Utilize AI and Maximize Our Teams' Efficiency by Automating Repetitive Tasks

There’s been a lot of discussion recently about AI's impact on the agency model.

Some say we’re being automated out of existence; others see a new era of creativity and efficiency. I believe the truth is in between, with opportunities far outweighing risks. 

AI won’t make good agencies irrelevant, but it will challenge traditional agency roles. Routine, repetitive tasks filling many retainers—reporting, campaign setup, spend management, account hygiene, commentary—are all versions of the same analysis, much of which needed improvement anyway.

Accepting this change shifts the focus to what agencies like ours choose to become.

At Vervaunt and across IDHL, that’s an important conversation—not because it’s easy, but because it pushes us to deliver value with greater determination.

We've Been Here Before

When I started in paid search, much of the work was manual optimization. We built teams to manage keyword structures and copy needs while applying detailed bid adjustments at the keyword level.

Today, machine bidding outperforms manual methods, with Google’s systems making optimization decisions at scales unmatched by humans. The same applies to social media. Previously, we spent days defining audiences and interests for brands. Now, platforms like Meta can often find the right customers as effectively as we did.

We are entering a new wave of automation becoming standard practice.

Next steps: campaign setups, reporting, account maintenance, performance commentary, and routine analysis are also moving toward automation. AI and modern technology increasingly handle lower-level agency work.

This layer of agency work is quietly being redefined by machines, and it won’t exist the same way in the future. So, what replaces it?

Automation Isn’t the Threat—Failing to Increase Your Value Is 

It’s not about doing the same work faster or more often. Speed matters only if it improves decision quality, spend efficiency, or commercial results—and that’s not guaranteed. 

The time freed from low-value tasks should be reinvested in areas where agency expertise is harder to replicate: judgment, strategy, creativity, commercial insight, and integrated thinking—the true sources of agency value. 

If your revenue relies on manual optimization, you likely face challenges. But if your value lies in understanding growth across media, product, customer experience, data, and margin, your future looks promising.

Agencies are expanding beyond traditional paid media management—evaluating total eCommerce profitability, optimizing for products with higher LTV, accounting for returns. As international trade grows, entering new markets via paid channels remains a core focus. With increasing spend on Meta and Google, measurement, attribution, and incrementality matter more than ever. Agencies already offer much beyond platform management, and AI will accelerate this progress. 

Creative Will Evolve Dramatically Across Multiple Dimensions 

As platform automation takes on more account management, ad build, and optimization tasks, creative becomes the key performance differentiator.

We’ve always valued great creative impact (whitepapers and case studies with Meta), and now we collaborate more with internal brand and content teams to analyze data and insights—understanding which creative ideas drive results, identify fatigue, discover effective messaging, and shape future content through performance data. 

A major shift recently is brand ATL merging with traditional digital marketing and eCommerce. Brand teams increasingly allocate budgets to social and need agency guidance to maintain brand aesthetics and tone while adapting to changing consumer content consumption. Brand campaigns have transitioned from photography shoots to frequent, diverse mobile-focused content designed to capture attention.

Alongside industry trends, AI will profoundly influence creative design, production, and optimization in coming years. We’re already seeing tools that produce high-quality content, with several clients approving AI-generated materials. Expect major advances where agencies must lead. 

Paid media optimization extends well beyond the click

Another positive trend we're observing is a much closer collaboration between ecommerce, CRO, and paid media.

In the past, there was a clear handoff: one team drove traffic, another handled what happened after. That separation is becoming less relevant today.

Growth now depends on understanding the entire journey: media strategy, landing experience, product page, checkout, offer, margin, return rates, LTV, and more. None of these fit neatly into one channel; siloed work and thinking only hold you back.

This is where Vervaunt’s role and the broader IDHL ecosystem become more valuable. Paid specialists can’t be just media buyers now. They must grasp onsite experience, challenge user journeys, and link performance to the business model. We focus heavily on this, working with brands to dynamically tailor user experiences based on origin—for example, new social prospects see more aspirational, TOF content. 

Better questions outperform bigger dashboards

More budget flows through platforms like Meta than ever, but chasing superficial efficiency is the wrong game. A campaign may look good on paper but still misallocate funds once all factors are considered. Agencies must dive deeper into data beyond standard dashboards to act more like brand, marketing, and business analysts.

Which products attract higher-value customers? Which categories convert but erode margins? Where do returns skew performance views? Which regions have low acquisition costs but weaker commercial value once fully analyzed?

AI can speed up finding answers—but only if we know the right questions and expected results.

These metrics would encompass broader business data—set apart from attribution and incrementality concerns. 

Technology is integral to the agency offering

Looking ahead, every serious agency will use their own data combined with AI to create unique client value.

At IDHL, a prime example is Vantage, our in-house performance intelligence platform. It’s built on a semantic layer across vast analytics datasets, enabling queries tailored to clients’ specific needs. Within seconds, we can find average day-over-day revenue changes in November to guide promo timing. We track CAC, platform cost shifts (like World Cup effects on the US), and compare a client’s jeans return rates against others.

Owning our technology means we don’t view client accounts in isolation; we spot macro patterns and behaviors across relevant larger datasets, faster.

AI-driven tools like this change conversations. Instead of weeks compiling data, we use tech to ask better questions.

The goal isn’t another flashy dashboard (the world has enough). It’s to equip teams with context and evidence for sharper advice, delivering clear client benefits.

Starting an agency today

One of the top questions my cofounder Paul and I get is, "If starting an agency from scratch today, what would it look like?"  
 
My answer is what we’re building now: a multidisciplinary growth specialist linking media, creative, data, commerce, and profitability.

I'd also prioritize technology from day one. Agency tools, workflows, and systems are no longer just internal; they’re increasingly part of the client experience. Direct platform integrations, clean data, automation, and smart agents will only grow in importance for consistent, scalable delivery.

At Vervaunt, we’re well along this path, with direct integrations across all media platforms enabling data pulling and pushing changes. We automatically adjust based on performance shifts and real-time data—for example, budget changes based on COS or MER.

We also automate issue detection and internal audits. When industries undergo technological shifts, two opportunities arise: 

One is simply leveraging innovations to scale faster and cheaper—like fast food’s evolution focusing on cost reduction rather than product improvement.

The other is drastically enhancing what you deliver through technology. Apple exemplifies this. We invest about 80% of our time on new initiatives adding more value than before.

Looking ahead, agency services will consolidate. AI can build landing pages, run tests, create new creatives, and build campaigns, reducing niche skill demand. Value will be in teams mastering all these areas and managing them holistically. This is a long-term view, but I don’t see roles for paid-search-only specialists; their scope will widen to add value beyond campaign activation and analysis, challenging onsite content and briefing more.

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 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 what our clients value most. In many cases, it’s the work that got in the way of spending more time on strategy, creative, journeys, insight, and commercial accountability.

The changes AI brings 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 part will quickly become normal. The useful part 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.