From First Day to Future-Ready: What AI Readiness Looks Like Once Graduates Are Hired transcript

Hi everyone, welcome to this amazing panel and discussion we are all going to have together on from first day to future Ready.

We are excited to have a fantastic panelist here.

I've got Pasquale here on screen, Ashok and Jenna, they join us from some really cool organizations that are really diving into this conversation around how do we prepare a future ready workforce in the age of AI to be able to be successful at when they join the opportunity or the the career of choice.

And so with that, Pasquale joins us here from ServiceNow.

I've had the pleasure of getting to know him and hearing some of what he's done at ServiceNow.

And his role is the GVP of Learning Solutions, Learning Solutions Studio.

And I've got Jenna Jorgensen who's the corporate vice president for corporate skilling with Microsoft and Ashok Sitaraman, excuse me if I've mispronounced that name, Ashok with he was the head of HR for TCSUS.

This is a, a great discussion for us because for some of you who are parents like myself, who are, are preparing our kids to go into the workforce, who are already in the workforce, we know there's a lot to be said about how best we prepare them and in some cases how well prepared they are and and certainly what that transition looks like.

So we're going to just jump right in.

We will have, I think, a conversation slash Q&A.

And with that, I get the pleasure of posing my first question to Gina.

OK, Gina, So when we think about AI, what do you think it means?

How do you think about that in the context of what employers should expect with our folks coming in, early career folks coming in and how do we prepare them?

Yeah, it's a super great question.

And I will tell you, every professional customer conversation I have with a customer or partner at Microsoft, inevitably there are parents in the room that turned the conversation over to.

And now what do we tell my kids, my kids trying to go to school, like how do I prepare my child?

So it's a very common question that shows that sort of transition into the workforce as an early and career person.

And there's a couple of things that we're seeing.

One, there's a lot of fear in the market right now being a young person, but how do I just get a job?

And those jobs all right now seem to be taken by AI.

And what I always tell everybody, first and foremost is there's not going to be a workforce in the future where it's all a bunch of older people like me, like we're going to be gone.

And it's not going to, there's not going to be a workforce where there are no humans in it.

And as long as there's relationships between corporations and companies and their users, people need to be there needs to be human.

So early in profession are always going to be hired.

It's about finding the right job.

And then what are the skills you need to demonstrate to be ready for that job?

Because there is an expectation that people come in at any level in their career, whether it's brand new or whether they're a seasoned professional, that they have a set of AI fluency skills that we all talk about.

And I'd say first and foremost, what I tell kids is go learn the tools that every employee should know.

How do I use the tools to summarize meeting notes?

How do I use the tools to do research to prepare for a customer meeting?

How do I use the AI out-of-the-box tools today?

Just Start learning that and showing how you are building capability.

And even if you haven't had a professional job yet, you can show them how you use it to plan a vacation, how to how you use it for everyday so you know, in your school work.

So just start using the tools.

And there's a whole bunch of, I would just call very unique, consistent set of skills that every employee needs to learn independent of their age or level and profession.

But the thing that I end up focusing on the most, and the thing that we're seeing really a struggle for these young people, is this notion of the human skills.

How do they demonstrate their ability to collaborate with other people, their ability to look somebody in the eye and deal with challenges?

How do they respond to failures?

Right?

There's lots of times at work where we actually mess something up.

We go in the wrong direction, something doesn't go our way, the market's not ready, the customer's not ready, and we need to be resilient.

And we're not seeing a lot of resilience and demonstration of that.

And so it's been a real struggle.

And I'll say one more thing, and I know Pasquale and I were talking about this previously about this, which was we've been doing a lot of internship reviews.

It's been super fascinating to see these next generation of kids who are presumably in school during COVID and how they are showing up in these internships.

And, and I would say the thing that we're really seeing as a struggle is this ability to get out of their phones and to have a communication conversation to not just take what AI has told them to do and take that as fact to question AI.

They're really struggling to have the second layer of detail around.

Well, great.

I'm glad you used AI for your project.

But do you know what the second follow up question to that is?

Can you answer a more deeper thoughtful question around your project and, and can you go beyond the AI to really demonstrate your command of the topic?

And so that's what we're seeing.

