Episode 179 Transcript:

Ramona Shaw [00:00:00]:

This is episode 179 on the topic of developing AI enabled leaders. Now, this is a bit of a unique episode. Different than what you usually get to hear on the Manager Track podcast because I am streaming here or I want to publish or share with you a panel discussion that I had on September 13, 2023 that was streamed on as a LinkedIn Live with three HR leaders. On the specific topic of developing AI enabled leaders, in which we discussed how organizations, specifically startups Series A, Series B companies are using and thinking about AI to help leaders with their leadership responsibilities. It was such a fabulous conversation. I wish we had another hour to dive into it that I wanted to share this with you here on the podcast as well. Whether or not you’re in a leadership position or you are in an HR role. The integration and intersection of AI and leadership and learning and development is big and is growing, as in so many other fields. And it’s really important for us to think about it and create the space and time to reflect and be interested in how other companies think about it and integrate AI tools along the way. Now, if you want to watch the conversation and not just listen to it, in case you are on a podcast platform right now rather than YouTube, then check the show notes and find the link, the direct link to the LinkedIn Live stream below. Otherwise I’m going to be quiet. Now there’s a quick introduction to the podcast and then we’ll dive right into the panel discussion. I hope you enjoyed this conversation, find it insightful, and also that it sparks some thoughts and reflections on how you might take some leadership or thought leadership here, or strategic initiatives on what to do with AI as it relates to learning and development or your personal leadership development. So let’s get started.

Ramona Shaw [00:01:59]:

Here’s the question how do you successfully transition into your first official leadership role, build the confidence and competence to lead your team successfully and establish yourself as a respected and trusted leader across the organization? That’s the question and this show provides the answers. Welcome to the Manager Track Podcast. I’m your host Ramona Shaw, and I’m on a mission to create workplaces where work is not seen as a source of stress and dread, but as a source of contribution, connection and fulfillment. And this transition starts with developing a new generation of leaders who know how to lead so everyone wins and grows. In the show, you’ll learn how to think, communicate and act as the confident and competent leader you know you can be.

Ramona Shaw [00:02:43]:

Welcome to this panel on the developing AI enabled leaders. My name is Ramona Shah. I am so grateful to be here and have this live panel today on this very important pertinent topic. I am joined by Velia, Jennifer and Bilal for this conversation. I’m not going to do the interest I actually want to hand right over to each of you to quickly talk about where you work at and what drives your interest in AI. And then we’re going to spend some time together today to really uncover what are the discussions like in 2023 about the technology, how it’s influencing your L and D conversations in your respective organizations. With a focus on the Series A, Series B, Startup environment and faster growing organizations, we’re trying to adapt and reap the benefits in terms of efficiency and productivity and up leveling the leaders in the organizations. So we have a really good lineup of questions here. I’ve prepared for us to talk about and address the topic of AI and leadership development and L D overall or HR aspects in more depth and really talk about best practice and current states of discussion. With that said, Velia, please introduce yourself briefly, and then we’re gonna hand over right to Jennifer and Pilaral.

Velia Murillo:

Thank you so much, Ramona. Hi, guys. Currently, I form part of the executive leadership team at Triple Music. As Ramona said, my name is Valia Murijo and I’m serving as the global head of People. As the first HR hire, I’m responsible for the successful creation of our HR operations. So building from scratch a structure that can continue to support our business growth, I lead the efforts and positive relations of over 100 plus talented folks internationally across culture and time zone, in languages in the US. Mexico, Armenia, Indonesia, Brazil, and Colombia. Treble Music Really Quickly is a fast growing music app in the world and the only licensed music service that offers on demand and offline songplay for users at no cost. Basically, Treble is an alternative to piracy for music listeners in emerging markets. Our Treble music app is currently available in Mexico, Indonesia, Colombia, Canada and the United States. And tell us briefly, what drives your interest in the AI space? Oh, that’s a wonderful question. For AI, I’m hearing both the excitement and apprehension of HR professionals while I find myself in the camp that is more open and appreciates the endless possibilities of what AI can offer, especially in our role, just making it more efficient. I realize that there’s other folks that are more on the worrisome side about what does AI mean, eliminating jobs or causing more conflict than positivity as far as confidential information. So I’m on the side that wants to ensure that leaders like us aren’t left behind. So that’s sort of what drives my interest. Thanks so much. Jennifer, how about you? Yeah.

Jennifer Ramcharan [00:06:10]:

My name is Jennifer Ramsharon. Thank you for having me. Today I am the Director of People operations, currently at Archaea. Archaea? We are in the personal care here, care and skincare biotech space. So for us, in the next month, we are launching a line of perfumes, and through DNA sequencing, we were able to bring back some extinct flowers. So the scents of those perfumes are these extinct flowers. For me, as a people leader, I’m really focused on efficiency, automation, using data to drive insights, scalability, talent acquisition and diversity. And I see AI playing a really great role in all of that as long as it’s used to the earlier points. Right. Smartly thinking about data, privacy, security. But I think it’s an enabler in all of the ways of pushing HR so we can get out of the space of just being task oriented and really being strategic leaders.

