Who Owns AI Visibility?

Listen to the Podcast

In this Kitchen Side episode of The Long Game Podcast, Alex Birkett and the team unpack a question that’s coming up more and more: who actually “owns” being found in AI search—and what AI visibility means for modern marketing teams. They explore why the “AI is killing SEO” debate misses the point, and how AI search is collapsing traditional channel boundaries while changing how buyers discover brands.

They also dig into what’s actually being cannibalized (undifferentiated, consensus content), how teams should rethink success metrics as clicks get harder to track, and what the velocity vs. quality debate looks like now—especially as some teams bet on subject-matter depth while others bet on scaled output with AI-assisted production.

Key Takeaways

• AI isn’t “killing SEO” so much as reducing the value of undifferentiated, consensus content that used to earn easy traffic.
• Losing traffic doesn’t automatically mean losing business value—teams should validate impact through conversions, leads, and pipeline, not sessions alone.
• AI visibility is increasingly a composite outcome of everything a company publishes and does (content, comms, brand, product, reviews, community, and customer experience).
• Measurement is getting harder as discovery shifts to “dark” channels (e.g., AI tools) and attribution breaks—teams may need new proxies and self-reported attribution.
• “Listicles dominate AI citations” may be partly a prompt and sampling bias problem—inputs strongly shape outputs and visibility reporting can be manipulated.
• The hardest visibility problem is higher up the funnel: influencing problem-aware searches before buyers even know what category or solution to ask for.
• Content teams are splitting into different bets: deep, SME-led quality (often from people who’ve done the job) vs. high-velocity production supported by AI.
• A modern in-house writer role trends toward “jack of all trades” output (research, PR-like writing, CEO comms, etc.), using AI to lower marginal cost without collapsing quality control.

Show Links

• Connect with David Khim on LinkedIn and Twitter
• Connect with Alex Birkett on LinkedIn and Twitter
• Connect with Allie Decker on LinkedIn and Twitter
• Connect with Omniscient Digital on LinkedIn or Twitter

Time Stamps

• [00:00] – Kitchen Side intro + framing the question: “Who owns AI visibility?”
• [02:00] – “Is AI killing SEO?” and defining SEO as a distribution/optimization mechanism
• [08:00] – Why AI/overviews change the mechanism of discovery (not the existence of search demand)
• [11:30] – Cannibalization of non-scarce, definitional “consensus” content (CRM example)
• [16:00] – The “traffic trap”: questioning whether lost traffic ever had business value
• [21:30] – Who’s saying “SEO is dead” (publishers/affiliate sites vs. consumers) + role/title patterns
• [28:30] – Measurement and attribution get harder (“dark SEO” problem)
• [30:30] – Restaurant analogy: shifting from “foot traffic” to revenue/self-reported attribution
• [36:00] – Should everyone just make BOFU listicles? Why “listicles dominate citations” may be prompt/sampling bias
• [43:00] – Moving up-funnel: problem-aware prompts, harder measurement; “citation share” as a proxy
• [50:00] – Content team bets: SME-led quality vs. velocity/output-focused programs
• [57:00] – Buyer journey nuance: tire-kicker vs decision maker; foundations vs scale vs leadership phases
• [64:00] – “Is the content writer role dead?” In-house writer as a jack-of-all-trades (CEO comms, PR, research) with AI support
• [69:30] – Velocity vs quality framed via experimentation/expected value (run more experiments vs raise hit rate vs bigger swings)
• [74:00] – Scaling output: lowering marginal cost with AI + quality control challenges; translation-at-scale example