AI is disrupting jobs faster than anyone expected.

Today we'll learn who's at risk, how to re skill at scale, and strategies to separate winners from those left behind.

Our guest is David Martin, global lead for people and organization at Boston Consulting Group.

I'm Michael Krigsman and welcome to CXO Talk episode 889.

Thank you so much, Michael.

I really appreciate the opportunity.

I love listening to you and the great interviews you've done, and so I'm very excited.

Give us a sense of your work at Boston Consulting Group.

I lead our people and organization business unit and that is everything involving operating model, redesign, talent and skills, culture change management.

So really all of the people related components that are now so important on the AI, on the AI front.

What do you see are the core dynamics that are driving changes in organizations as as a result of AI?

When ChatGPT came out in late 2022, I expected a lot more apprehension from companies to to get their hands dirty.

And one thing we're seeing is just, you know, widespread use of the tools.

We see a lot of excitement from both employees as well as, you know, in their own lives how they're using the tools.

But a lot of increased uncertainty, both at the individual level, what's going to happen to my role in the organization as well as at the leadership level?

How do I craft a strategy around this dynamic market?

Is my business disrupted?

So a great deal of uncertainty as well that companies are are struggling with.

Could you identify any large works workforce shifts that are already taking place?

Or is this all really kind of pushing into the future?

It's both, but certainly to to the first part, there are a lot of workforce shifts.

You could look at specific categories of jobs, so specific functions.

You see a lot of pushed in the customer service domain across obviously a lot of sectors.

You see a lot in software development, you see a lot in marketing.

And so you're already seeing workforce shift there.

A lot of it is OK, how do individuals in their current role start to use the technology?

How does their role change in these spaces?

I've spent a lot of work with software developers over the past year or so.

I actually was 1 before I joined BCG and you know, the uncertainty about how do I use the tools and how do I deal with such a very rapidly evolving set of tools.

You see GPT 5 come out yesterday, you know, which brings a host of new capabilities.

So you're seeing the impact there on both the day-to-day work as well as how they're feeling about it.

There's obviously much more down the line that that AI is going to impact in the workforce.

So I think there's a lot still ahead of us.

You raise a very interesting point about programmers and software development, because I think many people were under the impression initially that the kind of jobs that would be automated would be, I'm going to say, more rote or maybe lower skilled jobs.

But when you talk about major impacts and software development, it makes you realize that the impact of AI is just everywhere.

The tentacles are everywhere.

It is making folks question, you know what their role looks like.

It is impacting skilled labor administrative tasks too, as you mentioned, kind of the the toil that we talked about of folks day-to-day life.

I think very early on, historically one of the the roles that that was supposed to be most resilient to AI was like in the field of psychology and therapy.

And you saw data emerging in mid 2023 that actually augmented psychology was showing great benefit.

And so it really has been surprising the breadth of of how it's impacting individuals role and how it's helping many roles that maybe didn't expect to to be using AI so quickly.

You know, in terms of AI adoption, Greg Walters on LinkedIn asks a question.

He says there is a statistic making the round stating that 46% of AI implementations are failing and abandoned.

And I'd be really curious just to actually see that.

But he's saying there's also another stat that 40 billion has been invested in AI by companies but resulting in only an 8% increase in revenue.

So it seems like at least according to what he's saying, that there's this tremendous investment but not yet showing huge amounts of value from a people perspective.

Do you have any reactions or thoughts to that?

First of all, the stats don't surprise me.

Maybe I'm a little surprised it's only 40 billion, but the notion of either a, some companies are struggling to realize the value and so they're calling it unsuccessful or be that that the time to value is long.

So not necessarily that they're failing, but it's just, you know, not as not as quickly as as they might want it.

It comes for at least two reasons.

One is companies did a really good job of decentralizing experimentation and AI.

And so you saw what we call 1000 flowers blooming and every different part of an organization was testing it in some place.

So you saw a lot of initiatives and what our data shows is actually the companies who are showing success and positive ROI right now are actually doing fewer things.

That was surprising in our research, fewer, larger, more focused has been faster to value and more successful.

But I do think the other side of it is a timeline thing I'm sure we'll talk about.

And I've, I've heard you talk with many of your guys previously about data quality and really just some of the the necessary enablers that an organization needs to actually get the most value out of it.

And so a lot of companies are having to now play a little bit of catch up on just getting a ship in order.

The other thing I would say around delay or maybe even decreasing the magnitude of benefit, which does get right to the heart of the people.

Point is adoption of an employee workforce is not always what you know the the leaders and the decision makers have expected.

We saw actually the software company, 80% of the engineers had actually expressed excitement about using the new tools.

