Marketers who plan for either AI-driven extinction or AI-driven abundance are "optimizing for the wrong outcome," according to Greg Jarboe, speaking on the Search Engine Journal Show with Katie Morton. Asked whether AI will kill us all, his answer was: "Maybe, but probably not."

Jarboe's position is that both extremes distract from the practical work of adapting to AI. "The real work is happening in the space between those two stories, and that space doesn't get much airtime because it doesn't sell headlines," he said. His realistic forecast: "Real progress next to real problems, some measurable wins mixed in with a fair amount of disappointment."

The Y2K Playbook

Jarboe draws a direct parallel to Y2K. Planes stayed in the air and the power grid held, but he argues that calm outcome resulted from years of unglamorous fixing, not proof the warning was empty. AI warnings work the same way when they point at a specific risk and lead to a specific safeguard. They fail when the message is simply that the sky is falling. The utopian pitch — that AI will erase drudgery — comes from "the same hype machine wearing a different costume," he said.

Fact-Checking Is No Longer Enough

Most SEOs already know AI hallucinates. Jarboe argues that knowing this is no longer sufficient, because fact-checking only tells you whether a claim is technically accurate, not whether it holds up. He pushes practitioners toward "ground-truthing" instead: before shipping anything AI drafted, ask whether the underlying inference is right, whether the recommendation fits your market and customer, and what evidence would prove the central assumption wrong. "An AI system can hand you a clean-looking draft or a fast summary of a dataset. It cannot tell you whether the direction is correct. That's still your job," he said.

Silos Carry a Higher Price

The part practitioners underrate, according to Jarboe, is that AI did not just change how content gets made — it raised the cost of departments that do not talk to each other. When a press release says one thing, the landing page another, and social a third, human readers get confused, and so does every AI system trying to summarize the brand. "Inconsistency used to be a minor annoyance. Now it's a citation risk," he said. His prescription: SEO needs to be in the room with PR, and analytics needs to be involved from the start of a project, not summoned at the end to bless a decision already made.

Concrete Steps for This Week

Jarboe lays out three actions marketers can take immediately:

• Run AI-assisted content through the ground-truthing questions rather than a spellcheck-level review, asking what would have to be true for the conclusion to be wrong.
• Pull one person each from PR, content, and analytics into the next planning conversation on any piece touching brand messaging. The inconsistency AI systems pick up, he notes, is usually the same inconsistency departments created independently.
• Build evidence into PR pitches from the start. "A strong hook plus real data and a sample size that survives scrutiny beats a hook alone, and it's the difference between a piece that gets cited and one that gets ignored by the next model update," he said.

Why the Extremes Dominate

The doom-or-utopia framing persists for structural reasons, Jarboe argues. Fewer journalists are covering more AI claims, and incentives — algorithmic and human — reward the most dramatic version of any story. "Increasingly, your hair has to be on fire to get attention," he said. That pressure strips out the qualifiers, the "yes, but" and the "only if," until readers choose between two extremes that were never the real choice. His fix is not to abandon the strong hook but to back it with a story that can survive an editor's second look.

The implication for B2B marketers: as AI systems increasingly summarize and cite brands, the winners will be those whose messaging is consistent, evidence-backed and directionally correct — not those betting on either catastrophe or effortless abundance.