And so I would say definitely learn the human capability, like, or excuse me, all of the core AI fluency tools, out-of-the-box tools and learn how to summarize meetings and be prepared for your customer meetings.

But then really start to hone and fix those areas that we've let atrophy.

And our children, we're seeing it definitely atrophy me even more than the adults.

So the human skills of courage, resilience, collaboration are are key.

Yeah, no, I think it's, it's so brilliant the way you've described.

Well, First off, the topics trending.

I mean, it is, it's on our students mind how how they can be ready and what readiness means to them.

And to your point for for employers, what what do we signal as readiness?

And, and that I think is a big gap that you've just highlighted.

And, and I think it's, it's so important, as you just mentioned, the human skills, it's, it's goes hand in hand.

And this idea of don't outsource your thinking to AII mean some might actually just be shortcutting, like you said with some of the interns.

It's like, Oh, I, I, I did, I answered the test.

I you said recap the meeting.

Here you go.

And you read it and you're like, there's some, there's some like context thing that there's some stuff in there that didn't quite make sense.

So yeah, there's the two pieces, right?

Learn the tools.

And then once you've learned the tools, don't let them sort of command your everyday experience or command like AI slop is a real thing.

And there's also the question, the tool, but then also having your own critical thinking.

So critical thinking is so, so important.

And we're seeing people know how to use the tools.

The tools can help us all equally, but how do you reason above that exactly?

It's a bit of calibration around ready to them might be different than ready to us.

Yes, that's a very good point, Very good point.

So Ashok, tell me a bit about how I mean, TCS is in the business of just really thinking about bringing in early careers, you know, early career professionals at scale and and where are you seeing, you know, probably somewhere to Gina's discussion around the biggest gaps between what the graduates bring and what the workplace requires.

Again, we talked about like they might seem like or perceive they're ready, but when they come on board, there is that gap and and how how are you thinking about that?

Hi, thanks for the question.

And I think Jenna, you know, gave some very insightful, you know, perspectives.

See graduates, you know, the people who join us, increasingly, they come with very strong digital fluency.

They're curious, and they also have a very good exposure to a lot of AI tools, but they're very good at that.

But when you're talking about being AI ready, it's not just about knowing every AI tool or model.

Human skills, like what Jenna talked about are very important, but we also think there are other things like a lot of strong fundamentals.

When we say fundamentals, their ability to look at problem solving, you know, thinking critically, reasoning analytically, or their data literacy, You know, how do you look at data?

How do you, you know, you know, analyse them?

I, I think that's something that is very important apart from also, you know, having this understanding of how to use AI responsibly, you know, the principles of, you know, using AI, whether it's the ethical part of it or from a security prod privacy or, you know, every AI has a lot of bias.

So how do you, you know, you know, put this into context?

I think that's something that a lot of these, you know, young folks, while they have very good knowledge on the tools, that's something which we think is what is lacking.

And when I put this into actual project situations, when they come join, you know, and we are taking them into a project, the gap that we see is their lack of ability to convert their AI output into a, a business outcome.

You know, you should be able to link any of these AI outcomes into, you know, business outcomes, You know, critically evaluating, you know, whatever AI generated content has given, is it right?

You know, see, that comes in only when you have a lot of knowledge on the domain of the topic that you're working on a project, the business context, the industry context.

I think that's something that they do not have it when they come in.

And also, you know, the enterprise specific tools, you know, they may be good at one particular AI tool, I'm just saying, but the organization that you're working for may not be using that particular tool.

So they have to have exposure to those tools that an organization is, you know, working at, you know, working on.

Likewise, the processes that each of these organisations have, you know, software engineering concepts or any of those, you know, basics of how you deliver code or how do you, you know, do that?

And the other aspect is how do you apply some of these AI learning into real world outcomes?

I think those are things that we see is the the gap.

And finally, you know, their ability to collaborate between the various human, you know, like Jenna was talking about how do you collaborate with the others in the team and also look at how you can collaborate with the AI agents.

I think that is a very, very critical piece that we think we are focusing on when when we have a lot of people join in.

While they're good on the technology aspects, I think some of these other aspects is where we are spending time and trying to coach them and get them to see the context.

And you know, unless you see that you will not be able to create value for your customer, right, Right.

