This episode features an interview with Rajamma Krishnamurthy, Senior Director and Leader of Enterprise AI Strategy at Microsoft. Rajamma has over two decades of experience empowering human resources through technology at Fortune 100 companies. She has led large scale digital transformations and has managed teams across the globe. In this episode, Amanda sits down with Rajamma to discuss enabling HR through AI, tackling biases, and improving the employee lifecycle with AI.
This episode features an interview with Rajamma Krishnamurthy, Senior Director and Leader of Enterprise AI Strategy at Microsoft. Rajamma has over two decades of experience empowering human resources through technology at Fortune 100 companies. She has led large scale digital transformations and has managed teams across the globe.
In this episode, Amanda sits down with Rajamma to discuss enabling HR through AI, tackling biases, and improving the employee lifecycle with AI.
-------------------
“Think of AI as your caddie that's going to walk in with all of your golf clubs. They will even tell you which iron to take out and hit the golf ball with. But, you are the one that needs to decide which iron and where, how fast and how big you hit, and you need to make that hole in one. AI is going to be of tremendous help in all the burdensome aspects of your work. But, you have to take whatever AI gives, you have to judge it and you have to make a good judgment call based on that. And you have to then implement it in your area. I feel like there will always be humans in the middle of everything that we do.” – Rajamma Krishnamurthy
-------------------
Episode Timestamps:
*(02:09): Rajamma explains her new role at Microsoft
*(04:04): Segment: Story Time
*(06:43): Segment: Getting Tactical
*(07:03): How AI enables the HR space
*(13:09): Segment: Ripped From The Headlines
*(13:35): Rajamma’s stance on AI taking away jobs
*(17:07): How to deal with biases in AI
*(24:39): Segment: Asking For a Friend
*(27:03): How employees feel about AI in HR
-------------------
Links:
Download the Algorithmic Bias Safeguards for Workforce
Connect with Rajamma on LinkedIn
Connect with Amanda on LinkedIn
Amanda Berry: Rajamma, thank you so much for joining me again today. How are you?
Rajamma Krishnamurthy: I'm very well. Thank you, Amanda. Lovely to see you again.
Amanda Berry: Yeah, it's lovely to see you again too. It's been about a year and a half, I think, since our last podcast together, and I'm so glad to have you back. We've got a lot of great stuff to talk about, including AIin the HR space.
Amanda Berry: So the first time you were here, like I said, it was about a month and a half ago, you were the Senior Director of HR Technology. Now you're leading Enterprise AI, you're the Senior Director Architect AI. Tell us about your new role and what that entails.
Rajamma Krishnamurthy: So that's interesting. Obviously have been doing HR for far too long for, I remember it been over, I think 20 years or so since I've been in HR technology.
Rajamma Krishnamurthy: First as a developer, then later as a product leader in that space. And what happened over the last six months? AIis not new. I think everyone knew what AIwas and then suddenly the whole open AIhit and the chat G P T hit and AIbecame the talk of the town, and it was. Became obvious that where AIwas like lurking in the shadows and doing a, a whole lot of things that we know in our daily lives, suddenly it's now taken to the center stage and especially when it comes to enterprise.
Rajamma Krishnamurthy: And so you'd ask me specifically what, why did my role change, you know, what happened? So obviously like everything else, Microsoft recognized that as part of being a leader in the AIspace, also recognized that enterprise AIneeds a lot of attention. So within Microsoft, there is now an, I would say, whole experiment underway to understand how AIwill play in the enterprise and how we can now foster both employee experience and productivity through ai.
Rajamma Krishnamurthy: So over the last. I think it's been four months now that I've been asked to step into a role, which is more about an AIcenter of excellence. It's almost like a nerve center for looking at everything that we need to do in the enterprise with the ai. And so within Microsoft, obviously whatever we do, we will also talk about it outside of Microsoft as well.
Rajamma Krishnamurthy: But we start here at Microsoft to be our own guine pig of all the things that we do in ai.
