Artificial intelligence is
set to reshape our workplaces. What does this mean for my job? Am I going to have a job? Will my children have jobs? Companies are itching
to incorporate AI into their systems, but
are we really ready for it?

So two-thirds of our
desk worker population are still not using
this technology. I'm Isabel Berwick. I host the FT's
Working It podcast and write a newsletter
about the workplace. 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're
making work better. We have this extraordinary
responsibility to shape the new world of work. For everyone. San Francisco's one of the
tech hubs of the world,

and AI is definitely in the air. Generative AI is
kind of a subset of artificial
intelligence more broadly. There's a long history
behind this technology. But really, when we talk
about generative AI today what we're talking
about is really

something that's emerged
over the last three years. It's able to translate between text,
images, video, audio, even code. Now you're seeing that
technology applied to lots of other
types of patterns, including things like DNA even. And so the big turning point
was with the launch of ChatGPT

in 2022 at the end of that
year, where for the first time anybody, any user could
literally just communicate directly, interact with
a generative AI system. And since then, there's
been a lot of these.

Since AI's explosion into
public consciousness in 2022, we've also seen a huge
push from businesses to harness the power
of generative AI to streamline the workplace. The buzz of AI is
being felt everywhere. But when talking to
many business leaders, 

one wise person said to me
that CEOs have bought Ferraris in the shape of
state-of-the-art AI systems. They just haven't given any
driving lessons to their staff. A survey of 10,000 desk workers
found that the AI benefit that 

executives are most looking
forward to is increased productivity among workers. But leaders' biggest
concerns about embracing AI are around data
security and privacy, followed by distrust in AI's
accuracy and reliability. What we see in the data is
that the executive urgency 

to incorporate AI is at
an all-time high, right? This has increased seven times
over the last six months. So this is the most top-of-mind
thing for executives worldwide. But what's really interesting
is two-thirds of our desk worker 

population are still not
using this technology. So there's this really
interesting disconnect. Salesforce's global
HQ in San Francisco is home to Slack's
Workforce Lab, which studies how to make work better. The team there has
been researching what 

motivates workers to use AI. I went to meet the head
of the Workforce Lab and SVP of Research and
Analytics, Christina Janzer. So what are the
conditions that might make workers more
likely to trust AI or be 

Interested in using it? We've been really
interested in understanding this gap of executive urgency
and employee adoption. And so what we
really wanted to do was, let's better understand
the humans, right? Why are the humans using
it or not using it?

And so we did some research to
really understand the emotions that people are
feeling about AI. And we uncovered five
different personas that help us understand
the AI workplace. The first one is
called a maximalist. This is a person who's very
excited about the technology.

They use it very actively. The second persona, also
using AI very actively, is called the underground. And the really interesting
thing about the underground is although they're using it and
getting a lot of value from it, they're hiding their usage.

They're hiding their AI usage
because they feel guilty, and they feel like
people are going to think that they're cheating. And then the next three are
the ones that aren't really actively using AI. So the rebel is the
person who feels like AI

is a little bit of a threat. The superfan is very
excited about AI, but they aren't
using it themselves. They don't know how to start. And the final one
is the observer. The observer is
simply someone who's

in a wait-and-see mentality. They show some interest. They show some caution. They're just not
actively engaged, and they're kind of
just waiting to see how the whole thing plays out. Intrigued, I took
Slack's test to find out

What AI persona do I have? What is your AI persona? Take the Slack AI persona quiz to find out who you are. How frequently do you use AI tools for work-related tasks? Mm, probably a couple of times a week.

How do you feel about the use of AI in the workplace? Excited, guilty, indifferent, concerned, relieved, reluctant? Excited, actually. I'm concerned about AI replacing my job. I'm quite old, so I'm just going to put 2 for that.

I'm interested in learning or further developing AI skills. Yes, I'm a 5 on that. I'm a maximalist. As a maximalist, I can see the benefits that AI can offer. But with companies full of staff with such diverging views on AI,

is it a good idea to have everyone speeding ahead? So do you think that organisations should have put guardrails in place first? I mean, AI's moving so quickly. That's hard. Is there a trust piece missing here, I

guess is what I'm saying? There is a trust piece missing. I mean, what we see in the data is that only 7 percent of workers worldwide fully trust AI, right? And that's to be expected with new technology.

You have to use it. You have to get used to it in order to really understand whether you can trust it. The other thing that's really interesting about trust is there's a big manager component here. People who feel trusted by their manager

are twice as likely
to actually try AI. What I think you're
saying is that there's a very human part to this. Do you get on with
your colleagues? Do you trust your manager? Do you feel safe to communicate
where you've got things wrong?

Oh my gosh, I'm so happy
you said it like that, because I think so much
of the conversation that we're having is
around the technology, all of the amazing
advances that we're making, all of the amazing things
that this technology can do.

But you can build the coolest
technology in the world, and if people don't use
it, it doesn't matter. And so to your question
about, should people have come up with
guidelines earlier, maybe. But I also think we need
to give leaders a break.

