Automation and Machine Learning are Two Sides of the Same Coin 

The CIO and CISO of a nonprofit medical research organization echoed the sentiment of many recent ETR Insights guests in describing a still uncertain and rather bleak macro environment with continued uncertainty ahead. “Cash is not going to be as cheap as it once was, so it’s going to be tougher to ramp up spend, [and] encumbrances are going to be a lot higher to overcome in capital appropriations.” 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.” 

This summary is jam-packed with vendor commentary. Read on to learn more about how this organization’s RPA installation is maturing beyond “classical RPA” and how innovation spurred by technologies like OpenAI will be a game changer for ML/AI and RPA alike. Further, our guest describes the power of Microsoft in all of this, in addition to the vendor’s continuing arc of success in security. Finally, he runs the through the gamut of projects management tools including Airtable, Atlassian,, Notion, and others, as well as scheduling vendor Calendly, who is the latest in the series of Microsoft hit jobs, as the latter’s Bookings offer begins to reach parity. 

Vendors Mentioned: Airtable / Asana / Atlassian / Automation Anywhere / BeyondTrust / BluePrism / Calendly / Citrix (Wrike) / Databricks / Elastic / Microsoft (Bookings, Power Automate, Project, Sentinel) / / Nintex / Notion / Okta / OpenAI (ChatGPT) / Scale AI / Splunk / Talend / TensorFlow / UiPath

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.” 

He 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.” 

Additional Vendor Commentary

Microsoft in Security – Sentinel SIEM vs. Splunk + Elastic. Cybersecurity is another sector where our guest is “marveling” at how “Microsoft has pulled away from the pack, especially when you talk about Sentinel and other risk-based tools they’ve built into 365. It’s unbelievable. I’m not saying they’re always the best if you were to line them up. But again, the one-stop shop is becoming more and more palatable in my mind, especially because we’re focused so much on Microsoft for our operations.” Regardless of product offering, our guest notes that Microsoft often undercuts competitor pricing due to their scale. “Obviously you would love to have something as dynamic as a Splunk or Elastic, [but] Sentinel does a workman like job as a SIEM, and I think the cost of storage there is going to be negotiably less. This a major issue haunting the companies, especially Splunk. I mean, their storage costs are going out of control.” 

Quick Takes – Project Management. Our guest provided ample commentary on project management tools that he has come across in his decades-long career. Currently, his organization utilizes Airtable, Asana, and Atlassian for distinct use cases. Read on to see this CIO’s quick takes on these vendors and their peers. Notably, project management is the one area discussed by this executive where Microsoft’s offering falls short. 

Airtable: Airtable is interesting. We use it as right now as staging for a number of repositories that we need quick access to, and it is very, very quick on ramp, with a low barrier to understanding and usability, and a quick time to value. I definitely recommend it. I love that tool. 

Asana: Asana is used tactically. It’s not continual spend for us, it’s more ad hoc [due to how] we spawn projects. It’s got heavy resonance from our programmatic team, and a lot less barrier to entry in terms of learning the tool. 

Atlassian: Obviously if you’re a heavy Jira or Confluence shop, that’s going to be a great place to be. But if you’re not, [it takes a lot of] added effort to [stand up]. I still am a huge fan of Atlassian; they’re doing a great job. 

Microsoft Project: I honestly have not used [Project] in about 15 to 20 years. I think it was very, very complex. They do a tremendous job blanketing the area in terms of brand-building, brand recognition, and name recognition. The tool looks solid. I see that more as a midrange kind of project / collaboration tool. I haven’t heard anything negative necessarily about it. 

Notion: We’ve used that tactically here. Shout out to them as well; they’ve done a great job. 

Calendly vs. Microsoft Bookings. “Microsoft Bookings is starting to achieve feature parity in their offerings. It makes for a very interesting dynamic. We are going through this as we speak [and[ being very careful to make sure that we are matching up feature-for-feature [with Calendly]. If so, that could be a significant spend shift, I don’t need to tell you. Calendly does an excellent job. They’ve got a great reputation and great support, but it’s going to be very interesting to see how they keep up.” 

Want more? We have another clip from this interview on the ETR YouTube channel. Also, our ETR Observatory offers more insights on which machine learning/artificial intelligence vendors technology decision makers are exploring for their business use-case. Register for a free trial to see the full transcript or video of this interview.

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