Reflecting on DPP Leaders' Briefing 2025: what we learned
In late November 2025, three of our team members had the privilege of exhibiting at the DPP Flagship annual event, the Leaders’ Briefing 2025, where industry leaders come together to discuss trends and what truly matters to them with great honesty and clarity.
A High-Energy Event With Real Momentum
Attendance numbers were substantial, and the floor was buzzing with conversations and curiosity around AI. What stood out most to us: even during the leader conference sessions, our stand remained active. That’s unusual: typically exhibits go quiet while talks are on. For us, it signalled a genuine interest in practical AI implementations.
It was heartening to see that many conversations at our stand weren’t just surface-level demos - they were substantive discussions grounded in real challenges and opportunities that understood that AI could solve. That suggests a shift: people now have a clearer sense of what they need, and AI could potentially meet this, so they are ready to explore real-world implementation.
What the Industry Is Saying
There’s broad agreement that AI can save time and money while also increasing productivity, allowing for the output of more content to generate more revenue faster. There are now also real-life implementations that seem to support this belief, with anecdotal evidence suggesting that everything is now ‘better’ with AI, and companies are pleased with their investment. That said, while everyone who has implemented AI has no regrets, there appears to be a lack of quantifiable evidence to support the extent to which it has actually helped them. This seems to be due to a lack of metrics gathered both before and after AI implementation, such as comparing the time and cost of manual processes with and without AI support.
I’ve had customers make it a purchasing requirement for me to confirm how much time and money it will save before they buy, but when I ask the question, “How much time/cost does it take you today?” they don't know. Currently, vendors are unable to answer these questions when business data is unavailable. This lack of statistical evidence risks slowing down adoption, as while businesses are convinced that AI will have a significant positive impact, they struggle to sign off on the investment without a way to quantify the return on that investment.
At the same time, many broadcasters and media companies are already deploying AI, but a large portion of the industry remains on the sidelines. There seems to be consensus on the need for AI but less clarity around how to implement it practically, effectively, and in a way that delivers tangible benefit.
Why This Matters
For us, the quality of conversations confirmed something we’ve long believed: the discussion around AI in media is maturing. It’s no longer about “what is AI,” but “how do we make AI work for us?” and we are aware of the key challenges they need to overcome and why our solution was the right approach for their use cases, which is a leap forward from last year.
As an industry, the next step must be more disciplined: businesses need to start measuring and reporting impact and sharing these with AI vendors so they can consolidate and start providing tangible evidence.
Things like time-saved, cost reduced, resource freed, time to profit, increase in productivity, increase in revenue. Once we build consistent metrics and use cases, adoption won’t just be about an obvious benefit; it will be about a proven return on investment. For companies still on the fence: there’s no better time than now to explore AI, ask the hard questions, partner with experts, and pilot solutions.
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