This is new technology. It's developing so quickly, and
we're just trying to catch up. And so what we suggest is
it's not too late, right? Now's the time to really
sit down and figure out, what is your policy going to be?

What are you going to
allow your employees to do? And just be clear. The most important
thing is transparency. Slack has found
that when businesses cater for all types
of AI personas and have defined safe
usage guidelines,

employees are nearly six
times more likely to use AI tools in the workplace. But in a recent survey
of desk workers, 43 percent say they've received
no guidance from their leaders or organization on how
to use AI tools at work.

These models are
potentially so powerful. They are remarkable in what they
could provide to us as humans. And if we think that analysis
and structured thinking and creativity is a
net economic good, we really want to be
able to distribute that

as widely as we can. Tech investor and founder of
Exponential View, Azeem Azhar, looks at the impact
of AI on society. I invited Azeem to
the FT's offices to find out more about
what AI can and can't

do for the workplace. How are you using AI
yourself at the moment? One of my favorites is that I
have a number of different AI assistants who will
attend my meetings. So one is extremely good at
taking a detailed transcript,

and there's another assistant
which evaluates my performance in the meetings. And I'll get an email, and
it'll say, you did this well. You didn't do this so well. Next time, try doing this. What some of the academic
research has shown

is that the more
expertise you have, the better you can
get out of the system. The reason why somebody who's
senior can do better with AI than someone who
perhaps is junior is because when you use
a generative AI tool,

it's a little bit
like delegating tasks. And who best delegates tasks? Well, people who
have been delegating tasks for 15 or 20 years. That is, the senior exec. What are the downsides
that are obvious to you

as someone who is in
that world all the time? One of the biggest downsides
is that this is still quite a complicated
technology, and I think people that have used
AI know that it can also be a little bit unreliable.

And when you have a complicated
technology that's unreliable, you have got to be
prepared for things to go a bit askew and awry. And I think firms have to
figure out how they experiment and invest at a pace while
recognizing that the ground is

going to be shifting
quite a lot. A second issue is going
to be about the temptation that companies may have to
use this first and foremost as a cost-cutting exercise. And the reason they need
to be a little bit careful

is that this is
an unstable market and an unstable environment. And so one of the things
that I urge bosses to do is to be much, much
more circumspect about headcount reductions,
because you never know exactly where the
pieces are going to fall.

AI is set to be a skills
equalizer, helping weaker employees to level up. But Azeem has highlighted
the complexity of adoption, and that it is CEOs
who have to lead the charge. I think what's been different
with the generative AI wave is

that it is so easy
to use, and it doesn't require changing
your back-end systems or replacing big contracts that
you might have with enterprise software companies or whatever. Because in a lot of
cases tech companies that we already
have relationships

within the enterprise, like,
say, Microsoft or Google, these are the companies
offering generative AI. So it can easily pitch
to business leaders, saying, "We're the world's
biggest enterprise software companies, and we think this
is going to change the world."

There's been a lot
of buzz now verging on maybe even hype around
the idea that if you don't adopt this now, you're going to be left behind. It's a good job
of both marketing and a sort of
consumer-led technology.

HR software company
Lattice has made the move to becoming an
AI-powered platform. I went to their HQ to
see its capabilities. So right now, I'm logged
in as Alivia's manager. And what you'll
see on the right is

a summary of all of the
feedback Alivia received over the past year. Lattice's AI software takes all
the available data, feedback, previous reviews, and learns the
tone and grammar of the user. It then creates an authentic
performance review.

With the best will in
the world, some managers are terrible at feedback. They give bad feedback. They're blunt. They're clumsy. They may offend people. What can Lattice do to
stop that happening? So what we are
actually maintaining

is a set of what good
feedback looks like. It should be inclusive. It should be actionable. It should be concise. Regardless of what
level of experience you have with feedback delivery,
it up-levels your writing in a way that converges with
best feedback writing practices.

So it saves bad managers
from themselves, essentially. Yeah. I love it. Every time we've had advances in
tech, we've had to work harder. Is the promise of AI that
this time we'll get it right? We have more tech that's
supposed to simplify, 

that requires more
tech to integrate. But our collaboration
has not been easier because there's too much tech. This is what I think
is so powerful with AI, is that it really is simplifying
things down from an experience standpoint. 

The way that we will
experience the technology is the way that we
interact as humans. It doesn't matter if you're
in system A or system B. That data is brought
together behind the scenes. So when you ask it a question,
it can give you an answer. 

So what are you finding are
the main use cases for it? And also, how are
people responding in a perhaps more cautious way? In the world of HR,
you know a bunch of information about
structured data around your employee
record, your compensation, 

your performance,
the feedback you've received, all of your
skills that you may have. And by being able
to bring all of that together and just make your work
life easier right now to answer questions and give
you guidance, that's 

where we're at
right now with AI. And we're just going to see
this develop faster and faster and faster, which is amazing. But then it also makes you
question, how do I scale up my teams, my employees to
match these fast-changing 

expectations? And how do we govern it? Over the next year,
tech companies will unleash the next
wave of innovation to business: AI agents. These gen AI assistants won't
just tell you what to do, but will be given access to
perform actions on your behalf.

