AI and the Workforce

Summary

The panel discussion delves into the rapid evolution of technology, particularly Generative AI, and its profound impact on the workforce and skills required for the future. Speakers emphasize the importance of human skills, adaptability, and continuous learning in an era where jobs and required skillsets are transforming. The conversation highlights the necessity for individuals to approach their careers with a growth mindset, equipping themselves with a broad set of skills to navigate the dynamic landscape of work. Panelists also discuss the role of organizations and HR in fostering talent development and the need for a shift from traditional job descriptions to a focus on skills and capabilities that can adapt to technological advancements.

Takeaways

• 🚀 Rapid advancements in technology, particularly in Generative AI, are accelerating changes in the workforce and the nature of jobs.
• 🧠 The focus is shifting from just保住工作 (preserving jobs) to enhancing skills, emphasizing the importance of continuous learning and adaptability.
• 🌟 Human skills are increasingly important, but there's a need for clarity on what 'human skills' mean in the context of an AI-driven future.
• 👨‍👩‍👧‍👦 There's a critical need to prepare the younger generation for jobs that will be relevant in 5 to 10 years, which may not even exist today.
• 🏫 Educational institutions are tasked with identifying and teaching the necessary skills for the new age, which includes a balance of technical and human skills.
• 🏅 Today's workers are compared to Olympic athletes training for an unknown discipline, highlighting the need for versatile and adaptable skill sets.
• 🤖 AI and machine learning are not just about automation; they are tools for prediction and dealing with uncertainty in business.
• 📈 Economists initially predicted job loss due to AI, but evidence shows that AI investment has led to job growth, particularly in high-skilled roles.
• 💼 Organizations are hiring for roles that complement AI technology, which is leading to flatter organizational structures with less hierarchy.
• 🌱 The concept of a 'growth mindset' is crucial for leaders, emphasizing the importance of innovation, risk-taking, and adaptability.
• ⚖️ There's a need for a balance between technical proficiency and ethical considerations when implementing AI and other advanced technologies.

Q & A

How is technology, particularly Generative AI, influencing the current workforce?

Technology, and specifically Generative AI, is making rapid advancements, leading to significant changes in the workforce. It is shifting the focus from the fear of job loss to the necessity of skill development and adaptation to new technologies.

What does Tom Friedman's quote imply about the current job market?

Friedman's quote suggests that today's workers need to prepare for a dynamic and uncertain job market, where they must be versatile and adaptable, much like athletes training for the Olympics, but without knowing the exact discipline they'll compete in.

What is the role of 'human skills' in the age of AI?

Human skills are becoming increasingly important as they complement AI technologies. These skills include problem-solving, creativity, leadership, and social influence, which are critical for working effectively alongside AI and driving innovation.

How has the organizational structure been affected by AI?

Organizational structures are becoming flatter and less hierarchical as AI technologies require a more collaborative and flexible approach. There is a shift towards hiring highly educated workers who can contribute to product development and manage the production cycle.

What are the key skills that are necessary for success in the new world of work?

Key skills include problem-solving, analytical thinking, creativity, originality, initiative, leadership, social influence, active learning, self-management, resilience, stress tolerance, and flexibility.

How is the role of executives changing in the face of technological advancements?

Executives need to develop a growth mindset and a digital mindset, which involves a willingness to innovate, take calculated risks, and learn about next-generation capabilities. They must also be decisive, fast-moving, and have a foundational understanding of AI and digital technologies.

What advice would you give to someone starting their career in the current job market?

When choosing a job or role, prioritize opportunities that offer growth and development. Seek organizations that are set up for success with a culture that supports innovation and collaboration. Consider the entire fabric of the organization and the skills it needs.

How should companies approach the challenge of reskilling their workforce?

Companies should create programs that allow for malleability in skill sets, providing opportunities for employees to learn and adapt to new technologies. They should also be open to hiring individuals who may not have specific technical skills but are adaptable and capable of learning.

What is the impact of AI on the length of the workweek and the amount of work humans need to do?

AI has the potential to reduce the amount of work humans need to do by automating tedious and monotonous tasks, thereby freeing up time for higher-order tasks that require human creativity and strategic thinking.

How can HR departments adapt to the rapid changes in technology and skill requirements?

HR departments need to be more open-minded and adaptable, focusing on the skills that are learnable and those that don't exist yet. They should prioritize the right skill sets for the current stage of the organization's journey and be willing to make trade-offs.

What does the future of HR look like in the context of AI and automation?

The future of HR involves a shift from finding people for static jobs to understanding and orchestrating a collection of skills needed for the future. It requires a design mindset to rethink how work is done, with a focus on team dynamics and project-based work.

Outlines

00:00

😀 Introduction to the Panel on AI and Workforce Skills

The panel begins with an introduction to the rapid advancements in technology, particularly Generative AI, and its implications on the workforce. The moderator expresses concern over the potential obsolescence of current skills and jobs, emphasizing the need to understand how to adapt and learn in the new age of AI. The importance of human skills in the face of technological change is highlighted, and the panelists' expertise in innovation, entrepreneurship, and technological change is introduced.

05:00

🚀 AI as a Prediction Technology and its Impact on Jobs

The second paragraph delves into the nature of AI as a prediction technology that deals with structured and unstructured data. It contrasts past perceptions of AI as a job-replacing automation with current findings that show AI complementing high-skilled jobs rather than replacing them. The discussion focuses on how AI is integrated into product innovation and the types of jobs that are in demand, such as those involved in product development and management.

10:03

📚 The Evolving Role of Education in the Age of AI

The third paragraph addresses the challenges of educating individuals for a future where job roles and required skills are in flux. It emphasizes the need for a growth mindset and continuous learning as key to success in the new world. The importance of technical skills in conjunction with human skills is discussed, along with the role of self-management and adaptability in navigating the changing landscape of work.

15:06

🧑‍💼 Leadership Skills for the Digital Age

Angela Young discusses the critical leadership skills needed in the digital age, highlighting change management, growth mindset, and digital awareness. She mentions the '30% rule', suggesting that all employees, regardless of their role, should have a foundational understanding of AI and digital technologies. The need for leaders to be change agents, foster innovation, and be risk-aware is also covered.

20:08

🤔 The Changing Dynamics of Careers and Skill Requirements

The panelists explore the differences in skill requirements between the past and present, emphasizing the need for lifelong learning and adaptability. They discuss the concept of being 'serial masters' of various skills throughout one's career due to the shortening half-life of technical skills. The conversation also touches on the shift from linear career paths to more dynamic and project-based work.

25:09

🌟 Navigating Career Choices in a Changing Job Landscape

The panelists offer advice on choosing between different career options in a landscape where skills and job roles are evolving. They discuss the importance of seeking growth and development opportunities, aligning with one's values, and considering the company culture and platform. The conversation also addresses the need for organizations to be prepared for digital transformation and the role of integrity in leadership.

