The AI rollout is here - and it's messy | FT Working It

The last big tech bubble burst at the

start of this century and we may be

heading that way again.

>> The kind of investment wave in AI we've

seen is like probably nothing ever

before in history.

>> Hundreds of billions of dollars are

being spent on automating workplaces.

>> We have this amazing technology.

However, we're not seeing adoption fully

yet in every pocket of the the economy.

Only 1% of CEOs have a fully formed AI

strategy. With such high stakes, will

businesses see a return on investment?

I'm Isabelle Barrett. I lead the FTS

working at Grand speaking, presenting,

and writing about management,

leadership, and workplaces. In this

series, I'll explore some of the most

pressing issues around the future of

work and talk to senior leaders about

how they are making work better.

>> 3 5 years from now, I think things will

look quite different

>> for everyone.

I'm here at the Charter Workplace Summit

in New York in rooms filled with senior

leaders from some of America's biggest

companies. These are the people tasked

with AI roll out and preparing the

workforce for the skills needed for the

future.

>> Last is David.

>> Every 6 months a new model is dropping.

Every 6 months something shifts within

the marketplace where you have to stay

up to date. With AI, we're still in like

the very very very early days of

everything happening. We have this

amazing technology with the promise of

productivity enhancing gains. Roughly

10% of companies are fully starting to

integrate AI into their processes. But

there's going to be years of this

happening. We have to figure out exactly

how we can use it and where it makes

sense to use it.

A staggering amount of investment has

been made in AI over the last few years,

and it now accounts for a 40% share of

US GDP growth this year. Over 75% of

businesses worldwide are using

generative AI in at least one function.

But despite this, a study by MIT Media

Lab found that 95% of Gen AI pilots in

the workplace failed. I spoke with

editor-inchief of charter Kevin Delaney

about the state of AI rollouts in

industry.

>> Think about how AI is different from

humans.

>> Companies are adopting AI at two

separate speeds. You have the tech

companies who are actually quite far

along to the point where they think of

AI agents as co-workers. On the other

hand, you have companies that are still

getting their heads around what AI

adoption means. And these are the

companies that are still trying to get

their employees to use chat GPT or

claude. A lot of them are not seeing

gains in productivity at this point. So

you have these two extremes.

>> So we hear a lot about um the need to

upskill the workforce for AI. What does

that actually mean? Are people actually

doing it or are they just letting people

get on with it?

>> People are trying to figure out what

exactly that means. And I think part of

the challenge is that we don't actually

know what the ideal worker skills will

be in 3 years or 5 years as AI is rolled

out more pervasively. There's a lot of

discussion about is the ideal worker in

a more AI deployed environment someone

who is a real specialist in a field or

is it someone who is a generalist who

kind of knows a little bit about the

business and how business operates and

who can communicate clearly and knows

enough to be able to check what the AI

is bringing back.

>> So we need a lot more experimentation

and possibly failure.

>> Yeah. And so that's uncomfortable for

leaders too. To be comfortable with

failure is something that you are not

generally taught in business school.

Failure generally is something that

executives are allergic to encouraging

in their workers.

>> After a day of off thereord discussions,

panels, and big picture sessions, what's

emerged is that there's no clear path

forward for Genai at work. It's still

all to be decided. the reimagination of

work.

>> Leaders have spent billions on preparing

for an augmented future, but for what

gain?

So, at the FT, we wanted to look at how

is this roll out actually going and what

are companies saying about how they're

using AI. And so, we did this massive

analysis looking at um SP500 companies

in the US. Um we went through thousands

of earnings reports and um regulatory

filings and the s- the results were

quite surprising. Um in earnings reports

CEOs would often say you know AI is

amazing. It would bring incredible

productivity gains a Cambrian explosion

of innovation things like that. Um but

then in the filings which to be fair

tend to be more measured and um risk

averse no one really had anything

concrete to say of how they're actually

using it. And uh in those filings, the

risks outweighed the benefits very very

clearly. If you look at the SP500 index,

it's obviously going up, but a lot of

that growth is driven by seven big tech

companies. And the other companies on

the SP500 haven't necessarily grown that

much when they've said they use AI. AI

use is often phrased in their filings as

being something quite abstract. Um they

talk about productivity but don't really

offer any concrete examples of how

they're using it. Coca-Cola is one

example where in their earnings reports

they raved about how they're using

generative AI to transform their

business. Um, but in their filings, the

only example they could give was using

generative AI to create a Christmas ad.