Ramona Shaw [00:04:24]:

And I’ve been in this field for so long now. It’s just a different perspective now. I’m just in a leadership role, but so what? And that is the biggest myth or misconception that will get in the way of people actually being good leaders. Because just as much as you invested in becoming strong on the technical side or on your job, the hard skills, if you used to say just as much of effort and thinking and investment should go into developing your leadership skills over ten years or so as you embark on that journey and beyond, by the way, it never really ends. But especially in the beginning, the skills required and the mindset shift needed in order to be a leader people love to work with do not come naturally. They will build slowly, if at all, on the job. And we’ve seen plenty of not so good at leaders or not ideal leadership to prove that point. There are a few really great leaders and they do stand out.

Ramona Shaw [00:07:11]:

Beautiful. Thank you, Jennifer. Bilal, how are you?

Bilal Azam [00:07:15]:

Absolutely super excited to be here with the team. My name is Bilal Azam. I run all things head of People and Talent here at Parade AI. Parade AI. We are a freight automation platform helping automate basically everything when it comes to booking trucks between shippers and carriers. We use machine learning, automation and AI ourselves for our platform. And so how does AI relate? To me, it’s part of what our business does specifically. So if we’re using it for our customers, seeing how we use that internally help kind of ten x our productivity, 100 XR productivity down the line. Something that’s very near and dear to us as people leaders and as a company as a whole. As Jennifer and Valiant both mentioned, AI is a tool, in my opinion. It has to be used the right way in the right circumstances. It’s not a replacement, in my opinion, for any job out there, more so it’s an ability for our employees to be able to level their roles up and then use AI to do those mundane tasks that maybe we don’t need to be doing anymore.

Ramona Shaw [00:07:41]:

They are called the blind spots because we’re blind to them. They’re the things that we think we’re really good or we’re doing really well that other people don’t find effective and we’re not seeing it. There may be biases that we have. We’re all influenced by tons of biases, cognitive biases that get in the way of our effectiveness. The point is not to try to not have any biases, our brains are wired that way. The point is to become conscious of our biases and then be able to interject and intervene when we’re about to display them so that we’re becoming a lot more objective. A very common one that comes top of mind right now is the confirmation bias where we may pay a lot more attention to information that confirms our original belief and our original view. So if we don’t have a sounding board, someone who’s reflecting back what kind of biases they observe, or we don’t expose ourselves to other people or conversations where we are confronted with our own biases, we’ll likely just continue with our biases.

Ramona Shaw [00:08:12]:

Yeah, so let’s dive in. The topic of AI has really taken over, right, with the introduction of Chat GDP back in November. And I think we all have gotten onto that or jumped on that wave for served away, been serving that wave for a while now and I feel this is a really good time to look at what has actually come out of it. Right? We’re testing with it, we’re learning about it, we’re seeing different use cases. And what is the status now? What is the state of the opinion or the state of mind in your organization? Briefly, when you look at research that came out in August by AMD who said that 67% of It leaders believe that AI can increase employee efficiency, which is interesting, and in fact, it always almost surprised me not to see that number higher. But again, that speaks to the fact that we have people more on the risk average side and being more mindful and cautious about the introduction and use of AI, as well as then having other people at the campus being optimistic and really seeing the benefits that it can bring to employees. Let’s start with you, Bilal. What’s the state that you’re in and how do you see AI intersect with the L D space or the HR space overall?

Ramona Shaw [00:09:30]:

I often talk to my clients about building range and options so that in any given situation and the people that you lead, you have more than just one go to tool you have now options. You may have three to four approaches that you’re familiar with and you can try in order to see what works best. And then also just feed the brain with information. If you are trying to learn how to, let’s say, play chess, you will naturally learn to play chess better. If you watch chess games, if you play chess games, if you read books about chess, if you watch YouTube videos or so forth about strategies or these reviews of games, you are feeding your brain with information about chess that will make you better. Or you might have conversations about chess with your chess buddies. Similar with leadership, the more you’re exposed to conversations around leadership, the better you will get. In addition to, of course, applying it, but applying it alone will be to slow this nail track.

Bilal Azam [00:09:35]:

We don’t want that. Again, everything that I just said is like any other skill. The same things apply for leadership as well. When we look at research here, and I just picked up one, there’s tons of research out there that would show you numbers in terms of effectiveness and productivity that increases. The one that I picked up and want to share here is by DDI. They said that companies who have implemented effective leadership development programs see a productivity gain of 36% and work quality increases by 48% plus. There’s an additional benefit. Not only will you become more productive and your work product, your effectiveness will increase.