When we actually looked at how their initiatives with deploying some of those tools is playing out, only 20% of the engineers were actually using it.

So it's like even if that 20% has improved their productivity 100% and you're still at a much smaller amount of benefit than the company might have expected.

And, and so adoption challenges have probably been the most important lever that companies are now using or struggling with and then addressing to capture value and, and I think the problem is, and I'm sure we can dig into it later.

So sorry for the long winded answer, but one of the problems with adoption is either they don't have the skills yet, they haven't been taught properly out of prompt or they haven't even been trained on how to use the tool.

That's one side the skills and one other component is leadership.

And you know, have they communicated a vision on how they expect the role to change or how employees should be using it?

What is the what's the purpose of why they're rolling it out?

Are they trying to save costs?

Are they trying to increase output?

So all of those types of people related issues are many different factors diminishing adoption and and consequently, you know, companies might be struggling for for those reasons as well.

This is comment question from Simone Joe Moore on LinkedIn.

And it's, this is fairly large.

And actually, folks, I'm going to ask you to keep your questions on the shortish side so that the host that's me can more easily sort of read them.

But here's what she says.

It's a, it's a very interesting point.

She says there's a growing concern of employees getting too attached personally to the company AI or using their own AI.

And therefore, there's 2 problems that arise #1 they're putting inherent bias into the system and sharing far too personal data, and there's not enough guidance.

And #2 is when they leave the organization, they're exposing that organization and themselves to mental health, separation anxiety, to the AI that they've been using.

It does also point to the fact that training is not simply how to increase the output of the activities you do day-to-day, but training is also how to manage risk of AI.

So are you introducing biases, not just about the personal information you share, but you know, if you're in talent acquisition, are you introducing bias to the process?

So one is around training on risk, I think is incredible and probably a place that companies have under invested and then training on, you know, how the AI works and how it's using your data.

And I think the more we see employees understand the mechanics behind the models, the more we see them using it in ways that probably help address the first piece of it.

I would also encourage folks like, you know, if you're aware of it, which, you know, obviously great with the question.

That's the first step is, you know, being aware of it is, you know, there's a lot of places in some of these tools like system instruction, custom instructions inside of GPT, where you can actually do a purposeful job of managing what you're sharing that the GBT should kind of base a big part of its answer on.

So a lot, a lot of it there is about training.

I do anticipate, by the way, on this second piece or on the emotional attachment that especially now and, and in your Lenovo CIO interview, I think he did a good job of talking about now the prevalence of voice.

And I do think I, and I see in my personal life as I use voice mode on many of these tools, it, it does start to establish a little bit of a, a sense of friendship there.

It's probably a good reason then to also be using AI in your personal life and not necessarily your enterprise tools.

And that might, that might soften the blow a little bit if you were to separate.

But I it's going to be a challenge.

There's not a perfect solve to the to the second part of that, except I wouldn't encourage personal use outside of outside of work on your own model.

I have to say that I also like the voice, and there have been times it's like you kind of forget that you're talking to a machine.

It's kind, it listens to you, it gives you know, well thought out creative responses.

It comes with nice voices and I, I saw a G PD5 that's coming out with more voices.

And I mean, the scary thing is it's, that's the worst it'll ever be.

You know, the tools are only improving.

And I'm sure part of that is how do they become more more empathetic?

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So Simone Joe Moore comes back and she says she thinks that there needs to be more proper HR governance over AI during employee onboarding, role security, how they work within their team, department and organization, as well as an offboarding strategy to address some of these issues.

Absolutely true.

And I think you see onboarding now becoming exactly to this point, more cross functional.

Like it can't be an HR only thing.

But certainly how HR constructs learning and development and the and the process around onboarding and offboarding is critical to make sure that they're including it.

And, and probably including it more and more because some of the other skills they might be training on as part of the onboarding process now that AI can handle on its own.

Yeah, so, so completely agree with that one wholeheartedly.

I'd, I'd also say some of the tools that HR organizations and 3rd party software providers are coming out with a employee engagement platform.

So a lot of companies, HR departments are pushing on, hey, can we have a single pane of glass for a chat bot to, to work with employees and be more, you know, asynchronous and self-serve.

And I think you'll see the onboarding process also have that where employees are a little bit more willing to ask difficult questions.

And so I, I think that it's true in the onboarding process, some of it is structure and some of it is enhanced tools will actually help to deliver that type of training as well.

Just in order here on Twitter on X, Arsalan Khan says as a disruptive tool, do you think organizations are not adopting AI fast enough due to the lack of vision by the executive leadership?

In many cases, I do think that executives are struggling with the uncertainty and they don't have a concrete vision that if they try to communicate, would be compelling to the workforce.

So I do think articulating the vision is 1.

