The era of the autonomous enterprise is here, says Leslie Joseph, principal analyst at Forrester Research during UiPath’s AI Summit. However, still 81 per cent of all businesses has just taken the first steps in automating their processes. The end game is not just adopting deep learning, but to weave all levels into one. ‘Where humans and digital workers all play their part in the autonomous enterprise’, says Joseph.
During UiPath’s AI Summit, recently held online, multiple experts on AI took the audience on their journey towards an autonomous enterprise. In the opening talk Leslie Joseph, principal analyst at Forrester Research, spoke of the early stages we are in, but also of the possibilities the future still holds for us. But to take that leap of faith into the future, it is good to look back a bit, according to Joseph.
A moment of disruption
Joseph: ‘It was 2010 when digital, rich web apps were introduced, and we were all grappling with the question: how can we digitize our companies? Before we knew it, Uber, and Airbnb were conquering the market and changed the digital business model into the models that are common ground nowadays. Today we are at a similar moment: RPA, IoT, edge computing and robotics bring us closer and closer to the autonomous enterprise.’
But why are we looking for an autonomous enterprise in the first place? According to Joseph the motivation is multi-layered: ‘Companies progress in their automation journey: goals become more and more sophisticated and more complex. At first companies are trying to cut down costs and improve FTE productivity, but the end game is much more fundamental: it’s about fusing our ecosystems and personas with AI to transform the business.’
How much value can you unlock?
‘Disruption is a scary word, however. But the real question is: how much value can you unlock over the next five years with AI that is emerging today?’, according to Joseph. And it’s not like we can’t handle disruption, he says. ‘We’ve been through a pandemic, and we’ve seen unprecedented growth in automation. However, 81 per cent of those initiatives use AI which is primarily focused on the automation of processes.’
The automation of digital processes is the foundation, but for a completely autonomous enterprise, companies need to put other AI software to use. Level two uses NLP and RPA to automate employee- or customer-driven processes. Level three is machine learning and level four deep learning. An autonomous enterprise only exists if companies embrace level three and level four to let robots make better and faster decisions, according to Joseph.
The Big Weave
‘But you need all four layers to make a true autonomous enterprise. Human, digital, robotic components and AI agents will work together. Humans are for creative output, robots for augmenting human agility, digital workers for repetitive tasks and AI agents for analysis and decisioning’, says Joseph. He calls it the Big Weave, where humans and digital workers all play their part in the autonomous enterprise.
It’s a mindset shift, as much as a technical undertaking. Therefore, it’s not just a technology investment that needs to happen, and not just a technical shift, you also need to find the right people and invest in change management to let people adjust to the new way of working. Joseph: ‘It’s a disruption and it’s scary, but you need to change if you want to get ahead.’
To make AI more relatable, Tony Tzeng, Sr. Director of AI product management at UiPath, likes to make the comparison to the kitchen: the robot is like the kitchen intern. At first it doesn’t know how to do anything, and you need to give them step by step instruction on how to cut the onions. But eventually it learns and becomes a cook of his own. It enables the chef to do more high value tasks, like research the next ingredient or be more in the restaurant to talk to guests.’
‘The same is true for RPA and AI: you first need to stipulate what steps need to be taken, like enter this information, find that information. It is structured and rigid. We did that with RPA. Now we’re adding semantic automation, which focuses more on thinking. It can look more closely at data and understand what needs to be done. It can understand user intent and relationships between data, documents, applications and processes they are working with. Just like a human.’
It’s not just a technical undertaking
The idea that the CIO can single handedly make an autonomous enterprise is not correct. The foundation is the convergence of human and robot. It’s not a replacement of the human workforce, but an addition. Even though deep learning, like semantic automation, is mimicking a human, it’s the human who will still be the differentiator. And therefore, it’s not just a technological shift, but a human disruption as well.
You can watch a recording of the AI Summit here