Amanda Berry: Well congratulations on that change in role. So I wanna move into our segment story time. Welcome
Rajamma Krishnamurthy: to story time, story time, story time. Lemme give you a story
Amanda Berry: sort of back up quite a bit and talk about that employee experience in ai. As you said, it's not new, it's been around, and I'm wondering if you have an opinion on why there's been more of an emphasis on. Employee experience in the last few years,
Rajamma Krishnamurthy: you know, what happened over the last three years and if you count to the time just before 2 20 20, and you know what happened with the pandemic and the idea of where people work.
Rajamma Krishnamurthy: How they work and when they work has changed quite considerably. I mean, it's not all the roles I would say. I mean, there are some roles that need to be hands-on and in the office and in the place of work, but there are quite a number of roles that now are very remote and you know, you saw during the pandemic that it, they were pretty successful as well.
Rajamma Krishnamurthy: So what has now changed is now that there is no office. And there is no cooler to talk about or you know, or where people can look into people's eyes and have a conversation. How do we ensure that people are engaged? How do we ensure that there is a sense of belonging and that there's a sense of community?
Rajamma Krishnamurthy: And with that comes engagement. And with engagement comes productivity. And so there is obviously every. Our corporation out there that is employing people would want to have their employees happy and productive at the same time so that they can get their bottom lines going. So that is why there is such an emphasis on employee experience over the last three months, three, three years.
Rajamma Krishnamurthy: More so than before because there is a sense of recognition that it is not just good enough to have people employed. It's not just good enough to have hybrid workplace in place. It is not just good enough to know that there are teams. It's has to be more than that. It has to be how do we enhance both the employee engagement and employee performance at the same time, which are either way interdependent on each other, and that will actually overall increase the productivity of them, which in turn will, you know, affect the bottom line.
Rajamma Krishnamurthy: Yeah,
Amanda Berry: it feels like employee experience is really starting to become a differentiator that companies are looking for going, here's why you wanna work here. 'cause here's our experience.
Rajamma Krishnamurthy: More important thing is talent is also up earth, right? Skilled people are not easy to come by. Even if when people talk about, you know, economy that is not going so well talent, it's still, it's very hard to get good skilled people in certain areas and so on.
Rajamma Krishnamurthy: So people want to be the corporations and companies want to make sure that talent doesn't leave their shortes in a way. So,
Amanda Berry: yeah. Let's move into our next segment. Getting tactical.
Producer 1: I'm
Rajamma Krishnamurthy: trying to figure out tactics and to be perfectly honest, and I didn't have to worry about tactics too much, here I am in charge and trying to say, why did you sleep through tactics?
Rajamma Krishnamurthy: Tactics.
Amanda Berry: I wonder if you could just give us a, an understanding of how AIworks in the HR
Rajamma Krishnamurthy: space. Gosh, where do we begin? I think AIis a little bit ubiquitous when it comes to HR space. I think I read this in some recent research on I D C from I D C, which said they researched about 2000 companies and they said about 80% of the companies will employ AIin some form or the other in the, in their HR space, ai, and or ml.
Rajamma Krishnamurthy: So as we know it, to further foster. The employee experience or, you know, ensure that they have great hires and everything else. So from a talent perspective, there is a great deal of interest in bringing AIinto hr. So what does this mean from. When you look at hr, I would start at the very beginning. This answer is going to take a little bit of time, so kind of brace yourself here.
Rajamma Krishnamurthy: Absolutely, I'm ready. Okay. So from the very beginning when jobs are advertised and people are contacted, or people are reached out to those communications that happen to source the right kind of people into your jobs, And the jobs, creating the jobs themselves, you know, the writing the jobs themselves, and to ensure once when people come onto your sites to look for jobs or apply for jobs, how do you make it easy for them?
Rajamma Krishnamurthy: Through recommendations, through ai. How do you ensure you can screen the uh, folks? In a quick and a more easier way so that you can get the right people to the next levels of conversations. And then when the interviews happen, how do you, you know, ensure that you kind of quickly react and go get the feedback summarized, but also have a way to reflect upon the way you interview people as well.