What's fundamental to the question is, are they thinking about AI disruptively enough?

And I would say no to that as well.

A lot of companies right now are challenging with near term issues and cost pressure and inflation in geopolitical.

And so a lot of the uses of AI in the initiatives that companies are pushing on are too incremental.

It is how to use AI to further automate tasks or specific parts of a workflow.

And they're losing an opportunity to actually rethink the workflow end to end.

And I mean, that might mean consolidating roles.

It certainly is how humans and agents are going to work together to deliver a more seamless workflow.

It's not just automating specific tasks.

And so one pitfall, the companies have certainly experienced this thinking too incrementally and and consequently, you're not going to articulate an incremental vision.

So yeah, absolutely.

We call that reshaping, either reshaping a function or reshaping A workflow that might be cross functional.

You do have to completely almost almost clean sheet design what that should look like so that you can have a meaningful enough and an opportunity maximizing enough approach to using AI.

Kurt Milne on X says that if only 20% of an employee group is using AI, and that group has a range of skills and results, then the overall benefit may not meet expectations.

No, that's right.

That's why adoption is the biggest challenge facing companies right now in terms of getting the value they're looking for out of it.

And, and frankly, if you're rolling out tools that only 20% are using it, it's also a little bit deflating.

And I'm certainly, I'm certain for the decision makers to see low adoption like that.

And for the employees who you know in that case, I I think the 20% might be coming from my comment earlier in that case where 80% of the employees were excited about it.

Kurt Milne comes back with a really interesting question.

He says are there new cognitive skills needed to use AI?

For example to run, you run AI three times and you get 3 different outputs.

Then the need to spend time and mental cycles reading and comparing to pick the best answer, and that is a different skill than copy editing.

The path on that one specifically is you're going to start to see agents that smash, you know, feedback up against three models and try to avoid hallucinations, which is great.

It's what I do.

I'm nervous about hallucinations and how I use it.

So I'll take the output from one and put it in the out there and, you know, pressure test it.

So yeah, that that is that is a skill set or competency that is changing in some of the roles.

You could take customer service too.

I think a lot of companies have a vision that a customer service representative who right now is looking at, you know, dashboard with multiple screens and swivel chairing between them, getting instructed by, you know, those tools on what to do.

That role might completely change to actually almost a manager of agents and and that individual then is almost like a telecommunications network operation center where they're looking for trends that are coming back from the agents themselves.

They're looking for, Hey, when and how do I, you know, intercept some of these customer conversations?

So the the skills of being a a manager and observer of agents and knowing when to step in or when to pressure test what they're doing is going to be prevalent in many jobs that currently don't require that at all right now.

And and don't usually even, you know, recruit for that type of skill set.

I also think like the, there's another one on this cognitive to some degree that being really eager and willing to learn from the AI.

So again, working with software developers talking about vibe coding and talking about how to introduce AI into their workflow.

Some of the most like exciting interactions I saw the developers have with the tools is like asking a question, OK, why are you suggesting I do that?

And so really like embedding into the day-to-day like mindset of how do I use the tools as I'm using them to also help instruct me on what they're doing and potentially improve how I think about and do the job as well.

So yeah, IA lot of new cognitive skills.

You always hear creativity will be more valued.

And I think creativity will be introduced as part of many jobs that currently don't demand it.

Critical thinking because of hallucinations.

All all of these competencies, I think will be magnified in their importance.

There's so much that you just packed into that response, but one of the things that kind of grappling with right now is when you have employees that are managing groups of agents rather than other people as employees, it raises a whole host of issues, not just about job displacement, but definitely raises that issue, but the nature of job augmentation with AI and the relationship of jobs to AI.

Can you kind of unpack that for us a little bit?

You're going to see a lot of roles either working side by side with agents in a collaborative way or augmented way, or roles that are having to manage agents.

It's it's a completely different muscle to build.

You mentioned earlier about treating AI like people.

Your Jensen Wong talk about, you know, the CIO is the CHRO in the future.

Moderna integrated those two roles.

So I do think one element of that is really being clear on the role that the agents playing, not just how the role might change for the human, but the role that the agents playing.

And then that human who's working side by side with them or looking over many of those agents, their ability to to train it and coach it and intervene to give it more, you know, prescriptive detail.

A lot of how the interaction with agents will take place is very much like a manager and a frontline employee where it is, it's collaborative, it's coaching, it's training.

I think thankfully the performance reviews and the work life balance matter less for agents, which I know it's been, you know, talked about a lot or or maybe in the future, you know, we get agents who are.

Who are very interested in those things.

But yeah, I do a lot of components of the day-to-day life with an agent and how employees and even frontline employees like my customer service example earlier are now going to become managers, I think is really important.