It's definitely a mixed bag. The growth

of AI has led to a boom for

consultancies and learning platforms who

are keen to show business how to harness

the powers of AI at work. I visited the

HQ of AI upskilling platform Multiverse

and met with their CEO and founder Euan

Blair. So what are the ways in which

companies I guess your clients are

engaging with AI skills? Are they

hesitant? Are they all in? How is it

what does it look like?

>> So I I I think it's it's almost the kind

of polar opposite of hesitant. The kind

of investment wave in AI we've seen is

like probably nothing ever before in

history. So the big challenge a lot of

organizations are facing is how to turn

kind of potential AI gains into actual

realized AI gains. And that's where the

kind of training gap comes in because

what a lot of people are doing with AI

at the moment is the equivalent of

having an iPhone and just using it to

send text messages and make calls,

right? They're missing out on loads of

the capabilities that these tools

actually have. So we've seen a lot of

companies spend a lot of money on AI and

>> really a lot of money

>> and there haven't been right

>> particular productivity gains that I'm

aware of.

>> What's what's the where's this gap?

What's the gap?

>> We've seen accounts teams for example um

process invoices 50% more quickly and

with half the number of errors because

of introducing AI. We've seen um

software engineering teams increase

their speed of shipping code uh by 75%

in some cases. Those are big tangible

things that do actually have an impact.

One of the reasons we're not seeing

gains at the kind of big macro level yet

in terms of economic growth is this sort

of training and capability gap. Because

with previous versions of software, it

was often deemed enough to go and invest

in the technology and then over a period

of several years, people would figure

out how to use it and where to use it

and everything would be okay. The

difference this time is the inherent

capability of the systems is so much

greater. You need a lot of training to

be able to kind of fundamentally change

the way you work, but also the amounts

being spent are so much greater. So the

stakes are higher and that kind of

creates this this perfect set of

conditions where people realize the

people who spend the most on AI are not

the ones who are going to win. It's

going to be the people who have the most

AI enabled workforce and that's the kind

of space multiverse is playing in.

Everyone feels like they're behind the

curve when it comes to AI and they all

feel like they're not doing enough and

could be doing more. And that is kind of

creating this sort of um it's not even a

hype cycle but it's a just a desire to

kind of do more faster.

So when you think about the financial

gain of AI, a lot of that money is

flowing into tech companies. AI

companies, management consultants, and

companies adopting AI aren't necessarily

seeing those magical financial gains

that they were promised. But it's worth

bearing in mind that it's still really

early on. Um it's really early in the

deployment stage of these technologies.

Just a few years ago, they were still in

the lab. And so we have to be patient.

But obviously the question is how long

do we have to wait? Obviously,

businesses are hoping that these use

cases and gains will come sooner rather

than later.

>> The number of people turning to

commercial AI platforms on a daily basis

has been astronomical. The rate of

adoption for chat GPT alone outpaces the

rise in use of the internet when it was

first launched. But the gulf between

work related and personal usage is

growing.

So what you often see are these shadow

use cases where official uh corporate AI

initiatives are often untouched or

unused and people just use the AI tools

they like and this is often because

there there hasn't been necessary

communication between leadership and

staff about what they need and what kind

of tools they actually want but

different rules apply at workplaces

right workplaces often have sensitive

information or accuracy really matters

and so you have to pay attention to the

fact that these models often do make

factual mistakes and that could be

really embarrassing or even catastrophic

for an organization. So, every

organization needs to be thinking about

this and thinking about how these tools

apply to them and what they want their

employees to know about how to use them.

Some of the biggest challenges that

businesses face are that they just

aren't ready for this digital

transformation.

To use AI well, you need good structured

data, good cyber defenses, and perhaps

most importantly, AI literate staff.