Rajamma Krishnamurthy: Because when humans interview other humans, are we consistent? You know, get tips back and be a better interviewer and have better conversations with interviewees in order to kind of continue to. Accelerate and foster that relationship as well. So then, then you get onto offer being automated through ai.
Rajamma Krishnamurthy: Then getting into the validation of background verification to helping the employee onboard through very quickly, through ai, keeping them warm through the conversations through ai. Um, making sure that once they're on board, how do they get them through induction, the training, the connections through communities and through people.
Rajamma Krishnamurthy: All of that, through ai. And then, you know, talk about performance. Imagine if you can write your own employee performance review. I. With a lot of ease by collecting information across the world of work through AIthat you don't have to, you know, sit down and take notes through a year. I don't know how, however long people take to write their own performance, to have it consolidated in a beautiful way for you so that you can take a look at it and help write it better or make some changes and you are ready to submit your performance review.
Rajamma Krishnamurthy: Then within the company itself, how do you. Making sure that you have benefits and wellbeing that are being suggested to you in a good way throughout the day, throughout the work week, or what you have, whether it is information about what some changes in your life or some changes in your work that you've helped along the way through ai.
Rajamma Krishnamurthy: You don't have to remember the thousand URLs that that going into. Kind of going to access anything within the company that a question asked is a question answered and a task completed very quickly from a productivity perspective, then learning and then mentorships and connections and engagements through AI.
Rajamma Krishnamurthy: And la. Last but not the least is the. Conversations when it co comes to, if you do decide to leave the company, then how do you have a very nice offboarding? Because offboarding is as important as onboarding because you might be a talent that won't come back to this company. And then, uh, of course keeping in touch even after you left.
Rajamma Krishnamurthy: 'cause you are the brand ambassador for this company and you're going to help land more people and you are more of your products within the world. So, I think I'm, I've probably left out quite a few things in between, but that's how I see AIlike everywhere. Pretty ubiquitous in hr. When I
Amanda Berry: was listening to you give that answer, what popped in my head is it sounds like a HR using ai, AIwill benefit and touch every part of basically the employee lifecycle experience.
Amanda Berry: I mean, you went through a a lot there. Are there any areas where it's more critical that AIwould be more beneficial than others?
Rajamma Krishnamurthy: I think one of the things that I do believe, it all depends on who does it benefit as well. If you focus on employee experience first and foremost, then ensuring that the employees can get access to any questions that they have through their work life and life at work Answers.
Rajamma Krishnamurthy: Regardless of whether it's HR or otherwise, make it easy for them through some conversation and quickly completing their task. That will be the most valuable to an employee. That'll also reduce a lot of operational costs for the company as well. That's a critical one. Then there are sourcing the right talent for your company where you can use the AIto figure out.
Rajamma Krishnamurthy: Who are the right people Keeping in touch with communications are another way and other areas are like within the company itself to make sure that you're constantly, uh, keeping an eye out for the pulse of the employee engagement and having action suggested to you both as an organizational leader or line manager or even an individual to figure out how to be more of engaged and a thriving employee rather than just kind of an employee that's working for you at this company and so on.
Rajamma Krishnamurthy: So these are some of the things where, you know, I, I specifically focus on employee experience and employee engagement for sure. And, you know, bringing the right talent in and keeping the right talent in as the critical areas for ai.
Amanda Berry: Is there anything that you have found so far as you're implementing this at your own place of work that sort of stood out to you, that surprised
Rajamma Krishnamurthy: you?
Rajamma Krishnamurthy: Not, I would say surprise to me, but I was delighted by how much and having things like open AIhelp you create content very easily or, you know, correspond and, you know, summarize content very easily has been. I. Has been a great delighter. I would say I was expecting it, but I wasn't expecting the such beauty in, in those things.
Rajamma Krishnamurthy: So that has been a great experience
Amanda Berry: for, well, let's move into our next segment. Rip from the headlines. You hear the news, actually. Actually read all about it.
Rajamma Krishnamurthy: Our stories ripped
Producer 2: from the headlines. Ripped from the headlines. From the
Rajamma Krishnamurthy: headlines.
