You scanned. Good move!
Everything I referenced on stage at COMAR 2026, in one place. The research, the videos, the TASTE prompt card, the four moves you can run on Monday.
No LinkedIn request required. Take what is useful.
The talk, in three lines
AI should disappear into your invisible work. Your taste has to show up in the visible work. The trick is knowing which is which.
1. Invisible work is AI's job.
Data synthesis, personalisation, A/B testing at scale, optimisation, tagging, translating. Anything no human team could do at this speed.
2.Visible work is yours.
Brand voice, creative direction, cultural context, judgement, reading the room. The work your name goes on.
3. Decision science is the muscle that makes taste reliable.
Taste is the instinct. Experimentation is taste, operationalised.
If you take one thing away: AI makes your judgement more important, not less.
The TASTE prompt card
Exercise taste before you prompt, not after.
➡️Download your TASTE card here
The AI Confidence Ladder
Where are you today? Pick the rung. Pick what moving up one looks like next quarter.
1. Avoidant — "I don't use AI." (Riskier than it feels.)
2. Anxious — "I use it, but I second-guess everything."
3. Aware — "I know which tasks are invisible vs. visible."
4. Author — "I design prompts and checkpoints that bring my taste into the system upstream."
5. Architect — "I've built our processes, metrics, and hiring around the judgement we want to protect."
Four Mondays, four moves
The toolkit, in order:
Monday 1 - Run your first TASTE review. Take 3 AI outputs from last week. Score them against T-A-S-T-E. Where you score low, you now know why the output was average.
Monday 2 - Pick one workflow and redesign it invisible-first. Whiteboard it with the team. Anything invisible you're still doing by hand? Automate. Anything visible AI is doing for you? Take it back.
Monday 3 - Pick your first experiment. What does your team believe to be true that you've never tested? Pre-register your taste before you run it. Test causation, not correlation.
Monday 4 - Audit your team against the Ladder. Then swap one usage metric for a confidence metric. Replace "% of team using AI weekly" with "% of AI outputs that pass team TASTE review on first attempt."
The videos I played on stage
These are the clips, in the order you saw them. Worth watching again — or sharing with the colleague who didn't make it.
The face of our industry right now.
Waymo passenger reaction reel, a little delighted, a little terrified.
InstagramBrené Brown on AI hallucinations.
60 to 70% of the sources her team's AI returned were fabricated, confidently. Skip to ~1:02:38.
The Curiosity Shop with Adam Grant · Apple PodcastsAbout ADC
ADC is a boutique data and AI consultancy. We have decision science, design, and AI engineering in one team — and we work end-to-end across strategy, design, and delivery.
We help data-driven leaders turn ambition into action, especially in the high-stakes moments where the margin for error is small and the consequences of being wrong are real. Translated for today's talk: we help marketing teams put AI to work on the invisible stuff and sharpen the visible stuff. Without losing what makes their marketing good.
Want to chat?
If anything in the talk resonated, or you've got a marketing problem you'd like to talk through, please leave your details and I'll be in touch.
Leave your details. I read every one.The research, with receipts
Everything I cited, with the actual papers underneath. Clickable, in case you want to send a colleague the source instead of a screenshot of my slide.
On the payoff of doing this well
On invisible work, done well
- Abboud et al., "Agentic Personalisation at Scale," arXiv, June 2025. The 150M-user system behind the airline / retail example.
On why visible work is your moat
- Stefano Puntoni, "AI Is Upending Marketing on Two Fronts," Harvard Business Review, 23 February 2026 (Reprint H0931I). The Stack Overflow vs. Reddit chart, plus SEO → GEO and AI agents as buyers.
- Del Rio-Chanona, Laurentsyeva, et al., on Stack Overflow traffic after ChatGPT launch.
On taste as the new superpower
- Michael Schrage & David Kiron, "Philosophy Eats AI," MIT Sloan Management Review, 16 January 2025 (Reprint 66311). The Gemini image-generator story as a judgement problem, not a data problem.
- The Economist, "Is Google's Gemini chatbot woke by accident or design?"
- John Maeda, Design in Tech Report 2026: From UX to AX. The "design as evaluation" line.
- Elizabeth Goodspeed, "AI Can't Give You Good Taste," It's Nice That.
- Shlomo Genchin, The Creative Marketer newsletter — the side-by-side ad breakdowns I referenced for creative taste.
On decision science and experimentation
- Zalando data science team, "Marketing A/B Testing at Zalando."
- Think with Google, geo-experimentation guidance, March 2026.
- Google Ads Help, incrementality testing, November 2025 (the $100k → $5k cost drop).
- Google / BCG Global Measurement Survey, 2025 (the 80% of senior analytics leaders stat).
On the cognitive cost of doing this badly
- Bedard, Kropp, Hsu, Karaman, Hawes & Kellerman, "When Using AI Leads to Brain Fry," Harvard Business Review, March 2026. BCG survey of 1,488 US workers. Marketing tops the brain-fry chart at ~26%. Productivity peaks at 2-3 AI tools, then falls.
On where the labour market is heading
- Ana Elena Azpúrua, "Research: How AI Is Changing the Labor Market," HBR, 4 March 2026 (Reprint H092X3) — based on Suraj Srinivasan et al., "Displacement or Complementarity? The Labor Market Impact of Generative AI." Highly automatable postings down 13%; AI-augmented postings up 20%.
- Sam Ransbotham, David Kiron, Shervin Khodabandeh, Sesh Iyer & Amartya Das, "The Emerging Agentic Enterprise: How Leaders Must Navigate a New Age of AI," MIT Sloan Management Review & BCG, November 2025.