AI Leadership Insights: Workplace Productivity

Amanda Razani: Hello and welcome to the AI Leadership Insights video series. I’m Amanda Razani, and I’m excited to be here today with Jeff Evernham. He is the vice president of product strategy for Sinequa. How are you doing today?

Jeff Evernham: I’m doing great, Amanda. Thank you for having me.

Amanda Razani: Happy to have you on our show. Can you talk a little bit about Sinequa and the services that you provide?

Jeff Evernham: Certainly. We’re a software company and the software that we provide does enterprise search. If you’re not familiar with that term, the easiest way to explain it is it’s just like Google, but instead of on the internet, it’s for everything within your company. It doesn’t matter whether it’s Slack or Teams or email or SharePoint or shared folders or whatever, you have basically one search bar and you can find anything, any format from that location. You don’t have to go from application to application searching over and over and over again to find the information that you need.

Amanda Razani: Awesome. That would’ve been my first question, so thank you for clarifying. So it’s kind of a search for all the internal communications?

Jeff Evernham: Right. You can embed it with external sources as well. A lot of companies have external publications that they want to search alongside their internal content, but the beauty is that it’s your internal content. It’s delivered securely, it’s fast, and it’s super efficient. The real beauty of this is once you have the ability to access all of your information from one place, you can do other things with it, too. You can, for instance, build a 360-degree view of a part or a component or a customer, so that all of the information about that item, regardless of where it lives, is available in one screen.

Amanda Razani: Wonderful. That leads us into the topic of AI. We’re hearing a lot about AI these days.

Jeff Evernham: A bit.

Amanda Razani: How does… Yeah, just a little bit. How does artificial intelligence play a role in this area and what’s the big impact you’re seeing?

Jeff Evernham: Well, great question. That’s the topic everybody’s interested in now. AI plays a role in our business in two ways. One is that we use artificial intelligence for our search capabilities. We have several deep learning models based on large language models that improve the ability of finding things. If you don’t use the exact words or you don’t use the exact phrase, it gets the concept and it’s still able to retrieve that information effectively. That’s baked into the product that we provide. Where it’s perhaps even more exciting is this realm of generative AI. Now, we don’t have generative AI in our product per se. We’re trying to retrieve stuff that exists, not create something that’s new. But a lot of companies want to use generative AI as they should and it struggles in fact-based scenarios, because it’s generating language.
People have heard about the problems, right? It hallucinates, it makes stuff up. You can’t really trust it. But just as importantly, it was trained on public data. It doesn’t know anything about your company’s internal content. People wanted to use generative AI, but they’re really not sure how. There’s actually a technique that when you blend search with generative AI, you essentially solve those problems of generative AI because you can do the search on your own content, you pull up the information about your business, it’s secure and so forth, and then you tell the generative AI to, “Hey, read the information that I found here and give me an answer based only on that info.” When you do that, you solve the problems of generative AI. This is a technique called RAG, retrieval augmented generation, and it’s basically where everybody’s headed now to use generative AI to say, “Hey, let’s pair it with a search engine and let’s set that up.” Now, we can really leverage the power of generative AI inside our business on our own content without the risks of misinformation.

Amanda Razani: Interesting. Yes, I have heard a lot about that. Does this tend to speed up processes across the board?

Jeff Evernham: Well, absolutely, because we’re seeing in our customers tons of excitement here because it also… Not only does RAG solve the problems of generative AI, it makes search better, too. Because now instead of getting a list of links and saying, “Oh, let me click on that and read about it, let me click on this one and read that one,” and going through that process, the generative AI can do that. You just have it do the reading for you and now it gives you a natural language answer tailored specifically to your question. It’s much more efficient because it takes away the labor of reading and interpreting all of the results that come back from the search. We’ve got a bunch of companies very excited deploying this and getting really positive feedback from their users.

Amanda Razani: As rapidly as this technology is advancing and with everyone implementing it in these different ways, what are some future use cases that you’ve heard people speak about to use this technology moving forward?

