It’s been a month since Google’s GML event, and I’ve been reflecting on what it really means for our industry. This time, it feels like we’re standing at a genuine inflection point. AI isn’t just becoming embedded in the platforms we use; it’s actively reshaping how people find information, research, and make decisions in their daily lives.
The GML Event: Why This Time Feels Different
AI has been a talking point in marketing circles for years, but much of it felt like buzz. True, machine learning has long been a part of Google Ads, but this feels different. Now, AI is changing not only how we ask questions, but, crucially, where we ask them. This shift has profound implications for paid media strategists.
From Buzzword to Behaviour Change
The customer journey no longer starts or ends where it used to. As AI-driven platforms and LLMs (large language models) become more common, consumers are discovering brands and making decisions in entirely new arenas. It’s clear: AI is impacting daily behaviour, altering where and how attention flows.
Rethinking the Paid Media Playbook
For paid media, this means we need to flip the narrative. It’s not just a story of automation and efficiency—it’s a call for adaptation. Yes, smarter decision-making is part of it. But it also requires a total re-evaluation of our investment strategies. Google’s desktop search engine market share is the lowest it’s been in years, and social platforms are on the rise. And with LLMs integrating ads, the landscape is only getting more fragmented.
Chasing Attention, Not Just Keywords
We need to focus less on “which keywords should I enable?” and more on the fundamental questions:
- Where is audience attention flowing?
- What’s driving their intent?
- Which platforms align best with your objectives?
- How are people now researching and making purchase decisions?
Paid media isn’t just about turning on campaigns anymore. Today, it’s about following where intent and attention exist—and having the tools to measure and act on them.
Measurement in a Multi-Touch World
The classic last-click conversion model doesn’t cut it anymore. Measuring impact in a world where discovery is dispersed means embracing new tools—like META’s search lift or Google’s Causal Impact. Start small if you need to, but start. If you don’t assess the full journey, you’ll keep over-investing in the same old channels.
From Precision Marketers to Predictive Marketers
Our roles are evolving. Once, we could peek inside Google and Meta’s black boxes—remember the “average position” metric? Now, we’re in an era where the data we feed to the machine is just as important as the strategy itself. We’re no longer just precision marketers; we’re becoming predictive marketers.
Feeding Smarter Signals for Bigger Impact
Ask yourself:
- Are you using first-party data to its fullest potential?
- Are those signals truly connected to your biggest business goals?
- Is your creative consistent across all media, not just paid search?
- Are you tracking softer conversions (like micro-engagements or considered actions)?
A key idea that’s stayed with me: Bid strategies optimize for a user they think will convert. The keywords here are “think” and “signals.” If we want AI to drive real business impact, we must ensure our signals are deep, meaningful, and outcome-aligned.
Getting Started: Practical Steps to Adaptation
- Audit your platform mix—does it still fit modern attention habits?
- Expand your measurement approaches beyond last-click.
- Start aligning creative and messaging across all touchpoints.
- Test attribution tools and multi-touch reporting.
- Encourage your teams to challenge legacy metrics and processes.
None of this is about abandoning Google or any other platform. Instead, it’s about evolving with the ecosystem: being open to new signals, investing in new touchpoints, and adapting measurement to capture real impact. The pace of change is intimidating, but more exciting than ever.
Let’s keep pushing the boundaries, learning from every shift—and bring the best of GML’s AI-powered initiatives into our everyday work.