I think you'll also see, and again, maybe back to the cognitive point, a lot of roles and how this is different than how companies were attacking digital for the past 20 years.

A lot of roles themselves are going to be expected to identify where to use agents in the workflow and and to be trained on how to build agents because English is code now and you know, some of those tools are pretty easy to spin up new agents.

So many different roles are going to be thinking about how can I introduce agents into my workflow?

We have two questions, one from Greg Walters, one from Arsalan Khan that both are questioning the role of the C-Suite.

And let me just read you both of these and these are kind of loaded questions, but but but I think there's an interesting point here.

Greg Walter says AI is the end of the C-Suite.

And he also says, aren't AI and LO Ms.

an example of the fall of centralized C level command and control, shifting the way that we work away from 19th century managed structures?

And Arslan Khan says on Twitter X, if executive leadership has little vision, then what chance of success does the CIO even have?

AI is, again, like any other software adoption, which comes down to leadership and culture.

In both cases, they're kind of questioning the role of senior leaders.

First of all, to the very last point you mentioned on the role of the leaders in helping facilitate AI adoption is like the statistics on that are incredible.

We have seen in our research that maybe surprisingly, maybe not, but as adoption of AI increases, fear of job loss increases, like I said, maybe that's intuitive.

You see the power of it.

And so you see places where I might be able to, to do more of what you do, but the role of the leader is incredibly influential on that.

So 65% of employees, if they say their leader is not supportive or doesn't paint the vision, then they are fearful.

Whereas for the 25% of employees who say their leader is supportive, it's only 15%.

And one of one of those things is being able to articulate that vision that we talked about.

And, and it's funny, I, I know you've had other, other individuals on the podcast who talk about the importance of vulnerability and transparency for leaders, which is absolutely true.

I think it's also been really challenging for leaders to be vulnerable and admit they don't have a vision for AI.

And so you do have to be able to be both.

So communicating the vision incredibly important.

Now the role of the C-Suite.

I, I do think the first question and the second question around what does that mean for the CIO go hand in hand?

Because I mean, first of all, the C-Suite is almost by obligation there for fiduciary responsibility, but more importantly for the success of the organization, you are going to see more of those jobs be less based on practitioner skill sets and more based on strategic thinking.

And so I think there's a huge role across those different functions for what is the strategy related to the, the business objective that I'm trying to solve.

I think that the C-Suite might consolidate roles and you might see new types of roles emerging.

Do more companies, as an example, integrate sales and marketing and have a chief revenue officer like a lot of software companies have done potentially.

So you might see the C-Suite look different.

Now, the role of the CIO, if you go back to that point that the C-Suite is going to be much more strategic.

I mean, this would be the point is the CEO who's dealing with a lot of uncertainty right now about what the strategy is looking to a CIO to help be the thought partner there.

And I mean, the problem is, again, CEOs are facing so many different challenges right now.

I talked about inflation earlier in the multitude of those that they're not as able to stay on top of the cutting edge trends.

Whereas a CIOI think is, is actually very excited and enthused by, you know, all of the changes taking place and the new technology is coming out.

So the role of CIO is more important now than ever, and their ability to help craft the corporate vision and not just the technology vision for the organization is more important now than ever.

That also will require CIOs to upskill their understanding of how the business functions because historically the CIO role was primarily inward looking, taking care of systems.

And now what you're describing is CIO slash CHRO role in a way, but not just managing people, managing groups of agents.

And managing all of the risk that comes along with agentic workflows, whether it be alignment risk or cyber risk or bias risk, reputational, obviously a multitude of new risks and a larger amount of all of those risks that the CIO is having to deal with and having to support the organization on.

You do.

I mean, so it's funny because in HR you always talk about the HR business partner.

And I think where IT for the past 40 years has consistently struggled with the dynamic of how do I have a tighter relationship with the business, so to speak.

Those walls are being torn down.

And, and part of that is because a, the importance of technology is visibly so much more important be the, the understanding of technology is increasing as well.

You see, you know, whether it be a president or GM of a business unit or a functional leader, more and more of those individuals are more familiar with technology, more informed on the importance of it.

And so you see more of a a push pull, like more collaborative relationship with IT in the business, which I think is incredibly healthy.

And then, yeah, the complexity of the CIO role is, is expanding your point on managing agents, discovering them, managing all the risks, supporting the organization and all of that.

I think is, I mean, again, I think you're going to see CIO being a, a really critical role for companies who are, you know, realizing value from their investments.

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David, your AI at Work report describes frontline employees, a gap between frontline employees adopting AI tools.

51% of frontline employees, according to your report, have adopted AI tools and leadership has an 85% level of adoption.

