Podcast: Cornerstone’s CPO Karthik Suri on How Businesses Seek AI’s Potential

[00:00:00] You know what I like about I-Solved? Everything. I-Solved is people-centric, and in a people-centric world you need a people-centric solution. I-Solved PeopleCloud is a comprehensive human capital management solution that helps you employ, enable, and empower your workforce throughout the entire employment life cycle.

[00:00:19] From tracking to recruiting to onboarding your clients from payroll to benefits to time and labor management, transform your employee experience for a better today and a better tomorrow with I-Solved. For more information, go to isolvedhcm.com Welcome to PeopleTech, the podcast of workforceai.news. I'm Mark Feffer.

[00:00:40] Today I'm talking with Karthik Suri, the Chief Product Officer at Cornerstone on Demand. We'll cover the realities of AI and HR tech. For example, are vendors and customers still scrambling because there's so much buzz? Or are they taking a more business-like approach to the possibilities AI offers?

[00:01:07] And to make sure we're thinking about the real world, we'll talk about how they make their buying decisions when the field is moving so fast. All that and more on this edition of PeopleTech.

[00:01:18] And I wanted to talk about AI, of course. Specifically what I'm interested in is the impact it's having on planning for new products, both at Cornerstone but also what do you see going on within the wider industry?

[00:01:38] Absolutely. Look, there are many seismic shifts that are happening in the industry right in front of us as we see right now, Mark. First, there is a multi-generational workforce.

[00:01:50] Secondly, the proliferation of data and cost of compute reduction in cost of compute has substantially, the proliferation of data has substantially increased and the cost of compute has substantially come down.

[00:02:03] Number three, there are various emerging technologies and ESG efforts like electric vehicles, ESG efforts that is fundamentally helping people reimagine business models as well.

[00:02:14] And lastly, particularly AI and generative AI is becoming a disrupted in the industry as a whole. So this is a perfect storm and let's actually talk about AI and more recently generative AI on its impact.

[00:02:32] There are three pieces to this. One is a massive productivity piece of it. Number two is a complete disruption of business models turning around previous business models up on their head and previous form factors up on their head, more like fire and electricity or at least mobile and internet.

[00:02:55] And number three is the ethics, the governance and the risk management surrounding AI. So all three are simultaneously happening and several teams and organizations are essentially building the runway as the plane is landing right now, so to speak.

[00:03:14] It has come to a point when organizations are at the crossroad of either playing defense or offense, either embrace the fact that you can build more productivity within your organization using your existing capabilities and processes.

[00:03:28] You can get ahead of the business model disruption by actually, you know, busting the innovators dilemma and welcoming it and having countermeasures to your existing business model and shift it appropriately.

[00:03:40] And number three is establishing deep, deep governance processes about privacy, security, explainability, human in the middle, bias reduction, etc. So that AI can be a force for good.

[00:03:55] And it also means that companies have to prepare themselves for disruptions from like, you know, AI native companies as well and ingest that into their DNA, into their culture, into their ecosystem.

[00:04:07] So with all of this happening at this point in time, I would fundamentally consider particularly when software companies are thinking about products.

[00:04:15] AI broadly should be assumed as non-negotiable in terms of product advancements. Customers want to see it, industry wants to see it and everyone wants to ensure that that is used favorably and for good.

[00:04:30] Number two is either through organic or even through ingestion of some M&A, it is important to bring that AI native thinking into the business, particularly when you're in a SaaS or a product business or, you know, further matter even in brick and mortar businesses because every business right now is a digital business.

[00:04:49] And number three is not just in a product development and an engineering space, but in corporate governance as well having the right form of oversight for AI, the right amount of training for everyone in the organization so that people understand the goods and essentially the risks that come with it.

[00:05:10] One of the reasons why we recently launched Cornerstone Galaxy, which is the AI leading workforce readiness, workforce agility platform is actually to combat these multiple macro changes that are happening in the environment and not only, you know, launch and

[00:05:30] market ship our own products and services in help of our customers, but given we have a robust and rich content business, help PR customers and the broader ecosystem bring them along in this change in a way that robustly takes us into the next generation in the most responsible way.

[00:05:48] It is also with this mind that we also acquired two companies just this year, Sky High, which actually is a skills centric skills transformation company, which also evaluates the skills that are coming around the corner, right, like the foresight that is required for what skills are needed for organizations and tailspin,

[00:06:09] which fundamentally through spatial and artificial intelligence reimagines learning and adoption. So this way we are creating a portfolio of a lot of AI native companies right now. I hope that answered your question.

[00:06:23] Yeah, it did. A couple of sort of thoughts came up while you were talking. You said that basically everything needs to have AI incorporated into it and you certainly see that out in the marketplace.

[00:06:38] People are insisting on it. Do they know what they're insisting on? I mean, how much of what's going on with AI right now is really about the technology as opposed to the marketing?

