As businesses evolve following last year’s surge in AI and automation, the autonomous enterprise concept is emerging as the next major leap.
Experts claim that mixing artificial intelligence and automation may offer enterprises a future where technology can self-diagnose and solve issues without human intervention, reducing potential system downtime and boosting productivity.
The concept of an autonomous enterprise sees AI-driven systems manage tasks like predictive maintenance, allowing employees to focus their skills on innovation over troubleshooting. These systems operate in real-time, leading to fewer disruptions and enabling seamless operations across all departments.
Given GenAI’s momentum in recent years, are we anywhere nearer to seeing true autonomous enterprises?
According to Akhilesh Tripathi, CEO and founder of automation vendor Digitate, we are approaching a key moment in the development of AI that will see much more automation across the enterprise sector.
“When we started Digitate, we recognised that, in most large organisations, automation was siloed — it sits within its own island,” he explains. “We found these islands exist because automation doesn’t scale.”
In other words, automation for individual tasks or processes worked, but once additional complexity was introduced, most AI and automation platforms would fail or struggle.
The problem, of course, with having automation but only operating in silos is that it isn’t really automation because businesses still need someone or something to connect each of the processes.
And it is AI itself that can offer a solution, says Tripathi.
Digitate was launched in 2015 as part of Tata Consultancy Services. It initially offered its Ignio suite of services, which aims to automate enterprise operations.
Tripathi is a TCS veteran, having worked for the Indian giant for more than two decades and rising to head up its Canadian unit. He assumed the chief commercial officer of Digitate at launch and became CEO in 2020.
“Tata has been working on automation and AI since the 1980s. At one point, I worked on a project where we developed a way to automate the delivery of coolant for a water plant.
“As we got more into it, it became very clear that this sort of process automation could be transformative from an enterprise standpoint, but you need to put it directly in the hands of the enterprises so they can maximise its value.”
Digitate has already worked with several large enterprises to help them join up automated processes and deliver AI-powered services.
This includes a project with car rental firm Avis, which was facing a situation that had left its IT and support teams constantly firefighting and manually resolving issues, as well as several other challenges.
Avis engaged in an organisation-wide digital transformation project to move from manual and reactive operations across its 2,900 offices spanning 112 countries to an autonomous and predictive one.
At the time, the rental firm was using a third-party monitoring tool to monitor business-critical applications, but it had suffered availability issues caused by server-level problems, resulting in missed critical alerts.
To overcome this, Avis approached Digitate to implement a solution that would monitor and manage the availability of a third-party monitoring tool. Its Ignio AI platform allowed Avis to monitor any server-side issues, and whenever one arose, the platform conducted a root-cause analysis. It would then triage the issue automatically and perform ‘self-heal’ functions where possible.
Digitate also worked with Avis to reduce downtime of critical applications, including its booking tool for customers. Ignio monitored an Oracle database and functional attributes of a CMS system linked to the applications to isolate issues. It then drilled down further into the application layer, web layer, and database layer to triage issues and proactively fix them.
Overall, Ignio has managed more than 176,372 requests to date, leading to a 68.6% reduction in noise and 99.9% uptime for in-scope critical applications. Around 60% of detected incidents were resolved automatically by the platform.
“We love seeing innovation happen in areas that have been pain points for us for years. This saves us a ton of time and has dramatically improved our compliance,” said Avis in a customer testimonial.
The Ignio platform uses generative AI to assess data points produced by existing operations, then predict potential problems and, where possible, solve them before they need human attention. If it cannot resolve them, it can flag problems earlier, reducing downtime.
Data hygiene is one of the significant challenges facing any enterprise looking to automate processes. If the data used by analytics tools such as Ignio is not clean, its effectiveness will be reduced. However, many companies are using reems of legacy data that are not clean, which is embedded in the processes they are looking to automate.
Tripathi acknowledges this challenge but says AI can be used to recognise duplicity or anomalies within data sets.
“We will have both the logs and information from a sensor, so that helps us to make sense of those processes and survey what is good data and what is not,” he explains.
“We can also present this back to the enterprises so they can start the process of cleaning up their datasets internally, which also helps automate processes in the long run.”
The platform can also detect what is classed as “normal” performance from processes and devices in what Tripathi calls an enterprise contextual blueprint.
“This is dynamic – it is constantly updating,” he adds. “But we can know what ‘Monday morning normal’ is compared to other days and reverse populate that.”
Another Digitate customer, energy provider Engie, generated around 150,000 bills for its 12+ million customers every day.
“Even a minor percentage of problems with billing or invoicing leads to a huge impact, resulting in customer dissatisfaction, handling front desk manual corrections, and piles of unbilled revenue,” says Tripathi.
In some ways, technology made this worse. The introduction of smart meters led to a higher need to correct meter readings, negatively impacting customer satisfaction.
Engie turned to Digitate to help it reduce the generation of incorrect bills and invoicing, reduce revenue realisation loss caused by backlogs, and improve customer satisfaction.
Ignio was integrated with an Oracle database to conduct the automatic execution of service requests with scheduling while identifying and correcting erroneous data in SAP.
This led to more correct meter readings and billing, which in turn led to fewer erroneous bills and examples of double billing. Digitate also helped Engie automate more of its call centre functions to improve customer service.
Stats-wise, this involved more than 4,000 batch jobs that were monitored autonomously. On the finance side, payment files worth 2.5 million were integrated without delay, and monitoring improved system stability by 30%, according to Digitate.
Confidence in AI systems is on the rise, and according to Tripathi, this means that elements of automation have now gone mainstream. However, with it have also been some warnings, including several business leaders who warned of the threat newer AI models could pose to humanity.
Tripathi believes AI will make humans “appear more intelligent” because users will be able to extract more insights from business processes and incorporate them into discussions.
He argues that when mixed with automation, AI can “simplify conversations and accelerate problem resolution.”
“If you strengthen that relationship, businesses will see huge advantages. Leaders can better understand what is going on in their business and visualise challenges, helping to build more support for the most complex problems that automated systems can’t overcome alone,” he adds.
He concludes: “In my view, GenAI plus human is better than just a human. But GenAI plus automation AI, plus a human, is better than GenAI. We are big believers in augmenting intelligence – it is never about replacing it.”
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