Behind the Wheel of an AI-Driven Enterprise

The next wave of technological disruption is here, and it is called Artificial Intelligence (AI). Whether or not AI has yet gone mainstream remains a matter of debate. But the potentially transformative technology is increasingly being discussed in boardroom meetings worldwide. And, it is fairly evident that the vision of an AI-driven enterprise is far too compelling for chief executives to let go and simply adopt a wait-and-watch attitude.

From bots that are proving to be capable of servicing customer queries effectively to automated back-office processes that completely eliminate the need for manual intervention, AI is slowly transforming enterprises inside and out. Projected to deliver transformative business value, AI could very well become the most disruptive of all promising technologies in recent times. It could also usher in unprecedented growth opportunities for early adopters who are willing to venture into the hitherto unknown. However, in spite of all the excitement surrounding its many emerging and envisioned applications, most organizations remain clueless about how to deploy AI and become an AI-driven enterprise.

While consumer applications such as self-driving cars and digital personal assistants attract all the press, enterprise AI continues to be pushed under the carpet. One possible reason for this could be the complexity associated with data. Most organizations are still in the process of discovering the value of their data as digitalization efforts gather steam. With data being the core of AI, organizations will definitely need to switch gears to better manage data before they embrace AI to its full potential. Once that is accomplished, using machine learning, data can be converted into insights that the AI engines will use to drive intelligent automation comparable to human actions. This attribute, along with various other elements of AI including cognitive computing, natural language processing and advanced analytics, can then become the principal lever for an organization looking to use AI to take a quantum leap in their operations.

Consequently, the first step enterprises must take to become AI-driven, is to uncover and unlock the value of their data. This exercise should include both capturing the right data as well as transforming it. From a state where it is primarily designed for human use – perhaps with gaps or inaccuracies that humans can easily deal with – data should be transformed to a state where it can be interpreted by machines effectively. Hence, there is a pressing need for establishing robust data management practices, a capable data management infrastructure, and most importantly, a high level of data governance. Ensuring this will pave the way for organizations to cash in on the AI momentum by either deploying specific products or using “Intelligence as a service". They will then be able to replace time-consuming and error-prone human work with AI-powered superior intelligent automation. And that will be an unlimited canvas on which numerous other use cases of AI-driven enterprise services can be further drawn.

The enterprise AI adoption journey is marked by many milestones. The first critical milestone is to capture, process and turn voluminous amounts of data into business insights with ease. Next up will be the automation of most routine processes, backed by intelligent systems that can handle exceptions as they arise. The third significant milestone will be automated processes continuously focusing on self-learning to adapt to changing business environments. Finally, AI-driven business efficiency should become the foundation of all enterprise decisions and actions.

Contrary to popular belief though, the humans in an AI-driven enterprise become much more valuable as they start focusing on creativity and strategy to run the business, rather than worry about performing mundane tasks. But organizations would be wise to remember that deploying AI itself is not the end goal, it is the benefits that it can deliver to the business that hold the key.

Tags: Analytics

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