Jeff Evernham: How much time do you have? That’s a great question. We’re just scratching the surface. I mean, all of this is brand new. It is moving really quickly, but what we’re seeing is RAG is actually… For all the power that exists within RAG, it’s really a first step. We’re really moving into the realm of assistance. Microsoft calls it a Copilot, where we’re not just using it to retrieve and summarize information, but we’re using it to do things. Now, that may be automating a workflow that now, instead of a person having to do it, the AI can help make it happen. But I believe that very soon we’re going to see it move into the realm where the assistants become agents and they actually take action on behalf of employees.
Now, we’ve got to be smart about this. We’re not going to go have it do life-critical things yet, but I do see a lot of routine tasks get automated in a very safe manner. As the technology advances, the number of use cases, I really believe it’s going to take over almost every area… Not take over. Let me rephrase that. It’s going to impact almost every area of work as we know it today.

Amanda Razani: Let’s talk about that a little bit from the employee standpoint. When you’re speaking with business leaders, is there still some hesitancy on the part of staff and employees to embrace AI or is it quite the opposite? I’m just curious.

Jeff Evernham: It kind of depends on who you’re talking to. I mean, we’ve seen a lot of headlines where employees have been laid off either because of AI or because of anticipated improvements coming through AI. I think we’re going to continue to see that, not because AI replaces people but because people using AI become more efficient, so the total number of pool of people doing that work becomes smaller. But at the same time, we just talked about all the new use cases that this is going to infiltrate and it’s definitely going to create new jobs and expand new things. We’re going to be able to do a lot more. I think from an individual standpoint, there are some people who are concerned about this. People who are more senior level trying to run a business and figuring out where they can do this, the best thing they can do is start with this because they’re going to need this efficiency and look to figure out where can they do more now because they have the capacity to do that.

Amanda Razani: Do you think it’s going to be an important characteristic of employees to be able to adapt and constantly be skilling up as these shifts in technology occur?

Jeff Evernham: That is an interesting question. My personal take on it is this weird mix. You are going to have to be able to do your job differently or maybe do a different job. A lot of people are talking about re-skilling and that sort of thing. I don’t know how critical that’s going to be because now we don’t have to learn how to talk to computers. Computers have learned how to talk to us. I have no skill as a graphic designer, but there are tools out there right now where I can click on a piece of an image and literally say, “Replace that with an elephant,” and it’ll do it and it’ll look really good. I don’t need a lot of skill to start doing something in a completely different vein. I’m less focused on the skill repurposing than I am on just being flexible as a worker and recognizing that you’re going to be a lot more capable with these tools than you’ve probably even been able to imagine.

Amanda Razani: Absolutely. It’s incredible what the future holds. That being said, if there was one key takeaway that you could leave our audience with today, what would that be?

Jeff Evernham: Well, maybe I’ll cheat and say two, but one’s kind of obvious. I think the first is get started now. There’s a lot of people who are like, “Well, maybe it’s not time yet because the technology’s changing so fast.” I think that’s the wrong move. Get generative AI and start using it in your business now. Yes, it’s changing fast, but the foundation and the fundamentals are going to be here for a little while. And if you wait, you’re going to be left behind.
And then the real takeaway from this conversation, I say 2023 was the year of figuring out how are we going to use generative AI in the business. And we figured it out. The answer is RAG. 2024 is the year of getting started with RAG. That would be my takeaway is you can use generative AI in your business. It can be cost-effective. It can be trustworthy. We know how to do that. We’re just at the very beginning stages, but you should be at least experimenting, if not actually moving to put this into production sometime this year with some specific use cases.

Amanda Razani: Awesome. Well, thank you, Jeff, for coming on our show and sharing your insights with us today.

Jeff Evernham: My pleasure. I enjoyed the discussion. Thanks again for having me.

Amanda Razani: Thank you.