Mo Rafferty (Conlin)

If you couldn't make it to Las Vegas for #CES2026, ADWEEK just published the highlights from my conversation with Jenny Rooney. 👉 https://bit.ly/3NmAiai In the piece, we preview the AI Disruption Index, Moloco’s new research with Boston Consulting Group (BCG), which maps 15 industries into four strategic realities. When 75% of consumers believe LLMs help them find better deals than they can find on their own, AI isn’t just optimizing discovery. It’s replacing it entirely. With the AI Disruption Index, we wanted to give brands a clear, data driven way to understand their exposure to AI driven disruption, based on the strength of their customer relationships. Check out the article for the initial breakdown, but stay tuned for the deep dive when the full report releases on January 21st. #AIDisruptionIndex #MarketingStrategy

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Most metrics will tell you what your campaign delivered. But attention is the metric that finally tells you why it worked. The new mCanvas × Lumen study takes the conversation far beyond clicks and vanity metrics. It clearly demonstrates how high-attention environments drive stronger recall, deeper consideration, and higher intent — the outcomes that genuinely move the needle for brands. A big congratulations to my amazing team at mCanvas (Roshni Verma Shubhangi Kale Ryan Dsouza Tariq Nahas Meghna Soni Abhilash Krishnan) and our partners at Lumen Research for bringing this research to life. Truly proud of the depth and clarity this adds to the attention narrative. Link in the comments 👇 #AttentionEconomy #BrandImpact #MediaEffectiveness #AdTechInnovation

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AI's 2026 ROI reckoning starts now. In our first episode of The Hidden Future of AI, our forecasters deliver the three hardest truths every Enterprise leader must face to survive this pivot: 1. The great AI ROI reckoning: If you can't show business impact in three to six months, you're done. 2. The rise of true autonomous agents: Agents now make decisions and adapt without a human script. 3. The forward-deployed engineer Boom: FDEs will be the highest-paid talent for integrating AI with legacy systems. This is one of four sessions in The Hidden Future of AI series. Discover the full series and register now > https://gag.gl/dcErT3

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Had a great time chatting with Camille Ricketts and Mada Seghete about where AI is driving impact for Marketing teams, especially those targeting technical audiences. The fundamentals haven’t changed. Developers still want authentic, helpful content vs. the hard sell. Now we just have more tools to help them faster. Check out their full series - they have an awesome lineup of speakers on deck from a range of backgrounds and companies.

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I've spent about a decade deeply understanding Apple's approach to product design, usability and all the things since spending time at Flurry Analytics, which saw app usage **every day** on 2 billion smartphones, most of them iPhones. I had unusual access, and it was pretty cool if I'm being honest. Anyway, their approach to layering in AI is very "Apple" which means they have to consider myriad use cases on a massive existing multi-product surface area and they will not rush into it. Remember, Apple is a hardware company first which means they "measure twice and cut once" (maybe even three times). In complex production with massive supply chains, you're working multiple years out, so little problems become existential problems. For people who do "run-and-gun" fast cycle iterative software work, it's very, very different. So it doesn't surprise me that they're first looking for the intersections where AI can add outsized, obvious value and layering those experiences, first, in a slow and measured way. At the same time, a hardware-first company, they are not going to have the leading AI lab building the most cutting edge models. In the early days of AI, they will need that trust, however, as users are experiencing what LLMs can do for the first time through Apple products. And that experience needs to deliver.

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Every CMO I talk with right now is juggling AI pilots, brand risk, compliance drag, martech sprawl, and relentless ROI pressure. The experimentation phase is over. The operating model is changing. AI is table stakes. A creative multiplier is the edge. The real shift is moving from platforms with AI bolted on to an AI-powered creative operating system that helps teams actually create, ship, and scale work faster. This is the future Canva is building toward. On March 11, we’re bringing AI Vision to Spring Studios in NYC. 🗽 Join a room full of the people building what modern creative and marketing teams will run on next. Cameron Adams — Co-Founder & CPO, Canva Ashley Kramer — VP Enterprise, OpenAI Stefano (Stef) Corazza, PhD — Head of AI Research, Canva Alejandro Matamala-Ortiz — Co-Founder & CDO, Runway Jenny Wen — Product Design Lead, Anthropic …and more. If you’re rethinking how your team creates and operates in the AI era, this is the room to be in! Spots are limited: https://lnkd.in/dHsGhahU

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Rand Fishkin just mass-published research that should make every CMO rethink their AI visibility strategy. His team ran the same prompts 100 times across ChatGPT, Claude, and Google AI. The finding? Less than 1 in 1,000 chance of getting the same list of brand recommendations in the same order twice. If you're paying for reports that say "Your brand ranks no.3 in ChatGPT for this query," you're paying for noise. But here's where it gets interesting. I believe Rand went into this research trying to prove that ALL AI tracking was a waste of money. He came out with a more nuanced conclusion: ranking position is meaningless, but visibility percentage is statistically valid. When Bose showed up in 77% of headphone recommendation responses while competitors appeared in 38%, that gap represents something real. It tells you which brands are in the AI's consideration set and which ones aren't. LLMs are probability engines by design. Yes, you can go ahead and ask Claude or ChatGPT about it and they'll confirm that every response is a weighted lottery drawn from training data and retrieved sources. There is no "true ranking." There's only frequency of appearance. So what does this mean practically? - Stop chasing position. "We moved from # 5 to # 3" is not a real metric. - Start measuring share of voice. How often does your brand appear when someone asks about your category? That's the number that matters. Interrogate your AEO/GEO vendors. Ask them how many prompts they're running per query cluster. If it's less than 60, the data isn't statistically meaningful. If they can't explain their methodology, walk away. Rethink what "optimisation" means. You can't game an LLM like you gamed Google in 2016. AI visibility comes from being present everywhere the model learns from: earned media, Reddit threads, review sites, case studies, podcasts, third party mentions. It's brand building, not technical SEO. The companies winning in AI search are the ones showing up consistently across the sources that feed these models. Full research from SparkToro linked in comments. Worth the read.

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