Ramona Shaw [00:11:04]:

Absolutely. So for AI with us, we were pretty early adopters, I believe for Chat GPT as the first large language model and looking at many others along the way. In terms of adoption for us, we offer Chat GPT plus licenses to all of our employees who choose to sign up for it. It’s on a mandate. But what we do is we like to have some discussions around how we could use the tool, how leaders can use the tool. And again, that Ten x productivity is a phrase that we use a lot over here. How has affected the LND space for us? My belief is that we all haven’t finite amount of time that we can learn in or that we can gain skills in. And the options we now have are do we learn how to do that one skill, maybe it’s better writing ability or better communication ability, or how to do effective leadership, something like that. Or we learn how to use a tool that can do that job repetitively for us and other things on top. And so when you look at how it’s affected LND for us, my belief is that instead of learning how to do that one thing, let’s learn how to use a tool that can do that one thing and many others in that same amount of time. And so in that way you’re allowing yourself and your team to ten x their productivity because they know how to use a tool that can do so much more. So that’s probably been the biggest effect we’ve seen. There’s also other areas like other tools out there besides large language models. Things like tome. Tome is a presentation builder using AI. So using different tools like that allow us to build better presentations, better content, make learning a little bit easier for those who are visual learners versus written learners, another way of absorbing information. So AI has really become a big part of how we like to grow our team overall.

Ramona Shaw [00:11:06]:

That’s really interesting. It sounds like you’re really pushing the learning down to the leaders who say, like, we’re going to give you access, and each of you figure out how to best use it. And what are some of the tools? Is there a way for you to bring the conversation back together and have that knowledge transfer happening within the leaders in your organization?

Bilal Azam [00:11:26]:

Great question Ronald. That’s actually something that we just acknowledge ourselves as well. And so we are starting to do monthly manager meetups where we will have our managers come together and kind of share lessons. They’re not always going to be about AI, but anything around how they had better effective one on ones, how have they helped do their individual contributor level work while also being a people manager, how do they balance all that? And a lot of times AI will come into those conversations because of its productivity support. And so we like to use that as a single forum and then we also do town halls every two weeks and typically once a quarter. Twice a quarter we’ll have a section around new tools that we’re using or productivity increases that we can do and AIOs will jump into those conversations as well. We also like to promote our individual contributors to talk to each other, not just people leaders on this level, but those are typically the two main forms we have to share information.

Ramona Shaw [00:13:47]:

That’s really interesting. It sounds like you’re really pushing the learning down to the leaders who say, like, we’re going to give you access, and each of you figure out how to best use it. And what are some of the tools? Is there a way for you to bring the conversation back together and have that knowledge transfer happening within the leaders in your organization?

Ramona Shaw [00:14:45]:

And then the third aspect, the third pillar is around managing a team, especially advancing leaders who have growing teams often and people who have jobs and do things that you as a leader may have no knowledge about, right? So you’re leading someone with higher subject matter expertise. How do you manage that on a team level? How do you create connection on a team? How do you create a team spirit where people actually feel like I’m not an individual, even if remote or hybrid, we are a team. How do you do that? And then the fourth aspect is managing up and across. And we call this in the Leadership Advisory program their relationship operating system. So how do you build and cultivate relationships? How do you influence, how do you manage your stakeholders? How do you communicate across the different hierarchies effectively? So these are the four pillars. And if you think about each of them, what is a goal that you have in each pillar? How are you going to achieve that goal? What could get in the way and what kind of resources do you need? I would invite you to ask yourself for the four different pillars that we just talked about. What’s your goal? How are you going to get there? What could get in the way and what resources do you need? Now, last but not least, we want to talk about the question of the how. So how do you actually grow as a leader? What are the specific tools or formats to do it as well? I strongly believe that this is the most effective approach to leadership development.

Bilal Azam [00:11:26]:

Great question Ronald. That’s actually something that we just acknowledge ourselves as well. And so we are starting to do monthly manager meetups where we will have our managers come together and kind of share lessons. They’re not always going to be about AI, but anything around how they had better effective one on ones, how have they helped do their individual contributor level work while also being a people manager, how do they balance all that? And a lot of times AI will come into those conversations because of its productivity support. And so we like to use that as a single forum and then we also do town halls every two weeks and typically once a quarter. Twice a quarter we’ll have a section around new tools that we’re using or productivity increases that we can do and AIOs will jump into those conversations as well. We also like to promote our individual contributors to talk to each other, not just people leaders on this level, but those are typically the two main forms we have to share information.

Ramona Shaw [00:12:16]:

Love that I wanted to have like the Emoji clap emoji. I love those minutes around, roundtables or meetups very cost efficient way. Right. And to ensure that there’s this community and knowledge exchange. Jennifer, let’s hear from you. How is this working in your organization or what’s the state of the opinion on it?