[00:06:52] That's a fantastic point. Like no doubt that there is a hype cycle surrounding AI, but AI is real and is here to stay. And let me unpack both of those plans simultaneously.

[00:07:03] The hype cycle is here because everyone is looking, feeling and thinking AI at any given point in time. There is a large amount of discussion going on in all circles about what are you doing about AI, etc.

[00:07:16] That feeds itself. On the other hand, the technology of AI and the democratization of compute and availability of tools is also rapidly, rapidly expanding right now.

[00:07:27] So I don't believe that this is much a rubric of nothing. I believe this is real. I believe that the evolution of the technology, the usability and the product is following the market hype.

[00:07:39] But what I also do believe that it is very important to have the right tool for the right job. So in other words, there are certain instances where I see where it is a hammer looking to find a nail at which point it is a suboptimal deployment of such a technology.

[00:07:56] But the reality, let me talk about HR Tech business or whether it is learning or whether it is career planning and trajectory recruiting or skill building.

[00:08:07] AI is a force of goodness for change in this. For example, if you take our own skills graph with the augmentation of Sky High, which is a company we just bought,

[00:08:18] the ability to parse terabytes of data every single day, petabytes of data a month and the ability to actually scan billions of profiles including job descriptions, including open requisitions in the world

[00:08:34] and slice it by industry, by function and by geo and applying both the concept of AI and generative AI in this helps us not only understand say for a given company what are the skills that they have, what are the skills that they need and what are the skills that their employees want.

[00:08:51] This is fundamentally enabled by AI. Similarly for companies that are on the brink of disruption, having that visibility into which are those skills that they are completely lacking to invite the new era.

[00:09:07] Think about film photography. Have they known that digital photography editing is becoming a skill, a coin of the realm of the future? And if they have the humility to absorb that tsunami coming at them, they would have had the foresight to do the right business model shifts.

[00:09:25] Similarly, 11 years back, we started spotting that InfoSec is a skills gap in major locations in the world, right? Like in major tech hubs in the world. Imagine what you can do with that kind of data for strategic workforce planning, for compensation planning, your hirings and skill strategy.

[00:09:45] That is an enterprise view of how AI can be a change of good, change for good.

[00:09:50] The second is let me think about myself as an employee. I am an employee. I have my wants. I want my organization's needs to marry my wants such that when I thrive as an individual, we succeed as an organization.

[00:10:05] I also need an objective way for career planning. Our research shows that 90% of people that have left an organization have left because they don't have a tool that they can first have a conversation with on what those career opportunities are.

[00:10:19] And this is even more proof for underrepresented minorities. If you think that, and if you take that talent planning, career planning, skilling is a major initiative.

[00:10:31] And imagine I have a tool by which I understand the skills that I have. I am able to plot what are the destination roles that I can right at, right? Control my destiny and get to in a good period of time.

[00:10:46] What skills are lacking for me to build depending on the career path that I choose? And what are the things that I need to do in terms of learning, skilling, projects, mentoring gigs that helps me get there?

[00:11:00] Then I have a better control of my destiny. And I know that I can have a path to thrive within an organization and I have a better chance of staying within that company.

[00:11:10] That kind of an AI powered tool powered by a skills graph, powered by that navigation system for an employee is something that actually drives career progression for employees and business outcomes for employers. That is an employee-centric view of how AI can truly power that next-generation experience for people.

[00:11:32] And then the third example would be simple productivity. Think of all of the mundane tasks that we do that needs human intervention, that needs interpretation of some workflow manual that then gets manifested on the system.

[00:11:45] The automation of that totally drives productivity, which then gets reinvested into things that are more thought leadership-centric where people can truly use their intuition to make progress.

[00:12:02] We are moving from that knowledge economy to an intuition economy and we have a huge opportunity to unleash limitless potential in people and organizations to thrive in a changing world.

[00:12:13] All of the things that you just described, they are very true obviously. I'm wondering if we can break it down a little bit to sort of a nuts and bolts level.

[00:12:23] When you look at all of these capabilities and the impact that they can have both on employees and candidates or on the employers too, how do you sort of approach translating the capability to product?

[00:12:40] Beautiful question. Let me walk you through three real examples that I hear from customers and that have manifested themselves in our own products. The first example is a very large logistics management company that want to have a strategic workforce planning process in place that is skill-centric.

[00:13:03] It is not only a skill-centric approach for workforce planning for the future but also for tomorrow. So if I need a Spanish speaking forklift operator within this particular radius who knows to operate this particular machine like the hard-skill portion of it tomorrow,

[00:13:22] what is the list that is available to me that has completed the requisite training and checklist for me to deploy them? All the way through, am I going to have an infosec skill shortage in Netherlands where most of my development center is located in three years?

