AI integration in public relations

This podcast explores AI integration in public relations via automation strategies and maintaining human expert value.

AI Integration and Strategy
Agencies will implement AI by prioritizing internal efficiency and service innovation. Implementation success requires depth over breadth to maximize impact.

Human Augmentation and Risks
AI should serve as an augmentation tool to support experts rather than replacing critical thinking. Teams must guard against efficiency-focused work becoming low quality.

Operationalizing AI Implementation
Agencies should decentralize AI expertise by embedding champions within teams instead of separate hubs. Prioritizing repetitive tasks allows firms to scale high-value client services.

If you want to learn more about how the future of PR will be impacted by AI, don't miss PRmoment's PR Masterclass: AI in PR.

Details

• Introduction and Optimistic Outlook on AI in PR: Ben Smith welcomed Tom Symondson, who co-leads Accordience's AI team, to discuss the impact of AI on the PR agency model.
• Tom Symondson expressed extreme optimism about AI's impact, asserting that core PR skills like relationships, experience, creativity, bravery, and judgment are irreplaceable. They suggested that AI will automate tasks that are not highly valued by clients or consultants, such as general research and formatting of monitoring reports, allowing consultants to focus on high-value analysis and strategic input.
• Emerging Opportunities and UK Investment: Tom Symondson identified that AI will generate new mandates, clients, and revenue streams, particularly around technology-focused businesses, crises, and regulation issues stemming from AI. They expressed optimism about the UK industry's potential benefit from significant investments in large language models (LLMs) by companies like Anthropic and OpenAI in London and the UK. 
• Three Approaches for AI Implementation in PR: Agencies are anticipated to approach AI integration in three primary ways: improving internal efficiency, changing how client work is currently delivered, and creating entirely new tools and service lines that become new revenue streams. 
• The internal efficiency focus involves automating or augmenting repeatable, client-invisible backend functions such as transcribing meetings, building action lists, and reporting processes. Tom Symondson noted that businesses should focus on depth over breadth, selecting one area for the biggest impact before moving on to the next.
• Understanding AI Augmentation: AI augmentation, distinct from replacement, refers to the technology supporting human experts rather than substituting them, particularly because much of the PR industry's work requires nuance. Tom Symondson gave the example of using an enterprise LLM system for new business research, where the tool supports initial framing but does not replace the consultant’s own deep research process. They emphasized that the challenge for agencies is mapping out where this augmentation will have the greatest impact and providing training to take advantage of the tools.
• Obstacles to Successfully Embedding AI: The three main obstacles to integrating AI into an organization are cost, data and readiness risk, and time. Cost arises because enterprise-level access to AI tools is often high, and data readiness requires extensive security and system sign-off. Tom Symondson identified time as the biggest obstacle, as consultants need more time to experiment with different prompts and processes to understand the full range of AI's impact on their work.
• The Risk of Efficiency Over Effectiveness: Ben Smith cautioned that the "race to efficiency" can be a "race to the bottom" if not carefully managed. Tom Symondson agreed, noting the risk that increased automation could lead to less expert consultants if technology performs more research than people. The opportunity lies in using the time saved by AI to allow consultants to specialize further, for example, spending more time networking, attending events, or researching clients.
• The Role of Human Judgment and Criticality: Ben Smith highlighted the necessity of retaining a critical mind because LLMs, while able to generate answers quickly, still produce errors.
• Tom Symondson added that LLMs are excellent with structured data; therefore, agencies must connect their LLMs to accurate data tools, in addition to training colleagues on drafting effective prompts and knowing when to use the technology. They cited the doubling of AI's ability to complete long tasks every seven months, projecting that in 14 months, AI could complete a 40-hour human task.
• Importance of Openness and Ownership in AI Use: Tom Symondson stressed the need for consultants and agencies to use AI appropriately, ensuring it augments and supports work, rather than replacing critical thinking. A crucial element is fostering a culture of transparency where people are open about how they used AI for research, including what worked well, what struggled, and what human work was needed to finalize the product. This transparency ensures that people maintain ownership of the work product, balancing efficiency with quality.