Jennifer Ramcharan [00:12:37]:

Yeah, I would say as a company we have not really had the time to come together and really dig into this conversation. Right. Being a Series A, getting ready to launch a product, so we have not really defined what is AI and AI tools look for us, especially when thinking about data security and privacy. So we have not adopted it as a whole, but as a people operations team we’ve started to look into how it could help us specifically on LND with that continuous learning. So I’ve started to use it a little bit with course recommendations or putting together templates for how those continuous feedback conversations could happen. And then the goal will be to see how relevant the information we’re receiving from that is and then working with our legal counsel to really kind of put in some parameters in place. So we’re a little bit behind the curve in company wide adoption. I would say the area that we have adopted it the most is probably more on the talent acquisition recruiting side with Tap GPT and people GPT which has come out for more job description templatizing using it to ensure we don’t have bias language. Right. Using it kind of as our bias gender decoder. So that’s probably the area we’ve been the most successful in adopting yet.

No, I mean, I think it’s a great think. You know, when we think about the employee cycle, I can see AI playing a role right from the beginning. So we’ve talked a lot about hiring and recruitment, but it’s also using it for that onboarding experience. Some of the conversations that I have been having is that if we adopt this a little sooner and use it as part of our employee lifecycle, I think our leaders are set up for success when it comes to managing their teams. They’re able to create these individualized career paths and use it for continuous feedback. And if we’re being honest, that’s probably one of the areas we talk about a lot as leaders are we giving enough feedback and at the right intervals. And so even during my time of learning more about chat GPT and going into the functions of it and what it can do, it really can enable that feedback right loop at the beginning stage, day one for a new employee. So not only does that enhance and enable a leader to really make sure that they are connecting with their team, but it’s going to allow them to help really grow and upskill and up level their team faster, which in turn as a leader helps upskill and up level us faster. So for me, when I think about it, I really think about let’s get it right in the beginning, let’s make it part of this lifecycle and make it part of the journey not only for our leaders, but for everybody in the team.

Ramona Shaw [00:19:55]:

Did you see that? You mentioned the feedback. I think there’s huge potential in changing the feedback loop or the feedback cycles moving away from the very structured qualitative performance or anal performance reviews to build use AI for faster and quicker turnaround that can be immediately implemented as well. Bilal, where is your head at on this?

Bilal Azam [00:20:21]:

I believe so. Again, AI is a tool, right? And like Jennifer Leah, both have mentioned, it is something has to be used with some caution because you don’t want to put anything proprietary on there. All of it is their information, what you put onto their platforms. So I believe that for anything that is repetitive, that’s where AI can really come in and shape how a people leader can do their jobs. And what I mean by that, we talk about job description, talk about interview plan, we talk about performance feedback, we talk about onboarding. All of these things are great examples where these are things you’re going to continuously do as your team develops, as you have attrition, as you have chair, whatever that might be. You have to get better and better every single time. And so for me, AI has been a great tool for kind of gap analysis, saying, hey, here’s our plan today. Keeping it general, no proprietary information, but then from there saying, what are we missing? Right? What is something that could help enhance the employee experience of the employee onboarding? What could attract better people, more diverse talent to our platform? And so using it as an iteration tool is probably where I see the most support. Because we don’t know what we don’t know until we do it. And so AI can be that kind of it knows sometimes what we might not realize and bring us to that next level without having to make the mistake ourselves. So I think, to me, that’s probably the biggest fit for it is getting rid of the repetition tools and then do the gap analysis to iterate pretty quickly.

Ramona Shaw [00:21:40]:

Nice. Maria, how about you? These are such great ideas and great implementations. And I’m taking note, guys, I hope you don’t mind, I might wheel some of these myself. But one thing I would like to try to utilize Chat TPT and make the most out of it is, as we all know, managers are middle. Managers especially are super important for the retention of employees. And because, again, speaking of my experience in my company, we’re an international organization and cultures sometimes are different in the way we hear a message tones and wording and language. I’d love to figure out how to utilize existing Chat TPT. Or we have a talented group of engineers in Armenia that we’re proud of, that if time allows, speak with them about ideas, how we can build our own proprietary tool excuse me. To build out coaching mechanisms for our managers. So come up with scenarios, right? So we won’t use real names of people or places, but we can come up with scenarios and practice role play and give opportunity to ask managers to, okay, if I’m not available, I’m always available, 24/7. But if I’m not available, plant a scenario in Chat GBT, very generic. And plant the scenario that you’re facing right now and ask Chat GBT to be brief and concise. Because we know Chat GBT will go on and on for like 1200 lines. And just give me examples of how I can best approach the subject matter, how I can give feedback, how I can talk about positive or negative reviews. So basically a coaching mechanism. I think playing out role play would be great. My apologies. Another way I can think of is thinking about HR’s constantly repetitive slew of questions that come our way is also maybe again, proprietary. But build out our FAQs, the most popular FAQs in all parts of the world we’re in, for example, and make those translations and have them ready for day one of someone’s arrival. So those are just two areas that I think thinking outside the box, both employee and manager in development. Yeah, all of them. Such great little tips and ways that you’ve experimented with it. That are so easy to implement and try out. So thank you for sharing this. Now for Part B of that question, how does it influence or what do you see the future like in the intersection of AI and L D HR leadership development? If we dream big and we look at the real ability to personalize leverage mass amounts of data to create and optimize experiences, learning experiences, these coaching opportunities that we may see dreaming big. If we were to speak again twelve months from now, September 2024, what do you wish you would see or hope to explore further in that time frame? Let’s go back to you. I’m curious to hear where you see that going or hope to see that going.