[00:13:40] So this whole gamut of skills-based workforce planning with the right talent intelligence of what I have within the organization that I can deploy those assets

[00:13:50] is a use case number one whereby you understand the intent of the employer, the organization and the interests of the employee and marry them together in a way powered by AI in a way that is precise, contextual and relevant and actionable.

[00:14:07] Example number two, a large life sciences customers that have a lot of content that needs to be consumed by the people that need an AI powered search discovery and recommendation tool for the precise content at the precise moment in the development journey for their employees.

[00:14:29] So in this particular case, we call it the problem of the plenty like too much of anything is bad whereby there is a plethora of content, several of them are relevant,

[00:14:41] but how do we understand the context that as the adage goes when you search for Apple whether you're a fruit farmer or a technologist, it will determine what such results that you get.

[00:14:50] In a similar way, if we understand the skills of the employee, the context in which that employee is working, the associated perimeter around that employee on what their peers and coworkers are searching for at any given point in time.

[00:15:07] You have the right metadata tagging within the content that they are searching for.

[00:15:11] You have AI that is able to sniff the content and with all of this, it is precise in its relevance in not only surfacing the content but surfacing the answer what that the employee is looking for.

[00:15:26] So in other words, just giving videos or PDFs to watch if it says that you are looking how to solve this particular problem, here's your answer. If you want to click deeper, here are the most relevant pieces of information that you need to do.

[00:15:41] That is a true companion. So that truly helps people discover, curate, create an action the most intelligent content in the most intelligent fashion in the most productive way. So that is example number two of how that manifests itself. An example number three is what I had mentioned.

[00:16:02] A company that is in the process of strategic workforce planning trying to understand what is their talent strategy investment and what are those returns. Has that, those returns manifested themselves in performance?

[00:16:16] Do I have an understanding of upskilling that is happening at an organizational level, a business unit level, a geographic level, at an individual level on what are the desired skills? What are the actual skills?

[00:16:29] And if those, the skills and the proficiencies are constantly on an upward path depending on your investment into your talent development strategy. Now provide CEOs, CHROs and CFOs, foresight and insight into their strategies.

[00:16:46] And we know through research that about $8 trillion globally is left on the table by virtue of not having the right skills to fulfill the business strategy there.

[00:16:58] We know there is a $5 trillion impact due to attrition because there is an expectation gap between what the employees want and what the employers have in terms of learning growth development and mobility.

[00:17:11] Combine these two, there's a $14 trillion approach that purely can be if not solved but at least enhance, enable and mitigate it via responsible application of AI and generative AI. And that is what our Galaxy platform looks to solve. You know what do you look at?

[00:17:34] All right, I want to talk to you for a moment about retaining and developing your workforce. It's hard. Recruiting is hard. Retaining top employees is hard. Then you've got onboarding, payroll, benefits, time and labor management.

[00:17:48] You need to take care of your workforce and you can only do this successfully if you commit to transforming your employee experience. This is where Isof comes in. They empower you to be successful.

[00:18:00] We've seen it with a number of companies that we've worked with and this is why we partner with them here at WorkDefine. We trust them and you should too. Check them out at isolvedhcm.com. New offerings that vendors are coming out with based on AI.

[00:18:18] It seems most of them really do boil down to improved efficiency and higher productivity. Do you see any examples or do you see in the future a time when the AI actually improves the output?

[00:18:36] Not just of the technology itself but also of the team, the person who's using it. 100%. Maybe I can rewind back. One of the things Mark that every example that I had used thus far, whether it is the fulfillment of the role versus skill mapping,

[00:19:01] whether it is the right content at the right time in a development journey for a person or whether it is the visibility gap into skills that have one to need. In each of these, the ultimate solve is the business outcome.

[00:19:17] We have a 14 trillion workforce readiness gap that we are looking to solve for. Productivity. Think about all of the HR and talent professionals or for that matter business professionals that spend a lot of time in sifting, mining and understanding data and extracting the requisite knowledge.

[00:19:36] It is fundamentally a knowledge gap challenge that completely gets resolved by artificial intelligence. You reinvest all of that horsepower and the mind share from assimilating knowledge to applying intuition, instincts to solve bigger business and frankly world problems. That is thing number one.

[00:20:02] There is a direct productivity impact there. Number two is we often overlook in terms of business skills. We are stuck with org structures and we are stuck with hierarchy. So we prioritize title over talent and structure over skills.

[00:20:19] If you decompose that and that is a say, so the first one is a productivity challenge. The second one is a business opportunity challenge. You have a business opportunity to deploy data scientists to understand geological impact somewhere. So for you to have your strategies there towards clean energy.

[00:20:40] Your data scientists need not come from that org and the department who knows exactly who reports to that particular manager. Your company may have people that are highly skilled with transferable or adjacent skills as we call it to be in a position to solve that business problem.

