DataSeries
Published in

DataSeries

How will AI Drive the Next Wave of Enterprise Automation?

This article [part 2/2] has been written Tom Henriksson, GP at OpenOcean and originally published here.

So far automation has utilized robots focused on task mining and -automation, but process automation has the potential to be much more transformative. At OpenOcean, a European VC focused on early-stage data software startups, we believe that automation will become so seamlessly integrated and easy to use by organisations that it will just work in the background, providing a myriad of intelligent services and solutions. We set out to further explore this topic via our DataSeries community of global data leaders, gathering a roundtable of experts, top practitioners and leading vendors of automation technology with the goal of unpacking the real state of enterprise automation and the role of AI.

At the round table, there was general agreement that through process mining and analytics solutions like Celonis, KYP.ai and Minit, this is the area where automation is now showing the most promise. Detailed process mining and analytics rely on AI to oversee employees’ activities, determine what is a process, which systems are involved, and what efficiencies and automations could be implemented. By using software, there is a shift from a consultative, human-driven process, into a fully-automated solution, where “digital coworkers” are effectively configuring themselves.

If it sounds dystopian, our panelists disagree: “AI is just additional technology,” said Leyla Delic, Group CIO and CDO of Coca-Cola Icecek. “What will move us forward is the required scaling from an automation single product offering to a broad holistic and intelligent automation platform. Picking the right use cases to drive this process forward is hyper-critical.

There was, however, acknowledgement that this autonomous future is still slightly out-of-reach. Delic continued, “For instance, when working with image recognition, data labelling is taking most of the time and is too time-consuming. How do we accelerate this process? Building speed, streaming (edge computing), processing images in real time and ingesting it into digital twins is a hot space.

The key areas to tackle

We believe in democratizing AI to place it into the hands of people (enterprises), resolving major bottlenecks on the way. For instance, within AI, data tagging/labeling is a huge problem and consequently also a massive opportunity for startups to solve. Finding smarter ways to make sense of unstructured data and label it effectively is not only a technology challenge, but there is also a lot of opportunity to build innovative interfaces that enable people to enrich data whilst the system learns to do it automatically.

Our roundtable discussion honed in on the outlook for AI and frontier technologies within the enterprise automation space. Our panelists agreed that over time, more and more detailed data will be available for better decision making. AI is a frontier technology that will foster the learning curve and drive improvement in operations, decisions, tools and processes. Based on that, new software (robots) will automate specific activities and have an AI-driven genie provide recommendations on how to improve outcomes and eventually drive its own decisions.

To give an example of what this might look like under the hood: Feedback Loops enable learning and drive an efficient automation journey. The feedback loop doesn’t entail just data, but also the actions that result from it. ”AI, RPA and humans need to work together, even if the accuracy rate is only slightly higher than 50%. In order to make progress in AI decision making, we simply must accept that a 50% accuracy rate in AI-driven assistance is par for the course at this stage of the journey,” said Shobha Singh, Group Head of Operations and Automation at Mizuho Bank. She continued, “The path to AI development is also a human one which must be shared as a part of the enterprise culture. People need to firstly understand how AI/ML works so that they can trust it and then create a sophisticated feedback loop.

There was general agreement that currently there is serious talent scarcity. There simply isn’t enough fire power yet to source all capabilities that will enable us to scale quicker.

AI boosts automation to the decision making tables

Technology has traditionally been seen as a way to reduce costs by automating back office tasks, but now it is being used to take on front-office responsibilities such as identifying customer needs. The panelists agreed that AI tools can and will be used more frequently to develop front-office programs. Indeed, in the future, companies will need front-office AI systems to survive. Conversational AI tools that integrate with broader enterprise automation platforms are through automated customer dialogues and data-collection helping to foster innovation across verticals within mature industries. The increasing number of front-office teams who seek solutions to automate their workflows, and often implement them on their own, has shifted the paradigm of who takes responsibility for automation.

Andrei Brasoveanu of VC firm Accel said, “Once organisations get into the mindset of automating their processes, they don’t stop at the back office. The way front workers are now using automation tools for workforce/customer empowerment opens up multiple new sectors for investment.

Adam Bujak, CEO at KYP.ai says, “our clients are generating opportunities driving the value of both top and bottom line. It is high time to move the needle also in the front office space.

Antti Karjalainen, CEO at Robocorp agrees and adds: “At Robocorp, we’ve seen that often low-code tools end up being used by professional developers instead of citizen developers. That’s why we are building a developer-first RPA and automation stack”.

While some C-level executives have been pushed by the crisis into proliferating automation solutions, many teams within slower enterprises have taken the initiative to build solutions themselves. It turns out that many business users simply don’t want to wait for certain automation solutions to be implemented. Kulpreet Singh, Operative Partner at OpenOcean (previously MD at UiPath) noted, “A rise of bottom-up automation is appearing out of Covid”.

--

--

--

Imagine the future of data

Recommended from Medium

Conversational AI Events

Artificial Intelligence Salaries

HOW DOES ARTIFICIAL INTELLIGENCE AND ROBOTS CHANGE THE WORLD?

Innovating technical ideas to curb the spread of COVID-19

Gender parity in AI a ‘crisis’.

Improving Customer Acquisition With AI Technology

RT/ Robots sense human touch using camera and shadows

Project outlook

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
DataSeries

DataSeries

Follow our publication (https://medium.com/dataseries) 💡Connecting data leaders and curating their thoughts

More from Medium

The One Image Every Data Scientist Should Be Aware Of

You Will Like Cloud IAM!

How No-Code-ML Tools Carry Out The Hardwork For Data Scientists?

3 lessons I learned building customer-facing data science products