But are senior leaders
and employees really willing to hand
over their autonomy? The question then is, how
are we going to manage it? How are we going to
hold it accountable? How are we going to be
transparent with decisions

that we're making? There is no handbook, so hope
can't be our strategy that we're going to get it right. We have to hold
ourselves accountable and be very transparent
so that we can learn every step of the way.

And so that's the
thing for leaders, is that, how do you build
trust with your employees? With communication, education,
and a deep understanding of what you're intending the AI to do. So things are moving very
quickly in the AI world.

Is it too quickly? Should leaders be
pressing pause, or how should one
best be implementing? It's a great question
because one could say you move slow to go fast. The other thing is you need
to be rapidly experimenting

to learn along the way. What I will say is the thing
that is holding people back from going fast is their data
not being in order, integrations not being set up, and people
not having understanding for what's happening.

And then you can move very
fast because people will see, oh, I'm getting this value. Oh, my job just
got a lot easier. I think Sarah's reassuringly
unsure about the ways that AI is going to
change how we work.

It's the biggest workplace
shift in our lifetimes. No wonder there's a lot of
hype and some trepidation. We will only find by trial
and error what works. And companies like Lattice are
asking the questions now so

that we can all learn later. This is a very expensive
technology to build. For now, the companies
that are building it, they're not passing that cost
on to consumers or to customers because they want
people to adopt it.

And that's generally
the playbook of tech. How do you reach enough people
so that you get to a point where you basically
can't live without this? And then you start
to make money. That's the phase
they're in today.

But that's going to change,
because it is so expensive to train AI systems. Tens of billions of dollars
to build these huge models. And the more sophisticated
they get, the more expensive that becomes. So I think the first
question is, how much are you

willing to pay
when it's not clear yet what the real big
business benefits are? So many leaders have gone
all in on the hype around AI without really thinking about
their specific organizational needs. One size doesn't fit all.

Is the key to success simply to
take a step back, a deep breath, and think about where AI
might truly make a difference, and where it's not needed? Some staff won't want to
be forced into using it, and the tech itself
is still imperfect.

We aren't very patient about
mistakes in the workplace, but will we all be willing
to shift our behavior to accommodate the
software's learning curve? AI is going to transform
the world of work, no doubt about that. But it's right to
be a bit skeptical.

AI is transforming the world of work, are we ready for it? | FT Working It

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Financial Times

Introduction: AI's Impact on the Workplace

AI's potential to reshape workplaces and its impact on job security.

Introduction of Isabel Berwick and the podcast's focus on the future of work.

AI's prominence in tech hubs like San Francisco.

Explanation of generative AI and its recent emergence.

Businesses' Adoption of AI and Employee Response

Businesses' enthusiasm for AI despite lacking employee training.

Executives prioritize increased productivity through AI, but concerns remain about data security, privacy, and AI reliability.

Significant disconnect between executive urgency and employee adoption of AI.

Salesforce's Workforce Lab research on factors motivating AI adoption among workers.

Identification of five AI personas based on worker attitudes and usage.

Description of the 'Maximalist' persona: enthusiastic and active AI users.

Description of the 'Underground' persona: active AI users who hide their usage.

Description of the 'Rebel', 'Superfan', and 'Observer' personas: less active or hesitant AI users.

The Need for Trust and Transparency in AI Implementation

Discussion on whether organizations should prioritize guardrails before widespread AI adoption.

Low levels of worker trust in AI and the importance of practical experience in building trust.

The role of managers in fostering employee trust and encouraging AI adoption.

Emphasis on the human element in AI adoption, highlighting the importance of usability over technological advancements.

Recommendation for organizations to establish clear AI policies and guidelines.

AI's Broader Societal Impact and Potential Downsides

Discussion on the potential of AI to be a skills equalizer and improve economic output.

Azeem Azhar's perspective on AI's capabilities and limitations in the workplace.

Azhar's personal use of AI assistants for meeting transcription and performance evaluation.

The correlation between expertise and effective AI usage, particularly for senior executives.

Downsides of AI: complexity, unreliability, and the potential for misuse as a cost-cutting tool.

Lattice's AI software for generating performance reviews.

Lattice's approach to ensuring high-quality and unbiased feedback through AI.

Discussion on whether AI will simplify or complicate workplace processes.

Main use cases for AI in HR and challenges in scaling up employee capabilities to match AI advancements.

The Future of AI: Agents and Accountability

Emergence of AI agents and the challenge of managing autonomy and accountability.

The need for transparency and learning in managing AI's impact on the workplace.

Building trust through communication, education, and understanding of AI's intended purpose.

Balancing speed and caution in AI implementation, emphasizing the importance of data organization and employee understanding.

The Current State and Future of AI in Business

The current low cost of AI adoption for businesses and its potential to change as technology matures.

The need for businesses to assess the value proposition of AI before widespread adoption.

The importance of considering organizational needs and employee preferences when implementing AI.

Acknowledging the imperfections of AI and the need for patience and adaptation.