Does that indicate resistance from frontline employees or what's going on there?

And maybe we can you can take a step back and just give us an an overview of that research.

This is a study we conducted globally across 10,000 employees of all levels.

It focused on the the impact that people components of an organization have on adoption and success at AI initiatives.

A lot of what we focused on was leadership behavior.

We focused on talent and skills.

We did get into tool quality.

We do see, you know, are the tools are the tools, you know, good enough to use is a piece of that too frontline employee.

We look at adoption across all different levels of an employee base and we did see that not only was there a significant difference between adoption between leaders and frontline employees, but also the trend stagnated, I think, which surprised us.

The adoption of of AI tools at the frontline actually had not increased since the last time we were in the the survey.

There's multiple factors for that.

I do think part of it is what you said, which is there is a little bit of reticence to do it unless employees are told exactly what the objective is.

Many employees feel our data says many employees feel threatened by job loss and so they don't adopt.

But there's also like you can de average that answer frontline employee.

In many cases, frontline employees have less use for AI than leaders do.

You know, you're looking at retail store employees and field technicians who are more and more using it.

But you know, there's a lot of on the ground labor that takes place where AI is not going to be an important a piece of technology for the the employee to use in their day-to-day lives.

I'd say the other, the other thing it highlights, which, you know, keeps me up at night, is I do think that leaders have observed that that potential disruption to jobs and potential threat of, of, of AI to the jobs is probably as pronounced for leaders as it is for frontline employees.

I think there's been a lot of commentary and, and rightfully so, that that white collar labor and that management all the way up to the top, you know, there's a lot of opportunity to automate a lot of administrative tasks and, and make that part of the workforce more efficient too.

So I think they realize, you know, you need to stay ahead of the curve and and get familiar with the tools.

What should business and technology leaders be doing in order to encourage broader adoption?

I do think how they prioritize which initiatives the push on has probably changed historically for digital investment.

You said, you know, it's impact versus feasibility or time and there is a new dimension that does get into the leader piece and does influence adoption a lot on selecting initiatives that also reduce the toil of an employee's life.

And again, it may be why leaders are using it more is administrative tasks, as an example, are something that employees would prefer to not have to do and to hand off to AI.

So how leaders prioritize initiatives and how they include employee centricity in the decisions they make on where to invest, I think matters significantly.

I mentioned vision and I just touched on a more specific part of a vision, which is objective setting.

So being able to really clearly communicate what the intent of the impact of AI usage is as as an example, the tech company I'm working with, with their software engineers, obviously huge opportunity to improve productivity.

This company has no interest in reducing the size of that workforce or the cost of that workforce.

In many cases across companies I'm working with, they're so far behind on their digital road map that they are absolutely looking for quad code and all of the different tools that help cursor all the tools that help support software engineering as a means to accelerate their road map.

No interest in cost savings on that front for this company, but because they haven't said that specifically, most of the frontline employees we talked to are worried about that and we see their adoption not be what we think it could be.

So that's another piece of leader.

The the third one that came out in the research is leaders modeling the right behavior.

And I think that comes in two forms.

One is using it themselves, which we do see leaders doing.

And that we had this funny, I was in India last week and I was meeting with Aceo and his team and they were preparing for a board meeting and they created custom GPTS for different board members.

And I mean, you could debate the, you know, the cost benefit trade off and all of that.

It was a hilarious use case that I'm imagine a lot of the C-Suite executives are starting to learn how to do.

And I was like, you need to tell your employees some of these stories so they understand that you're embracing the technology too, and that you're taking the time to upskill yourself on it.

And the the last piece, I was so modeling the right behaviors.

It also comes in the form of communication.

And are you setting, you know, a positive tone around AI and the benefits that it can have on augmenting, augmenting the workforce?

The last one is investing in training.

If if you are a company facing cost pressure, you're looking to, you know, reduce people costs with AI tools, then you need to be reinvesting some of that productivity savings in training and upskilling.

And if you can cut 25% of time spent, you better be applying 5% or 10% of that back into training the employee, the employee base.

And we see it has a huge impact on employee morale.

We see it has a huge impact on the effectiveness of adoption.

And it's great signalling to the workforce that that you're not just doing it myopically, but that you have more of a plan around it.

So upskilling is another big piece that leaders can really invest in.

At the same time, yes, leaders should be investing in reskilling, but there is a lot of temptation to use AI purely for cost cutting purposes.

Let's get rid of, you know, it's industrial automation only.

It's done with agents as opposed to, you know, people, you know machines.

That's been true, you know, since predictive AI to your point and you know, finance organizations have used it to improve forecasting and reduce some of the people cost they put into forecasting.

So undeniably that's true.