I think, I mean, you, you touched on some really good themes as well.

The, the idea around AI governance.

It is important that students, you know, are using it in a way that it does not become a liability, but of course, the capability.

So that that's certainly key.

And and I think this is a, a great segue certainly with Pasquale around, you know, there is investment on our part.

I mean, we, we have, we play a role and and I love the work that, you know, I think you guys are all doing.

But certainly as we think about building capability again, that's sort of like closing that gap.

Pascal, I want, I want to turn it over to you and just, you know, kind of get an idea from your perspective around, you know, from building AI capability on the job, which also I think we're speaking about is also building key experiences on the job, which is super key.

I mean, a lot of what we've talked about are just these are like first time they won type of experiences in a corporate environment and they don't know yet those expectations.

But for Pasquale, when you think about completing AI training, it's it's, you know, it's not the same as being able to use it effectively.

Variances count, context counts.

But what, what do you think are, are helping employees make that leap to really from, you know, to go from learning to application, from AI Fluence to AI trans, you know, AI fluency to AI translation.

I'd love to hear your perspective on that.

Thanks for the question, Natalie, and thanks for having me.

So I am an AI optimist, but I'm also a human optimist, and I think this is the most exciting time for us to be alive, both in personal and professional.

I mean, the AI games that we're all getting, you know, whether your hobbies, you know, gardening or painting or whatever, like you can learn so much so quickly.

And then the tooling 2 is really moving and lightning pace.

So no matter where folks are in their career, I'm sure they've experienced an LMS at some point, right?

Where you log in and you've got to complete that training because your boss is going to e-mail you and say, hey, you got to do this thing before the date or you're going to get locked out of your computer.

Imagine if every time you were doom scrolling on TikTok, you got prompted with you have to enroll in this video before you watch it.

Like you, you would probably stop doing scrolling.

Wow.

Yeah.

And and and so that's a good mental mental analogy.

Yeah.

We should make T-shirt.

And so why is it in the consumer world, the way that we're teaching people things, whether it's YouTube shorts or TikTok or whatever, we've essentially removed all friction.

But in the professional world, we still have a lot of friction and there's a lot of legacy there.

What I would say to folks that are looking to advance their career or, you know, get to the next thing is like you, you, you just have to have an insatiable appetite to learn more about these tools.

Like every weekend I discover something new and I'm like, wow, like that's so cool.

That's the newest part.

And then the next weekend, you know, my wife is always like, are you cheating on with me with ChatGPT?

I'm like, no, no, I'm not.

I just, I found this new thing and it's so amazing.

You have to have that insatiable appetite because you know, and I, I promise I won't be too verbose here with it.

It's an important concept for the, you know, learning was built out of constraints forever and ever and ever.

The equity that we would build in ourselves is like, I'm an expert in this thing and I have 152025 years of experience.

That's still going to be valuable, but less valuable than it was before because now you have a PhD in your pocket on every single topic.

If you want to talk to like Frank Lloyd Wright new like architecture, I mean, he's passed away, but there's models that emulate him and you can talk to him or an Egyptian pyramid architect or all of the things.

And So what is your value in that environment?

Your value is your ability to orchestrate those agents, to command them, to delegate to them, and then also to get the most value out of whatever the newest thing is in that given week.

And so it's hyper, you know, fast pace of change, but it's also super exciting.

So I, you know, I guess the, the, the pin that I would put it in is just like every week, challenge yourself to learn something new and you will be incredibly valuable to yourself and your organization.

Amazing.

I, I just, I was just having a conversation with someone about how do we sort of switch the conversation from, you know, AI is learning a is progressing and it just gets smarter to, I think what you're saying is let's actually start with like human progression.

How do we, you know, continue to put in the front, you know, really talk about human progression in this context and, and what we're doing and the opportunity in front of us to help us learn and help us progress at some in some ways the same pace, which I know would be be kind of crazy, but certainly at pace to certainly keep up with all the innovations happening around us.

But I, I love that human optimistic approach.

You just, you just articulated and, and I think the, the idea of, you know, you're, you're speaking to for yourself, like curiosity, You know, obviously we don't want you cheating or being accused of cheating with ChatGPT.