30:10

📈 The Role of AI in Complementing Human Work

The panelists discuss the complementary role of AI in the workplace, using the example of HR professionals who have seen their roles evolve with AI tools taking over more routine tasks. They express optimism about AI's potential to enhance human work rather than replace it and emphasize the importance of understanding AI's capabilities and limitations.

35:10

🛠️ The Future of HR and Workforce Management

The final paragraph addresses the future of HR in the context of AI and automation. The panelists suggest that HR must adapt to new trends in hiring and talent management, focusing on the potential for AI to augment human work rather than replace it. They discuss the need for HR departments to become more comfortable with change and to prioritize the right skill sets for the future.

Keywords

💡Generative AI

Generative AI refers to a category of artificial intelligence technologies that can create new content, such as text, images, or music. It is a significant driver of change in the workforce, as discussed in the video, because it can automate certain tasks, thereby affecting job roles and the skills required of workers. In the context of the video, generative AI is associated with the fear that jobs may become obsolete, but it's also seen as a complementary technology that can enhance human work.

💡Workforce Skills

Workforce skills are the abilities and competencies that employees need to perform their jobs effectively. The video emphasizes the importance of evolving these skills in the age of AI. It suggests that traditional skills may become less relevant while new skills, particularly those that harness the power of AI, will become more valuable. The panelists discuss the necessity for continuous learning and adaptation as the workforce changes.

💡Human Skills

Human skills are non-technical abilities that complement technical expertise. They include creativity, emotional intelligence, leadership, and social influence. The video script highlights that while technical skills are crucial, human skills remain indispensable, especially in an AI-driven future. The panelists suggest that fostering human skills is key to preparing for changes in the job market.

💡Product Innovation

Product innovation involves creating new products or improving existing ones. In the context of the video, product innovation is mentioned as a common application of AI technologies, such as self-driving cars and the development of the Covid-19 vaccine by Moderna. The script suggests that AI has been particularly useful in accelerating product development cycles, which in turn has implications for the types of skills needed in the workforce.

💡Organizational Structure

Organizational structure refers to the arrangement of roles, departments, and reporting relationships within a company. The video discusses how AI has led to changes in organizational hierarchies, with a trend towards flatter structures that emphasize collaboration and innovation. The panelists suggest that as AI complements certain roles, there is a shift in the types of skills and roles that are valued within organizations.

💡Self-Management

Self-management is the ability of individuals to regulate their own behavior and work effectively without close supervision. The video script identifies self-management skills, including resilience and stress tolerance, as increasingly important in the modern workforce. These skills are crucial for navigating the uncertainties and rapid changes brought about by technological advancements.

💡Active Learning

Active learning is an educational approach that emphasizes student participation and engagement, as opposed to passive absorption of information. The video highlights active learning as a meta-skill, meaning the ability to learn new skills is itself a valuable skill. This is particularly relevant in a future where workers are expected to continually update their skillsets in response to technological changes.

💡Technology Use

Technology use involves not only the interaction with technology but also the ability to monitor, control, and work effectively with technological tools. The video script discusses the importance of understanding how to integrate technology into the workforce. It suggests that the ability to work with technology, rather than simply using it, is a critical skill in the age of AI.

💡Digital Mindset

A digital mindset refers to an individual's willingness and ability to understand, engage with, and leverage digital technologies for innovation and problem-solving. In the video, the concept is tied to leadership and the need for executives to embrace digital transformation. It implies a proactive approach to learning about and utilizing new technologies to stay competitive.

💡Growth Mindset

A growth mindset is the belief that abilities and intelligence can be developed through dedication and hard work. The video script discusses the importance of a growth mindset in the context of lifelong learning and career development. It suggests that individuals with a growth mindset are better equipped to adapt to changes in the job market and to learn new skills required for evolving job roles.

💡Career Development

Career development involves the process by which individuals acquire new skills, gain work experience, and progress in their professional lives. The video script touches on the changing nature of careers in the face of technological advancements, emphasizing the need for individuals to seek out opportunities for growth and development. It suggests that careers are no longer linear paths but rather portfolios of diverse experiences and skills.

Highlights

The panelists discuss the rapid evolution of technology and its impact on the workforce, emphasizing the importance of adapting to changes brought by generative AI.

The debate on job displacement due to AI is juxtaposed with the need for evolving skills to keep up with the changing job landscape.

Tanya Bambina highlights her empirical work on how AI has been used for product innovation and its effect on employment, countering initial predictions of job loss.

Angela Young discusses her role in recruiting transformational technological executives and the importance of a foundational understanding of AI for all roles.

Jeff Schwartz speaks on the future of work, emphasizing the necessity for individuals to approach their careers with a growth mindset akin to training for the Olympics.

The panel agrees that 'human skills' are crucial, but there's a need for clarity on what these skills entail in the context of an AI-driven world.

The importance of fostering a movement towards learning and adaptability is underscored as a key strategy for thriving in the new age of AI.

Panelists stress the need for leaders to not only understand the technological landscape but also to be able to work alongside technology, highlighting the intersection of human and technical skills.

The concept of a 'growth mindset' is introduced as a critical skill for continuous learning and adaptation to new challenges.

The discussion points to a flatter organizational structure with less hierarchy and more emphasis on collaboration and innovation.

The panelists explore the idea that careers are no longer linear progressions but rather portfolios of diverse experiences and skills.

There's an emphasis on the individual's responsibility for their own lifelong learning and professional development in the face of rapid technological change.

AI is presented as a complementary tool to human workers, capable of taking over mundane tasks and allowing humans to focus on more complex and creative work.

The panelists suggest that the role of HR is evolving from filling static job positions to understanding and cultivating a diverse set of skills for dynamic work environments.

The conversation underscores the importance of ethical considerations and empathy in leadership when navigating the transition to AI and technology-centric workplaces.

The potential for AI to reduce the amount of work humans need to do is discussed, hinting at a future where work-life balance could be significantly improved.

The panel concludes on a positive note, expressing optimism about the exciting new ways careers are evolving and the opportunities presented by lifelong learning.

Transcripts

Welcome to this afternoon lunch panel.

Now, almost every panel, I'm on it right now.

I could basically start the same way.

So technology is going fast.

Generative AI made it even faster.

Stuff is changing.

Uh, now often the debate when it comes to workforce is also

about like our jobs going to go away.

But I think, uh, almost equally important is like, you know,

what about skills?

What is the how does the workforce actually change?

And on a, on a very personal level, you know,

what what do I need to know learn, master in this new

age of of AI.

And that's kind of the question we want to tackle this, um, uh,

over lunch here.

You know, as I have two teenagers who are thinking

about college now, it becomes very critical to think about,

you know, what, what jobs skills are going to be relevant

in 5 or 10 years.

Maybe they're going to be gone.

Uh, maybe you have to pick the right thing.