Bilal Azam [00:25:04]:

All right, so, ideal state in twelve months, where do you want to be without AI? That’s a great question. I think it can go a lot of different ways when it comes specifically to people management, my hope would be to see all the mundane tasks, all the things that a manager doesn’t want to do besides the forge management and difficult conversations they have to have, all of that would be automated. Now, that is a dream state. I don’t think the AI technology is already yet, nor do I think adoption is going to be that quick. But to be able to see a manager truly able to focus on developing their team, pushing their team to that next career growth level, they want to be really focused on metrics like retention and productivity metrics and velocity, product velocity, things like those would be fantastic. As an example, I think a lot of us as people leaders and as middle managers might see that reporting could be something that takes a lot of time, right? Making sure that we have our project plans updated. Salesforce is updated. For our Sales team, whatever those tools are, they use, putting that work into making sure that they’re higher up so whoever has the visibility they need to do more metrics at a high level. If AI can take over those type of things, whether it’s chat GPT, using Zapier to integrate with Salesforce into a dashboard or whatever that might be, allowing those connections to happen and to read that data in a safe and secure way would be fantastic. Because then the team that’s hours a week that someone probably is using to update all these different data sources, if that’s con that’s time spent back into your one on ones, back into your personal L. D. Development, back into personal individual contributor work or learning more about AI tools that can help you automate more and more. And so to be able to take AI as kind of like your assistant and let it do the things that you can trust your assistant to do versus you have to do, that would be an ideal state, I think.

Ramona Shaw [00:26:53]:

Interesting that you highlight this right? Because I think some of the risk concerns would be that people have is that AI will take over or automate what’s the human part of it, of leadership. And you’re actually saying, no, we want to automate what is not the human part so that leaders can actually double down on the human aspect of it and really strengthen the relationships, dive deeper into the specific career goals or growth goals that the individual has, and tailor their experience of the employee lifecycle even further to the person in front of them.

Bilal Azam [00:27:26]:

100%. They say that people don’t leave jobs, they leave managers, right? And so if we give our managers more time to go focus on their people, obviously that equation right there means that you hopefully have higher retention, and higher retention typically means better product velocity. And so let’s give our humans time to be humans is really the goal I look forward to. So, yeah, great call out.

Ramona Shaw [00:27:48]:

Love that. Velia, how is it for you? What is your dream state twelve months from then?

Velia Murillo:

I believe that the part of our title I believe all of us have it is the word human. And Bilal has touched on it. I think rather than be scared of the technology, the innovation, the what could be, the what ifs, we have to take this a day at a time and utilize this to our advantage. The thing that I think will come to be more important is the human aspect, is the fact that we’re going to get so caught up with automating a lot of things. The one thing that AI won’t do, at least not in my lifetime, is prevent the need for connection, the need for empathy, the need for feeling, the need to back. If I take this back to my testimony call center operation days, humans need humans. Humans want someone else to listen and empathize, even though they can go to the chat box and get a quick frequently asked question in second. Even if I, as a human, am going to repeat the same thing, they want to hear it from me. They want to hear that they are being heard, that they understand all the pleasantries that will go away. In my current position, I would love to see us taking advantage of Chat GPT in some way, or over proprietary, because I think the only way this won’t be a one size fits all for companies. So we need to learn how to create our own tools. And I would love to take advantage of this for well being, how to help find ways to cope with stressful days. Maybe my teammate will not always come to me, but they can go to Chat GPT and maybe get a few tips and tricks of how to manage the workday in mental state, you release stress. We can go with this for so many ways that I think the human aspect of our role will be even more important. Communication, facilitating communication. And I. Think properly. Prompting chat GBT is another way to improve our communication. If you don’t prompt it, instruct it, give correct parameters, you’re not going to get the outcome we want. So practicing our own communication. Yeah. You build on something that you said earlier too, there with the intercultural barriers or challenges that sometimes come up, including the language barriers, I really see a great potential there to help leaders be able to tailor more to recognize potential biases to adapt and learn and be coached through different communication styles to better meet people where they’re at in terms of the cultural background or the location, the language that they may speak, or cultural norms to build that awareness. And we’re not all the same, right? And sometimes, especially coming from the US. We may have a bit of a US centric view and then recognizing, wait a second, I’m working with all different cultures and I recognize these little nuances, but I’m learning on the go. I’m learning through mistakes, potentially or through challenging moments versus really getting coached and building that awareness upfront that then helps us be set up for success in those different. Agreed. Beautiful. Jennifer, how about know?