But I, I love that, that that's a very funny, funny dialogue between you and your wife.

But this idea of when you are engaging with the new tools, you probably brought some of those sort of learning skills along with you so that you can quickly adopt and, and go forward with it.

So I'm assuming that's a big part of your AI readiness curriculum as well is just those learning to learn skills, which is fantastic.

OK, Ashok, I'm going to come back to you and just love to hear from your perspective again, sort of in the same spirit around building AI capability on the job.

How is AI changing the way you're on boarding folks?

We talked about the sort of that day one experience, some coming right out of school, some may be in job too, but I I think it's it's important for us all to think through that's probably shifting a very different conversation now in the context of how the roles and the work has changed.

Absolutely.

You know, see, traditionally, you know, the early career employees spent significant time learning processes and they took time before they could start adding value.

But that's changing right now.

And, you know, we, you know, just for context, we hire a few hundreds every, you know, quarter, you know, graduates from colleges.

So we see this, you know, pattern very clearly emerging from how it used to be, say five years ago to what we are seeing right now today.

These, you know, new hires who come in, they have access to knowledge instantly, you know, through, you know, various AI tools, they are able to learn while performing their tasks much more effectively than what used to be earlier.

And they also get a lot of contextual guidance.

And, you know, they're becoming much faster, You know, they're becoming productive much faster than what it used to be.

No, traditionally, but so right now, you know, when, when you say, you know how this is changing given that they are becoming productive more faster than what it used to be earlier.

Now I think the goal is also shifting from, you know, not just being AI literate, you know, or AI, you know, learning.

It's about how you know, start applying those learning to everything that you do.

It can be to the project that you work, how do you, you know, make it more effective?

Or you could use AI for your own personal effectiveness.

So that's something that we are driving.

And we also see a lot of these, you know, graduates who come in.

You know, we were recently doing a survey within the organization to see how many agents each of these people are creating for themselves for personal productivity.

As well As for, you know, project productivity or the, you know the, the deliverables that they have.

It's amazing to see how they can make this, you know so very effective and efficient the way they are able to you know create these agents.

And we also, you know, sort of now stop looking at whether they've gone to training, have they, how many hours they're spending on training and all that.

Because just last quarter when we looked at our data, almost 5, almost half a million hours of learning has happened just on AI in North America, just for, you know, you know, some context.

So I think now that's, that's a way because there are newer tools coming in, they're learning, but they're also making sure that they're applying.

And that's where we are trying to, you know, focus our efforts on how do we make them apply that learning and how you can encourage them to, you know, come up with these agents.

But at the same time, we're trying to see how we can create a safe space for people to experiment as well.

And these new, you know, so we have something called an AI garden.

So we've put all our AI tools there.

And depending on the role that they perform, they have access levels of access to each of these tools that they can play around because you need to create a safe playing ground for them so that they can experiment without, you know, looking at repercussions and so on.

So we've created a environment with data that's all very internal.

And so they can do that so very fast.

We have moved.

Practice.

Sounds like practice.

Yeah, absolutely.

See, getting trained is like getting a license to drive, but then the more you drive, you become more efficient.

And it's moving away from literacy to fluency.

And exactly, it's also about how they can combine human expertise with machine intelligence.

How do you collaborate bring together?

I think excellent ready.

That's very good framing.

And and again, we all know how important the day one experience is for anybody.

And and actually I thought if Gina, if you don't mind, you answer the question and chat for Stephanie, which is a great question.

This is broadly around building capability and where do you start?

I think you know that whole learning to learn in the learning skills is really about making time, obviously, but I like this idea of sort of choosing one thing.

So Jenna, do you want to do you want to talk a little bit about that and just some of the ways that you bring that conversation to life?

Because it's it's about breaking it down and taking some micro steps and building habits, which I love.

And how you articulated that shock was talking about that too is like you can give all the long term training, all this micro credentialing and long term credentialing.

People are learning in various different ways.

But this notion of stick based skilling, which is you must complete by X or X machine will get shut off.

You know, it's it's it's over, it's done right.

And so I think there's a couple of things that are really important, like social skilling, community skilling, learning from other experiential learning is, you know, that's how we all have learned our whole lives.

AI is no different from that, right?

