Product Decisions in the World of AI With Lattice's Neha Monga

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[00:00:56] Welcome to PeopleTech, the podcast of WorkforceAI.news.

[00:01:01] I'm Mark Pfeffer.

[00:01:13] Today I'm talking with Nihamanga, Vice President of Products at Lattice.

[00:01:18] Like everyone else, they're facing a number of questions about how their platform can leverage AI.

[00:01:23] We're going to talk about the thought processes and decision-making that go around that,

[00:01:28] what users think, and more on this edition of PeopleTech.

[00:01:34] Hi, Niham. Welcome.

[00:01:35] Tell me, how do you see AI fitting into Lattice's product?

[00:01:42] The product has been around for a time, but now everybody's looking for ways to use AI.

[00:01:50] How are you doing it?

[00:01:52] Yeah, what a great question.

[00:01:54] So Lattice, you know, we really have been at the forefront of technology ever since for HR Tech, right?

[00:02:00] And even before all of the generative AI stuff took the industry by storm, you know, we did have a bunch of AI features in our products.

[00:02:08] We had a sentiment analysis and a bunch of other things.

[00:02:11] But since the arrival of Gen AI and new tools and this growing appetite of our customers to use AI, we are bringing it on.

[00:02:20] We are integrating this in all the different aspects.

[00:02:23] And pretty much all of our products will have AI capabilities by end of this year, if not sooner.

[00:02:30] We started with our engagement products where we had all the comments and all the survey insights be summarized using the power of AI.

[00:02:39] We use OpenAI under our backend and we use the APIs to do a bunch of this work.

[00:02:45] And then we looked at performance, which is our flagship product.

[00:02:48] And knowing that customers want this performance insight to be summarized for easy consumption, that's the next one we went to.

[00:02:55] And now we're looking at integrating it in our goals product, growth product, and so on, and also like magic tools.

[00:03:02] So our customers have received our AI products really well.

[00:03:07] I remember when we launched engagement insights, 40% of the customers went and turned it on within a month, which is really hard.

[00:03:14] You know, which is not kind of a reception we see for all the products because it takes time for change management, folks to even learn about the product.

[00:03:21] But there was such eager demand for this.

[00:03:25] And immediately people started using it.

[00:03:27] They're giving us really good feedback.

[00:03:29] Most ways positive.

[00:03:30] You're still learning about like things they want to have us do.

[00:03:33] So a lot of things happening in Lattice with AI.

[00:03:37] How do you decide where you're going to use AI and how you're going to use it?

[00:03:44] I mean, you said that you're going to be incorporating it throughout your platform.

[00:03:49] But, you know, you need to decide, well, where is the technology going to give the most value?

[00:03:55] So how do you make that decision?

[00:03:58] That's such a great question.

[00:03:59] Because, you know, I've definitely come across places where like, hey, we just want to use Gen AI no matter what.

[00:04:03] And that's not the approach we're taking at all.

[00:04:06] You know, and Lattice, when it comes to thinking about the products, we always work backwards from our customers.

[00:04:11] Like what are the big problems customers are having?

[00:04:14] And some of the problems have been longstanding, right?

[00:04:17] For example, like, you know, waiting in data after running the engagement survey.

[00:04:21] Those problems have been there for a while, but we didn't have a good solution for that.

[00:04:25] But now for us, how we're approaching AI is like we're looking at what are the tough customer problems that we are now able to solve and where it creates the most value, time savings, productivity gains, and just like better quality of output, like which is objective bias-free that AI can bring, which sometimes humans can't.

[00:04:44] And prioritizing those things hide in our roadmap.

[00:04:47] So that has been our approach.

[00:04:49] Like, you know, what are the big problems you can solve for customers in a better way than is even possible in applying there?

[00:04:55] Versus like, hey, let's just stick Gen AI onto this feature.

[00:04:57] That's not how we're going to approach this at all.

[00:04:59] Like it has to be a very considered way of using AI.

[00:05:03] If you look at the industry, the HR technology industry, not just Lattice, obviously in the last, say, 18 months, everybody and their brother is launching an AI product of one sort or another.