As a professor here at the business school, we have to

think about what should we teach you?

Um, what are the skills that are necessary in this new age?

There was a quote which I think is interesting, that Tom

Friedman once said, you know, it says today's worker need to

approach the workplace like somebody who's training for the

Olympics but doesn't know what discipline he is competing in

or she is competing in.

So in this panel, I want to discuss, you know, how do we

train if we don't know what discipline we're we're

competing in and what impact does technology and I have on

leaders and the workforce in general?

Now to speed the discussion up a little bit and almost a lot

of those discussion, one answer is always, well,

the human skills.

But we want to know what does that mean?

Uh, I mean, we all know that like one answer could be, well,

we need to foster the movement, but but what are

those human skills going forward?

So I have an amazing panel here today to help me kind of

answer those questions.

Let me quickly introduce all the three panelists.

Uh, Angela, unfortunately, at an emergency.

So she's on zoom.

Um, but let's start to my left here with, uh, Tanya Bambina.

She is an assistant professor here at the business school and

the finance department and does a lot of work on, you know,

innovation, entrepreneurship and

technological change in particular.

Also, what does the AI, uh, how does that affect workplaces

?

How does it affect the skills that workers need in those

workplaces?

It's empirical work that we're going to come back to.

Then there is Angela, uh, young.

She's a consultant technology in cybersecurity at Russell

Reynolds Associates, one of the leading executive

search firms.

So she specializes in recruiting transformational

technological executives for Global Fortune 500

private equity, venture capital and growth stage firms.

She's based in Miami and New York and is really a leader is

the leader in in their, uh, global cyber security team and

a member of the technology practice.

She has an MBA from Columbia Business School and 2020.

And I think the most important part of our video is that she

took strategy with me when she was a student here, which was

I'm sure it was transformational.

I'm not sure whether it was good or bad, but

hopefully left an impact.

Um, and then last but not least,

there's Jeff Schwartz.

Uh, so he's an adjunct professor here.

I'm actually teaching together with them.

Um, everything I do with Future of Work here.

He's also a vice president of insight and impact at Gloat.

This is a startup firms firm who does like

internal marketplaces, so thinks about skills

within the firm.

But prior to that, you know, he was a principal

at Deloitte, uh, for 20 years.

Most recently, he was the US leader for the Future of work

practice and the senior partner in global in the global

human capital, um, practice in Deloitte.

So so let me start with Tanya.

So you're you're empirically work looked at how skills and

also the organizational

structure changed.

So okay.

Um, changed uh when in the age of II, can you tell us a little

bit what you found?

And also how do you interpret those changes in required

skills and the org structure, uh, that you found?

Well, first of all, thank you so much for having me.

Can you hear me?

Yeah.

Not so well.

Okay, awesome.

Um, so I want to preface by just defining what I means,

and I'm going to use standard industry definition.

Uh, industry thinks about AI in terms of

three interrelated technologies.

Machine learning, natural language processing,

computer vision.

How are they different from what we had before?

I mean, in essence, it's a continuation of

business analytics trend.

But these technologies, what they do, they are able to

take a lot of data structured but most importantly

unstructured like text images and make

much better predictions.

Right.

So it's a prediction technology and where predictions are

useful in business where we have uncertainty which

is almost everywhere.

Right.

So I just want to fix definition.

What we mean with we're not talking about robots.

We're talking about prediction technologies.

Um, now, in terms of what did we expect, what do economists

say these technologies are going to do?

I know like five years ago, um, what economists

essentially they, uh, thought more about this

technology as an automation, like robotic type

of technology.

And they predicted that it's going to take kill all

our jobs.

And we're going to be all jobless and specifically

high skilled labor.

Uh, your type of jobs, right before technologies were

mostly replacing lost skill, um, routine jobs.

Think factory worker doing the same thing over and

over again.

Uh, this technology, economists predicted, is going

to take away a lot of high skilled jobs where you need to

have a decision making process, right,

where you face uncertainty, what you want to make

good decisions, facing that uncertainty.

So I just want to preface that what happens so far.

This is where my research comes in.

Um, it turns out that, uh.

Firms so far have used AI to solve all kinds

of business problems.

So these technologies can be useful to to

solve many problems.

But one common application across all forms and

technologies that we document in our work, it's actually

for product innovation.

Let me give you examples.

Self-Driving cars, recent generation.

They all have computer vision building in them, right?

It stops before you hit something if you are not paying

attention or self-driving cars down the road.

Um.

Covid 19 vaccine by Moderna was designed through the

AI factory.

You might remember when Covid started, people said it's

going to take us years to design vaccine, but these new

technologies that allow us to shorten this product

development or, uh, vaccine development,

drug development process, speed up this process.

Um, so there are many applications where AI

essentially is being built into products and

services of companies.

We also find and this is going to lead me to the answer your

question in that paper, that firms and industries that

invested more in AI over the past ten years have actually

seen growing employment.

Remember economist predicted all job skills actually find

employment is is is is increasing.

And then we dived into what kind of jobs and who is being

hired and who is being not hired.

Um, we find that most of the new jobs in this farm state

invested in AI in industries as well, tend to be

actually high skilled.

Highly educated workers that help firms in this product

development and management of their whole production, uh,

cycle of product innovation and sales and marketing.

Um, so we actually find the opposite.

What economists predicted, suggesting that this technology

is so far have been complementary to the jobs that

all you are going to have.

Now, we also found that in terms of thinking, in terms of

hierarchical structure, do we have more senior uh,

management, very senior management versus a little bit

less of an entry type jobs?

Uh, we find that it's mostly, uh, highly educated workers

that come in at a lower, uh, jobs.

How we interpret this is that when this new

technology arrives, right.

Firms do not know how to use them.

They figured out eventually.

And they need people with skills complementary

to this technology.

Right.

Um, and that's exactly what we find in the paper.

Firms start hiring a ton of recent grads from IT degrees,

mostly technical degrees, to help them kind of build out

this new capabilities in terms of developing AI internally and

then developing the whole product cycle from the

development to sales.

Interesting.

And so the organizational structure becomes flatter

or less hierarchical.

Yeah.

So it's you think, um, as it comes to

contractual structure, right.

Uh, we see that since there is new, new workers tend to be

recent grads, they mostly take lower level positions.

Right.

So the it's just become flatter.

Interesting.

Thank you.

So so let me move on to to Jeff.

Given that so, you know, you study the future of work

for decades I think and consulted the, you know,

the biggest players in every industry.

So what would you say to somebody, you know,

also knowing now how somebody who is one of the students,

what what skills are necessary to succeed in, in in this new

world?

So I love this question.

I know a few minutes ago you were talking about what advice

we would give to, uh, people finishing high school

or starting college.

Um, I'm at a slightly different point in my life.

I have a three month old granddaughter and a two

week old, a grand nephew.

My brother just had a grandson.