• Innovation and Use Case Clarity: Ben Smith noted increased innovation in PR firms over the last 18 months, which Tom Symondson attributed to the significantly reduced ease and cost of experimentation, allowing someone to build a Minimum Viable Product (MVP) in a weekend. However, Tom Symondson suggested that there might be less innovation this year as the industry moves toward a "substance phase," focusing on embedding existing AI use cases across the organization.
• Creative Quality and the Need for Uniquely Human Work: Tom Symondson identified the risk of "AI slop" or ideas that look and feel similar due to over-reliance on AI-generated content (e.g., AI writing, image, or PowerPoint generation). Great creative agencies will continue to succeed because their ideas are expected to feel "uniquely human" and grounded in culture, emotional intelligence (EQ), and personality.
• Operationalizing AI Implementation Across Agencies: Recognizing that time is a major barrier for busy teams, Tom Symondson emphasized the McKinsey principle that depth is more critical than breadth when implementing AI.
• Identifying and Managing Repetitive Tasks: In the internal productivity bucket, agencies focus on automating repeatable tasks, such as templating monitoring reports from spreadsheets into client emails, which Tom Symondson estimated could number in the thousands.
• Structure for AI Implementation and Expert Teams: The practical implementation of AI is highly decentralized, residing within the agencies themselves. Instead of a separate AI hub, teams have AI champions who are client-facing staff who integrate AI into their normal day jobs. Tom Symondson stressed the importance of having people work on AI who are connected to the day-to-day client work.
• The Opportunity for PR Compared to Other Marcom Sectors: Tom Symondson suggested that because PR is less structured and repeatable than sectors like production or media buying, the impact of AI is different, offering more opportunity for PR. 
• AI will improve PR's ability to measure and articulate the value of its work by making it easier to structure and analyze diverse data sources. The discussion concluded that in the long term, AI will not replace talent, but rather reduce the fee earned from less-valued tasks, while increasing revenue from high-value services that require judgment, advice, and impactful results.

Transcript

Welcome to the PR Moment Podcast, produced
in association with the Marketierrs Network.
To celebrate the speaker lineup for PR Moment's PR Masterclass, AI in PR. We're publishing a series of
interviews looking at the intersection of PR and AI. And today we're talking to Accordance's Tom
Symondson. Tom co-leads Accordance's AI team. And if you are not aware,
Accordance's' agencies are Red, Citigate, Grayling and Cirkle. Do check out the full agenda to PR
Moment's next PR Masterclass, AI in PR. Genuinely, it really is an amazing speaker line-up.
It's on the PRmasterclasses.com website. Or just go to the homepage of PR Moment. You can see it
there. Tom, welcome to the PR Moment podcast. Thanks for having me, Ben. An absolute pleasure.
Come on, let's go broad to start with, shall we? How do you predict AI will impact the PR agency
model? I am, perhaps unsurprisingly, incredibly optimistic about the impact AI will have on our
industry. I think firstly... you look at the skills that really underpin great work in PR,
whether that is relationships, experience, creativity, bravery,
judgment, those aren't replaceable. And I think that means the fundamentals of what clients want
from businesses like ours and the industry more broadly actually is really well protected from AI.
