AI & Digital Transformation

AI presents many of the same issues and challenges as a Digital Transformation initiative. They are both needed, however there is one big difference between the two; Digital transformation leads to efficiency by improving the efficiencies in business processes whereas AI is driven by improving the overall business outcome. Some of the changes that AI will introduce and impact business policies relate to:

#1. Customer trust: AI systems will mimic a human worker, so your customers should know if they are interacting with a software or a human. Chatbots are a prime example of it. They are far more efficient and effective in presenting to the customer with choices or alternatives that would meet their contextual need as compared to human agents.

#2. AI systems require nurturing: AI systems improve with usage. You should have processes in-place to make training data available to it at all times. Many AI initiatives fail to yield results because employees perceive them as threats to their jobs and therefore show little to no tolerance for wrong predictions in its initial phase. DevOps is another challenge because most algorithms run over cleansed data and the systems are not geared towards taking the extra workload of cleansing the raw data for a new system.

#3. Brace for automation. One of the key objectives of AI systems is to automate few business processes. Organization’s decision-making is invariably top-down whereas the acceptance of change is driven by employee whose job might be at stake. Hence the feedback that bubbles up are less than praise-worthy about AI systems. Decision-makers expect significant improvement in performance of current process or product because of AI. Whereas the reality is that for AI to become a differentiator people and software have to learn to build off each other’s strengths. That requires shift in culture and organizational structure.