By Katie Herzog – Chief Client Officer
Why marketing teams need a new standard — and why leaders should expect more from their agencies.
Every few years, marketing gets a new “make or break” moment. Search. Social. Mobile. Now, it’s AI.
This time is different, though. AI isn’t just changing what we make. It’s redefining how we work, the value of that work and what modern agencies must become to lead their clients forward.
One of the first bold assertions coming out of the generative AI revolution is that the agency model is dead. There are dozens of tools claiming to replace agencies and the people that support an organization’s marketing discipline. And it’s true: AI can replace a lot of the rote executional work that has kept creative, account service and media departments busy in the past.
But anyone who believes that AI can fill the role of an agency misunderstands the real value of a marketing partner: not execution, but orchestration. True, reliable execution matters. The real advantage of an agency is its ability to make complex things work — to apply strategy, creativity and business logic in ways internal teams can’t always reach on their own.
From here on out, the job of any marketer is simple: make AI work. And the job of any executive is just as simple: Make sure your agency actually knows how.
Five AI-focused characteristics of leading agencies.
Google and Boston Consulting Group recently completed a study that identified key characteristics of agencies that are excelling in AI. This research offers a blueprint for understanding where an agency sits on the AI maturity curve and what your organization should expect if your partners are truly ahead of the curve. Here’s what the best agencies are already doing:
1. Actively upskilling talent, turning curiosity into capability.
Accenture’s recent restructuring around AI fluency sent a clear message: skills are the new strategy. They exited 11,000 workers who could not be upskilled fast enough for AI adoption. Salesforce slashed the size of their customer support teams in favor of AI agents. As CEO Mark Benioff said, “I’ve reduced it from 9,000 heads to about 5,000, because I need less heads.”
“Skills are the new strategy.”
The agencies leading the AI wave aren’t waiting for specialists to appear. They’re building them — creating internal AI labs, hosting weekly ‘prompt practice’ sessions and training teams to use AI as a thinking partner rather than a task rabbit. The gap between those who experiment and those who operationalize is widening fast.
2. Powering AI models with owned data.
Without clean, connected data, AI is a parlor trick. And while getting to that data might be the biggest business challenge of the decade, great agencies can take even a little bit of data and make it go a long way. Data is what builds the bridge between predictive intelligence and generative creativity.
Predictive models can help define ideal customer profiles (ICPs), anticipate performance and uncover untapped opportunities. Generative tools take that insight and bring it to life through data-driven campaign plans, recommendations for core messaging and the ability to personalize campaigns at scale.
A common workflow looks like this: Use owned data to build data-based ICPs, evaluate any in-progress creative against those profiles, then use AI to optimize or generate new assets that more directly reflect what matters to those audiences.
If getting all your data aligned is a long-term project, you can start where you are. Use your CRM, analytics and customer surveys to fuel predictive models. Then pair them with tools like ChatGPT, Jasper or Midjourney to tailor messaging and creative that feels customized to your individual audience.
When your data and creativity start talking to each other, your marketing stops guessing and starts growing.
3. Expanding, not replacing, creativity with AI.
AI shouldn’t shrink creativity — it should stretch it. But even with all that acceleration, one truth remains: machines can’t replicate the parts of communication that give it meaning.
We’ve already seen AI used for inspiration (“give me ten campaign ideas”), persuasion (prototypes that sell through faster) and multiplication (versions of assets in seconds). With all of this work happening, why do we keep talking about “human at the center” in our AI work?
Meaning comes from the human elements AI cannot replicate — values, cultural nuance, ethics, subtext, taste and social responsibility. A future where AI handles the heavy lifting still requires humans who can interpret it.
The most forward-thinking agencies are blending machine efficiency with human discernment. They may be replacing some brainstorms with bots, but they’re still relying on humans to create connection.
4. Incorporating AI into daily workflows: valuing integration over experimentation.
AI can’t live on an island. If it doesn’t integrate into real workflows, it won’t change anything.
The agencies that thrive with AI operationalize it. They build custom GPTs aligned to their strategy frameworks, use agents to summarize client threads, automate research and reporting and create repeatable ‘AI rituals’ that raise the floor on quality and the ceiling on speed. That’s the difference between teams who dabble in AI and teams who transform because of it.
5. Measuring outcomes instead of outputs.
As AI accelerates execution, time no longer equals value. Work is not about how many hours we spend, it’s about how much impact we make. And the KPIs span across marketing disciplines:
- In our people, we used to value capacity; now we need to evaluate based on an individual’s adaptability.
- In media, we celebrated quantity. Impressions, leads, reach, frequency. In the new media world, the metric is precision. We’re trading talking a lot for communicating with the right people.
- In our creative ideas, we’ve historically celebrated the number of concepts generated. After all, who didn’t love to see a whole bunch of creative ideas? As AI commoditizes brainstorming, breakthroughs will become the new creative currency.
In an AI-accelerated world, agencies shouldn’t charge for the hours they spend. They should charge for the difference they’re able to make.
The real shift: from output to orchestration.
Agencies that win with AI don’t sell execution. They deliver orchestration — the ability to connect data, tools and talent into something intelligent and human.
Curious how E&S is making the shift from AI-powered to AI-integrated? We’d love to show you what that looks like in practice.