I think where you look at... And actually, it's really well placed to take advantage of the new
technology. I think if you look at the work that is more easily automatable,
it's not what clients value. And I don't really think it's what consultants in our businesses value
either. I think if you look at pulling together an agenda or if you look at monitoring an example,
clients really value the analysis that comes with monitoring, whether that's media monitoring or
political monitoring. They don't mind how that information is researched. They don't mind how it's
formatted. They want that analysis about what it means for their business. And again, so that's an
area where AI is going to make the life of a consultant easier and focus on what the clients really
want. I'm probably also optimistic because I think there's going to be some really new skills,
mandates, clients that we're going to see as a result of AI, whether it's new businesses who are
operating at the forefront of technology. whether it is crises or regulation issues that are coming
about just because of AI. And to be honest, I'm quite optimistic as a UK business about the way the
industry can benefit from the investment that we're seeing in the UK. Even if you look over the
last month, it just feels like it's been announcement after announcement about big LLMs like
Anthropic and OpenAI who are investing in London, investing in the UK. And I think that will have a
knock-on effect in a positive way in the industry as well. Well, I hope so, because we certainly
we do need to start talking more positively about about UK PLC. Well, that's a whole nother
podcast. Yeah, I'm just exploring that a little bit more. Right. So the devil is always in the
detail. So when you talk about the impact of AI on PR,
so from a broad perspective, you're relatively positive about it. When we talked before,
we. well, I guess you identified three approaches really about how AI is being used in PR
currently, which I guess kind of goes into another layer of detail about how PR firms are and
indeed will be using AI within their teams. Yeah,
and I think every business will be different, but I think fundamentally agencies are going to be
looking at it. How can it help them become more efficient in internal processes?
automate or augment repeatable tasks that a client never sees whether it is um you know around
transcribing meetings and building action lists or it's or it's you know it's reporting so it's a
back end function in the back end exactly and clients will probably never see that change but that
would be a benefit to agencies i think ai is going to change how we deliver client work currently
and there's probably going to be a bit of a shift from actually the amount of hours that go into
something the technology is used for something but the technology that's used to deliver something
whether that's research whether that is um analysis whether it is monitoring you know that systems
are going to change that and then i think we're going to see whole new tools and service lines that
come about through AI, new revenue streams that agencies are going to have access to. It feels like
the job that most agencies will be looking at now is, there's a really good McKinsey study that
recommends that businesses need to look at depth, not breadth. not try and do too much.
And I think for most agency leaders, there's probably 20 different things you could see and think,
God, AI could really help us there. It's picking one, what's going to have the biggest impact and
really trying to land that and then move on to the next thing rather than trying to do too much at
once.
We'll talk a bit more about the automation opportunities, but I think a lot of people have got
their head around that in terms of how it might help. They're not necessarily doing it just yet,
but they're moving that way. When you talk about AI augmentation, Give us a little bit more detail,
a bit more examples of what you mean by that. I think that comes back to the point we talked about
at the start. You know, in every... every job, in your job, in my job,
and everyone in our business's job, there's some of the work they do that is expert that only they
can do. And then there's a bit of work they do that's inexpert that kind of anyone or a system can
do. And actually, I think most of what our industry does is expert in some way because there is
some nuance involved. And that means AI will never be able to replace that, but it will be able to
support with it. And that's what we mean when we talk about augmentation. If I look at, you know,
we've brought in an enterprise LLM system and we're really encouraging teams, colleagues to use
that on an everyday basis. If they're doing that for new business research, I don't want them to
stop researching themselves about a company or about an issue or about a leader. I want that to
support them. So it might do some really initial framing around sort of topics. It might look at
one specific thing. They might go and do a deep research thing around one specific issue. it's not
replacing their research process it's just augmenting it and i think that's what we're going to see
in lots of you know in lots of cases with ai tools technology are going to support what people do
and not replace it again the job for agencies is to you know be able to map out where that's going
to have the most impact and look at training embedding support so that colleagues can take
advantage of it because something we talked about the other day you know there's probably three
obstacles to really successfully embedding ai in an organization one is cost because the more of
these tools you have access to the more that you know the more that cost racks up and actually
sometimes you see the cost it takes to access a tool as a personal user is quite low and as
enterprise user it can get quite high there is a big um you know data and readiness risk so again
you've got to make sure you're working security teams to get tools systems innovation signed off
but the third one and the biggest one is time and i think there's across our business and lots of
other businesses there's real appetite you know and engagement with ai already but people just need
more time to understand how it can you know actually all the different areas that can impact their
work try different prompts try different processes to try and make the most most of it as possible
And again, I suspect a lot of agencies are then asking that question, how can we give more time to
our consultants? to make the most of the technology. Yeah, I mean, I definitely wouldn't say it is
more nuanced. I see a variation of how AI is being used and it comes across in the speaker line up
the agenda for our event we've got coming up in July. But you do see there is a danger.