Amanda Berry: From the headlines. One of those answers we just spoke about all of the ways that you can use AR to to save time and write position descriptions and help.
Amanda Berry: Create, you know, your performance review content. So there's a lot of people out there. One of the biggest conversations happening is about worrying that AIis gonna take their jobs. So someone in HR might be hearing this with a lot of concern that, oh no, it's gonna do everything that we do. It's gonna take our jobs, and I'm wondering what you have to say about
Rajamma Krishnamurthy: that.
Rajamma Krishnamurthy: The jobs will change and it'll change for the better in my mind. And the reason is that think of AIas your caddy that's going to walk in with all of your golf clubs. They will even tell you which iron to take out and hit the golf ball with. But you are the one that needs to design with which iron and where, how fast and how big you hit.
Rajamma Krishnamurthy: And you need to make that hole in one. So Ian's going to be of tremendous help in all the burdensome aspects of your work, but you have to take that, whatever AIgives, you have to judge it and you have to make a good judgment calls based on that, and you have to then implement it in your area. There will, I feel like there will always be humans in the middle.
Rajamma Krishnamurthy: Of everything that we do and that the only thing that different about, as I said, the way the work will get done is basically about how they will learn, how to interpret what AIis producing, how to make the right judgment calls based on what they see and what they hear coming back from any outputs from ai, and how do they then make use of it in the best way.
Amanda Berry: Yeah, I've been hearing a lot about that too. Like, you know, you need to learn how to use ai. It's gonna enhance your job. So that's quite a bit of the conversation that's going on. So with everyone talking about this, there's good stuff and then there's this bad stuff. I'm wondering if you could walk us through and maybe a couple examples of successes that you've seen in a couple, maybe pitfalls where you've seen AIhasn't lived up to its potential.
Rajamma Krishnamurthy: I'm going to mix, give you some daily examples of successes that you've seen, and I will use the same examples to shine on the pit pitfalls as well. And that's where the judgment calls comes in. I'm not even gonna talk about a HR take. Your texting that you use on your phone gives you suggestions of words, and you know, sometimes it just doesn't listen because it'll keep suggesting the word that you don't want it to suggest.
Rajamma Krishnamurthy: And so you are, before you hit that send, you're going to have to take a look at it. The text really meets. Sense, and then you hit that send, right? So you are using AIon a daily basis. It is helping you in natural language processing. It is helping you do your stuff better. That's the same way everything will work in terms of HR as well.
Rajamma Krishnamurthy: For example, if they, there are a hundred candidates that are applying for a job. I'm just coming up with an example that I have seen in the industry. And then it'll go, it's going to match it with your job description that you have created, which has been held by AIas well. And then it'll rank those jobs against the job description or give you some ideas about why one is better than the other, and summarize that for you.
Rajamma Krishnamurthy: Then you'll have to still make a call. Sometimes, you know, you go with your guts rather than with the facts. So there's a combination of facts and guts and human intuition that you'll need to bring in, make those decisions. So I would say that instead of talking about the good and the bad and the ugly or anything like that, there is always goodness in anything that AIwill bring in.
Rajamma Krishnamurthy: But the ugliness will come when you're not like paying attention to the details from the. Of how you have implemented it, what data you have used, and what data that your, your, the outputs are. And if you're blindly making decisions based on that, I mean, you should let the human intelligence still prevail over and above the AIis what I'm trying to.
Rajamma Krishnamurthy: Yeah.
Amanda Berry: No, that makes sense. I like that. Being able to rank job candidates based on a, a position. I know this is something that I've read about and then I'm just love to have your expertise. If you could shed some light on it. The fear of AIin that, let's say in that particular example, creating it and having its own set of biases when working, let's just, even in the HR space,
Rajamma Krishnamurthy: I mean, this is a topic that's very close to my heart, and I think the reason that it's close is because like anything new, any tools, any accelerators, any biases that we, any patterns that we used to have will just get enhanced and, you know, amplified.