Jennifer Ramcharan [00:31:30]:

I agree with everything they said about the mundane tasks and kind of handling that. But for me, when I think about the landscape, I focus a lot on emergence. So whether emerging leaders or succession planning, and as HR or people Ops leaders, we have all of this data. And I’d love to see, in a way, obviously mining data, security and privacy to be able to take all of that and use it to analyze the data that we have and figure out who are our emerging leaders, who are the people within the organization that might be even right for a role on a different team. As we think about succession planning, using that data to really see who were the high potential individuals we already have within the organization, because I think it is very hard. We do have all of this data, and I would really love to see AI synthesize it and then be able to use that to kind of start doing some predictive analysis of whether that’s even our internal employees. Right. Figuring out how long do employees that we have typically stay at an organization and even using that as an influx to start a new conversation with that person. Right. We are coming up on that three year mark. What does that future look for you? Look like for you? So I’d love to see AI start to help with that future and emerging trends conversations.

Ramona Shaw [00:32:53]:

Can I ask a follow up question here? When you say we have this vast amount of data that we could use to dive deeper into the analytical part, can you give us some examples of specific data that you find interesting that you’re already collecting or intend to collect?

Jennifer Ramcharan [00:33:07]:

Yeah, I mean, some of the data that we use we have our performance management tools and the data that comes out of there. We do a lot of skills and gaps assessments, so we have a lot of the data there. Our team does coaching, so there’s data that we get back from those coaching sessions, even social network analysis, figuring out who really our ambassadors are outside of the organization and how do we utilize them more within the company.

Ramona Shaw [00:33:38]:

Nice bilal. And any comments here or anything to add on the predictive index or analytical part or how that intersects with Know?

Bilal Azam [00:33:50]:

That’s a great call from Jennifer, I believe when it comes to the using, we have so much data, right? I think every company has vast amounts of data. So many databases for sales tools and CX platforms and people platforms, engineering, there’s data everywhere, right? And the reality is that data sits there until we have a way of analyzing it to help with productivity, or for the people function for retention or for sales, how to target your audience better for CX, how to minimize churn, and so using AI, a Jude’s fantastic idea to say here’s the data. Now again, we have to figure out a way to keep that secure to the team that’s proprietary, but here’s the data. What trends are you seeing? What are we missing, right? Being able to ask that open ended question and have a supercomputer on the back end, process all of that for you in real time and say, hey, did you realize that your small to mid sized business cohort has become 50% of your business with a sales cycle of 15 days? Are there more here that we can look at? Simple example for sales, let’s say for CX, if they talk about churn, there’s a lot of times a net dollar retention is a big metric for them. Hey, have you noticed that enterprise customers or this type of customer base is the most at risk? Why? Here’s analysis of the data and the calls you’ve had. Maybe the CSM is not as in tune with a smaller mid sized business. They’ve been churning high levels because of that. These are things that can actually be actionable by your business to support business goals. And it’s just something that takes so much time and honestly, a very high quality individual who understands SQL and data analytics and Python and R and all these different high level tools and then languages to be able to do that analysis for you. We have a platform that can do that automatically if there’s a way we can do it securely. I mean, we have to do that, otherwise we will be left behind. That was a great call, Jennifer.

Jennifer Ramcharan [00:35:36]:

Then to add to that, how do you monitor that? Right? Because that takes a whole different team of people to do that. So if we’re able to utilize that tool for the emerging part and then the monitoring, it really would revolutionize our data. Days and our leaders day to days.

Bilal Azam [00:35:53]:

How do you put AI into your normal function versus making another thing to go look at?

Ramona Shaw [00:35:59]:

It’s pretty interesting, guys. You bring that up because when Jennifer Belika started talking about data, I thought of the one thing that I love, but that is always very time consuming is employee surveys. Right. Satisfaction surveys. Employee net promoter scores. They come in and they come in fast. But how do I take all that information? And then over time am able to see the jumps, the peaks and valleys of satisfaction or dissatisfaction and being able to quickly identify some of our surveys that we perform are anonymous and some of them, at times depending on the comfort level. I feel depending on the topic, they actually will have names and the part of the world that my team member is answering from, so that I know how to address them, when to address them. So that’s the immediate thought of when we started talking about data outside of the usual. But employee surveys, I mean, satisfaction is key.

Bilal Azam [00:37:00]:

Great call out.

