Walking away from the launch of the DMA’s The Value of AI report earlier this month (16 June 2026), one thought stayed with me.
For the past couple of years, much of the conversation has centred on AI adoption. Which tools are organisations using? How quickly are they implementing them? Who’s ahead of the curve?
The report asks a far more interesting question… What value is AI actually delivering?
As a member of the DMA’s Customer Engagement Committee, it was encouraging to see a discussion grounded in evidence. Drawing on around 2,000 DMA award entries spanning 2017-2025, the report looks beyond adoption to understand where AI is creating measurable value for marketers and businesses.
My biggest takeaway is that AI itself is no longer the differentiator. Increasingly, competitive advantage will come from how organisations apply, measure and combine it with human expertise.
Three themes stood out for me:
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AI is proving its value, but mainly through efficiency
The report provides plenty of evidence that AI is already delivering measurable benefits.
AI-led campaigns are 40% more likely to report efficiency improvements, while a small sample of case studies showed an average 59% uplift in ROI.
That reflects what we’re seeing across the industry. AI is helping marketing teams automate repetitive tasks, accelerate content production, identify patterns in data more quickly and deliver more personalised customer experiences at scale.
In many organisations, those efficiencies are already making a tangible difference. But efficiency is only part of the story.
One of the report’s most interesting observations is that marketers are far more likely to measure AI through efficiency metrics than broader business outcomes. That’s understandable, efficiency is often the quickest benefit to realise, but it also risks underselling AI’s long-term potential.
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Better outcomes still depend on people
One finding that generated plenty of discussion at the launch was the gap between short-term performance and longer-term effectiveness.
Across the DMA Effectiveness Databank, AI campaigns generated 20% more response effects than average, but fewer brand and business effects overall.
As the report highlights through contributor commentary, this appears to be less a technology problem than a goal-setting problem.
If AI is asked to reduce cost per acquisition or improve conversion rates, that’s exactly what it’ll optimise. If organisations want AI to strengthen customer relationships, build brand value or improve lifetime loyalty, those objectives need to be built into the brief from the outset.
I was equally interested by another finding: AI-driven campaigns scored 12% lower for creativity than the wider DMA award average.
To me, that doesn’t suggest AI lacks creative potential. It reinforces the importance of human judgement.
The strongest examples in the report weren’t created by AI working independently. They combined technology with experienced marketers who understood the audience, challenged the outputs and applied creativity, context and commercial thinking.
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Better data creates better AI
One of my own reflections from the report and discussions at the launch was that AI is only ever as good as the data behind it.
Whether organisations are using AI to personalise communications, improve audience segmentation, optimise customer journeys or generate insight, success depends on having high-quality, well-governed data and a clear understanding of customers.
Poor-quality data doesn’t become more valuable because AI is involved. It just produces poor-quality outputs more quickly.
The report also makes the important distinction between AI literacy and AI capability. Many organisations now know how to use AI tools. Far fewer have embedded the governance, workflows and accountability needed to use them consistently and responsibly.
For me, that’s likely to become the real differentiator over the next few years.
Looking beyond the hype
The launch left me feeling optimistic, not because AI can suddenly solve every marketing challenge, but because the conversation is becoming more mature.
We’re moving beyond asking whether organisations should use AI, most already are. Perhaps the most valuable distinction the report makes is between efficiency and effectiveness.
AI is already proving exceptionally good at helping marketers work faster, automate processes and improve productivity. The bigger opportunity now is using AI to create more effective marketing – marketing that builds brands, strengthens customer relationships and delivers long-term business value.
That won’t happen through technology alone, it’ll require quality data, clear governance, human creativity and a relentless focus on what success actually looks like.
The organisations that succeed won’t be those using the most AI. They’ll be the ones using it with the clearest purpose.
