Artificial intelligence (AI) powers computers and machines to simulate the problem-solving capabilities of the human mind. Machine learning (ML), on the other hand, is to program computers using statistical models and algorithms to automate tasks. It is part of AI.
We have a lot of data to make use of. AI helps in utilising these data to identify patterns and do a predictive analysis of the situation. This saves time and helps change professionals take corrective measures in advance. AI helps automating or simplifying repetitive tasks like collating and analysing a data set.
The next disruption is expected from a perfect marriage between AI and OCM to drive the people-side of change.
Given the current situation of virtual presence, AI helps to drive change in an agile approach. AI comes to rescue not only in solutioning but also in the day-to-day change engagements. The data collected can be used to analyse the change impact in advance, understand the magnitude of change resistance and resistance parameters to foresee which changes are most likely to fail. To give a medical analogy, it is better to prevent a cardiac arrest by managing a patient’s blood pressure with medication than saving him after he gets a stroke. Change professionals will get to leverage the benefits of predictive data for solution design rather than relying on historical data.
In one of the projects I executed two years back we implemented the Human Resource Information System (HRIS). Something that we did new in HRIS was to introduce an AI powered chatbot to eliminate the existence of a HR helpline/helpdesk. The chatbot was programmed to handle FAQs related to leaves, insurance, and other policies. This helped get a quick resolution cycle.
Personally speaking, I would love to get an AI solution tailored to monitor minutes of the meeting, sending reminders on action items, manage emails and documents so that a great share of manual repetitive work – like coordination, reminders, maintaining risk register, tab on time etc. is taken care of.