[00:05:17] And sometimes the features they're describing are things we've actually heard about before, but they're repositioning them as an AI-based product.

[00:05:29] So let me ask this way.

[00:05:33] Are these simply relabeling or are there truly new approaches that are going on?

[00:05:41] And what do you think the dynamic of the industry is?

[00:05:44] Is the industry really building new stuff?

[00:05:47] First of all, I do think industry is building new stuff.

[00:05:50] But at the same time, I think there's some players who are also rebranding.

[00:05:53] I think you'll always have a spectrum of like, you know, true innovators versus people who are still like learning how to best apply that.

[00:05:59] And in the defense, they might be, you know, just using a different technology to make the existing features better or like trying a few things out.

[00:06:06] And I think it's all fair.

[00:06:07] Many of us are learning about AI technology.

[00:06:08] So I don't want to be overly critical of those.

[00:06:11] We should always try new things.

[00:06:13] But yeah, knowing that not everything is going to land.

[00:06:14] I am most excited about thoughtful applications of AI, you know, where you're like changing the games, you know, creating solutions like never before that actually enhance whatever goal they might be.

[00:06:26] For example, like managers have so much on their shoulders.

[00:06:29] Like how do we relieve the burden on there?

[00:06:31] How do we make them more effective in their jobs by providing them the insights, shortcuts that they can do things much better, right?

[00:06:39] So those have always been our goals.

[00:06:41] And yeah, there are a few others who might not be as successful at achieving them, but, you know, it's worth trying.

[00:06:47] And yeah, you're right.

[00:06:48] I've definitely seen some examples like, well, I don't want AI to tell me the weather.

[00:06:52] I can look up in the sky and tell like, yeah, it's sunny.

[00:06:54] So I am looking for those differentiated things that we can do for our customers, which are not the surface level of these things, but like deeper problem solving for them.

[00:07:05] I'll give an example.

[00:07:06] You know, one of the things that is now maybe possible more than our HR leaders, a lot of our HR business partners will tell you, they spend a lot of time answering tactical questions for the employees, right?

[00:07:19] Oh, when is the next performance cycle?

[00:07:21] What does it take for me to get to the next level?

[00:07:24] And a lot of these things can be found in things, right?

[00:07:26] Like employee handbook, or they can be found in like leveling guidelines or job architecture documents that they might be shared.

[00:07:33] But how do we like use generative AI to provide this situational answers to the employees and relieving this burden on the HR admins?

[00:07:40] Like that's one of the things we're looking at.

[00:07:42] And I think that does provide like a next level value for our customers.

[00:07:46] Or like I mentioned to you, performance insights, you know, as a manager who had a lot of reports, I would go around synthesizing, oh, has my report, like what is the feedback from different people?

[00:07:57] How have they been in the goals?

[00:07:59] What was the feedback last time?

[00:08:00] Where do they want to be in their career?

[00:08:02] Synthesizing all these inputs and creating this performance review packet.

[00:08:05] But now AI helped me summarize all this so I can focus on providing the subjective view on top of the objective things that AI gives me.

[00:08:13] So I think we are definitely focused on more of those like exciting things that create tremendous differentiated experiences.

[00:08:22] Do you think customers are getting their arms around this?

[00:08:26] In other words, are they still asking, do you have AI or are they asking more about the capabilities that AI allows you to offer?

[00:08:38] I think the buyers and customers are very smart.

[00:08:41] They can see past like, yeah, this has AI, but this is not really AI, right?

[00:08:45] They're like, hey, what can AI do for me, right?

[00:08:48] They're very astute in their questions they're asking us.

[00:08:52] Like, hey, okay, AI does this and so what?

[00:08:55] Like, where is the sell here, right?

[00:08:57] So if you can tell our customers, for example, when we did the engagement summaries, we were able to tell them like, hey, like customer testimonials that tell us, save me two weeks of work.

[00:09:06] Or I was spending $10,000 to this external company to summarize my engagement results for me.

[00:09:12] Now I can do this in minutes for free.

[00:09:14] They're looking for those kind of savings because I think the economy that we are in right now, there's definitely pressure on everybody to be more efficient.