Ramona Shaw [00:37:02]:

Yeah. From my perspective as a coach and leadership development consultant, I find that really interesting too. To see what can we do proactively in terms of both identifying breakdowns and collaborations? Potential conflict on the horizon by looking at interactions. By looking at communication that happens between different teams or between different people, as well as what is the data that AI can learn from to then identify who are the high potentials. Or like you were saying, there the ambassadors of the organization who are the ones with the skill set that would fit what we’re looking for, for a specific role in the future based on that job profile or strength profile. Skill profile required. And then being able to use the data to get us a head start in identifying both the downside risks as well as the upside potential right now, some of finding the talent within our talent. Right. So I think of the times where we’re trying to rediscover, get to know our employees again. They’ve been with us for a long time, years, and getting to know them again. So we’re getting to court them again. We have to do those, set up the scheduled one on ones, think about the questions, figure out the right time zone differences and with something that we can think of and create through AI the opportunities to improve that are endless. Yeah. So we’ll see in twelve months where we land. We will the conversation and then probably even paint bigger picture and vision for the subsequent twelve months. Now, as we’re wrapping up, I do want to talk about the risks and concerns that we may have or we further are being engaged with in conversations around AI and introduction of AI into the HR field, including asset L. D. What are some of the concerns that have come up? And I’ll leave it open for whoever wants to jump in and speak first. I’ll quickly jump in there guys I know in our world, and really I think every major industry is highly regulated, some more than others. So I think one of the things to watch out for because who knows what will happen in twelve months. But I can predict some state regulations, maybe consideration by the federal governments or representatives, creating bills and passing them to govern how far and how risky AI is going to get. Just like privacy data security, it’s going to be a little messy. And if we’re in my case, I have to think about Mexico, Armenia and all these other countries and I’m still a small team handling this. That’s on my radar and a big concern for me. It’s hard enough trying to just do the day to day regulations that we have to worry about with employee law, but on top of that sort of maneuver and do the right dance around those regulations.

Bilal Azam [00:40:27]:

Yeah, I would say my biggest concern is definitely the regulation and the proprietary data. All these large language models have the kind of disclaimer that what you put in here is not our information to learn on, which means it’s a very large limiting factor. Our engineering team can never put code into that thing, even though it could be great code quality assessor and figure out the gaps that’s proprietary data, especially for our CX team and stuff, they can’t put our customer data onto there because that’s again very proprietary and safe information. But besides the data security, I think the next thing is the blind acceptance of what an LLM will say to you. And what I mean by that is that there’s already examples out there where you feed something into Chat GPT. It’s only learning from September 2021. And so people put in there, hey, how does employment law affect this? It spits out an answer for you. Again, this is just a large language model. It’s just assuming this word makes sense after that word and spits it out for you, it doesn’t really have intelligence to it. And so my worry is that people start blindly following, say, oh well, Chat CPD says this is right, so I’m going to go with it. And that’s where you have to remember this is a tool, but we are still the humans that are monitoring that tool and using that tool and have to validate what it says. So I get a little worried about people taking it as a replacer again versus just a tool in their tool.

Jennifer Ramcharan [00:41:47]:

And I agree with that too. Like that over reliance for me, when I think about it, I worry about the bias and fairness. These algorithms inherit bias from the data they’re trained on, so it can result sometimes in unfair discriminatory outcomes. And so my worry is making sure that as leaders, we ensure the systems are regularly audited for bias and we take steps to mitigate that. The other part of this is that I call it that transparency and explainability of these algorithms, they’re complex and they’re difficult to interpret. So making sure we understand and we strive for the transparency that explainability factor in all of the decisions because it’s how we maintain our employees trust. So if we can’t explain it or understand it, then we should need to make sure that we don’t roll something out that’s going to wither away or degrade the trust that our role is to build within the organization.

Ramona Shaw [00:42:48]:

Yeah. To add another part there, building on a bit of the recognizing that this is just a tool, I think one of the challenges that I see with a lot of the tools that come out in the coaching space specifically that use some kind of tools, a chat box to have interactions or to give suggestions or people that I work with who say, oh, I put that into that question, into chat TV or into whatever tool that they’re using to then see what the output would be. And actually was great. And I think that over reliance on it where we actually diminish our ability to develop critical thinking and that human aspect that we actually want to hone in more, where we rely just too much and also pass on some of the accountability to any of those tools. Definitely a concern that I see. It reminds me of something that happened, it was in the news where it could happen to the most intelligent of people to really take chat GPT generated results and apply it and share it with the world. You guys probably heard it. It was a lawyer who took some content and put it out there to the world where it was outdated, it wasn’t even real. I think it was, but I think one of the things that as HR leaders and just executives and professionals in everyday day to day work is remind our team members that don’t be scared of this. Here are some parameters that these are things that we’re using it for now that are okay for you to try. And like I said early on, keep practicing with it. It doesn’t have to be like serious. You could take a break and just play with it. Ask it questions that you know the answer to and see what it says right. And treat it. I think of it as sort of like when you first started learning to ride a bike, right. With the trading wheels. That’s what’s happening with AI for me, that’s the way I’m taking it. Could be a while before I decide I’m going to go full steam ahead, take off the training wheel. But in the meantime, this is good practice. I’m not going to be scared of it. But I need to know to Jennifer’s point, I need to know what I’m talking about. So I need to see the good and the bad and the ugly of this tool and innovation and figure it out. I want to grow with it. I don’t want to be like I said before, I don’t want to be left behind. I have to stay abreast of what’s going on. Yeah, totally. And also not replying to Son as we’re coming to the close of this panel conversation, which I so enjoyed, and I think we could probably spend another hour on these topics, but I want to quickly open up. Is there anything that you wish we had talked about or you think is relevant for this conversation that we haven’t yet touched on? Go for it, Jennifer.