Sometimes there's a bit of a race. to it for efficiency isn't there which if you're not very very
careful can be a bit of a race to the bottom um and it's you do need to put your handbrake on that
sometimes because it doesn't always end up going to the place you think it's going to go no i think
that's right and i think you know there was like one particular monitoring report that um when i
when i used to work at grayling one of the teams used to do and it was a real behemoth it was you
know maybe four hours work five hours work And so you'd look at it and you'd be like, God, this is
such a difficult task. But actually it was great because it meant that through reading all of this
news every week, people became really expert about tech policy. And actually the consultants who
became brilliant at what they did, one of the proving grounds for that was this monitoring report.
They really learned the topic area. So one of the risks is that actually AI means that people are
engaging with these issues less. If more research is being done by a tech tool than by a person,
are you going to get less expert consultants? I think the opportunity is actually the time saved is
used for consultants to become really specialist in what they do. If we can make it much easier to
build a media list and a political stakeholder list around... you know the around green energy for
example we've got to make sure we're giving those consultants time to go and spend more time
networking with um with you know clients in green energy or attending events or you know spending
more time researching what our clients are doing so i think it's just making sure that you know one
we're looking at efficiency and how can it augment and support people and two how can we make sure
that people are still really expert in the skills and the sectors and the services that matter It's
true, and I imagine it'll all work its way out, but there definitely is a, it's not even a
spectrum, is there, between that efficiency and effectiveness, but it's,
I just, as you talk about that then, so if you put into whatever, Claw,
Gemini, whatever your LLM of the day is,
do me a great media list for whatever. whatever sector it's only by having that experienced and
having um grown up through through many years of doing this stuff you might go well they've left
that email's wrong um because it does it does it still spits out it wants to give you an answer for
this stuff doesn't it so it's it's it as you talk about that i just got me thinking is it it i in a
different world i i it spits out um i asked various prompts of of AI and it's only because I've
been doing this a while ago well no that's not right and you know it's that critical mind to it and
so you I mean it's exactly the same within a in a PR firm or our team isn't it you if you don't
it's that critical element to it but I'm sure it'll all we're quite early days so I imagine that
will work its way through better than it currently the other critical element is is llm's ai is
brilliant at working with structured data so if you ask if you ask a um you know an llm to give you
a media list in a particular sector it's got to rely on what it can find in the internet that's
potentially outdated information that's potentially like patch information maybe it's plugging
together something gets seen on linkedin with something it's seen somewhere else if you can give
access to a data tool you know something else that a lot of agencies have access to and it queries
that then you know it's going to be really accurate so that comes down to for an agency there's
both a training job and an experience job to make sure the colleagues know how to draft a great
prompt to know when to use it and when not to use it but also agencies have got to set up these
tools in the right way so you're plugging in your llm so the right kind of data that they can be
most effective with yeah absolutely i mean just to finish on that where do you see this whole
efficiency um versus effectiveness i mean do you because you must you you're on that curve
somewhere i imagine aren't you as a business yeah and it's and it's also looking for my my favorite
um sort of stat at the moment there's an organization called meter metr and they measure um ai's
ability to complete long tasks they sort of they do it using software engineering tasks and they've
shown over six years of data that um ai can complete about every seven months the amount of work
that ai can complete in a single task doubles and currently they show that it can complete a task
that takes a human about 10 hours and so following that Following that process, that would mean
that in 14 months' time, so say in June next year, AI will be able to complete a human task that
takes 40 hours. So again, we're literally, you know, seven months ago, the steps forward of making
efficiency are moving so quickly. I think the big, I think the real thing that matters here is that
consultants and agencies are using it in the right way. Again, that point that it augments and
supports, not replaces. You know, we've... You hire brilliant people who are critical thinkers and
are analytical and are expert in what they do. A tool like this isn't going to be more effective
than they want. They're not going to be more effective than them. So it's just making sure it's
used in the right way. There's the right checks and balances. There's the right approach to
prompting. you know a big thing for me at the moment is people being quite open about how it's
being used so say you're in a new business pitch and someone says oh here's a research doc about
this company that they feel able to say here's a research doc i am i used ai for a good chunk of it
particularly to help me to look at what their leadership had said over the last 12 months it really
