data faster and more efficiently. Self-driving cars for example gather data from their surroundings in real time and processes the information to make intelligent decisions on the road.

Every 10 years since the popularity of the PC in mid-eighties we have seen the industry being disrupted with new technologies. Each successive decade saw the revolutionary impact of new disruptive technologies, like the internet in 1995, introduction of mobile phones in 2005, and these have created new opportunities for the services industry. Cognitive systems which encompass machine learning, natural language processing, object recognition have been around for a while, but it is only in the last few years with the convergence of several technological developments, specifically affordable cloud computing, availability of large datasets, and leaps in algorithm optimization, that AI has come into the mainstream of computing. Intelligent automation encompassing a variety of strategies, skills, tools, and techniques in conjunction with AI is seen as the next big disruption for the industry. This is now being embraced by IT service providers as the new opportunity, to deliver enhanced value with a superior experience.

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