‘AI algorithms are helping to automate automation itself’
PremiumThe goal isn’t to make it (bot) the same as a human, but to make sure it can take 80% of the things that humans handle, says Mihir Shukla, co-founder, Automation Anywhere.
NEW DELHI : A combination of accelerated covid-induced digital transformation and scarcity of tech talent is leading companies to improve their operating models using intelligent automation.
In an interview, Mihir Shukla, chief executive and co-founder of California-based enterprise automation firm, Automation Anywhere, which is also planning a public listing, said AI algorithms are not only able to automate mundane tasks, but also to predict and suggest the processes that should be automated. Edited excerpts:
How does automation help fill the industry’s talent shortage?`
There’s a large group of people that is doing (both) mundane and high value work. By automating the mundane work, you can increase the capacity to do, say, customer facing work.
Utilizing our people like human beings instead of robots and allowing them to add value at a higher level is changing the equation for many large Indian enterprises. Some of these are among the largest enterprises that India has.
What happens to the talent doing the mundane work if it’s automated? Are they ready for other tasks?
Absolutely. I have seen this not just in India but across the world. It wasn’t the people that was the problem. People were amazing everywhere and it is us who didn’t leverage the capability they have to offer.We needed certain work to get done and we employed people to do it.
Across every Indian enterprise and GIC (global in-house centre) that I have visited, we have repeatedly said that when you deploy automation, people will be able to take on more meaningful work.
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Why is there a sudden talent gap? Is this only because of added digital transformation?
My view is that the world has changed very meaningfully in the last 10 years. First, the working age population has dropped around the world, while demand is increasing every day.
Also, our businesses have moved from millions of interactions to trillions. Just imagine the number of interactions you have with your bank on your mobile device. It wasn’t there five years ago. Where is the workforce to handle these trillions of transactions across so many systems and create the customer experience? What organizations are realizing is that we take trillions of interactions and apply intelligent automation and bots to it to simplify it and create insights and specific actions and then pass it on to people to take it further. That’s the new operating model everywhere.
How does intelligent automation differ from what we used to call robotic process automation (RPA)?
When RPA started, it was automating repeated or mundane tasks. Intelligent automation takes the category to a different level. You are able to make decisions, including suggesting and guiding companies on what processes to automate. Using different AI algorithms, it is able to automate the automation itself.
Previously, we had to go around and understand what processes people are doing to document and automate them. Now the AI automatically tells you what processes people are doing and if you automate this process, you can save 2,000 hours, while if you automate that other one, you can save 10,000 hours of mundane work.
How are we sure that the algos are capable of making such decisions and doing it accurately?
Take an example of invoice processing, where you could have thousands of invoices. You could decide that under a certain amount you are comfortable with the AI taking decisions, which is one way to draw a line.
However, even in the invoices under that set amount, the AI algorithms are able to show you as it learns that its confidence on a decision is say 30% after processing 100 invoices.
At one point, it will tell you that its confidence is 98%. At a certain confidence level, you can allow the computer to make decisions in a controlled and compliant way.
In the early days of automation, we had a problem of not having clean data. Has that problem been mitigated now?
I would say it has made significant progress. In the last eight years, for instance, our product that processes invoice documents has seen millions of invoices and in 18 different languages, and has learned from that experience. There’s not a single human being on the planet with that much exposure and it’s remarkable the accuracy it is able to achieve.
How much have bots evolved, given that the promise was that they will eventually replace human support operators?
It has improved significantly in the last three years. For example, our contact centre solution, which uses Google DialogFlow technology, is fairly sophisticated. If I tell to you that I’m married and then somewhere later I say ‘her’, it can recognize that you’re talking about your wife. That wasn’t there till a few years ago.
The goal isn’t to make it the same as a human, but to make sure it can take 80% of the things that humans handle, ao that the 20% of the times when you need people, they are available and you don’t have to wait for 20 minutes to get a call answered.
How are the plans for the initial public offering progressing?
We’re focused on growing. Our cloud platform is the fastest growing today, and the intelligent automation platform is doing extremely well. We’re definitely headed that way.
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