Rajamma Krishnamurthy: It's just whatever was happening. One or two or a hundred cases now can happen in thousands because of the acceleration you might get from these tools. So biases don't happen just because they happen, right? Like some are called conscious biases, some are unconscious biases. And so one has to kind of like everything else, make a lot of effort to make sure that that doesn't happen.
Rajamma Krishnamurthy: And that starts with the fact that you almost need to start with a question now as to whether do we really need AIto implement? Whatever we are trying to implement here, it's not a one size fits all. We will just bring AIto everything. So AIis also something, it's a tool that that is powerful, should be used in a very thoughtful manner as well.
Rajamma Krishnamurthy: So you need to start with, should I use AIhere? If I use ai, what data that I'm bringing to train the model and is the patterns of. The past already biased. Have I always hired, for example, male engineers and have been ignoring female engineers and so on? Is that pattern going to continue if I use the same technique or the pattern to train the model as I'm testing these out and am I being very transparent to the end user that this is a AIrelated.
Rajamma Krishnamurthy: That it's coming out of an ai, whether it is a candidate that is getting recommendations or whether it is the recruiter that is looking at the list to say that, Hey, this is AIrecommended, please take another look at, you know, everything before you make a decision, because you might want to have your own opinion.
Rajamma Krishnamurthy: Don't just take it at the face value and so on. And then always, always put in a lot of methods to kind of catch things about bias, even after you go into production and make sure that it's a continuous thing, whether we like it or not, the outcomes. That has been, whether you use AIor whether you use human beings to do one thing that manually like they have always done, or even through the traditional ways of computing.
Rajamma Krishnamurthy: The outcomes are the same. The regulations that have been established by countries, by states, by group of countries, like EU and other things, those regulations still dictate that you be fair, inclusive, and transparent to your overall process. And so that just remains so, just because it's ai, it's now that a lot more regulations are coming into play and we that continue to happen as well.
Rajamma Krishnamurthy: So those are some of the things that, from a bias perspective, you gotta be. Careful how you implement the ai, but you also need to be very, of the continuous regulations that are coming in from the various government bodies that you need to, we'll be audited, you'll need to be transparent and all of the other stuff related to ai.
Rajamma Krishnamurthy: I
Amanda Berry: wanna move on and talk just a little about the ethical concerns, and we're picking at those now because a lot of people are also concerned about, you know, other ethics issues with ai. How are you thinking about using AIin an ethical
Rajamma Krishnamurthy: way? Similar to what I just described, which is always be conscious of where you are using it, why you're using it, and if you're using it, testing thoroughly, making sure that it's not only biased from making in, if, especially if you're using it in recommendations and decisions.
Rajamma Krishnamurthy: Are we being conscious about, are we putting other human being in between or are you making sure that there is another checkpoint that you know that it doesn't? Take the wrong decisions for you. Bias can also come in language. Is it using the right kind of language? And are there any chances of it coming through as any kind of abusive language or otherwise, or even discriminatory language.
Rajamma Krishnamurthy: You know, it may not necessarily call, we can't, you don't have to call it abusive, but sometimes a word or two may mean something to some other, uh, culture, and it means something else to other culture. So being careful about all aspects of those will need to be followed through when it comes to ethics.
Rajamma Krishnamurthy: It
Amanda Berry: sounds like we shouldn't just go on autopilot. When we use ai, we still have to be very present and evaluate
Rajamma Krishnamurthy: what we're looking at constantly, especially after you go into production, to be on constant lookout for what the outputs that you produced. You have to do an analysis of whether are we doing the right things?
Rajamma Krishnamurthy: Are we doing the right things over and over again? I think it'll continue to evolve. There are plenty of tools and organizations and methods available in the market, and even free from non-for-profit agencies that are focused on ethics. I can send you a list that you can post along with the podcast if you wish, but those are all very valuable things for people to learn as they think about ai.
