AI Is the New Experiential: How Digital Agencies Are Repeating the Same Hype Cycle

Let’s be clear - AI and experiential marketing aren’t the same. The scale and impact of artificial intelligence across industries like healthcare, education, and tech far outweigh even the most impressive brand activation.  But from inside the agency world, the parallels are hard to ignore. Much like the experiential gold rush a decade ago, AI has become the shiny new thing agencies are racing to sell - regardless of whether they know what they’re doing.

The Experiential Illusion / The AI Hype Cycle

Several years ago, while exploring new opportunities in the experiential space, it quickly became clear that landing interviews was the easy part - finding an agency truly delivering the kind of experiential work they advertised was the real challenge. In many cases, 'experiential' amounted to a single button triggering an on-screen animation. Despite bold positioning, few had true case studies to support their capabilities - yet nearly all were eager to pitch experiential as a core offering.

Agencies raced to claim experiential expertise, whether or not they had the ability to execute it. It was a gold rush, and clients eager to engage audiences in new ways were willing to buy in - sometimes without realising that what they were getting wasn’t quite what was promised.

Now, AI is experiencing the exact same hype cycle.

Agencies are labelling everything 'AI-powered,' regardless of whether any real AI is involved. What’s often marketed as ground breaking technology is, in reality, basic automation, an off-the-shelf chatbot, or a slightly refined recommendation algorithm that’s been around for years - or worse, something that still relies entirely on manual human effort behind the scenes.

The parallels to experiential are striking. A decade ago, agencies marketed 'immersive experiences' that were, at best, touchscreen kiosks or projection-mapped logos. Today, 'AI' can mean anything from a chatbot with a few canned responses to if/then logic inside a CMS. The surface-level branding may be polished, but the underlying work doesn’t always live up to the promise.

Just like with experiential, the key is to look beyond the flashy sales pitch and scrutinise the actual work. The agencies truly leading in AI aren’t making the loudest claims - they’re the ones delivering real, measurable innovation.

The Reality of AI Work in Agencies

True AI work requires strategic thinking, technical investment, and thoughtful implementation to ensure AI is genuinely adding value. It's about solving real problems in more intelligent, scalable, or efficient ways. 

Some clients have shown interest in AI, not because it addresses a business need but simply because it’s the current industry trend. In those moments, we’ve had to ask hard questions and, at times, decline projects that lacked a strategic rationale. The approach should always be to let the business problem guide the solution - not the other way around. That means starting with a clear understanding of the problem we’re trying to solve, rather than retrofitting a piece of technology to fit.

There is a fundamental difference between adopting AI strategically and chasing the AI trend for optics. As agencies, we are responsible for guiding clients toward meaningful implementations that create impact, rather than selling AI as a buzzword and solutions that lack real value.

How to Spot the Real AI Experts

As more agencies rush to pitch themselves as AI-savvy leaders, it’s getting harder to tell who’s actually building something meaningful versus who’s just adding to the noise.  Here are four questions you should ask of any new creative tech partner:

1. Can they show real, working examples?

Genuine AI expertise shows up in working demos, detailed case studies, or technical documentation, not just vague concepts or flashy decks. Look for real demos, prototypes, or detailed case studies. Credible teams are often eager to show how the technology works and what it delivers.

2. What problem is the AI solving?

AI isn’t inherently valuable - it’s a tool. The real question is: what does it enable you to do better than what you are using now? Is it automating a repetitive task, offering smarter personalisation, or unlocking scale in a way that wasn’t possible before? If it’s being added for novelty alone, its value is likely limited.

3. Are they overusing the word “AI”?

If every slide, sentence, or pitch revolves around the word 'AI' without explaining how it’s used, that’s a red flag. Legitimate AI use cases come with specifics - what models are being used, what kind of data is involved, and what value it’s delivering. Genuine AI implementations tend to come with transparency around methodology, data, and results.

4. Are their promises grounded in reality?

Beware of agencies pitching moonshot AI capabilities without a track record.  Ambitious visions are great - but a track record of delivery should support them. “This model will predict behaviour with 100% accuracy” is a bold claim – ask what they’ve delivered today. If they haven’t shipped real work, those future promises are just that: promises. 

Final Thoughts

The agencies doing the most meaningful work in AI are often not the loudest. They’re heads-down, building systems that work and deliver value. Just like with experiential, separating hype from reality takes curiosity, a willingness to dig deeper, and a healthy dose of scepticism.

If you’re evaluating potential partners, don’t be afraid to ask hard questions, ask the specifics on what they have done. The ones worth working with will welcome the conversation.