[00:09:19] So I think it's really important for the customers to see the true value it brings in terms of time saved, dollar saved, you know, not having to do more tactical stuff that is not, that frees them up to do most tragic stuff.

[00:09:35] So they're asking smart questions and they can, the ones that we've seen can see positive and they're demanding.

[00:09:40] And I love that actually.

[00:09:43] Hey, it's Bob Pulver, host Q podcast.

[00:09:46] Human-centric AI, AI-driven transformation, hiring for skills and potential, dynamic workforce ecosystems, responsible innovation.

[00:09:55] These are some of the themes my expert guests and I chat about, and we certainly geek out on the details.

[00:10:00] Nothing too technical.

[00:10:01] I hope you check it out.

[00:10:04] Have you ever been to a webinar where the topic was great, but there wasn't enough time to ask questions or have a dialogue to learn more?

[00:10:10] Well, welcome to HR and Payroll 2.0, the podcast where those post-webinar questions become episodes.

[00:10:16] We feature HR practitioners, leaders, and founders of HR, payroll, and workplace innovation and transformation, sharing their insights and lessons learned from the trenches.

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[00:10:30] So join us for highly authentic, unscripted conversations, and let's learn together.

[00:10:37] Let me ask you to step back even a little further and look at the whole industry again.

[00:10:44] I can't help but ask.

[00:10:46] I can't resist.

[00:10:48] Where do you think the balance is right now between hype and reality?

[00:10:53] Do you think that the technology is living up to everything that's being said about it?

[00:10:59] Do you think we still have a ways to go?

[00:11:02] How are you feeling from a product point of view?

[00:11:05] That is such a great question.

[00:11:07] So, you know, it's been a couple of years since ChatGPT came out.

[00:11:10] And I think when it first came out, there was definitely a lot of hype, right?

[00:11:13] I feel like kind of seeing the hype die down a little bit and reality emerge a little bit.

[00:11:18] And I actually love to be in this space because people are not, you know, just buying things just because AI.

[00:11:23] Or people are not just like building crazy stuff, which actually cannot be supported with the technology, right?

[00:11:29] Like promising big things, which is actually not a reality.

[00:11:31] So I think there's a little bit of like reality check happening with the hype.

[00:11:36] And that is a really good place to be in because now we can start having real conversations,

[00:11:40] real discussions about what AI can actually achieve and how it actually serves a purpose in daily lives of our customers

[00:11:47] and like employees, managers, senior leaders, and so on.

[00:11:51] So I feel like that's where I think it's meeting the road a little bit where people are like,

[00:11:56] oh, yeah, how am I actually incorporating my life and not just getting wowed?

[00:12:01] Like, oh, this product has AI or like this thing has AI.

[00:12:05] Yeah.

[00:12:06] How about pricing?

[00:12:09] You know, Microsoft raised the price at $30 per user for Office 365 for the AI version.

[00:12:17] That's almost $400 a year, you know, per head.

[00:12:22] Do you think it's worth it, you know, for the kind of features that Microsoft's been able to add?

[00:12:33] Do you think customers are willing to pay that kind of a premium for these features?

[00:12:39] Or are they starting to just expect it to be baked in?

[00:12:44] You know, that is such a good question because I think pricing is one area that I think the jury is still out.

[00:12:49] I think Microsoft did a really cool step.

[00:12:51] Like, yeah, let's start charging for it.

[00:12:53] And sometimes I think you need those kind of steps to see where it actually falls eventually.

[00:12:58] But I think it's great to take a first step and see what value people are finding.

[00:13:01] Are they renewing?

[00:13:02] Are they continuing to purchase AI, right?

[00:13:04] I think it's a valuable step in that direction.

[00:13:06] But I do think the jury is still out.

[00:13:08] I think people are still making up their mind on paying for AI.

[00:13:12] I think, number one, I do think people want to pay for AI because they see the differentiator.

[00:13:17] Like, well, it's saving me tens of thousands of dollars or it's saving me X number of hours.

[00:13:20] I think they see the value net.

[00:13:22] But I think it's been hard to separate out, like, what is truly valuable, differentiator, and step change in productivity versus, like, oh, that's kind of a neat enhancement, kind of quality of life thing.

