Utilise AI and maximise our teams efficiency automating repeated tasks

There’s been plenty of talk over the past couple of years about what AI means for the agency model.

Depending on who you ask, we’re either being automated out of existence or at the dawn of a new age of creativity and efficiency. Personally, I think reality sits somewhere in the middle, but the opportunities far outweigh the risks. 

First of all, AI is not about making good agencies irrelevant. It is, however, going to make a lot of traditional agency work harder to justify. The critical but repetitive low-level tasks that have filled plenty of retainers for years are being stripped away. Reporting, campaign build, spend management, account hygiene or commentary are all versions of the same analysis, and much of that work needed to be improved anyway.

So, if you can accept that change is happening, the conversation becomes centred on what agencies like ours choose to become.

At Vervaunt, and across IDHL, we see that as a good conversation to have. Not because it makes our life easier, it doesn’t, but because it forces us to focus on providing value with even more determination.

We've been through this before

When I first started in paid search, a huge amount of the job was manual optimisation. We built teams to manage keyword structures and copy requirements, whilst assessing and applying granular bid adjustments and keyword level bids.

Today, machine bidding has long outperformed manual bidding and Google’s systems can make optimisation decisions at a scale no human team can match. The same is true across social. A few years ago, we would spend days working with a brand to define audiences, map interests, and build detailed targeting structures. Now, in many cases, platforms like Meta are just as good at finding the right customer as we ever were.

We’re clearly going through a new environment of automation. These are simply the first wave of automation becoming the new normal.

We are now moving into the next wave: campaign builds, reporting, account maintenance, performance commentary and routine analysis are all moving in that direction. Ultimately, AI and modern technology will be the drivers behind the lower layers of agency work being automated.

The lower layer of agency work is being quietly rewritten by machines. And if we are honest, it's unlikely any of that work will exist in the same way in the future. So, what replaces it?

Automation isn't the threat. Not increasing your value is 

The answer is not “doing the same, just more of it or faster”. That is useful, but speed only matters when it improves the quality of the decision, the efficiency of the spend, or the commercial result, and that isn't guaranteed. 

The opportunity that removing low-value effort activities provides is to reinvest that time in the areas where agency expertise is harder to replicate, Judgement, strategy, creativity, commercial understanding, and joined-up thinking is where the real value of an agency has always come from. 

If your model depends on revenue from manual optimisation, you probably do have a problem. But if your value comes from understanding how growth actually happens across media, product, customer experience, data and margin, then I think you'll have a much more interesting future.

Agencies are already massively enhancing their offering from traditional paid media management. Agencies now assess full eCommerce profitability, optimises towards products which drive higher LTV, account for returns. International trade continues to grow and entering new markets via paid channels has been a core focus of our agency over recent years. With more and more media spend going into Meta and Google; measurement, attribution and incrementality are more important than ever. Agencies today are already offering much more than in-platform management, but this will progress much quicker with AI. 

Creative will continue to massively evolve across many facets 

As platform automation takes on more of the account management load, ad build and optimisation work, creative becomes the key differentiator for performance.

We've always championed the impact of great creative (whitepapers and case studies with Meta) but we're now spending more time working in partnership with internal brand and content teams to drill into the data and insights and understand which creative ideas are really driving results, where fatigue is setting in, what messages are moving customers, and how performance data can shape the next round of content. 

A major shift over recent years is brand ATL merging with traditional digital marketing, and eCom activity. Brand teams are spending more and more budget with social and there is a huge need to agencies to consult and advise on brand ATL content, keeping aesthetic and brand TOV whilst accounting for shifting consumer content consumption. Brand teams have gone through a major transition of campaign, photography shoots – to content now needing to be diverse, frequent, shot for mobile and produced to capture attention.

Alongside all of the broader industry trends – AI will have massive implications on creative design, production, and optimisation over coming years. We’re already seeing tools produce incredibly high quality content, with a number of our clients signing off AI produced content. Expect huge developments in this space – where agencies will need to be at the forefront. 

Paid media optimisation continuing well beyond the click

Another positive change we're seeing is a much closer relationship between ecommerce, CRO and paid media.

Historically, there was a fairly neat handover. One team drove traffic and another worried about what happened when the user got there. That separation makes less and less sense today.

More than ever before, growth comes from understanding the entirety of the journey. That means the media strategy, the landing experience, the product detail page, the checkout, the offer, the margin, the return rate, the LTV, and much more. None of those things live neatly inside one channel so siloed working and thinking can only hold you back.

This is where Vervaunt’s role, and the wider IDHL ecosystem, becomes more valuable. Paid specialists cannot only be media buyers. Today, they need to understand the onsite experience, challenge the user journey and connect performance back to the commercial model. This is something we are doubled down into where we have worked with brands to dynamically enrich the user experience based on where they came from e.g. new prospects from social see more aspirational, TOF content. 

Better questions beat bigger dashboards

More spend than ever is flowing through platforms like Meta, but chasing surface-level efficiency is the wrong race. A campaign can look healthy on paper and still be sending budget in the wrong direction once you factor in all the other variables. That means agencies need to get closer to the numbers behind the numbers and look beyond traditional dashboard metrics to become more like brand, marketing and business analysts.