And I think we separate this thing that is AI into a totally different bucket, which it actually doesn't need to be.

But I will say one thing that is so critical that we're, we've, we've missed the boat on.

I again, like Pasquale said, like I am an AI optimist, I'm a human optimist.

So as well, I'm also a realist.

There's so much fear in the market around so many different things.

I'm it'll replace me.

I won't get a job because of it.

I'm too late.

I haven't gotten started and I'm so far behind.

I'll never catch up.

It moves so fast.

I can't possibly keep up even if I do get started.

There's fear everywhere and psychologically and just I, I would say in the world that we live in, you cannot learn any new skill, forget AI, you can't learn anything when you're coming from a place of fear.

And the one skill to me that I think every person, especially new and career, like you can learn this early in your life, right, is around your mindset, right?

You think about, you train your body to be a great athlete.

You train your craft to be whatever it is, a great painter, a great whatever.

You have to train your mind.

And so many people are not doing that and are not focused on that.

They go straight to their immediate sort of visceral response, their instinct, which, you know, we all are raised with different life experiences and we all come in with different mentalities.

And your mindset is one that you have to train.

And I would say if there's one skill, forget the tools.

The tools are, we're all going to be able to use them.

Consistency, this AI fluency notion is, you know, anything that you do is about habit making behavior, anything you do to improve, like you go in with, I'm going to get 1% better every day and I'm going to try this thing.

That's great.

But you have to have the mindset of it's OK to fail.

I, I know it's not too late to get started as long as I get started.

And then how do I just train my mind to not be fearful?

You would you asked a previous question along these lines, lines in our earlier conversations.

And it's so critical when we're operating next to agents, right?

When we're operating next to something that doesn't have emotion, that can work 24 hours a day, that's going to outperform us by all intents and purposes.

What's the unique value that the human brings?

And we need to not go into this thing's always going to be better.

Like what are the unique characteristics that you as an individual and we as humans bring?

And it is your mindset, it is your judgement, and it is your ability to, to understand the human emotion behind things that AI is never truly going to.

They, it's never going to have empathy, right?

It can never have empathy.

And so if, if you think about that, for every kid that's learning to be, or they're all going through this adulting phase and they're all trying to get into their first, first really big corporate job.

But there's so much work that needs to be done on mindset.

And we don't focus on that at all with children, with young adults.

We focus that more as we get older.

It's called wisdom, but wisdom, you can't learn that super early.

It's not just about your institutional knowledge that you've gained over decades and decades.

You can train your mind today.

But I think that's a what I see in so many young kids is this like this fear and then this notion of like, I'm behind, I'm not going to get a job.

And it just compounds And that they haven't fully developed that capability to say, I'm OK, I understand my unique valid value here it is.

And and I think that's just been such a struggle we've seen, especially when we let things like social media, you know, dictate our mindset.

Sometimes you have to be able to extract yourself and all that.

So I love scoring these comments too in the chat, which is like, so much of this is psychological.

And that is something I underestimated as a person in tech.

I did not under fully concept I I didn't fully grasp this notion of how much of A psychological barrier there would be to AI adoption.

And that's where you have to start with the employee satisfaction and what is the learner coming in and what is, you know, like, how do they feel?

Yes, yeah.

How do they feel coming in here?

Right.

Everybody's coming in from a place of worry, imposter syndrome.

We've all know it.

So like mindset training, number one, the number one skill set, it's amazing.

You said something about being smart versus wise.

And I think there's a, an important distinction around AI may be getting smarter, but I think to your point, wisdom can come early.

And also it's actually what is what humans are bringing.

We're bringing wisdom, we're being wise about how we use the tools.

And I, I love what you, you articulated and, and I think it's going to just bring me to Pasquale.

I'm going to, I want to talk to you a bit about, you know, and we've, we've certainly circled around this topic around, you know, AI literacy to AI fluency.

And I know there's been some cool work on AI within service now and, and certainly what you guys are doing.

So as AI becomes more embedded in the workflow, how does that change what both employees need to learn and how they need to learn it?

And and again, we've we've done this sort of like carrot versus stick.

But I would love to just think, you know, have you, have you talked first Pasquale about what, how you think about that and then to her, and then I'll bring it to the rest of the team to, to answer that as well.