And it's a very interesting question,

by the way, for anybody who's at Columbia Business School,

certainly if you're a graduate and an alumnus, what is it

going to be like to actually educate and train people who

are being born now in the age of GPT?

For I'll ask Tanya to tell me what version of GPT will be

on in, uh, in 15 years, because part of what we're

talking about is, how are we hitting a moving target?

What does it mean to educate and build skills for

GPT seven, GPT eight, um, that sort of thing.

Um, but one way there's many ways to think about this

and the, the coursework that Stefan, you and I do.

One of the key things that we talk about is how do you frame

the question?

Um, uh, sometimes we talk about human skills as if they are

separate from our ability to work with technology.

So I'll just give 3 or 4 very quick examples.

This is from a World Economic Forum study, and it literally

asks the question, what's the difference between the skills

that the workforce needs in 2025 and the skills that the

workforce needed in 2015?

They actually compared, um, what was required?

No surprise.

The number one skill is problem solving and analytical

thinking and innovation.

I think that builds, Tanya on what you were saying.

Um, number three is creativity,

originality and initiative.

Again, not a surprise, but here are and again shortly after

that is working with people, leadership and

social influence.

But there were two categories of skills that to me

were particularly interesting.

Um, there were two sets of skills that related to a

category that they call self-management.

There's a category around active learning

and learning strategies.

Think about this in terms of how do we make the meta skill

of learning a new skill, right.

Learning itself, becoming a skill.

And then they have another self-management skill,

which they call self-management around resilience,

stress tolerance and flexibility.

I think we can all relate to this idea that we are living in

a time where it is very stressful and we're going

through constant change and we'll we'll come back to this.

So we have we have two skills in 2025 that we weren't even

thinking about in 2015 self-management,

learning as a meta skill and dealing with uncertainty and

stress also as a skill.

And then there were two other skills.

And the reason I find this particularly interesting is.

We tend to talk about human skills, or soft skills or

power skills on one side and technical skills on the other.

And we're getting to a point where the intersection of human

and technical skills are themselves critical skills

for the future.

And again and again, the way the World Economic

Forum lists this.

And again, the first one they list on this list of ten

is technology use.

But how do we use technology?

How do we monitor technology and how do we control technology

?

Right?

How do we work with technology.

And we'll come back to this.

How do we put technology on the team?

It's not about putting humans in the loop.

As Tom Ballard at MIT says, it's about putting computers

in the group.

Or really, it's how do we put technology and people on

the same team.

And then after we have this sort of technology use in terms

of monitoring and control, then they list technology use

in terms of design and programming, right?

And so again, to me, I just want to highlight the

difference self-management, learning as a skill,

resilience as a skill.

And if you looked at the 2024 LinkedIn skills that they just

published in February, the the top skill that they listed

was adaptability, which I think relates to this as well.

Cool.

Thank you Jeff.

So let me let me go to Angela.

Now, you know, you observe on the frontline what skills are

important for executives right now.

Now, Angela, you worked ten years in in executive search.

So what what changed in this decade and and what does it

need today to be a successful leader?

Yeah.

So, um, in the executive search world, particularly my

firm at Russell Reynolds Associates,

we specialize at the sea level recruiting base.

So, um, any CEO, chief, um, you know, fill in the blank

officer all the way up to the board of directors.

And what we've been finding is that, uh, change management

is really front and center as far as the critical and

mandatory leadership skills.

So, um, Jeff, you touched on a lot of these points.

Um, but one of the biggest things is definitely that

growth mindset and that digital mindset that what that means is

the willingness and the attitude and the right

behaviors towards innovating, taking more calculated risks,

learning about next gen capabilities.

Um, and then next there's the need to be decisive and the

need to commit and be a fast mover.

Otherwise you're just going to be obsolete.

Everyone is asking the question around generative AI

and its capabilities.

So if if you're still reluctant, uh, you're,

you're going to become obsolete and fall behind the times.

Um, there's also a saying or a phrase called the 30% rule.

So, uh, even if you're not a chief information officer or

chief technology officer, chief AI officer, um, the 30%

rule kind of says that every employee, especially at

the leadership level, you're they require a

foundational level of understanding around, um,

AI and digital and next gen technology.

Um, so you don't need to be a master and hands on

keyboard technologists, but you do have to be a bit more

digitally aware and savvy.

Um, again, Jeff touched on this a bunch, but that change agency

and the ability to influence create that culture of

innovation and collaboration too, because what

we've been finding is it's not just solely left up to the

chief technology officer to drive the digital

adoption around AI.

Um, but it has to be a collective effort and a system

wide effort to internally and agile across the

leadership teams, down to the employees and also externally

to as far as um industry advisors,

co innovators, co collaborators.

Um, so the change agency and the leadership and influencing

ability is key.

Um, other big important point that we've been finding is

around you had a healthy dose of skepticism and the ability

to ask the right smart questions, okay, to not

know the ones and zeros of AI and technology, but, um,

being smart around, well, how does this apply to

our business, to our customers?

Um, and also, are we asking the right questions?

Are we maybe, uh, leaning on a biased set of data?

So it's actually a bit biased and discriminatory in terms

of the, the suggestions and the recommendation that, um,

generative AI is proposing.

Um, the other thing, too, is threats, competitors,

adversaries, they're also getting smarter as well.

So, um, from a competitor differentiation standpoint, um,

you also have to ask what what is the competitor or what is

the competitive landscape looking at.

Um, and also what are the bad actors and the adversary is

doing to, um, expose our vulnerability?

Um, so the risk awareness has to be really key here.

Um, secondly I for talent.

So again, do we have the right technical skill sets at all

levels of the organization?

If it doesn't make sense to hire internally, then where

can we, uh, foster more partnerships and industry

collaboration?

Um, and then finally, integrity is a huge one because

in this nascent space where people are still figuring

things out, we have to ask more questions around, are we

leading with empathy?

The whether it's low scale or high school employees that are

concerned and afraid about losing their job?

And, um, uh, we have to instill trust that there's opportunity

still ahead, even though the organization and the

industry is changing.

Um, not all jobs are going to be replaced by automation.

So you have to instill trust in the workforce to maintain

that healthy workforce.

Um, and we have to put the right guardrails around the

ethical use of, um, of these technologies and AI.

So those are the biggest things that we're seeing in

the executive level.

Thank.

Thank you Angela.

Now, let let me be a little provocative here.

So first of all, you're saying we need to know.

They need to know more technical skills, social skills

and all of it.

More of it.

So they just need to know more.

Um, and the second is, if you would have if I would have had

a panel like that 20 years ago, I would have had

what do good leaders need to know?

They would say, well, I need some technical, you know,

like some technical skills, some social skills.

So what is really different today and how is that shift?

You know, where how do students like today figure out how much

do I need to know whatever Python or like now

AI or whatever.

How much do I need to learn how to lead, uh, or how to work in

teams?