I went to Google's newest campus in New

York to meet Amanda Broofphy, director

of Grow with Google. It's Google's

professional training arm and offers

courses to businesses and individuals on

how to use AI. What's your advice for

leaders who have maybe a cohort of staff

who are still very skeptical of AI or

slow to adopt? I think you need to find

how to make the AI work for that

specific person in their role and what

they're doing. What makes AI so powerful

is when you can translate it into what

you are doing today and now that's

specific to you. So if a marketer is

trying to use AI and we're helping them

figure out how to use this to write

social captions for their social media

posts for customer service to think

about how they use this to write

responses back in a way that's polite

when someone's getting upset and it's

escalating. Making it custom to that

person and role is when you actually see

the real benefits. And so being able to

test that for you is what allows that

skepticism to go away and see the real

benefit from it. One of the big problems

with AI rollout is that people aren't

really getting trained. So what do you

say to employers? You need both the

technology and the training, right? You

need the tools in the training. It's an

and not an or. And so what we're finding

is just rolling out the technology isn't

enough. We have a course, the Google AI

essentials course. And what we've seen

is that being able to teach people how

to use the technology, how to prompt and

make sure that they're using it in an

effective and reliable way helps them to

get to use it every day to upskill and

reskill. What I think makes AI different

is it's not learning about it. It's you

have to use it and do it. You have to

have the daily practice to make it a

regular habit in the work that you do.

It's one of those ones that you need to

have the intrinsic interest to be able

to see the value of AI in the day-to-day

of your professional and personal

benefits and the employer needs to be

able to deliver and have this available

for employees so that people are

consuming this information for their for

the company. And what's your best tip

for anyone watching this who wants to

get better with AI in their job? You

need to be able to prompt the AI

effectively to make sure you get the

desired output that you want.

Highlighting pieces like who's the

audience you're trying to reach? What's

the goals in the context? What's the

reference materials? And so being able

to prompt AI effectively is critical to

get the output that you will then see to

make this a regular habit and the

efficiencies that you want.

>> So do you think journalists make good

prompters? I bet we do.

>> I think you make excellent prompters

because you're good at the questions.

It's exactly what it is. You understand

who the audience is, what the questions

are. I think journalists are excellent

prompters.

>> Perhaps not surprisingly, the tech

sector has been an enthusiastic AI

adopter.

I met with Cisco's UK and Ireland CEO

Sarah Walker to see how it's working for

them. So internally at Cisco, it's a

tech company ahead of the curve.

>> What does AI usage look like generally

internally here?

>> Really, really broad spectrum. So if I

think of it in terms of our product

development, um things like our WebEx

platform have AI agents built in and

they do some fabulous things which have

made my life a lot easier and more

efficient. We've also then got some

really great platforms that we use as as

employees. There's different levels of

adoption of that. As you can imagine,

some are super proficient, some still

are trying to get to grips with with

what that means. But that's where

adoption becomes key because for for us

to really capitalize on the efficiencies

that those investments um can and should

deliver um our next task is, you know,

how do people adopt that and and make

that a part of their kind of DNA and how

they operate on a daily basis.

>> From talking to people, there's a kind

of you know, people bring in AI systems

and then they don't really monitor

adoption. How can leaders get over that?

>> Well, first of all, you have to lead by

example because my team will never adopt

those sorts of platforms if I'm not

talking about it and using it myself.

So, we did a master class actually with

our senior leadership team across the

UK. And I speak really really positively

about pro workforce and pro AI. It's not

an eitheror and using AI doesn't mean

that at some point in the future your

role will be replaced by it. This is

about using these applications to say

how do you become more efficient in the

things that you can and should automate.

And candidly, it's human nature to want

to find a quicker and more efficient way

to do things. We've always been like

that just because it's now called AI or

that's more kind of broadly known. We

shouldn't be we shouldn't be fearful um

of that. But it is a a common mistake

that businesses make that thinking just

because you've got the applications or

the opportunity that adoption will

follow. Everyone should definitely try

these tools. They're a lot of fun to

play around with and that's the quickest

way to learn how these might work for

you or how they might not work for you.

You have to use them for use cases where

the tools are actually beneficial

instead of expecting it to be some sort

of magic wand that can fix all problems.

And so currently we're operating in the

fact that this all will work and it'll

lead to amazing things in the future.

But if that were to change, if this were

a ma massive bubble that were to burst,

um the reality is that a lot of these AI

experiments, only the use cases that

actually work and that bring benefits to

employees will stay. Everything else I

can't really see surviving.

The challenge of AI rollout in

workplaces doesn't have a

one-sizefits-all solution. Businesses

need input from staff, but equally those

staff need support and training from

their leaders if any of us are to

realize the financial and productivity

gains that AI promises. I'm old enough

to remember when the internet rolled out

in the mid 1990s, and it seems to me

we're at a very similar early stage of

the cycle with Gen AI. There's a lot of

boom and bust to come and with it

disruption and I hope excitement at

work.