Sure, thank you.

So I always like to give like a, you know, consumer example and an enterprise example, so I can talk to what we're building.

But I had someone the other day they were trying to solve the business problem and we use various LMS.

We, you know, we have copilot and clawed and a few other things and they're like, I don't even know what, what to do here.

And I was like, you know, and, and I was like, well, you know, you can use AI for that.

And they're like, well, I don't even know what to ask.

And I'm like, the, the beauty of this is, and if no one's ever done this before is you can literally say, I have this problem, like quiz me back and forth.

Like help me get to like, you know, it'll take you through the Socratic method and help you get there.

So like there's no unsolvable problem in the world of AI in terms of what we're building from an enterprise point of view.

We want to, you know, just like the way that you're learning in consumer, you know, you talk to Claude or Gemini or Chechi PT, we want to get to a world where you log in, it knows who you are.

We're building something called talent signature, which knows like what role you have, what role you want, your aspirations, your hopes, your dreams, and then all of the learning that you've already taken.

And then maybe a brief assessment to calibrate on what you actually know and then give you recommended learning.

But recommended learning, Isn't that like swivel chair?

Stop what you're doing, turn to your right, go do this thing for 30 minutes and then go back to your job.

It's not like can we do that in the flow of work?

So from a technical training point of view, if anyone's in, in ServiceNow universities free.

So folks can go and take a lot of this learning online.

We built something called SIM Studio and AI Learning Guide, which is essentially you go into the platform in the old world, you would do a bunch of things and then you would sit at the end for a really long test where now you have a companion app that can essentially intuit where you're having problems, where you might need help.

For any gamers out there, you know, if you're struggling figuring out a puzzle, you might get a little Yoda or whatever.

That's that'd say, hey, you need help with that.

And it's so much better if you're getting in the flow of work from a knowledge retention and application point of view, but also the speed at what you can get things done.

We're all, whether you work at a consultancy or not, we're all billable resources.

Time is money.

So if we can shrink the amount of time that it takes you to do that thing, that's that's our aim And and also make it joyful.

It shouldn't be like, I gotta go do that training thing.

Then the last kind of cherry on the top is we're thinking a lot about the way that we test.

And so we have a wonderful partner in Pearson who were doing some of the the, you know, strategic thinking on this is, but the concept is essentially ambient assessment.

So the, the example that I'll use here is like, I don't know if you were trying to assess who the best soccer player in the world is.

I'm sure I'll create a firestorm in the chat here.

You might say Ronaldo or Messi or and Maradona's not around anymore.

But for me it's Maradona.

But you wouldn't watch them play a game and then have them sit for a test at the end, right?

You, you'd be able to watch them for 30 minutes and say, oh man, this person's the one of the best I've ever seen.

And so can we develop technology that through telemetry, analyzes their performance and then attributes a level to that and reduce the, the, the load at the end of all the learning that we built out of, you know, legacy of constraints and everything.

So I know that's a lot, but that's, that's how I'm thinking about it overall.

Yeah, no.

And I think I mean, what, what you, you're also speaking to, which I think is so important is, and this might be that sort of psychological barrier, that sort of trust that we're trying to build is that you're, you're talking about things that that AI is able to do to help hyper personalize, you know, our, our, our own learning journeys.

It knows me, it guides me.

Now, of course we don't want to remove the, the manager, the peers and mentorship that, that this surrounds those, those conversations.

But I think it's really important to to leverage these, this capability to really help complement, but also hyper personalize that journey, which is which is really cool.

And then I'd love to just, you know, Gina, I think you, you guys, certainly we've we've picked up on this as well, but you know, as we're working alongside copilot and agents and, and we talked about the sort of human plus, in some cases human plus agents.

But I'd love to just see, you know, or hear from your perspective, how's that changing the role, especially as we think about early career folks coming in and there's some early kind of management skills, supervising skills that are coming into play.

So I'd love to hear just your thoughts on that as you think not just AI fluency, but what are some of the things that were might actually be bringing forward in early careers, you know, with the early career folks around, you know, management, supervising type, orchestrating type roles.

Yeah, that's a great question.

You know, it's super interesting, right?

You're managing agents or you're working alongside agents as peers, right?