So maybe a question to all three of you, and maybe whoever

wants to go first, think about how to do.

They just need to know more.

We just need to know more.

Um, and what is different today than like 20, 30 years ago

?

Well, good leaders always had had some content knowledge and

some interpersonal

leadership skills.

I'm happy to go first and then, um, Tanya and Angela

can add to it or correct me on on a perspective.

Um, I think there are a few things that are different.

Um, there is more that we need to know today than we

ever did before.

Part of this is because there's a concept that we often

talk about, which is the half life of a skill.

How long is the skill useful when you learn the particular a

particular knowledge around it.

And, and many people have looked at this JSP John Seely

Brown has looked at it and we know, or at least I would

say we've observed, that the half life of technical skills,

specific skills are getting shorter.

It may have been ten years, five years.

I was on a panel with Joe Fuller from, uh, from Harvard a

couple of weeks ago who said, we may be getting we may be

getting to the point where the half life of a technical skill

is roughly equal to how long it takes an individual and a team

and a company to acquire and be proficient of that skill.

So it raises questions about what is mastery and how long we

can be the master of a subject.

Um, so some people hear that and say, so, okay, Jeff,

we're supposed to become generalist and jack

of all trades.

I actually don't think that that's the direction.

And and Linda Gratton at London Business School said about ten

years ago that one way to think about this is that we need to

be serial masters, right?

We need to be masters of many skills and many technical

domains during our lives.

And that's a different way of looking at it.

But but there are, there are there are two other things that

I think to, to think about.

One is that work is increasingly work looks

increasingly less like an assembly line and more like a

series of projects and problems that we're solving.

Right.

And if something looks like an assembly line, but it could be

a physical assembly line, it could be the assembly line

of processing mortgages, which also looks like an

assembly line, anything that looks like an assembly line,

big parts of that work are going to be in some way

automated when work is project sized.

There's a different dynamic to what we're trying to do.

How do we create?

And so the shift is at work is project sized, work is becoming

more team based.

Teams are becoming the focus.

So we're looking at the skills and the capabilities of

the team, how we work on teams become important.

And another thing that's different is that increasingly

companies and organizations are managing workforces that are

much broader than the people and employees that work for

them as well.

We call this workforce ecosystems.

I wrote a book on this with some colleagues from MIT

and Deloitte, and then we're moving from a sort of control

and supervisory skill base, if you will, for leaders to

much more of an influence and a team orchestration role.

So I think there are some some major shifts going on.

And the last comment I'll make and Angela mentioned

the growth mindset.

There was a book written 26 years ago called The

War for talent.

Um, great book written by great colleagues at McKinsey.

But the war for talent from one perspective is a fixed mindset

view of talent.

That is a fixed amount of talent out there and we need to

compete for it.

Today, leaders and managers are in a world where we're not

competing for a fixed amount of talent, because much of the

talent we need doesn't exist yet.

The war is to grow talent, right?

So we are literally moving to a growth mindset for

everything we do.

It's not an allocation problem,

it's a growth problem.

And I think that's a different perspective for

leaders and managers.

Yeah, I can go for a second.

Um.

You know, I study innovation more generally, and I'm a

student of history, and I feel like history teaches us a lot.

You know, people say history doesn't repeat, but it rhymes,

right?

If you look back over the past 100 years, as I did thinking

about technology, what are the new technologies that emerged

and how they changed the work environment?

Um, you know, one of the greatest.

Uh, 100 years ago, there were three,

right?

Electricity, automotive.

Um, and I'm forgetting the third one.

But there was a big change.

You see it in innovation, 1920s being exponential.

I think now, 100 years later, we are in a similar position

where we have many different types of technologies

starting to emerge.

AI is just one of them.

Um, but quantum computing, the use cases, which is going

to revolutionize, uh, how we compute things, uh,

many other things.

Storage.

Right.

Batteries.

What Tesla managed to do, it's just amazing over the

past 15 years.

So all of these technologies, um, uh, that are all emerging

at the same time.

So I think that's what a little bit different from maybe past

20 years, uh, where we on, uh, verge of several technologies

emerging and complementing each other.

Right.

Because AI is not useful without compute, it's not

useful without storage.

Um, and it's not useful without people who implement it.

That's why then the technical understanding or how what does

this technology help us to do?

And I think this is where the business, uh, argument.

The ability to jump in and out, the ability to

understand what problems you are solving and which tools are

helpful for solving.

These problems are always going to be helpful and hopefully in

business school you will continue gaining

these these skills.

But I do think it's quite important to understand which

technologies which help, uh, solve different skills.

Right?

If I when I talk to computer scientists, uh,

who actually work for for companies, they say we are

useless without domain area expertise.

People who actually understand the industry.

Um, and what are the biggest problems and what are the tools

being used?

So I'm much more optimistic about business

school education.

Um, problem solving is where the, you know,

the growth opportunities are.

What are the biggest problems?

What are the appropriate tools to, um, to, to use?

Um, but for that, I agree, you don't need to be,

you know, doing PhD in, in machine learning to be able

to implement these algorithms.

As a manager, you just need to understand, um,

where they're useful and where they're not useful.

Thank you.

Angela.

Yeah, I would agree with, um, everything that Tanya and

Jeff has shared.

So the other thing too, is it depends on what level, uh,

of the organization you're looking at.

The more junior levels are within, the technology and

development organizations probably need to be a little

bit more technical than the rest of

your enterprise colleagues.

But, um, holistically, especially at the

leadership levels, as an executive, you have to

look at the whole fabric of where the skills, where do we

where are we trying to go?

What skills are we missing?

Can we train from within through certifications?

Or, um, do we need to bring in the right external talent?

Do we need to bring a chief data and AI officer?

Um, so you kind of have to look at the organization as a whole

and take an inventory of what exists internally and what

needs to be brought in from the outside.

Um, and the, the whole war for talent.

Um, it is a dynamic and evolving space, especially with

this new digital age.

So, um, so with the skill sets that are in high demand,

yet you're always going to need a specific technology, uh,

expert, whether it's, um, you know, developing or

modernizing the infrastructure that supports the systems

across the business, whether it's, um, the person

that's responsible for the data, um, storage,

hygiene and then converting that to actionable intelligence

and analytics, um, or whether it is the more business savvy,

um, the technologist or digital leader, right.

That can kind of tie it all together, but it has to be

done in unison.

It can't be looked at in silos or really specified to what one

specific skill or technical learning that you

should apply.

The answer is kind of depends, which I know is a

consultant answer, but it really does depend where you're

looking in the organization and how that applies

to your business.

Cool.

Thank you.

So I want to afterwards quickly talk about leadership.

But before I want to ask you a question about career.

So they're all embarking on a on a career now.

Now if you pick a job, you know, if you picked a

job 30, 40 years ago, you went like, this is

a great company.

This is a great industry.