Rajamma Krishnamurthy: It doesn't matter whether in HR or otherwise. AIwhen it comes to affecting human beings and decisions that we make about them is very, very important that we, we take a look at that. Yeah, we'd like to
Amanda Berry: post some resources and that we can point our listeners to regarding AIethics and best practices. Is there, are there a couple that really stand out in
Rajamma Krishnamurthy: your mind?
Rajamma Krishnamurthy: There are a few, um, there are data and ai, especially universities have done a lot of good work. The New York University has done some work. University of Washington has done some work, and I know of some private concerns that are publishing a lot of things related to ai.
Amanda Berry: Is there a topic related to AIethics that people aren't really paying attention to that you think that should be, get a bigger spotlight on it?
Rajamma Krishnamurthy: I would specially say there are a lot of companies and small vendors that have started, you know, you come bringing in AIand algorithms and so on. I do understand it's going to be very difficult for them to be transparent about how they're arriving at a particular solution or anything. As I said to you earlier, the regulations about whatever outcomes that you derive, whether you use AIor not use AI, are the same equal employment opportunity.
Rajamma Krishnamurthy: Rules haven't changed in, I think since 1978. The the same outcomes are, uh, always be required. Whatever tools you use. There are some new regulations coming through like the one in New York where you know you have to. Every company that is using AIwill need to audit its processes to make sure that it's transparent and inclusive.
Rajamma Krishnamurthy: What's not being talked about? The is the fact that whatever AIyou implement, you become the owner of that process. So it doesn't matter if you're engaging with another company to kind of implement. Let's say you are engaging with the company to implement a. New hire process within your organization or a new interview process within your organization.
Rajamma Krishnamurthy: All of those companies are doing what they can, they should to kind of ensure bias, you know, any kind of bias in issues and all of that, but you become the owner. You are responsible for whatever happens in your company, and so there are these organizations that are giving you a great deal of guidance on how to engage with these companies.
Rajamma Krishnamurthy: What kind of questions do you ask? How do you prevent yourselves from breaking into jail? By not following some simple guidelines I know of asking the right questions about what AIpractices, what bias. What outcomes could come? How did they train their data in the first place and so on. So you don't wanna be caught afterwards trying to explain what's going on.
Rajamma Krishnamurthy: You need to be talking about it before you implement these systems in your company. So that's where the ethics play comes in a lot more. So people talk about it, but it's not openly said like, you know, Hey, you are responsible, so better be pay attention to it. Absolutely.
Amanda Berry: Let's move into our last segment.
Amanda Berry: Asking for a friend who's asking for
Producer 1: a friend.
Rajamma Krishnamurthy: Hey. Asking for a friend. Asking for a friend.
Amanda Berry: We just spent a good 10, 15 minutes talking about ethics and concerns. Let's move into more positive. What are you most excited about right now with ai?
Rajamma Krishnamurthy: If we can get employee experience and employee productivity taken care of through ai, that would be the most exciting part of ai. What is interesting, over the last few years, there have been multiple ways that companies have tried to create the employee experiences through, let me give you a single portal to go and get whatever you need.
Rajamma Krishnamurthy: Let me go to a single place, this whole one stop shop that has been talked about. Can we finally realized through AIyou can actually have AIgo do all the grunt work to go figure out what the answer is. Whether it is the answer lies in a policy answer, but it also be, can be made a very personalized answer.
Rajamma Krishnamurthy: So if you're asking specifically about, let's say, I want to take a family leave or something like that. Then knowing that you are in the United States, knowing that you have spent so much time in the company giving you the right answer with a, with an ability for you to quickly complete a task here, do you wanna apply for the family, leave from when to when, and these are the five steps you need to do in order to get that, to be able to guide that employee through in a very quick way.
Rajamma Krishnamurthy: It's great because today if I have to do that in any company, it'll probably take me hours, if not days, to get something like that done. What if you can get that done in five minutes? Then you are done with that and you're walking away happy getting that answer that you need, completing the tasks that you wanted to, but you can get going with the rest of your day, which is working for the company.