My point there is they need to be reinvesting some of that savings and you can't as we would say you know how do you cash the check on productivity if it's in cost, you need to be reinvesting some of them.

Elizabeth Shaw has an interesting question and she says you talked about rethinking workflows.

This is not a quick process and is fraught with business danger.

For remember, there were plenty of organizations that experienced business emergencies and failed projects when quote UN quote redesigning workflows for digital transformation and ERP.

Being a former product manager and software engineer, this one touches on the software development life cycle.

And they say, you know, how does the bill become a lot?

Well, you have market research and consumer insights, customer experience work.

You got product management, UIUX solution architecture, enterprise architecture, DeVos front end, full stack engineering data.

Like everyone here probably knows all the SDLC.

And we've had some organizations say, how do I turn that eleven person team that I don't really know if it's a 2 pizza box team anymore.

How do I take that eleven person team and do it with three people using agents?

That is a disruptive change exactly to the question.

That would be a disruptive change to that workflow that is rife with risk.

I would say the first one is just quality risk.

Like can those three people actually sufficiently do those jobs at the same level of quality?

And then what would the downstream impact be by having a lower degree of quality?

But you absolutely, if you're thinking about it end to end, have to have a plan.

You need to do it so that your near term decisions, you're making an AI investment and with your people, you're not going to try to rewind those later.

You need to have the plan, but call it a three-year end to end vision.

And then you need to be looking at what are the proper steps along the way to get to that plan that allow for, you know, some of the risks that you describe, whether it be skilling risks or cultural risks by, you know, that type of disruptive stuff.

I think you'll see org restructuring too as part of that I mentioned earlier kind of sales and marketing.

You know, you could think about engineering a product, things like that.

Companies are not just going to be changing the workflow and how people like the ways of working, but also will be rethinking their organizational structures as part of that.

Or if they don't, I think it it increases the risk for sure.

Microsoft Research recently came out with a very interesting report where they described jobs that are most likely to be affected or displaced by AI and jobs least likely.

And the top jobs that they said were going to be displaced are interpreters and translators, historians, passenger attendants, and we could say parking parking lot attendants.

I'm sure we've all been to automated parking lots.

And you have to pull out your phone and try to figure out how it works.

Sales reps.

And among the the least likely to be affected are dredge operators and lock operators.

You know, locks like on bodies of water.

I live next to Volter's lock on the Thames in Maidenhead, England.

It was one of the most exciting things in my day.

I was watching the locks work.

I can imagine that is a difficult one to replace.

Yes, I, I would say also like to to pile on the ones that I'm sure will be in increased demand is if you look at the amount of infrastructure investment that the US and other countries are making on their power as well as in semiconductor manufacturing, there's a lot of both blue collar and white collar work that's needed there that will be I think immune to the the impact of AI.

So I do think there's a lot of manual task labor at the front line that we talked about earlier that is highly immune, as you mentioned, and I do.

That's going to have an implication, by the way, on education generally.

And I know we've talked about, you know, how the education system works for a long time now.

But but because those jobs are going to be an increased demand, we're going to need to rethink how we're building skills and building career paths so that we can encourage individuals to step into those roles.

There are many jobs, by the way, that will be significantly impacted by AI, but it will not lead to job loss necessarily, but actually just an incredible explosion of, you know, work in that space.

You could take software engineering.

I'm sure there's going to be a lot.

I wondered if lawyers who people say are potentially, you know, there's a lot of automation there.

Will there be 100 times the legal case like you do?

You do wonder how much people use the productivity improvements from AI to increase output and activity versus just replace human labor.

On this topic of training and skilling, a recent Fortune article warned that Gen.

Z should learn AI, but their job prospects may still be difficult because of structural changes caused by AI.

So what advice do you have for folks in Gen.

Z who are going to be facing this wall of automation?

You're seeing it some right now.

Well, I, I believe I read that unemployment rate for recent grads has ticked up a little bit.

And it's interesting.

We don't talk about it, but I have a 18 year old daughter who's about to go off to college.

So there's a lot of conversation about how AI is going to impact her, you know, post college career and, and what she should study and all those things.

I mean, 11 great thing about Gen.

Z is I'm positive that they will be highly adaptable and resilient.

They're obviously the savviest users of digital technology and it's already embedded into most of the apps that they're using.

So at least they'll have the familiarity with the tools.

Now what are they going to do from a job perspective?

You're going to see an incredible explosion of innovation and new companies and new industries that emerge.

I just like we did with.com and I think that Gen.

Z will be on the forefront just like, you know, a lot of them created the YouTube creator industry out of nothing.

I think you'll see a lot of really neat new industries emerge from the creativity that comes from that age group.

