Making Industrial Revolutions Routine

Praful Krishna
3 min readJul 10, 2020

Intelligent Process Automation is only one among transformative technologies that are going to make previous industrial revolutions routine.

Over the last few centuries, the steam engine has shaped geopolitics and laid the foundation for modern societies. Electricity has driven accelerated innovation in every aspect of human life for over 100 years. The transistor — cornerstone of electronics, internet, and social media — is part of every definition of modern existence within decades. The third industrial revolution has also enabled people to merge their dreams, thoughts, and endeavors in a single, ephemeral collective.

Now we are int the midst of another wave of transformations that has the promise to dwarf the impact of first three. The fourth industrial revolution is the anticipated change in human behavior, human capability and human potential driven by artificial intelligence. It has the promise that humans can focus on tasks involving creativity or judgment, while technology will take care of everything mundane.

As with any revolution, it has already been lurking unnoticed in small changes. These steps are now aggregating to a powerful reality; good reality or bad is yet to be determined. Today’s Echos, Teslas and Pandoras are already prominent in homes. Many other household names use AI to power them behind the scenes. As powerful as AI seems in our homes, enterprises it has impacted enterprises even more. Let’s take an aspect of this — AI-led intelligence process automation.

Consider something mundane, like generating a purchase order. For any organization with multiple BUs and multiple locations, usually there are multiple contracts with multiple vendors for each item. In most cases these contracts are not centrally collated; almost always they are not digitized. So the purchase manager does anecdotal research for a few hours and pulls up contracts that they can remember or serendipitously find. Then they convert the requisition to an ad hoc work order. They may also call the vendor to confirm some aspects, or to ensure that their contract is still valid. Finally an inefficient purchase order goes out.

That is the past. Now, artificial intelligence can ingest all the contracts seamlessly. For any requisition, the system can figure out the best option among these contracts, then compare with publicly available options and place the right order. The executive now saves their time and finds the best possible answer. This is something very unglamorous, simple, yet so full of potential.

Now consider something more fundamental. Enterprises the world over have capable executives make decisions about routine issues everyday. These decisions are issued, reported, and filed, and then lost forever. A similar issue elsewhere, or at a different time, has to be dealt starting afresh. With cognitive computing, on the other hand, AI keeps track of everything and makes the entire history available on fingertips, likely behind a natural language search interface. Using AI the unparalleled experiences of the organization — its institutional memory — comes to life.

Each of these is an example of small improvements in productivity. As more and more such workflows are taken over by AI, it is easy to imagine an operation where humans are focused on improving its performance, and not running it. Then it is not hard to imagine the leaps in innovation, quality, invention or creativity this organization is likely to make.

--

--