[00:13:32] So I think it's just very important to separate, you know, what is the real value versus from, like, oh, kind of nice to have.

[00:13:39] And being able to price that appropriately with the right pricing model.

[00:13:45] And I don't think anybody in the industry knows that quite yet.

[00:13:48] And I think we'll have to play with a few pricing models to see what sticks, what lands, and what people are comfortable with.

[00:13:53] But I fundamentally do believe, I think AI does add differentiated step-level change value.

[00:14:00] And I do think there is intention and desire for people to pay more for what AI can achieve for them.

[00:14:07] And I think there's some kind of meeting in the middle that needs to happen with that right pricing model.

[00:14:11] So whether that is, like, oh, yeah, it's, like, all you can eat in a single SKU, like, you know, $30 for a whole pilot.

[00:14:18] Or maybe there's a premium option, like, yeah, basic stuff is free.

[00:14:21] And then you pay for where this truly differentiated step-level change.

[00:14:25] And versus, like, yeah, all of it is free, like Zoom does it.

[00:14:29] But because it helps, you know, stickiness of the product in some other way or maybe the entire value is not there yet, it will eventually come.

[00:14:39] I think those kind of things can happen.

[00:14:41] But I do think we should experiment, play, find out.

[00:14:47] And I think there'll be some, like, going forward, changing direction, pivoting a little bit.

[00:14:52] And that is the natural part of this technology.

[00:14:56] One more question.

[00:14:58] When you think about your job, you think about developing new products, you think about, you know, identifying the needs that people have.

[00:15:06] Has AI made that easier or more difficult?

[00:15:10] In other words, is the task that HR technology vendors face today more complicated because the technology is becoming more complicated?

[00:15:20] That is such a fun question.

[00:15:22] So I think there are a few dimensions of that.

[00:15:24] I think, first of all, we do internally use a lot of AI products within Lattice.

[00:15:28] That makes our job easier.

[00:15:30] Like, I love getting, like, all the customer feedback I receive summarized for me.

[00:15:35] And I can see, like, heat maps and all those different things.

[00:15:37] So I think in some ways, like, you know, AI does help me just do my job better, my team's job better.

[00:15:43] But I think there is definitely, like, a learning curve.

[00:15:45] I think tech companies, HR tech companies have to stay on top of what is the latest.

[00:15:49] Like, you know, what are the different types of technologies?

[00:15:52] What is edge tuning?

[00:15:53] What are the different models we can explore, like rags and whatnot?

[00:15:56] So I think there's definitely, like, a learning cycle that the companies will have in developing the AI and technical muscle behind it so that they can envision better solutions, right?

[00:16:07] Just by understanding new problems, just by, you know, knowing people want AI and what problems they want to solve.

[00:16:12] I think you have to also, like, innovate and think of the solutions and the cost behind using different AI technology.

[00:16:18] So, yeah, there is definitely a job out there to become more sophisticated in this area.

[00:16:22] So, which is exciting because I think many of us are, like, super curious, want to learn new things.

[00:16:27] I think it's great for us.

[00:16:29] But, yeah, like, you know, it cannot happen with the same mindset or same knowledge level.

[00:16:36] Like, something has to change.

[00:16:37] Like, you have to hire the right people.

[00:16:38] You have to upskill existing folks in the team to know more about this technology and build with it and test a few things and do this feedback loop.

[00:16:49] Well, Nia, thank you very much for talking with me today.

[00:16:52] I hope we can talk again.

[00:16:54] And thank you.

[00:16:56] Yeah, no, thank you.

[00:16:58] It was fun talking with you as always.

[00:17:00] Thank you, Mark.

[00:17:14] My guest today has been Nia Monga, Vice President of Products at Lattice.

[00:17:18] And this has been People Tech, the podcast of WorkforceAI.news.

[00:17:23] We're also a part of the Work Defined Podcast Network.

[00:17:26] Find them at www.wrkdefined.com.

[00:17:33] And to keep up with AI technology and HR, subscribe to Workforce AI today.

[00:17:38] We're the most trusted source of news in the HR tech industry.

[00:17:42] Find us at www.workforceai.news.

[00:17:47] I'm Mark Pfeffer.