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 economy.

Only 1 per cent of CEOs have a fully formed AI strategy.

With such high stakes, will businesses

see a return on investment?

I'm Isabel Berwick.

I lead the FT's Working It brand,

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.

Three to five 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 rollout

and preparing the workforce for the skills needed

for the future.

Every six months, a new model is dropping.

Every six months, something shifts

within the marketplace where you have to stay up to date.

With AI, we're still in very, very, very early days

of everything happening.

We have this amazing technology with the promise of productivity

enhancing gains.

Roughly 10 per cent 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 per cent share of US GDP growth

this year.

Over 75 per cent of businesses worldwide

are using generative AI in at least one function.

But despite this, a study by MIT Media Lab

found that 95 per cent of GenAI pilots in the workplace failed.

I spoke with editor-in-chief 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 ChatGPT

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 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 workers' skills

will be in three years or five 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 the record discussions,

panels and big picture sessions, what's emerged

is that there's no clear path forward for Gen GenAI at work.

It's still all to be decided.

Re-imagination 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 rollout actually

going and what are companies saying

about how they're using AI.

And so we did this massive analysis looking

at S&P 500 companies in the US.

We went through thousands of earnings reports

and regulatory filings.

And the results were quite surprising.

In earnings reports, CEOs would often say AI is amazing.

It would bring incredible productivity gains,

a Cambrian explosion of innovation, things like that.

But then in the filings, which, to be fair,

tend to be more measured and risk averse,

no one really had anything concrete

to say of how they're actually using it.

And in those filings, the risks outweighed the benefits very,

very clearly.

If you look at the S&P 500 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 S&P 500

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.

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.

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.

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 think it's almost the kind of polar opposite of hesitant.

The kind of investment wave in AI we've seen

is probably nothing ever before in history.

So the big

Challenge a lot of organisations are facing is how to turn kind

of potential AI gains into actual realised AI gains.

And that's where the 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.

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 particular productivity gains

that I'm aware of.

Where's this gap?

What's the gap?

We've seen accounts teams, for example, process invoices

50% more quickly and with half the number of errors

because of introducing AI.

We've seen software engineering teams

increase their speed of shipping code 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 OK.

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 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 perfect set of conditions where

people realise 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 creating this, it's not even a hype cycle,

but it's just a desire to 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.

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 ChatGPT 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 corporate AI initiatives, often

untouched or unused, and people just use AI tools they like.

And this is often because there hasn't been necessarily

a communication between leadership and staff

about what they need and what kind of tools

they actually want.

But different rules apply at workplaces.

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 organisation.

So every organisation 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

defences, and most importantly, AI literate staff.

I went to Google's newest campus in New York

to meet Amanda Brophy, 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 sceptical 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 are 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 scepticism 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.

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 practise 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 the company.

What's your best tip for anyone watching

this who wants to get better with AI in their job?

That 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, because--

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 generally internally here?

Really, really broad spectrum.

So if I think of it in terms of our product development,

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 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 what that means.

But that's where adoption becomes key,

because for us to really capitalise on the efficiencies

that those investments can and should deliver.

And our next task is how do people

adopt that and make that a part of their DNA

and how they operate on a daily basis.

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

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 masterclass 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 either/or 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, a 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 of that.

But it is 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 massive bubble that

were to burst, 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 size fits all solution.

Businesses need input from staff, but equally,

those staff need support and training from their leaders

if any of us are to realise 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 and boom and bust to come

and with it, disruption and I hope, excitement at work.