I do think probably their career looks very different than what my career looked like.

But I think that's true between, you know, myself and my father as well.

So that's, that's just the nature of time and how we evolved.

But but it is a concern and and like I mentioned, I do think it's a concern too on where they spend their time and how they invest in skills leading up to entering the workforce.

Absolutely.

You mentioned earlier this time dividend that arises from AI automation.

It raises the question to what extent are these benefits real?

So as companies adopt AI, will they really migrate employees to higher value work or as we were talking earlier, will, will these employees simply be made redundant and fired as part of garden variety cost cutting measures?

So how do you think this all plays out?

It's dangerous to only focus on the cost measures.

And, and, and here's why, because I think a lot of companies who are probably asking those questions are also potentially ripe for disruption or their industry, you know, being disrupted.

And so I think you will see part of the time dividends start to go toward innovation.

If you think about the old Google model, and it might still currently be, but I, I know it from a long time ago of, you know, spending 20% of your time thinking about other, you know, blue sky initiatives are working on it.

You will see companies more strategically allocate time from this productivity savings and time dividend toward innovation.

And, and it's because I think a lot of companies are going to start realizing the disruptive threat of, of, of disruption.

Obviously, I think the other piece on on time dividend, and I'll use a specific example because you asked like, will they do higher value activities again, going back to software development, It's going to be true in marketing as well.

And we see that a little bit talking to a company about using AI to improve the productivity of the daily coding.

And that individual, that team actually was dealing with legacy IT that has a bunch of interdependencies.

It's all the technical debt that in all of our enterprise listeners here deal with everyday and they have not been able to spend the time and the thinking power on refactoring code and how do we design this is a Java 8 to Java 11 upgrade or something to that nature.

And so it's like the strategy behind improving the quality of the existing assets that the company has, I think will be increasingly an important role for for the time dividend that you're describing right now.

Back to the vision point, I do think if companies aren't using it for cost savings, then many companies are not being creative enough or forward thinking enough to not just say, OK, do more of the same.

So if you think about that example I just use, it's like you could just say, OK, go build more code and you know, go deploy more code.

Instead they're saying OK, let's go re architect.

So being really thoughtful about, you know, leaders and setting the expectations for how you're using the time, I think it's really important we see that at BCG as well.

You know, we've rolled out a lot of AI tools for our consulting staff.

They say they're saving time.

You know, we wonder, OK, are they sleeping more at night?

Because for us, in a job where our employees work really hard and work life balance is increasingly important, it's like, great.

Yeah.

Our goal with the productivity is, you know, they can get more time to have a more sustainable work life, but you need a plan for what you're going to do with it.

To your point, I don't think that everyone is just going to say do more of the same thing.

That would be myopic.

On the subject of consulting, I recently saw a demo of agentic AI tools that are designed specifically to replace junior consulting consultants doing research and gathering information.

How real is this AI threat in consulting?

It's an incredibly helpful tool for our consultants to use is, is one thing.

So and, and what I mean by that is yes, it does do a lot of the work that many of our consultants do.

So there's a threat side of that.

And then in the near term, there's a, it takes a lot of toil out of their job and allows them to be more strategic.

I think it opens up opportunities for new business models for us.

You know, are there opportunities as an example for us to provide more of a software as a service and a consultant as a service?

Because we might think we can train that type of model better than anyone else can.

That's one example.

But we are tracking and, and by the way, I think all of us partners, before we go into any of our client meetings, are doing deep research on the, on the client.

We are pressure testing our own analysis and saying, if I'm a client, what would I be seeing from AI?

And are we exceeding that bar and justifying, you know, the fees that we charge?

So I think that it's been very important for consulting to appreciate, you know, the, the side by side threat.

We actually have been measuring what components of the value we provide our clients are replaced by AI, to your point, and it stretches across many different dimensions, industry expertise and all that kind of stuff.

And one place that AI has not come close to cracking the nut is our ability to understand our clients and their needs at a company specific level very deeply and to tailor our answers.

Right now, if you run deep research or if you're using any off the shelf tools to try to solve the strategic problems that we saw on a day-to-day basis, it's going to be more generic and more for the industry rather than more specific to the company.

And I think that's harder to replace.

You'll of course see enterprise models being trained over time, I'm sure.

But right now we feel like our ability to really think with the lens of our specific client in mind and tailor solutions for them is is improved because of this.

Like back to the point, I think it frees up our time to think more about those strategic tasks.

This question about OR issue about LLMS not providing deep company specific information.

I wonder if that's at least partially a data problem because I have seen a number of companies recently that go out to essentially aggregate interrogate databases across a company.