struggled with these things but it was good with these things this was the prompt i used but
actually at the end of it i really had to combine it with this work i'd done so again it's it's
like having a having a culture where people feel they can take advantage of the technology but
they're also they they really take ownership of their work still so that it's efficiency but it's
not changing the quality of the product yeah it's interesting just just pondering what you just
said there because you know in that data example just just just in in that one in isolation i mean
fairly obviously um scarcity of data is not going to be the problem is it it's the problem is going
to be too much data and trying to trying to work it out trying to work out that you know the the
weeds from from from from the good bits and uh and the interpretation of that data especially when
you consider clearly all data sets are not the same they're all different they some of them are
more better than others some of them are better than others in different contexts and different
regions etc etc so yeah it's all gonna it it does um yeah it's the interpretation of that data is
going to be extremely interesting as as it all evolves um just on that the last point you said
there on your on your three approaches was around innovation uh i just wanted to talk about that a
little bit as well because i i'm i've seen some more innovation i think within pr firms in the last
18 months and i don't know previous five years something like that it's it is it's quite exciting
it's definitely happening and you know the nature of innovations that some things work some things
don't but the fact it's happening is uh it's great to see the the ease of experimentation has just
like transformed over the last 12 months you could and this comes back to the example we talked
about before in that not not everything we'll talk about is isn't you know not all of the products
and the innovations are ai products but it's often ai that enables us to build them if you looked
at scoping out anything whether it's around a data or it's a production tool or it's an internal
tool. If you were looking at it two years ago, you might have had to have put aside £150,000 and
an external partner and a 12-year plan. actually someone could build an mvp only to 80 but using a
using a vibe coding tool or a coding tool in a weekend and that's meant that you can as you say you
can get stuff together and test it and see if you want to take it forward in a much quicker way
rather than the commitment we'd have had a couple of years ago um i think you're right i think We
might see less. I wouldn't be surprised, strangely, if we see less innovation this year than more
innovation, because I think people are now moving from to the kind of the substance phase of AI.
So more people looking at how can we embed it across the organization and make sure that all of our
employees are using it every day rather than actually let's look at that sort of shiny client tool.
The use case has become clearer, I think, hasn't it, over the last 12 months. But as before,
there's quite a bit of variation on a theme. Now it's, okay, yeah, this is probably where we need
to use it. It might change, but right now, this is kind of, yeah. How long ago, what was it,
12 months ago, 18 months ago, when everyone was using AI to post? pictures on linkedin of them as a
um an action figure character with you know the things that you know and that was like that was the
ai use case a year ago and now you know huge workflows or tasks within agencies are being and
replaced essentially revolution though is it just to think about that moment if it was it was being
used in campaigns probably more a year ago than it is now so i maybe maybe that's a sort of a bit
of a lesson for us that because there was there was no barrier to entry to any of that everyone had
access it frankly quickly became boring and yeah and that's the kind of and that's the sort of ai
slop narrative which i think is is you know is a bit reductive but in general i think if you're an
amazing creative i think you're looking at the trend of what's happening in the moment and you're
really enjoying it because i if i think people will go into a pitch with ideas that you know maybe
they're not entirely generated by ai but they've been involved in the ideation process the creation
process maybe they're you know mocking up the idea and they will just look and feel similar you
know whether it's ai writing or ai image generation or if you use claw at the moment ai powerpoint
generation you can just wait you can just tell and i think at the moment great creative agencies
will continue to succeed because their ideas will feel uniquely human they will feel like they're
really grounded in culture and eq and personality um so yeah i think you know that's probably that
it felt like it felt like something that was novel a year ago whereas now there's actually a risk
to it feeling samey i do um as part of it's part of your role isn't it to to sort of co-lead um
accordions um ai journey if you like um how do PR teams become more more tech enabled because it's
easier said than done isn't it I mean I think we all get that it's a good idea but when you're in
the nuts and bolts of your day job you've got clients demanding this and that you've you've got
your home life you know you've got there's so many priorities now aren't there and it's difficult
to say well actually no I'm just gonna potter over here for for the next couple of hours and
innovate and experiment and probably not come up I may well not come up with very much at all. Is
that all right with everybody? It doesn't quite work like that all the time, is it? Yeah. And
again, I think that comes back to the obstacle that everyone has is time is such a big issue.
