AI Future

How To Design An AI Marketing Strategy?

How are media & marketing closing the AI skills gaps? What are the ethical considerations? A panel of experts at EMX tackle these questions

By Creative Salon

Artificial intelligence (AI) is offering marketers and their brands unprecedented insights into consumer behaviour and the potential for tailored solutions, products and experiences. All while creating a massive amount of unimagined new capabilities. As AI becomes increasingly integrated into marketing strategies, prioritising skills gaps and ethical considerations is essential. In pursuing both innovation and efficiency, do we need to pause and reflect on the critical role of ethics in this AI-powered landscape? And how can and should brands approach AI when using it at scale?

These were some of the topics that were explored at a recent panel discussion at EssenceMediacomX with Creative Salon. The panelists included EMX COO Anna Berry; Rob Meldrum, head of creative futures, EMX; and WPP’s chief creative AI officer Perry Nightingale.

Creative Salon: The AI space is booming, and no one wants to be left behind. What are the skills and gaps you see within the existing marketing and media teams to effectively collaborate with the tools?

Anna Berry: People are essential to the success of any digital transformation project.

And with AI I think there is a gap and there isn't a gap.
I think one of the reasons there isn't gap is that we recruit and train people to be curious.
And actually, if we bring people into our business who are curious and like to experiment, that's that's the sort of skill set of mindset that we need. And we already have that.
The thing that we don't quite know is that when we are talking AI is that you have to learn every day. And so it's not a skill that you can teach in one moment of time. For instance we have this tool called EM Sidekick - an advanced AI tool designed exclusively for our people. We've given that tool to our people in a very safe environment so that they can experiment and learn. But I don't think it's a gap that can ever be filled. It will always be constant learning and I think that's that's how we as businesses need to learn to train our people, give them the opportunity to experiment, work with our clients so that we can experiment and appreciate that it's a constant learning curve.

Creative Salon: What should marketers be doing now to prepare?

Rob Meldrum: Thinking more specifically about the work that we're being asked to do, there are some quick wins.
I think probably if you spent any time thinking about how to use Gen AI for creative ideation, it gives you an interesting starting point and a different way of thinking about answering a brief.
As agencies we can help brands lean on AI to break the creative process, twist it around, and then we might just get to somewhere we’d never considered.

It feels a little bit 'hacky', but the point is that we just need to be playing with it more to really kind of see how the AI tools can help us every day.
I don't believe it's going to replace an individual coming up with really interesting thinking, but it should augment that thinking and should allow actually for better thinking because it's taking us in all these different directions.
So that's how I encourage everyone to think about AI.

Perry Nightingale: I've noticed a couple of interesting things.
One is - if you would have gone to a client two years ago and said do you wanna save 20 per cent on your production next year and they would have gone, 'yeah, that's amazing'.
But now the incremental gains can be 200 times or even 2,000 times and that is pretty significant right now.
And they're mainly deliverable by people using the latest AI tools. I think as a client, there's a lot of opportunity to bring some of those costs down.

Anna Berry: I'm a planner at heart - so for me it's all about test and learn, test and learn. See where the scale is and learn from it, and then test again and then learn.
I think again the interesting area to consider will be how we prepare around the ethics of of it all.
And so test and learn in a safe environment before you scale it, I think is what we as agencies and as brands need to really take into consideration.
Yes it's about experimentation, but making sure that there are checks and balances in place. 

CS: You have picked up on governance issues as well and the use of third party AI tools. 
What kind of safeguards have you put in place for your clients? What are the ethical considerations surrounding the use of AI in advertising and media and how can they be addressed?

Anna Berry: So I think the safeguards is the test and learn, and also that we don't put anything out open at all until we have put those checks and governances in place.
We wouldn't ever build anything unless we've gone through sort of the governance of WPP legal. It's a very big team and making sure that we're doing that right.
There's experimentation across the whole area, but we are very cognizant of the impact of advertising and therefore the safeguards that we need to put in place. It's about making sure that the humans are there to kind of measure all of that.
And from a media perspective AI will help us with custom algorithms, optimisations and efficiencies but privacy is kind of front and centre of all of this.

Rob Meldrum: We are all very much in an early stage of learning.
And understanding what's the potential, but also what's out there.
And so there is a lot more for us all to learn whether that is in our daily lives or at work

Perry Nightingale: We've actually stopped the use of Midjourney [AI Image Generator from Text] and Discord [instant messaging service for gamers], with most WPP campuses having blocked these to stop people accidentally using mid-journey for client work because it is trained on non-copyright or unfair sources of data.

What I will see is that AI and its use needs a lot of human attention. I do know that Uber worked out when your battery was low, you'd pay more for your car and they had to turn that off. Our industry has been using these technologies for a long time and many of the checks and balances that have been around data from the beginning are probably fairly robust already.


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