“How Do I Start With AI?”: Answering the Multi-Billion Dollar Question
About a year ago, I was convinced that the key to succeeding with Artificial Intelligence (AI) was to take a platform approach. In other words, the synergies that accrue from appropriately bringing together the range of technologies that are making AI a reality for enterprises was, I believed, the way to go. I still firmly believe that.
In fact, having personally met over 200 executives (business and technology) since then, from around the world, who seek to find relief and new value from AI, I am convinced that opting for best of breed capabilities from a variety of vendors is not necessarily going to work out in practice. For one, despite claims of using only open standards in building these offerings, deploying the offerings from a variety of vendors in an integrated manner is a challenge. Further, the business and operational challenges that naturally occur in such situations with multiple providers are deterrents too.
In my conversations with the aforementioned executives, it also became abundantly clear that adoption of AI, while desirable for many, is still a daunting proposition for a great number of them. This made it clear to me that something beyond a mere platform approach is needed. After all, no one wakes up in the morning going, “Today, I must go get myself an AI platform.”
Path to AI, a recent survey conducted by Infosys, reveals that while many recognize the gains that AI can bring to their industry and, by extension, to their company, only about 20% have created a strategy to take their organization from point A (automation) to point B (AI adoption). This is despite decision-makers (CEOs, heads of innovation hubs/centers of excellence, CTO/CIOs, operations heads, and IT personnel) recognizing the fact that even at the outset, AI can bring improvements. The research shows that only 18% have a complete AI strategy to manage their transition from intelligent automation to AI. A staggering 55% state that they still don’t have a strategy in place despite planning to make the shift.
Perhaps instead of approaching AI as an organization-wide solution, they ought to have the option of starting their journey with a manageable chunk of effort that brings quick success. What experience has taught us is that when attempting to introduce new technology it is often better to do it in small chunks with a greater likelihood of success.
One approach could be to start with robotic process automation (RPA) and realizing the benefits that come with it, and subsequently making the transition to more cognitive automation that leverages AI capabilities more directly and deeply. Perhaps, yet another approach could be to use bite-sized non-disruptive applications that solve unique pain points by leveraging AI capabilities. Let us consider each one.
Let us take, for instance, a large telecom group managing multiple companies in mobile, IP TV, broadband etc. faced with challenges related to customer service. In this situation, it is required of their agents to coordinate effectively with field technicians, such that issues can be resolved in real time. Using an automation platform, they can integrate various applications and data across companies enabling agents to access the right expertise to address customer concerns in real time. Such a solution can deliver a significant increase in customer service with a dramatic reduction in query handling time, thus resulting in substantial cost savings.
Having started this, the organization will have gained the ability to manage its vast treasure trove of data in a disciplined manner and learn the discipline of working with data for greater process efficiency.