Rajamma Krishnamurthy: So having these delightful, productive, valuable experiences from the get go, from the time you're a candidate to even to the time that you're an alumni. Is the most exciting part of ai, which is the conversational ai. That ability of the AIto be able to have that conversation with you, to be able to predict and understand and predict your intent as you're asking those questions is gonna be very, Yeah.
Amanda Berry: And what are employees saying as they're interacting? I'm thinking like on the other side now we've been talking about implementing and using it from the back end. What about that more employee facing side? What are employees feeling or thinking or saying about using some of this technology? I.
Rajamma Krishnamurthy: It's very interesting.
Rajamma Krishnamurthy: Some research that I just read recently has been like more than 80 to 90% of the employees are like, regardless of the companies are excited about AIand how they can use it in the workplace, but with excitement. You can have excitement, but can also have the fear. You know, you talked about the fear earlier on.
Rajamma Krishnamurthy: What will it mean to my own job? How will it like change it? Change is always scary and so what changes will it bring and will I be prepared for that? Those are some of the things that, you know, about 50% are still going through that time, will cure some of this and then it'll, people have to make that effort over the next few years as things catch up in, in every aspect of what we do, not just at work.
Rajamma Krishnamurthy: AIis going to kind of show up in a lot of places that we interact with on a daily basis. Whether you, you're in a cinema hall or you know, watching, trying to watch Barbie and getting for that, or whether you are just buying popcorn or you know, Is gonna start showing up in ways that you never expected it would, and I'm seeing that already in a lot of ways in my daily life.
Amanda Berry: Yeah, we had a guest on a gentleman named Sean Randall. He said, and I love this line, he says, AIwon't replace you, but someone who uses AIwill. What advice would you give to someone looking to implement into their HR functions to help improve the employee experience? I would
Rajamma Krishnamurthy: always say start with getting educated yourself.
Rajamma Krishnamurthy: Understand what AIactually means and educating the people around you. Like when HR was asked to kind of start dealing with data and analytics, there was a whole moment to kind of educating HR on data. I think the same thing needs to be done with AIto be able to get every individual understand, what does this even mean?
Rajamma Krishnamurthy: What is one AIversus the other? Ai, what is ML versus natural language processing versus generative ai. Versus, you know, what is open AIor, or chat G p T and so on. So to understand the various aspect of AIand how it can be used. Then take a look at your own organizations where all you are spending most of your time, that if you could get that back, you'd actually spend that time in a better way.
Rajamma Krishnamurthy: Whether it is answering questions that is just looking at three different documents and answering a question. Or whether it is, oh, I would really like to like redo the strategy on something. So where is it that you would want to spend more time and that you can't get because you're spending time on things that you shouldn't be?
Rajamma Krishnamurthy: And so then those are the areas that we can very quickly go after. Look at the problems that you have in your organizations. Is talent a problem? Is, uh, understanding, uh, or, uh, the engagement of your team's problem Is teaming a problem? Is coaching your managers a problem? So figure out where all that you would think that you don't have necessarily the amount of resources that you would need to go change that problem to a solution and then start bringing in AIwherever you can to kind of subsist.
Rajamma Krishnamurthy: So that is a way to implement AIjust because a vendor comes to you and says, we can do this for you. Or, you know, while I, or the here is the fireworks may or may or not not be useful for you, um, because we are probably backing up the wrong tree. If you are implementing AIbased on a. What vendor is suggesting, you need to be very introspective when it comes to implementation of ai.
Rajamma Krishnamurthy: This is your chance to be a lot more introspective than you have ever been because AIneeds to be very strategic and very structured in your implementation, especially in hr, because the implications are far higher than anywhere else, so you've got to be very careful how you bring that in.
Amanda Berry: I love that idea of stop assess, like what your biggest issues are and then go look at AIthat could help solve those issues.
Amanda Berry: Well, what does the future look like? So, you know, any technology we have, you can look back 20 years ago and go, oh, those cell phones were big, or the cars were clunky, and now everything so feels so streamlined. What do you think the future looks like with
Rajamma Krishnamurthy: ai? I feel, and this is just me talking, like my own reflection on what's going to happen.
