AI is being adopted by businesses around the world. ManageEngine in its quest to improve business growth and customer experience is working on a slew of projects dedicated to emerging technologies. Ramprakash Ramamoorthy, Director of Research at ManageEngine, discusses the focus areas for AI, the workings of the R&D Labs and the trends he foresees in the domain.
What are the key areas of focus that ManageEngine is leveraging AI for?
We use AI-assisted user and entity behavior analytics (UEBA) in our security information and event management (SIEM) stack, and we’ve built powerful forecasting and anomaly detection techniques in our monitoring stack to help IT managers predict events and trace the root cause of anomalous issues. We’ve also launched a plethora of natural language processing features in our service delivery stack including chatbots, smart agent assignment, and ticket topic detection to ensure maximum agent productivity.
Apart from AI, what are some of the technologies ManageEngine’s R&D working on?
At ManageEngine Labs, we’ve been working on a slew of projects that enable IT teams to optimise processes and maximise productivity. We make sure to select and develop meaningful research projects that have the potential to see the light of day.
We have a dedicated, expert database research team building innovative database solutions to ensure our products operate at scale with a minimal footprint. Co-located with the AI and database teams is our hardware acceleration team, which works on putting application-specific integrated circuits (ASICs) like field programmable gate arrays (FPGAs) to use and ensures our AI models and databases make the most of the hardware underneath.
We also have a blockchain and cryptography research group that helps our customers stay on top of newer advancements in the world of decentralised computing and ensures our security products are up-to-date with the most recent trends in cryptography.
With the rapid adoption of AI due to pandemic, what kind of trends do you anticipate the industry to pick up?
Digitisation has seen increased acceleration since the onset of the pandemic. In addition to the growth of new age, digital-first businesses, traditional industries like banking and health care are also heavily investing in digital infrastructure. Naturally, as a result of this digitisation, organisations want to use the data they collect to their competitive advantage—this has lead to an upward trend in AI adoption as well. IT is becoming a more critical aspect of business since a modern-day customer experience is heavily dependent on the quality of the IT infrastructure upkeep.
Today, AI is widely used in services like marketing, customer support, and product positioning. As IT teams warm up to the idea of AI predictions in core system maintenance tasks and start using AI on a day-to-day basis, we’ll see more adoption in IT infrastructure upkeep and use cases like threat detection, outage prediction, malware analysis, and root cause analysis of incidents. We can also expect to see the use of AI in core services like lending in banking or report analysis in health care.
As for AI itself, the technology will move towards explainable predictions, which can help teams interpret decisions made by the AI model. AI is also evolving to work with smaller amounts of data, helping small and medium-sized businesses that don’t have the luxury of huge data sets stay on par with bigger enterprises.
How has AI-augmenting helped ManageEngine’s customers in addressing industry challenges?
Data is a key asset for modern-day organisations—they build successful business models around data and leverage AI to put this data to better use. Today, it’s not enough just being a digital-first brand; the key is how reliable your digital interface is.
ManageEngine products’ AI capabilities help customers secure their network and ensure uptime. We provide an extensive UEBA platform via Log360, our SIEM solution, to ensure security isn’t compromised by malicious actors.
Our network monitoring tools, OpManager and Site24x7, use AI features like anomaly detection and incident prediction to help better forecast network needs and mitigate outages.
Our service delivery tool, ServiceDesk Plus, utilises advanced natural language processing techniques to ensure faster resolution of incoming tickets by identifying the context of tickets and assigning them to the right technicians.