Which products are driving higher-value customers? Which categories convert well but hurt your margin? Where are returns distorting the view of performance? Which regions offer lower acquisition costs but are weaker commercially once the full journey is understood?

AI can help us get to the answer faster, but only if we know what to ask and what the answer should be.

These would simply be metrics encompassing wider business data – without all of the consideration around attribution and incrementality. 

Tech is part of the agency product

In the future, I think every serious agency will be using their owned data combined with AI to create unique client value.

For IDHL, one of the clearest examples is Vantage, our in-house performance intelligence platform. It's built on a semantic layer across a huge dataset of analytics accounts, allowing us to interrogate multiple datasets in ways designed around our clients and their specific needs. Within seconds we can ask for our avg. Day on day revenue change in November to help inform promotion timings. We can see where CAC costs, platform costs are changing (whether World Cup inflluences US etc) as well as how your clients returns on jeans compare to all our other clients.

Developing our own tech also means that rather than looking at a client account in isolation, we can see relevant macro patterns, shifts and behaviours across a larger and more relevant dataset and in much less time.

AI-based tools and technologies like this change the nature of the conversation. Instead of spending weeks pulling data together, we’re using the technology to find the right questions.

The point is not to build another shiny dashboard (the world has enough dashboards). The point is to give our teams better context and evidence, so they can make sharper recommendations, and our clients see the direct benefits.

Starting an agency today

Probably one of the questions my cofounder, Paul, and I get asked the most is "If we were building an agency from scratch today, what would it look like?"  
 
My answer is I would build what we're building today; a multidisciplinary growth specialist who understands how media, creative, data, commerce and profitability connect.

I would also prioritise technology from day one. The tools, workflows and systems an agency uses are no longer just internal infrastructure. They are increasingly part of the client experience. Direct platform integrations, clean data structures, useful automation and intelligent agents will only become more important to how agencies deliver consistently and at scale.

At Vervaunt, we’re a decent way down this road, including direct integrations across all media platforms allowing us to both pull data but also push changes. Automatically pushing changes through based on major performance changes, real time data e.g. adjusting budget based on a COS, MER.

Also includes more basic flagging issues – automating a lot of our internal auditing processes. One reference I like is when industries go through massive technological innovation – generally there are 2 opportunities. 

One to use simply capitilise on the innovations and do more of your work quicker and to a wider scale. Essentially today’s offering at a lower cost. You’ll see non-service based sectors often progress this way – fast foods evolution has been on lowering cost as opposed to massively enhancing their product.

The second option is for the business to massively enhance what they can drive following the technological advances. Apple would be a more relevant example here. As I’ve mentioned above – agencies are constantly looking to create more value. In the last 4 years alone – I would comfortably say our team spend 80% of their time on new initiatives which add more value than prior.

If I had to take an initial stab at where agencies will become, I see services becoming massively consolidated. This is further down the line but when AI can build landing pages, run tests, create net new creative, build ad campaigns, the specific skillset somewhat lessens. Value lies in a team understanding all of these areas and their capability to manage simultaneously together. This would be a longer term view – but I don’t see a role for a paid search only specialist. Their remit will be much wider where they can add more value beyond simply campaign activation, analysis aspects. They will need to challenge onsite content and would have the ability to brief more here.

Governance isn't optional

Of course, more automation creates more responsibility. So, if agencies are going to automate more of the work, clients need to understand what's being automated, why it's being automated, and where human oversight sits.

All of that means governance can't be treated as an afterthought. We need clear standards for how AI is being used, what data is involved, what gets checked, what gets signed off, and where the limits are. Clients need to know the clearly how an agency relies on AI, and not be left guessing whether a recommendation came from a person, a model, or a mix of both.

Across IDHL Labs, this is a big part of how we think about applied AI. Our goal isn't to automate everything we can, just because we can. The aim is to define the right challenges, understand the opportunity and the risks, and make informed decisions that benefit the agency and our clients, with the visibility every stakeholder needs. 

We think that's a more useful ambition than chasing novelty or making claims that fall apart the minute someone asks to look under the hood.

Making ourselves the most useful agency

AI will automate a fair chunk of agency work, and there's no point pretending otherwise. But the work being automated is not the work our clients value most. In many cases, it's the work that got in the way of us spending more time on strategy, creative, journeys, insight and commercial accountability.

The changes AI brings about won’t be felt equally. Every agency will use AI, so adoption won’t be a differentiator. I like the analogy of an agency promoting that they use Excel well.. AI will be an expectation in many areas.

It’ll be a question of whether they use AI to protect the old model, and do the same work faster and cheaper, or to get better at what clients care about: strategy, creative, and commercial outcomes. The automation bit will quickly become normal. The useful bit is where the real value will be.

So yes, AI is coming to shake up our agency model. At the end of the day, the future of agency value was never going to be found in doing more of the same. Like every industry shift we've seen, success will come from being commercially useful and responsible for the outcomes clients expect.

If that’s the agency model of the future, we’re good with that.