Jennifer Ramcharan [00:45:44]:

No, I was just going to say reminding leaders to make sure they’re educating and training themselves over and over. This is not going to be a quick sprint. This is a journey with AI, and so taking courses, whether Coursera or Edx, and utilizing that and understanding AI, not just from the People Operations or HR lens, but understanding it from the business lens, is going to be huge in ensuring that you get the right adoption within your company. There’s also a couple of good books that I recommend for people when they ask me about it. There’s one called AI for HR. It’s by Ben Eubanks that use AI to build a successful workforce. And then human Plus Machine by Paul Daugherty and James Wilson. And it’s kind of reimagining the workplace in the age of AI. And so it’s talking about it from all lenses. And I think it’s going to be important that we continuously have these conversations and continue the education process.

Ramona Shaw [00:46:47]:

Very nice. Jennifer, after our panel ends, would you drop those in the comments on LinkedIn? Yeah, of course. Awesome. Thank you. Milia or Bilal, any additional resources or comments as we wrap up?

Bilal Azam [00:47:00]:

I would say online, there’s a ton of these cheat sheets for Chat GPT. I don’t have a specific one I go to, but what I do is almost on a weekly basis, I will just Google it or I’ll even ask Chat GPT to give me a little cheat sheet for it. And to me, that’s been a really big, helpful part of learning how to use a tool, because it not only tells you the languages it can talk in, it tells you tones, it can speak in the right way to prompt, it how to specify prompt after prompt. And so to me, a big thing to look at there would also be how do you refine your ability to use it? Because, again, it’s a tool. It’s only going to be as good as the user putting information into it.

Ramona Shaw [00:47:36]:

It doesn’t matter. Yeah, huge. Very closely. A huge opportunity to step up as a leader and really dive into this to then be guiding the conversations and the initiatives around AI.

Bilal Azam [00:47:47]:

Exactly.

Ramona Shaw [00:47:48]:

I’ll add one quick thing in there. Ramona, I follow you and I have been following you for a while. I think taking advantage of LinkedIn, it is something that all of us in HR we were very active on. Try know, find the right people to follow. Don’t do this alone. Right? And creating opportunities. It doesn’t have to be a live panel for us to keep discussing. I’d love to continue conversations. And for anybody that’s listening live now or ends up looking over, listening to the recording, I’d love to have conversations about it. What are people thinking, what’s on their mind? And just connect. There’s so many. I know there’s plenty of academies that offer courses just for HR. Just six months, five months. Just keep learning, just be open to exploring this new world that we’re emerging in. Absolutely. Great point to end on. So let’s keep that conversation going. And for anyone listening who’s also interested in it, please comment or reach out to the panelists here as well to stay in touch. And we’ll definitely do a part two. So that’s going on the schedule for 2024 to follow up on it for any of the resources that you have mentioned. Again, if you drop those in the comments, I think I’m sure people will appreciate that as well or any additional tools that come to mind as you reflect on our conversation. Thank you everyone, so much for listening in and for the three of you for joining us this morning on the panel on the topic of AI and developing AI enabled leaders. Thank you so much for being here and a great rest of your day.

Bilal Azam [00:49:23]:

You too.

Reflection & Discussion Questions:

1. 1. How can AI tools like ChatGPT be utilized to improve communication and understanding among managers in an international organization with different cultures?
2. 2. How are startups utilizing AI to support leaders’ responsibilities in Series A and Series B companies, as discussed by the panel? Can these strategies be applied to other industries?
3. 3. How can integrating AI tools in learning and development and personal leadership development benefit organizations and individual leaders? What considerations should be taken into account?

• Episode 142 – ChatGPT and 8 Ways it Can Help You at Work
• Episode 170 – Teaming in a Hybrid World with Sally Loftis

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00:02:43 Panel on AI-enabled leaders; introductions and interests.

00:08:12 AI’s impact on HR and L&D.

00:09:35 Early adopters of AI, including Chat GPT. Adoption for employees, discussions around usage. Increased productivity, use of AI tools. AI in L&D and presentation building.

00:14:02 Using AI tools to support leadership responsibilities.

00:20:21 AI as tool for repetitive tasks, iteration.

00:21:40 Utilizing Chat TPT and coaching mechanisms. AI in HR leadership development. Future possibilities and exploration.

00:27:48 Advocate for utilizing technology to enhance communication.

00:33:50 Using AI to analyze vast amounts of data for various business functions such as sales and customer experience. This automated analysis can provide actionable insights for achieving business goals.

00:37:02 Using AI to identify talent and risks, concerns around AI regulations.

00:42:48 Over-reliance on coaching tools limits critical thinking.

00:47:48 Connect, learn, and continue the conversation.