And I think, again, that comes back to that McKinsey point about depth is more important than
breadth. You can't try and do five or six different things at once. You've got to pick one and
really invest in it. Our process. you know we've got four very different businesses if you look at
what red do versus what citygate do versus what grading public affairs do you know on the face of
it they feel quite different different audiences different types of content different objectives
different measurables they're monitoring different you know the different um platforms but we try
to chunk it down be like well what what are the what actually is you know What actions are the same
across each of those businesses? And I think this is probably true across all financial comms,
public affairs, PR businesses. There's a real bucket of work around thinking. So that's research,
strategy, insight, data, planning. There's a bucket of work around creation,
whether that's content creation, visual, video, written, reports for leadership. There's a bucket
around delivery, client execution, whether that is literally email. the client on a daily basis
executing campaigns writing that up and then there's a measurement element whether that's
monitoring reporting um you know sort of articulating the value and actually each of each of our
four agencies deliver work in each of those four buckets and then to we're able to look in those
four buckets and be like okay what within these can we automate what can we um what can we try and
innovate in so that we can see that if we're going to invest in something it's going to have an
impact across the four agencies but at that level it's kind of you're looking for repetitive tasks
are you is that what you're trying to identify and and automate is that is that i think a bit of a
certification but is that is that roughly what you're trying to do i think a big mix i think you're
probably you're either If we come back to those three buckets, if we have internal productivity,
client delivery and new services, in that productivity bucket, we're looking at things we can
automate. And that might be a really big process or it might be just one really small thing.
Again, I come back to monitoring as a really good example. Every agency does monitoring in a
different way, but at some point they have to take it from an Excel doc or a Word doc. google sheet
into an email to the client and so can we just automate that that um that templating process it
doesn't that you know even that in itself is saving time have you got any idea how many repetitive
tasks you've found within pr firms to be clear to the listeners i did not tee this one up which
wouldn't be a bad idea but what do you reckon thousands hundreds tens be thousands but i think it's
a bit like Okay, so if you take your morning routine, you could say that your morning routine is
one process. Or you could say that brushing your teeth is one. Actually, even putting the
toothpaste on your toothbrush is one. Shaving is one. Like, you know, it's like, you know, putting
your aftershave on. But the reason I ask the question is because I found, and I might be wrong,
but I think I found that I have fewer repetitive tasks in my... working routine than i had imagined
i might do so i i haven't had the um productivity benefits in some respects it's helped you know
here and there but it hasn't i haven't found it it hasn't changed my world now maybe that's just
because i've got it wrong um but i suspect within pr firms there's a bit there is more more
repetition going on right so i think i think there will be i think there'll be thousands and i
think that the way you'll be able to judge it in uh a year's time is look at how many gpts look at
how many skills look at how many projects we have across the group and that i think by them will be
in its thousands because they're each replicating some kind of repeatable task whether it's a
repeatable task for one client or it's a repeatable task for a whole service like public affairs i
think the other area we're seeing how do you keep that in in check because i mean if you're not
careful you have so many of these in effect agents
um and in a sense you want to encourage innovation and bespokeness, don't you?
But you've also got to be a little bit careful, haven't you? I guess that everything's working in
the way it should. Yeah, and I think that comes down, again, comes back to that depth,
not breadth point. It's you're better doing getting things right and then rolling them out and
going from there. Billy, who leads AI for Grayling in the UK, has really put a lot of store on
that. Like, actually, we're better getting doing a small number of things really well. So let's get
a project set up for, you know, clients have a really great process for building projects for
clients. Let's have a really rigorous process for building skills rather than trying to do too much
at once. And that informs everything else, doesn't it? You do one thing well and then you can roll
it out.