I'm making a career there.

Now, if those skills are changing, you know,

the careers, the first job, the second job, the third job,

the fourth is going to be different.

They have options.

How would you advise to choose between those different options

that are different than they were like 40, 30, maybe,

maybe 15 years ago?

Do you want to start?

You want me to start?

Go ahead.

Okay, so I actually asked this question to our class at

Columbia last night, and the question I asked was, when you

were thinking about your job or your role or your next

adventure when you leave CBS.

Um, we had sort of 5 or 6 items on the list.

And how would you rank them?

And one of them was the company you work for.

One of them was the compensation you receive.

One of them was corporate values.

The the number one item that the class listed when they rank

them was a company that provides a position that

provides growth and development opportunity.

Right.

Which makes of course sense in the context of what we're

talking about today.

Um, and then what we talked about is, how do you know that

the company of the organization that you're going to is a good

place to grow and develop opportunities?

So there are indices.

There's the opportunity index that was developed that looks

at this, but it raises some very interesting questions,

because the way that I think you get that data is you can go

to places like Glassdoor and others.

But what people are really looking for is, is this an

organization where I can actually grow and not only go

vertically growth, but explore things and have different

options?

So I think that's a sort of top of the list.

The other is I'm just reflecting on some of the

language that we're using.

Um, we know that the world is not about silos.

We know that the world is.

It's not mechanistic anymore.

For many, many decades, we talked about companies and

organizations as if a mechanistic model

applied to them.

Right.

They are much more organic.

Right.

And the whole notion of growth.

And I'll sort of end with this observation.

Stefan.

Um, from age zero to age 20.

Right.

We are growth being things right.

Every year we are almost a different person, right?

When you look at it at an infant and a toddler and

a young child.

Um, you know, we are sort of we are built for growth.

And then at a certain point, we ask the question to this 20

year old, what do you want to do?

What's the linear path that you want to get on?

Right.

Maybe we're not even structuring the

whole question correctly.

Right?

Right.

And so is it about change.

And I'll sort of end with this observation.

When we talk about the future and all the things that

are happening, we sort of sort of recoil when we think about

the amount of change that's going on.

Right.

One way to ask the question is, is this about

change or is this about growth?

Right.

And if you are thinking about your life in the next 30 or

40 years, how can you sequence the work that you do,

the volunteering that you do, your personal life so that it's

organized around a growth trajectory and a plan that

you're thinking about?

It's not about a ladder.

It's not about a linear plan.

This is a big shift that we are in the middle of right now.

Thank you.

Want to go next door?

Should I, Angela, maybe I can ask you.

So what do you observe kind of how careers of those topics

that could change, that could inform like somebody who just

starts the career and say like, that's probably a

very successful path forward in this, in this new, in this

quote unquote new environment.

Mhm.

So, um, in an old mentor of mine, when I first started

out in the search business, um, uh, shared a framework called

the Five P's and touches a lot on what Jeff has shared around

what motivates an individual to pursue

different opportunities.

Uh, so the five P's are one pay.

That's that's an obvious one.

Um, the position itself, the people and the culture,

the platform.

So the company and the organization you're moving into

and then, uh, play physical geography generally

throughout someone's, um, different phases

of their career.

Maybe 2 or 3 will spike a little bit higher in weighting

compared to the others, and it'll shift and it'll be

dynamic over time based on, um, you know, different changes in

your life, family obligations or personal ambitions.

So it's very dynamic and that will evolve over time.

Um, but as individuals are considering, um, what is

the right opportunity ahead of me at this point in time of my

career?

And how does it catapult me into that next phase of

continued success and growth and development as I continue

on as an executive leader?

Um, those are those five keys are probably a good start

to start evaluating.

Okay.

What are the most important things for me at this given time

?

And does the opportunity in front of me, or maybe 2 or 3

opportunities ahead of me, which ones align best with

where I'm prioritizing around my needs?

Um, at that given time.

And then just in general, especially at the

executive level, again, everyone's talking about AI,

everyone's talking about the the next disruptive technical

expert or, you know, adding more diverse leadership

to the team.

The the biggest thing around the organization,

particularly the culture, um, that from the

candidate's perspective, they're asking us as

recruiters or, um, asking the companies that are doing the

hiring are, well, how is the organization set up and is it

set up in the way, in the right way, where I'm set up for

success in my role because the organization, the company

just may not be ready structurally,

culturally to be ready for that disruption or change.

There has to be a little bit of a crawl, walk, run evolution.

Um, because what what we focus on is trying to mitigate the

amount of risk of an organ rejection.

Right?

So, um, different maturity levels of an organization and

the level of disruption that an executive brings, there has to

be a little bit of a coordinated dance there.

Um, but I hope that was helpful.

Yeah.

Thank you.

So, Tanya, and then we're going to go to Q&A.

But like.

Yeah, one thing I just want to abstract.

A little bit from all the AI hype, right?

When we start, when we start this research into

southern 19, people would look at us as if we're like crazy or

stupid to like, do to look into AI.

I mean, we were convinced that was very useful technology

that's been used by firms.

Um, so I just want to abstract a little bit from the current

hype about it.

It's going to be useful, but it's not going to be a

panacea for everything.

And I want to revert to the first principles, which is how

who is going to be always useful and rewarded, um,

in their career.

So somebody who can solve big problems, right.

Uh, whether you are doing this for big organization or you are

starting your own companies.

Um, as I know some of you will, I have my

students here, some of them who go on and

start amazing companies.

So trying to find the biggest problems for society.

More generally, for companies you work with, um, or maybe for

your own is where the opportunities will always be.

And for that I think what's really important.

This goes back to what Jeff said at the very beginning.

Self-learning and ability to learn, uh, more and more

about what's happened.

Terms of technologies.

And Angela brought it as well, which is understanding

different tools that can be used to solve big problems is

always going to be valuable no matter what you do.

And I'd like to add two just quick ideas to this,

because when we the whole question of what does a 21st

century career look like is a really interesting question.

So one piece of data and one observation.

Linda Gratton and Andrew Scott wrote a book about 7 or 8

years ago, um, titled the 100 Year Life.

This is about demography.

We know that lives in the 21st century are roughly twice as

long as they were at the beginning of the 20th century.

It's 2024.

If you're 24 years old now and you live to be 100,

you're going to be alive in the year 2100, right?

And so part of what we're talking about is what does it

mean to plan for careers, either as a business leader or

a public sector leader, or as an individual, where if you

live to be 100, God willing, you may have a career where

you're working for 50 or 60 years.

And I'm going to add a P to Angela's list.

And maybe this was on the list.

Um, our careers or portfolios, our careers or portfolios,

they are not ladders.

They are not linear progressions.

Right.

And they are portfolios of ongoing reinvention.

Right.

