What is in store for enterprises going through the Intelligent Automation journey?

Enterprises are finding themselves in an "Ubiquitech" moment, as technology disruption has been rocking their industry from time to time. Intelligent automation (IA) is the latest addition to the list. It is the fastest growing technology with the greatest power for disruption. Faced with enormous IA opportunities, what is in store for enterprises going through the IA journey?

Customer service will be redefined with Robotics led self-service (via mobile, web, IVR, speech recognition) and BOTs will fulfil requests with no human intervention. From traditional RPA to IA, there will be a progression as the BOTs' functionalities will become more sophisticated and intelligent and applications more specialized and niche.

Cognitive solutions (prescriptive analytics and machine learning based process execution) will start aiding mid office and back office executives to make judgement which were hitherto left to humans to think and apply. Enterprises will not only be able to run back office core functions (IT, finance, HR) at half the cost and double the throughput, but also mid office functions encompassing industry-specific processes such as claims processing in insurance; logistics in retail, trade settlement in banking.

Interaction with machines through Voice instructions is set to enter industrial and corporate interactions. NLP and NLG algorithms will continue to learn and will take steps towards understanding humans instructions. Eventually these interactions will have to reach human-level precision to make the assumptions and apply implicit knowledge ? in just the same way as humans do.

Artificial Intelligence (AI) will move from theory to practice and will enable improved data models; newer insights and autonomous organizations. AI will effectively apply the same recommendation engines or speech and image recognition algorithms that we are used to in our personal, online engagements, to the corporate environment. Its impact will be felt across the enterprise in HR, marketing, risk, finance, regulation, etc.

Each industry will identify its narrow AI domain and integrate it in a compelling use-case. As the number of AI applications under development and deployments grow, AI will get definitive boundary for each function and sector. Enterprises will be able to build narrow AI applications more independently and quickly by accessing a set of packaged foundational AI services which may include industry-specific, pre-curated data; analytics service and an AI engine.

Already 67% of CEOs believe technology, not people, is the key to survival. [1] The onus will be on the future leaders ? to balance digital and human workforce and reskill/ reorient existing workforce to embrace the opportunity.

Services industry - IT, Banking, Telecom, Travel and other - will redefine work for their teams, human and machine interaction will be new design mantra. New services will emerge to synchronise, sequence and monitor processes to provide last mile integration between humans and machines.

Progressive companies will join global race to advance ahead of the others in AI R&D ? through massive investments in patents and intellectual property (IP). While technology behemoths seem to have established themselves as presumptive winners, the next wave of AI titans will be made up of established companies in more "traditional" industries ? that figure out how to innovate by leveraging their proprietary industry knowledge with the power of AI.

Underpinned by high processing power and availability of diverse data sets, Deep Learning will be used to create bespoke products and services ? capable of accommodating different client engagement flows and tailoring the customer experience.

Convergence of block chain and cognitive will take place for several sectors such as Financial Services, Utilities and Industrial manufacturing. There is huge potential for developing Cognitive applications using blockchain and this combination can solve some of the key problems that limit Cognitive adoption, such as scalability. Data can be analyzed and fed into blockchain smart contracts for running rules and complete transactions that can be validated by all the participating peers.

There will emerge a strong need to steer regulations for AI across key legal aspects to clarify accountability and to establish an ability to challenge algorithmic decisions via an ombudsman. Enterprises of the future will be run by complex layers of algorithms that reach across enterprise operations. This makes enterprises vulnerable to a new type of risk, because resulting dependencies (based on interactions between algorithms) and mistakes can grow exponentially out of control.

The author is Lead - Intelligent Automation, Ernst and Young.