Ironically, the process of building things like GPTs or skills or whatever is quite repeatable in
itself. So once you've done, there's a skill on ChatGPT for building skills.
So once you've mastered it once, you should be able to master it again and again. And who's doing
it? I mean, have you got a little AI hub or are you saying to the account teams, you know, someone
who's good at that? good at that stuff passionate about that stuff get off you go get on with it i
just on a practical level who's actually doing it like very much in the agencies themselves you
know grayling has um you know an ai like group of champions that's the same across each in that
sense you have a group of experts who are helping
client facing people who are people who are you know alongside their normal day job have taken an
interest in this or taking responsibility for it and i think that's and i think that's really
important you need people who who are working on this who are connecting it to their day-to-day
rather than people are looking at systems that are completely disconnected from what people are
doing for clients yeah it's pr Do you think AI is more of an opportunity for PR than quite a bit of
the rest of the Marcom sector? It's an interesting one to think about, isn't it? I mean, I'm no
expert in media buying or the business model of media buying agencies, but that would seem a
business a bit more vulnerable to AI automation than public relations, I suspect. I don't know.
Yeah, we'd probably both say that because, you know, turkeys don't vote for it early Christmas,
but I do think that.
you know, perhaps one way of thinking about it is the more like structured and repeatable an
industry is, the more, you know, the bigger impact AI could have on it. And so again,
if you look at, I don't know, production or media buying, are they more structured? Whereas if I
look across the different businesses we have, there's just so much nuance involved in the,
you know, in the topics we're looking at and the type of work that's being done. I also think for
PR, there's actually an opportunity in some of the challenges the industry has faced. I think if we
look at measuring And showing the impact of PR's work has felt like it's been something that for 10
years, you know, the industry has talked about. And that's something that's great. I'd say it's a
load better than it was. A hundred percent. A million percent. I think it's so much,
you know, big leaps forward over the last 10 years. But as you said before, the fact that it
becomes easier to take lots of different data sources and structure it and do analysis from it,
I think will make it even easier to actually for the sector. to show the impact of work.
Is there a more fundamental point, do you think? If you look, we're going a bit technical now,
but if you look at the fee income per head of agencies, it hasn't increased that much in 10, 15
years. So you have to say that maybe AI is a chance for PR to make that jump,
which will frankly mean maybe we employ fewer. better people do you see what i mean there is that
because in the end you are going to need to employ some very very good consultants who really are
experts in what would it whichever bit of pr you're talking about that's what it's all going to
come down to in the end isn't it talent 100 it could because again if we come back to that first
point around You know, the things that AI can't impact in the industry, relationships,
creativity, bravery, experience, judgment, that comes down to talent.
And so, again, if you were saying 10 years ago to 10 years time, what's the most important thing
for the success of a PR industry? It would still be talent. That wouldn't have changed. I think it
is, you know, whether you're looking at law or accountancy or consulting or PR, you know,
fundamentally, the. the the tasks the client values less we're going to do less of and earn less
fee from and the stuff that they value more that judgment the advice you know really impactful
results they're going to be going to get more of a critical moment you you what you still want to
pick up the phone or talk to someone who knows exactly what they're talking about who's done it
before and that's yeah and i think public affairs is a great example of that you know i feel like
the only upside for that and there's only upside for that industry because AI can't build
relationships with stakeholders. It can't, you know, it's going to help automate policy,
you know, bits of policy analysis. But again, policy analysis is all about new ones. So a human's
always going to have to be all over that. I think it feels like it's going to make the job easier
and allow people to focus on the bit of the work they're really enjoying. Tom Somerson, thanks so
much for coming on to the PMM podcast. Massively enjoyed chatting to you. If some of the themes
there piqued your interest, then as I say, do take a look at... um masterclass we've got coming up
all around ai in pr that's coming up in july thanks for having me
thanks for listening to the pr moment podcast produced in association with the marketeers network
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