And part of the opportunity, not the risk, not the challenge

is what does it mean to have a career that is a portfolio

where we all should expect to do many different things during

our lives, and that is simply a shift from the way that we

almost always talk about careers.

Again, I'll end with this question.

We ask people 14, 15 years old, 12 years old,

18 years old, what do you want to do in your life?

As if there were one thing that you were going to do?

And maybe the question is, what 3 or 4 dozen things would

you like to do in your life?

And then how do you develop the skills and the capabilities and

the mindsets to do that?

Great.

Thank you.

So so let's open it up.

So there are mics on both sides.

So maybe there.

Julie.

Hi there.

Uh, thank you all for your time.

Uh, I had a question that centers around creative

destruction and how you guys, you guys are talking a

lot about, uh, the youth and people of our age that are

going into the workforce.

But I'm really interested.

Every time technology comes into society, it usually ends

up helping society as a whole.

But there's that lag period where there's maybe a ten,

15 year generation of people who need to acquire skills.

And if you look at 19th century Europe,

you have the Luddites.

So how do you acclimate the the new generation or the 30 plus

year olds in the industry that are starting to automate?

And so my question is, do companies need to start

taking a more nurturing point of view, for example,

Amazon teaching their employees how to code or creating

programs for that, or boot camps that allow for that

malleability in skill set instead of asking the employees

only to develop those skills.

Yeah, I'm happy to start.

I'm interested because you mentioned earlier that you

looked at this over 100 year historical period.

So I'm hoping to hear a little bit about what we've learned

about this in this the last century.

I completely agree that, you know, um, I feel like

sometimes economists, um, focus on the negative aspects

of technological change.

But like you said, technology made us our lives

so much better.

Think how people worked 100 years ago.

They worked for ten hours in, you know, awful conditions.

They didn't have.

Much, um, luxuries that we have today that makes

our lives better.

So I completely agree with you that on.

Net technologies make our and society better.

Now going back to your question,

should who okay, the speed of innovation is increasing.

We need to, uh, adapt to that and understand

what's happening.

Who should pay for that?

Typically, who are the usual suspects?

The employers, the government or you?

And I would argue that you going back to self-learning

aspect that you have brought up is in the is, is who end up,

uh, investing in yourself and ability to learn how to

use this technology.

Why is that?

Well, a classic economic issue with companies training

their employees, uh, is that they cannot necessarily get

rewarded from training you because you can get trained and

another company is going to poach you and pay your higher

salary to for your new acquired skill.

So when I talk to economists who actually do cutting edge

research and try to understand what the companies in the US do

a lot of retraining, the answer is disappointingly,

depressingly, no.

Should it be the government who invests in in training programs

?

Well, in theory, that sounds great, right?

Because governments are there to internalize externalities.

But the issue is most governments are not that

great at this.

So that leaves you.

Um, in terms of self-learning, understand how to use

these technologies, and I have plenty amazing examples.

Um, you know, I studied AI and some of my students, um, now ML

engineers and I talked to them.

I was like, how did you become an engineer while they were

just doing some other engineering?

And then they saw an opportunity.

And they are smart people like, you know,

all of you, and they self learned how to use these

technologies and where the useful way or not.

So I think at the end of the day, um.

It's it's it's about, uh, self-learning.

Going back to Jeff's point, I think it's practically.

It's the most important part.

I know Angela may have a comment what I'll add to it.

I mean, you asked like three questions in one, by the way,

so we could talk about creative destruction,

the rate of technology.

But I'll pick one thread of the question, um, which has to

do for me thinking about what does it mean to have a career

and live a long life?

What does it mean to for an individual or for an

organization to manage an employee in their 20s, 30s and

40s and 50s, 60s and 70s.

Right.

And I think I totally agree.

I think the individual is going to bear the most responsibility

for this, because government simply is going to lag on it.

There are governments that are making progress on it.

There are some models in Scandinavia and Germany where I

think there's some better, uh, approaches to this.

I think companies are beginning to recognize that making a

broad set of learning and skill development

programs available, often where the employee has to take her

time or his time or their time to do it, is important.

But I think the other thing that we're seeing is I would

not count out the workforce that you have that are in

their 30s, 40s, 5060s and 70s.

But I don't think the future of work and the workforce is about

recruiting and skilling people only in their 20s and

their early 30s.

And I think we're just beginning to think about what

does it mean to really help people reskill and upskill

throughout their lives.

Yeah, I would agree with both Tanya and Jeff.

Um, with regards to reskilling, especially the

further up in the organization you go.

Um, I mean, probably doesn't make sense for the organization

to expect the, you know, chief executive officer to take

a Python class, right, or coding class, but at the

same time that that individual appetite and learning ability

and the growth mindset that is going to be key to be a

successful digital leader when you're, um, expected to

lead a more increasingly diverse and

dynamic digital workforce.

Right.

Um, so there has to be an internal motivating driver for

any executive to, to better understand the digital world

that we live in and the different technology

skill sets, um, that would exist within your domain and

your remit at the same time.

Um, the senior up, you go in the organization, the less

technically deep you need to be, but you need to be broad

enough and well-versed enough in terms of, uh, within your

sphere of influence.

What are those disruptive capabilities or emerging talent

skill that you need to bring into the organization?

And, um, what I brought up earlier around.

Yeah, collaborating externally and and building an ecosystem

of the right partners around you.

I mean, for several clients, um, rather than a traditional

board of directors, uh, with fiscal responsibility and

risk oversight, we're also seeing more increased demand

for a digital board of advisors, so more geared

around technical experts that can guide, um, the strategic

pivot of an organization from a legacy established enterprise

into one that's more prepared, um,

to embrace digital technologies.

So.

Thank you.

Question.

Other question.

They're working out okay.

Perfect.

Hi, there.

Thank you so much for coming.

And I think my question relates to one of your

comments around, like how our average lifespan is increasing

and we're likely to live up to or even more than 100 years.

That implies, uh, actually having

longer careers.

That is not necessarily a prospect that makes

me super happy.

And especially, um, in thinking of AI as having this power of

automation and being complimentary.

So my question for you is, do you see this complimentary

aspect of AI as being something that could potentially be

deployed to reduce the amount of work that humans need to do

and the current, uh, length of the week work journey.

Uh, and how would be the potential implications

of that, like, um, the long term?

Yeah.

You want to start, you want to start.

So, so far, um, AI tools have been complimentary to workers.

You know, some firms tried to replace, uh,

workers with AI, and they cannot.

Why?

Because a job was typically a bundle of different

things you do.

Right.

And most of the things you do are not necessarily cannot be

resolved by AI, right?

Writing, you know, ChatGPT or whatever that's useful to,

to help with those skills.

But a lot of other things you do meetings, strategizing,

all kinds of things are not necessarily even

replaceable by AI.

Right?

So I just want to start with that.

So so far what we've seen, uh, in my own work,

AI has been complementary.

And let me give you one of the examples that hopefully is

going to be easy to, uh, to, to, to relate to.