Rajamma Krishnamurthy: I think every job will be assisted with ai. Every job, there will not be a single role. I think that will be left without any kind of assistance with ai. I. There will be some jobs that, you know, over a period of time that will be totally replaced with ai, but then a new kinds of jobs will open up. For example, today any content that you create is con created for somebody to read the content.
Rajamma Krishnamurthy: It is not created for being summarized by AIresponding back, so the way you write the content is has to change. So you will need people to start thinking about, how do I want to get the answers? There might be tools to help you. That will be, you will be assisted, but then writing content will be different.
Rajamma Krishnamurthy: You are still the owner of the content, right? At the end of the day, policies are not gonna be written by ai. You'll have to write your own policies for the company. Culture will manifest itself in terms of how people collaborate, how people engage, and there needs to be some deliberate. Things that we need to do in order to, uh, use AIin those spaces and so on.
Rajamma Krishnamurthy: So yeah, things will change for sure. As you said earlier on, everyone will need to learn AIbecause you'll only be replaced with people who know ai, not do not buy AIper se. And like you're used to having your texts being half done and all you need to do is tap, you will. Just take it in your stride and then five years from now, people will stop talking about it.
Rajamma Krishnamurthy: The hype is now, but then once you get through the next five years, I think it'll just become part of our lives and there'll be the next whatever thing. I don't know what that is going to be, but there will be something else that'll lock Occupy the hype. Yeah, I didn't
Amanda Berry: even think about the text, sort of auto complete being a part of ai, but we're okay with that.
Amanda Berry: I know there's a few words that always of mind changes, so I think you have to go back, but that's a really great example. Thank you. So Mima, this has been a lot of fun. I know we're gonna keep talking about AIand its impact on business, whether it be hr, internal comms, you know how it fits in there. So we'd love to have you back maybe even in a year, or we can look back and go, Hey, I.
Amanda Berry: This is what we talked about. Now, what's different? Would you have any
Rajamma Krishnamurthy: interest in that? Absolutely. Let me know. I, I always like to talk about these areas, whether it is HR or AIor employee experiences or engagement and stuff like that. And more importantly, now I'd like to talk about ethics in AIand that's going to grow a multifold over the next few years.
Rajamma Krishnamurthy: The next few months even people are still trying to figure out what regulations they need to bring about and how do you actually even implement those regulations. Because you know, one thing is to have regulations. Another thing is how do you make it like hit the road? And so states and governments are trying to figure out what that looks like, but this is where HR needs to self-regulate.
Rajamma Krishnamurthy: How do we start thinking about it ourselves rather than any government agencies to kind of intervene on our
Amanda Berry: behalf? So, yeah. Yeah. Is there something they can be doing now? Be thinking about like in terms of self-regulation. Yeah.
Rajamma Krishnamurthy: They need to start learning about the outcomes have been changed, so the outcomes are still the same.
Rajamma Krishnamurthy: So as they interact, like I said, as they interact with these third party vendors and everybody else that bring in these solutions to accelerate whatever you're trying to do, the problem areas that you're trying to solve, be careful. And ask the questions that you need to ask. Go ask those questions. Be curious constantly and be watchful always, because whatever the mistakes of the past will just get accelerated and amplified with the numbers that you could actually get done with the help of something as powerful as ai.
Rajamma Krishnamurthy: Yeah, like I
Amanda Berry: said earlier, this is not the time to go on autopilot and let AItake over.
Rajamma Krishnamurthy: Yeah, that's why I think Microsoft calls it the copilot or the caddy or you know, talk about anything that will help you be better. But no, no need to have a takeover, the real just yet. Yeah.
Amanda Berry: That's great. Well, thank you so much.
Amanda Berry: This has been a lot of fun. Before I let you go, will you let our listeners know where they can find you?
Rajamma Krishnamurthy: Always on LinkedIn so you can find me. I am always connected and I'll respond anytime anyone wants to reach out to me.
Amanda Berry: Great. Thank you so much for joining me today, Rajamma. This has been great.
Rajamma Krishnamurthy: Lovely talking to you, Amanda.