[00:20:56] But your current paradigm and your current structure and your job architecture may not allow that democratization of problem solving across boundaries.

[00:21:06] So the jobs to skill architecture on who are the skilled people that I want at given point in time to solve that particular problem becomes a huge competitive advantage for someone who is in a position to have access to that data.

[00:21:21] So one is moving from knowledge to intuition. Two is going from jobs to skills with the power of AI to unleash net new business potential and three is frankly employee morale and engagement.

[00:21:35] The ability to leverage the power of artificial intelligence to drive engagement to drive business performance that in turn manifests itself as productivity output or engagement output or increased stop line.

[00:21:51] Is also a massive advantage including early warning systems around retention, early warning systems around growth and development and upskilling promoting top talent etc.

[00:22:02] And I just gave three examples of our own customer base the 7000 customer base and 125 million employees that we touch in the world and sure there are numerous more that could harness the power of artificial intelligence.

[00:22:17] You know we've been talking a lot about sort of strategic things, you know over a few things. So my last question but I want to really get this down into the weeds.

[00:22:27] At some point somebody in your customers organization has to make a decision that they are going to buy a system. Somebody in an organization has to make the decision about what they're actually going to buy.

[00:22:43] Now most of the talk that seems to go on about it what you've been talking about and also sort of the organizational advantages that it can bring. How do you think companies in the procurement people the executives who have to sign off on the deal.

[00:23:01] How are they looking at it and making their decision that they're going to pick say your system over somebody's else. How do they measure the solution.

[00:23:13] Yeah that's a really good question. First and foremost when I talk to customers whether it is our existing customers or prospects it is seldom about the tool of the technology right at least not at the starting point.

[00:23:28] It is about the value that it creates for them and that value is typically in terms of increasing their top line growth by accelerating their strategies through people development and growth.

[00:23:42] It is by bottom line productivity where people are in a position to you know manufacturing lines stop when people are not in a position to get certified on a particular activity that they're supposed to do right.

[00:23:56] So a very seamless intuitive workflow to not stop this to enhance their productivity is the second big thing that I talked to our customers about and three is overall engagement morale and performance.

[00:24:10] The drivers that they need within their organization to improve retention improve performance improve workforce agility substantially drives their both top line and bottom line because you have a much engaged workforce.

[00:24:22] The translates into a much more productive workforce that translates into top and bottom line impact to them. So first and foremost AI or you know workforce agility platform whether it's learn or elevate or talent marketplace aside.

[00:24:37] It is about business outcomes and value creation for each one of these so that fundamentally resonates number two how are you doing this we go through a fairly detailed there are three things that are most important the first and foremost is it's human centered digital.

[00:24:52] So the first thing is how do you design which means that you are designing your designing products for the person behind the professional your form factors are appealing they're highly intuitive and they can get their job to be done gets done as quickly and as frictionlessly as possible.

[00:25:07] Number two is responsibly leveraging the power of data I'll come to that in a minute and three is solutions that plug and play with their wider ecosystem right but with AI or otherwise people do not want to be locked in they do not want it to be in a wall garden they wanted to be a playground.

[00:25:28] They want to future proof their investments and fundamentally we share the road with our broader ecosystem because it you know we know that our Galaxy platform is part of a larger universe.

[00:25:39] So those are the three things in addition to the three sets of value creation of top line bottom line and engagement and productivity that fundamentally resonate with the buyers.

[00:25:48] Now the next big portion that is very important and I fundamentally think we should play offense with it and not talk about it is the ethics governance and responsibility of AI.

[00:26:02] And this is a big topic in the minds of the buyers, not just the CIOs and the information security team members but I think as humans everyone wants to do right by each other which means bias reduction is a big part right like even if it's just a big part of the business.

[00:26:18] So with our own skills matching or job description capabilities, simple examples like salesman versus salesperson matters.

[00:26:28] Number two is human in the middle right we always want to have a eject button whereby a human is able to monitor the progress appropriately and there is nothing that is irreversible you cannot put the toothpaste back in the tube right.

[00:26:41] You do not want that kind of a scenario at any given point in time. Number three is explainability it is very easy with swats of data to happen in such a way that people just have to you know live by the recommendations versus challenged recommendations understand it and feed it back into the system.

[00:27:01] That explainability with the human in the middle with the privacy security governance you know data lineage etc are the three big things that our customers are most concerned about. Well Karthik thanks very much this has been really interesting and I appreciate your coming back.

[00:27:20] My guest today has been Karthik Suri Chief Product Officer at Cornerstone on Demand and this has been People Tech the podcast of workforceai.news we're also a part of the work defined podcast network you can find them at www.wrkdefined.com.

[00:27:53] To keep up with AI technology and HR subscribe to workforceai today we're the most trusted source of news in the HR tech industry find us at www.workforceai.news.