Um.

About five years ago when like the whole economists,

you know, uh, uh, society started to

think about economics.

So I.

Economists never agree on anything, okay?

Never.

But they agreed on one thing at that time.

That is going to be H.R.

That is going to be decimated by AI tools.

Okay.

Five years later, what do we see?

No, it was not decimated.

And I talked to each other professionals.

And I try to understand VCs who invest in HR, uh, you know,

powering tools.

What has been happening?

Well, what has been happening is a lot of these ML tools, uh,

replaced very tedious, monotonous type of works,

looking into resumes, you know, all types of

things like this.

And instead it freed up time to for much higher order tasks,

like thinking about how can I make you happy so you I retain

your you and benefit from your talent.

How can we build teams together so people work well

together and, you know, feel good about being part of

the organization?

Um, so.

Another.

You can say you can.

You can see I'm more of an optimist.

Right on, on.

I, um, and the final thing I want to say is that I is going

to do what we allow it to do.

We have agency.

And for issues where there are externalities

that are governments.

To solve those issues, we can go into the weeds of should we

regulate I should we not?

But I just want to say at a very high level that we control

what's going to happen with AI impact on society more

generally?

No, I think that's very powerful.

And I think it's it's a question I like the way

you put it.

One sometimes we ask the question, what are the

trends we're seeing with the impact that I will have on work

?

And I think, Tanya, what you're highlighting is, yes,

it's interesting to know what the trends are.

It's actually maybe more interesting to think about what

we want to do with AI and how we want to use it in our lives

and in our work, and that that sort of I'll come back to

a question, that stuff when you asked a few minutes ago that

comes back to this leadership and management question,

because one of the and we haven't mentioned it just to be

explicit about it, one of the really interesting domains of

leadership and management today, in the next

few years, more than ever, it's we're in a design phase

of the future.

We are designing and redesigning work.

And the way that it's done, when we say that work is

project ized and not only process, it leads us to

think about what does it mean to be a designer?

What does it mean to have teams that are redesigning and

designing the work that we're doing, where people in

technology are working together?

It's less about supervision.

It's less about control, it's less about monitoring.

Of course, we're going to do all those things, but how do we

get into a design mindset when we're thinking about how people

in AI work together?

Thank you.

Angela.

If it's.

Okay, let's move.

To the last question.

Um, and so yeah, go ahead.

All right.

Yeah, I actually have to jump in two minutes, but, uh,

okay.

Yeah.

Please go ahead.

Yeah.

All right.

So I read a job description today that required ten years

of experience in large language models.

Of course.

Not possible.

And it's a symptom that companies want to catch up with

all of this hype of AI and they basically don't know

what they want.

And what we discuss today, that this half life of

technical skills is only going to get worse.

How can a HR departments catch up on this new trend, or how

can they adapt to this new way of hiring that maybe people

need to be malleable and they don't.

They basically don't have these technical skills, but they can

adapt to it.

You want to let Angela start on this before she can?

Yeah, Angela.

Maybe you can.

Absolutely.

Yeah.

We, uh, we grapple with this all the time.

So even, uh, when I started at the firm, um, nine years ago,

I remember seeing something similar around.

We want 20 years of, um, cloud architecture experience.

And I was like, okay, I don't think that exists, but, um,

uh, especially with technical, um, experiences or technical

depth and skill sets, um, especially in, in a time

where again, Jeff said it's it's in the design phase.

We're still in the very early stages of this, actually taking

full swing where there's a track record and, um, there is

substantial operational

implementation expertise.

So to work with your HR partners,

your hiring managers, I mean that that's what we deal with

all the time when we try to educate and and just

demonstrate this is the landscape.

This is the stage of maturity that we're at right now

in the industry.

And by the way, this is the available talent that exists at

this point in time.

Um, these are probably the learnable skills.

These are the the skills that just don't exist yet.

And these are the trade offs.

So what what what trade offs are you willing to make.

And how do we prioritize the right skill sets at this

moment in time.

That can set you right for the next stage of

your organization's journey.

So it has to be an iterative process.

But I think we as organizations have to be a lot more

comfortable in, again, being open minded, um, and and

being willing to listen and learn about the market dynamics

and the talent landscape and what's available and

what's not, and being willing to make those trade offs.

So.

Yeah, it's a great question.

It's a great question.

Are you gonna.

You're gonna run, Angela?

Is that.

Unfortunately, I have to.

Yes, but this was such an honor, and, uh,

it really looked.

Look forward to hearing all the lessons learned that come, um,

following this.

But it was a pleasure.

Thank you so much again.

So the question about the I'm going to summarize it

this way.

What's the future of H.R.

And Tanya, you spoke about this a second ago.

Um, you know, I'll I'll be a little tongue in cheek.

HDR is dead, but air is being totally reinvented.

We spent about 100, 150 years organizing human resources

around the idea of standard jobs effectively on, um,

in factories or on some sort of linear process lines.

Right.

And the notion of a job, a static job, a standard job

that you can do and grow in a linear way, I think is actually

an outmoded concept.

Right.

So the opportunity now for HR, but it's not just HR, it's for

everybody who's leading a business unit is to say if it's

not the job anymore, what is it?

Right.

And it's a collection of skills.

It's a collection of aspirations.

It's how teams work and it's how we actually get work done.

So we're shifting the unit of analysis, if I can put

it that way.

And much of what HR has done, by the way, this is true in

almost every functional division.

The standard transaction compliance reporting processes

that we do in every business function are will be

significantly automated, right?

And significantly enhanced by by AI to make predictions and

gen AI to actually write reports.

So we're seeing the shift in HR from finding people for static

jobs and building long pipelines to actually

understanding the skills that we need in the future based on

the work we're trying to do.

How do we find people and not just recruit them, but access

them in different ways that maybe as an employee, maybe as

a freelancer?

And how do we orchestrate them in different ways?

So my hope is over the next 5 or 7 years, we're going to see

an outdated word, a renaissance in what we're doing

in business, because we're going to be reinventing it

around new problems with these new tools.

I don't have anything, anything insightful to add.

I'm just going to say that.

It's very costly to require.

Very rare skills.

Uh, for an HR department.

So they're going to learn.

They're going to learn their lesson.

And those who will not learn.

Will be in creative destruction.

They'll be creatively destroyed.

Exactly.

So.

Okay, so thank you so much.

I mean, what, uh, this was interesting to see how the

environment kind of changes to workplace.

I took away a positive note.

I mean, it's exciting new ways that careers are happening.

And because there is lifelong learning,

those students are going to come back to Columbia to learn

when they have to reskill again in a couple of years.

So we see you back here in a couple of years.

We see you back here in a couple of years.

So thank you so much, Tanya and Jeff, for um,

for this conversation.

And thanks so much for, for spending the lunch time

with us and have a good afternoon.

Thank.