In this ETR Insights interview, the CIO and CISO of a small nonprofit medical research enterprise discussed how his organization is trying to leverage optimal value from their existing IT portfolio, while reducing spend where possible across SaaS workflows and cloud. He expects that current efforts to ramp up RPA and machine learning and artificial intelligence will help to reduce spend in time. He sees RPA and ML/AI as means to the same end: “essentially [they are] trying to solve the same business use case – automation or removal of excess resources, whether human or otherwise.”
Scaling RPA & ML/AI for Future Savings. This CIO expects that cybersecurity will continue to be a top organizational priority, in part as “a byproduct of newsworthy headlines,” but he also thinks that ”once we get more leverage out of AI and RPA that will help close the gap in a lot of these cyber risk models. More and more, we're finally seeing an accurate representation of the application of artificial intelligence towards security, rather than it just being a buzzword, and we're seeing it essentially become a true measure in terms of risk management.”
By now, his organization's initial RPA implementation is “in the rear-view mirror” but he described a “not unpleasant experience” during proof-of-concept stages, with “a lot of great players” to explore. He favorably mentioned UiPath and Blue Prism, in addition to Nintex for “when we were using RPA a little bit heavier.” He thinks that Automation Anywhere maintains “a great reputation...[They] still may carry the stigma of a classic RPA play, but I think they're going to be able to turn the corner.”
The organization also plans to leverage Power Automate as part of a late-stage ERP implementation. “Being in the Microsoft ecosystem is starting to pay more and more dividends as we're able to abstract out. About 20 years ago, we could have stayed in the traditional Microsoft on-premise environment, and it was still like building silos no matter what the product. Here, the add-ons are almost instantaneous and it's phenomenal.”
ETR Data: Accodring to data from the July 2023 Technology Spendings Intentions Survey (TSIS), spending trajectories for both UiPath and Blue Prism have both fallen considerably over the past few years, coupled with Pervasion losses. Meanwhile, spending on Microsoft Power Automate has also eased but to a much lower extent, and Pervasion has grown impressively, with Power Automate the clear leader.
Generative AI Technologies Will “Bridge a Gap between RPA & ML/AI.” Our guest is very excited about OpenAI’s ChatGPT and its impact on the greater industry: ”I think the messaging is going to be unbelievably at a 45-degree right angle. Everybody is going to want to sound like generative AI startups or ChatGPT. People have just fallen in love with that interface. It's going to be tough to bring to market a product that doesn't at least align somehow.”
He thinks that technologies like this will bridge a gap between RPA and ML/AI use cases in the enterprise. “When you think 'classical' RPA, it's user and operational experience of the types of work benches, and the way you build workflows. What OpenAI has shown with ChatGPT, for instance, is that you can get rid of a lot of what I would call 'overhead,' complicated artifact building, or user actors around typical RPA. I see that as a very interesting value proposition, to be able to supplant some of these work benches, like in 'classical' RPA, that take quite a while to master and quite a while to get any value past the regular use cases.”
ETR Data: ETR recently conducted a drill-down survey focusing on Generative AI trends and impacts within the large enterprise landscape. While only 18% of respondents indicated their organization had a formalized/documented Generative AI strategy, 66% indicated they were already in the midst of developing one with another 12% to begin within the next year.
Our guest sees innovation in machine learning “rapidly improving” beyond “typical use cases in finance or the back office” and spreading into other operational areas, including cybersecurity. “It's much more tangible now... It’s going to be very interesting to see how vendors position their messaging around this given what we've seen. ChatGPT is the opening salvo. Obviously, there’s going to be more generative AI solutions out there that are going to be niche or incremental. A very interesting dynamic that I’m going to be watching.”
Beyond ChatGPT, our guest noted TensorFlow as a “solid” name with “a great community ecosystem.” He also noted Databricks for their data modeling, as well as Scale AI. “In general, I see so many 'next movers' out there in AI, maybe 10 to 15 a month coming to play and trying to whittle out any gaps... It’s exciting, but at the same time very difficult to do a true objective differentiation on any of these vendors. [Where are these players] going to fall? I think for a lot of them strength will be in niche sector plays.”
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Enterprise Technology Research (ETR) is a technology market research firm that leverages proprietary data from our targeted IT decision maker (ITDM) community to provide actionable insights about spending intentions and industry trends. Since 2010, we have worked diligently at achieving one goal: eliminating the need for opinions in enterprise research, which are often formed from incomplete, biased, and statistically insignificant data. Our community of ITDMs represents $1+ trillion in annual IT spend and is positioned to provide best-in-class customer/evaluator perspectives. ETR’s proprietary data and insights from this community empower institutional investors, technology companies, and ITDMs to navigate the complex enterprise technology landscape amid an expanding marketplace. Discover what ETR can do for you at www.etr.ai