Within the first half of 2026, search behavior shifted underneath our ft, software program valuations cratered on sentiment relatively than proof, and corporations blamed layoffs on AI lengthy earlier than anybody might present the receipts.
Kevin Indig posted a hyperlink on LinkedIn final week to his AI Halftime Report, H1 2026, and it’s value noting that his H1 2025 report predicted each Google’s continued AI Mode rollout and the concept that AI layoffs have been largely a PR narrative relatively than an operational actuality. Each predictions held up, and the report opens with a line that doubles because the thesis for your entire first half of the 12 months: AI’s influence saved rising quicker than anybody’s skill to measure it. That hole between influence and measurement is the true story of H1 2026, greater than any single product launch or earnings name.
Belief Grew to become A Rating Issue Readers Really feel In Their Personal Outcomes
Indig’s analysis discovered that roughly three out of 4 shoppers choose the highest end in an AI shortlist, until a brand they already trust seems anyplace else on that listing, during which case they choose the trusted title as an alternative. Software program shares fell by near 30% over the interval, and the decline tracked nearly totally with how the market perceived an organization’s publicity to AI disruption relatively than with how that firm truly carried out. The underside quartile of software program shares dragged the entire sector down whereas the median and high quartile outperformed the broader ETF, which tells you the selloff was a narrative about narrative, not fundamentals.
Meta engineers reportedly burned via 73.7 trillion tokens in a single month chasing an inside leaderboard that ranked greater than 85,000 staff by token consumption. No one might level to the return on that spending, and Meta shut the leaderboard down in April as soon as CFOs realized annual token budgets had been blown via in 4 months.
AI Took The Blame For Cuts It Did Not Make
Layoffs instructed the same story of narrative racing forward of proof. Challenger, Gray & Christmas discovered AI cited as the rationale behind greater than 87,000 job cuts via Might, roughly a fifth of all 2026 layoffs to that time. Indig’s personal reporting, going again to his H1 2025 predictions, argues AI is usually a handy clarification for cuts that have been actually about pandemic over-hiring and capital expenditure self-discipline. Among the similar firms that blamed AI for layoffs rotated and quietly rehired.
My take (and I’ve been saying versions of this since spring) is that Indig has named one thing structural relatively than seasonal. Each certainly one of his H1 storylines, the SaaS selloff, the AI layoff narrative, the traffic collapse publishers are actually combating in court docket, comes again to the identical root trigger. We constructed our measurement scoreboards for traditional search years in the past, and none of them have been designed to show one thing as nonlinear and probabilistic as AI search has turned out to be.
That nonlinear narrative reveals up starkly in Indig’s quotation information. He discovered that 91% of citations seem in solely certainly one of ChatGPT, Perplexity, or AI Overviews, by no means in a couple of. Prompt tracking, he argues, must behave extra like polling and focus-group analysis than just like the rank monitoring SEOs have leaned on for 20 years. Brand mentions, not citations, correlate extra intently with actual enterprise outcomes, since most patrons care whether or not a model reveals up favorably throughout a panel of prompts relatively than whether or not one particular quotation landed in a single particular reply. Google’s personal Search Console data is reportedly 75% incomplete for this new panorama, so even practitioners who assume they’re measuring fastidiously are working from a partial image.
There was an upside to all that token burning. Indig factors out that the wave of utilization round Claude’s Opus releases pushed way more folks into daily AI use than any advertising marketing campaign might have, and that surge fed development at infrastructure firms additional down the stack, the form of second-order impact that not often reveals up in a quarterly earnings name however shapes a complete ecosystem anyway.
The agent market itself reshuffled simply as a lot because the metrics did. ChatGPT’s share slid from 78% to 56% between July 2025 and July 2026, whereas Gemini climbed from 15% to 30% and Claude grew from 2% to 10%. Mannequin alternative has develop into a real enterprise danger relatively than a desire, which is yet one more variable that resists simple measurement.
Publishers Took The Combat To Courts And Regulators
Publishers spent H1 2026 combating the identical battle in a unique enviornment. A Munich court dominated Google answerable for false statements generated by AI Overviews. Four hundred newspapers sued OpenAI and Microsoft over unauthorized content material use. The UK’s Competition and Markets Authority ordered Google to provide publishers extra management and transparency over how their content material is utilized in AI search, together with opt-outs from AI Overviews, AI Mode, and Uncover summaries. Each a kind of fights is admittedly an argument over who will get to regulate entry and attribution as soon as a human is not the one clicking via.
The Second Half Splits Intelligence From Company
Indig closes his report with a preview of the second half that deserves as a lot consideration as something within the H1 recap. He argues H2 2026 will “separate intelligence from company.” Mannequin functionality retains getting cheaper and extra commoditized via open-weight competitors, however the permission to truly act on somebody’s behalf, spend cash, attain information, or impersonate an individual via an agent, is getting locked down more durable by platforms, governments, cost networks, and customers themselves. The writer lawsuits and the UK CMA order are early proof that this tightening has already began.
That distinction issues extra for search engine optimization technique than most of what acquired consideration in H1. Here’s what practitioners can do with it heading into the second half.
First, retire the belief {that a} single rank-tracking instrument covers AI search. Construct a immediate panel that spans ChatGPT, Claude, AI Overviews, AI Mode, and a minimum of one open-weight mannequin, and deal with the outcomes the way in which a pollster treats a pattern relatively than the way in which an search engine optimization treats a SERP. Given how little overlap Indig discovered between engines, monitoring just one is near monitoring none.
Second, shift reporting away from citation counts and towards point out frequency, sentiment, and suggestion rank throughout that panel. A dashboard that solely counts citations is measuring the smaller half of what truly drives purchaser conduct, and it’ll hold understating your actual AI footprint to shoppers or management.
Third, begin auditing your agentic access layer now, properly earlier than H2 forces the difficulty. Examine whether or not your product data, pricing, and checkout flow are structured so a licensed AI agent can truly full a transaction on a buyer’s behalf, and whether or not your model reveals up as a trusted, nameable possibility when an agent is selecting amongst a number of opponents. Indig’s break up between intelligence and company means the winners in H2 would be the manufacturers brokers are permitted to behave on behalf of, not merely the manufacturers that get talked about most frequently.
I agree with Indig that the flexibility to measure AI’s influence fell behind the influence itself in H1 2026, and I don’t assume that hole closes by itself between now and the top of the 12 months.
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