And once you start doing that, you you build up the data that you need that a sufficiently fast and powerful LLM could then use to report back whatever depth you might want on all aspects of the company, sales, marketing, everything, customers, you name it.

Yes, and using a generative AI as a potential mechanism to leapfrog some of the like this is I think part of I think this is partly in there like using Jenny I to actually leapfrog and maybe mitigate some of the lack of connectedness with company data is also an opportunity.

I think you're spot on.

And and that is fed, you know, historically into things like retrieval augmented generation where you're using off the shelf LLM you're you're injecting some first party data in there to get something that's more company specific.

I think that's absolutely right.

That's part of the near term future.

I think The thing is our clients are not necessarily saying that that is the highest priority place for them to be spending their time.

And in a world where as we know, talent is so slim and IT talent specifically and tech talent specifically and core business needs for a company are so pronounced and there's so much opportunity to improve there.

I have not seen a lot of our clients dedicate a lot of time and resources to what you just described because they they have incredibly important priorities they're pushing on in parallel.

So.

Arsalan Khan says I'll just read his question verbatim.

What about power of 1 AI in one department versus AI in another department?

Whichever department has more power, people, revenue, will they get their way?

Who is the AI referee?

Right.

Well, and you've seen that in like data reporting and analytics now for the past 10 years where every organization has their own analytics team that's creating their own dashboards.

I think there's some truth to that.

I think it, it points toward the importance of IT and the enterprise IT strategy and platform strategy.

I think one danger that companies are facing is the fragmentation of platform decisions, you know, across different functions.

And so resource allocation, to your point that comes from central IT and the distribution of tech talent toward different functions is increased in importance.

There's something about human nature there.

And the question that's like, I think of course different parts of the organization are probably going to have more power and influence than others.

AI is not solving for, you know, basic human nature at this point, for better or for worse.

So that will probably be the case.

I think it's really important to be at ACEO and CIO level though, and how the strategy is crafted there.

Because what you don't want to do is have a lot of function specific platforms that again, like only really harden how the organization currently works.

And the more you can make the platforms cross functional, the more you'll be able to realize a more seamless customer experience.

So ideally you're not having those siloed platforms.

Your AI at Work report talks about global differences in AI adoption.

I think this is very, very important for people to understand.

The report states that respondents from the global S have significantly higher adoption rates than in the West.

For example, India and folks listen to this has India has 92% adoption compared to 64% in the US.

Can you just tell us about the implications of this?

It seems very profound to me.

The implications are right and I just came back from Delhi in Mumbai and it's incredible what they're doing there.

Some of it is job specific.

You know, we talked earlier about just the nature of some roles using it more than others.

India obviously has an incredibly large and strong population of software developers and those types of roles that are more suited to use it.

Demographic difference it does.

It points out some of the differences in demographics too and where some of just countries will differ because they're either a younger workforce or a more aging workforce.

India on the younger side relative to some of the developed markets it.

But your last point I think is the most important, which are it does have implications on what you think the future looks like 5 years from now.

Now I think India like amazing users.

You'll probably see a lot of innovation coming from there because of the usage and because of time.

Other than all we talked about there, I do think the US while behind on adoption is obviously making very important infrastructure strategic decisions.

And so you'll still see despite some of the lack of adoption, I think the incredibly important AI capabilities coming out of the US, but it is it is fascinating to see there's a very broad difference across geographies on, on usage adoption fear.

India was also one of the highest in terms of their fear of job loss with AI, which goes back to leader point their interest in shadow.

IT was also pronounced in high individuals who are not provided the right tools are using tools on their own, which is I think scary for CIOs and highly prevalent and we talked about that in the report.

So a lot of interesting geospecific Nuggets in there.

David, fundamentally, are you an optimist, A pessimist, or do you think this world is so confusing that who knows?

I'm a huge optimist.

I'm not going to end on a down point.

It'll be down and up real fast.

I had a daughter, 4 kids.

One of my daughter's passed away from pediatric cancer a few years ago and I viewed it so close to breakthrough.

So I'm an optimist because of the impact that AI is going to have on science and on public health.

And so I think you have to be excited just about the innovation that's going to come through there.

I think human ingenuity and all of the past data we have in terms of job loss and recreation is like, we're an incredibly resilient population and incredibly creative population.

So the doomer side of it, I, I'm very optimistic.

I think that we continue to thrive.

We, we find the right ways to use AI as a helpful tool to make our lives better.

So very, very much an optimist.

And with that, a huge thank you to David Martin.

He's global lead for people and organization at Boston Consulting Group.

David, I can't thank you enough.

Thank you for being here with us today.

Thank you Michael.

I've I've loved loved the time today and really appreciate what you do.

Your your podcasts are fascinating.

Encourage folks to sign up.

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