So much comes down to leadership, right?

You're learning early leadership, right?

It might not.

Again, those agents don't have emotion.

And so it's going to be a really interesting test.

Like if I look at my own children, they learn to talk to Alexa very early on.

And Alexa, you don't say please or thank you to Alexa.

And there's manners that need to be incorporated.

So we're, we're just watching that right now as you're managing an agent, the way you communicate with an agent is different than the way you want to communicate with a human right.

And so there's this notion of situational leadership that's going to be super critical for all of these early and professions to learn, which is how do I like have distinction in the way in which I'm working with leading these agents versus working with and leading these people.

And also this is the thing that I think is so interesting.

We always talk about leadership is not managing people.

Leadership is you, you have leadership as an individual contributor.

You also have leadership when you do get the opportunity to people manage.

But the thing that's so critical for these early and profession for me is how do they demonstrate leadership?

How are how are they not just using the tools in a way that's new and compelling?

How are they making a much larger radius of area that they're covering with their impact, right.

And I think that's a very interesting piece.

And what we're watching very closely is that these early and profession folks are not losing sight of leadership does not mean I got there fastest necessarily.

Leadership means I had the biggest array of impact right on the most amount of people and solve the biggest business problem.

And that's another piece that's just like, hey, like because AI is so ego driven, it's about get there fast and deliver and I gotta be faster than everybody else.

And so it immediately goes to our own personal egos and things that we're trying to get out in front of.

And so just teaching these early in profession as they're working and managing these these Co pilots and agents and whatnot, is that notion of situational leadership super, super critical when to when to how and when to have impact with the, with the degree of agents and then how and when to have impact with humans.

And it's very different and they're going to need to learn that.

And again, it goes back to our whole topic of this conversation that's come up a lot is those collaboration skills, those human skills, empathy and the things that are durably human are going to be so, so important.

And it is something we've seen atrophy in our new hires over time.

And so it's something that we're having to build on the job.

And so it's the more somebody can prepare those things and understand that leadership comes in the way you approach things with curiosity is the most impactful leadership, right?

So it'll be, it'll be fascinating to see.

Amazing.

Well, I think I have a minute or two to spare.

I would love, I'll start with Pasquale.

What, what, what's the one thing you want us to hear from you in terms of how you're really thinking about AI readiness?

And, and certainly for the any parents on the call or early careers themselves, you know, how, how we're thinking about it.

And, and also, I think hopefully people feel a lot of confidence in all of you and what you're doing.

So Pasquale, I'm going to start with you.

I would say that the world will not being inherited by the learned, like the folks that read the most books, but the people that are the most agile and adaptable.

So if you can, if you can instill that in your cells and your kids and whoever that like whatever it is that interests you in for even the folks that are like, oh, this is the worst, like forget about work.

Like find the one thing that they love, you know, let's say it's sports or whatever, and then use AI to like make that easier or more fun.

They'll have this like twinkle in the eye moment where they're like, wow, that's so cool.

Time flies and then time goes by fast.

If you can do that for that thing, then it'll catch fire for everything else.

If that's one thing that you can take away, it's that very wise.

Thank you, Ashok, what do you, what's on your mind?

What do you want to share?

So see, I think AI is there to stay and see, I think these graduates should have a perspective of what AI can do for them and great, you know, it's important that they have they, they, they sort of confidently collaborate with AI to see how they can find solutions for their own problems or, you know, your customer problems.

Only then you'll be able to create value.

So I think everybody excellent and yeah, excellent, excellent.

Gina, over to you.

I'd say close it out.

Just focus on creating their own human agency, learning the things they can control, learning the things they can't.

Human agency.

And that development of that skill independent of AI is so hyper critical to a person's everyday happiness in work and personal life and wherever it is.

So helping people focus on that and learn what that means and how to develop it.

Train your brain.

It's all about mindset going forward.

Awesome.

Well, thank you guys.

I learned so much from you.

Very insightful approaches and and ways of thinking, but also quite wise advice.

So many, Many thanks.

And again, I'm back to the folks that have participated on this call and been contributing on the chat.

Thank you for joining.

We hope you learned something as well.

And Many thanks Gina, Ashok and Pasquale.

Thank you.

Bye bye.