AI halftime report: H1 2026

AI search grew, token spending surged, software stocks fell, and publishers lost traffic in H1 2026, according to a report by Growth Memo. Google's AI Mode reached 1 billion monthly active users with queries three times longer than classic search, while 91% of AI citations appear in only one of ChatGPT, Perplexity, or AI Overviews. The report highlights that brand mentions in AI answers are more impactful than citations, with 75% of consumers picking the number one result in an AI shortlist.

SEO https://searchengineland.com/library/seo » AI halftime report: H1 2026 AI search grew, token spending surged, software stocks fell, and publishers lost traffic. Here’s what H1 2026 revealed about AI’s impact. Every six months, I take a sharp look at the latest developments in AI and Search. Based on how quickly things are developing, I would almost need to increase that cadence to monthly. And maybe I will. But first, here’s what happened in H1 2026. H1 2026 moved money, traffic, jobs, and market cap before anyone could prove how much value AI created. Search behavior changed, token budgets exploded, software stocks sold off, and companies blamed layoffs on AI. Every major AI story in H1 2026 was really a story about attribution. - We’re still figuring out how to improve accuracy in measuring AI visibility. - Companies spent billions on inference, but there is no obvious answer to “What’s the ROI?” - Public markets punished software companies, but were investors reacting to actual or perceived disruption? - We’re hearing “AI caused layoffs,” but when you look deeper, the real causes aren’t connected. - It’s clear where the traffic loss is coming from, but it’s not clear what content marketplace model will replace it. The common thread: AI’s economic impact is expanding faster than we can attribute it. AI Search In the H1 2025 report, I predicted Google would roll AI Mode out further, and that turned out to be true. AI Mode is now a click https://techcrunch.com/2026/01/27/google-now-lets-users-jump-from-ai-overviews-into-ai-mode-conversations/ away from AI Overviews, which means it’s just two clicks away from regular search results. - AI Mode reached 1 billion MAU https://blog.google/products-and-platforms/products/search/search-io-2026/ with queries around 3x longer than classic search. - Google called it the biggest search box upgrade in 25 years https://blog.google/products-and-platforms/products/search/search-io-2026/ at I/O 2026. - Gemini 3 auto browse is shipping https://support.google.com/chrome/answer/16821166?hl=en inside Chrome. - Nick Fox says Google’s AI Mode sends out billions of clicks https://searchengineland.com/google-says-ai-search-features-sending-billions-of-clicks-to-websites-each-week-482599 to the open web. To understand the impact of this shift, I published https://www.growth-memo.com/p/2026-growth-memo-research-summary a series of user behavior studies and data analyses in the first half of 2026. The through line of Growth Memo research in H1 2026: - Tracking a brand’s presence in AI Search is highly complex. You need to factor in the engine, personalization, reasoning levels, model updates, stochastic variability, etc. Measurement is fragmented. The citation/mention overlap between engines is minuscule: 91% of citations appear in only one of ChatGPT, Perplexity, or AI Overviews. Prompt tracking should be closer to polling and focus groups than SEO rank tracking. - Brand mentions in AI answers are more impactful on business outcomes than citations. Don’t get me wrong, citations shape the answer, and for some businesses, that’s most important. But the majority of vendors and merchants need to pay attention to how often t https://library.growth-memo.com/p/brand-prominence hey show up in a panel of prompts, in which context, what sentiment, and whether they’re recommended or not ahead of competitors . Trust is the highest currency in AI search. Close to 75% of consumers pick the number one result in an AI shortlist. But if they see a trusted brand anywhere on that list, they will pick it.- The average U.S. adult has high trust in AI recommendations. 88% of the time, users accepted AI Mode product recommendations as best there is. In AI Overviews, on the other hand, users click, evaluate, and compare https://library.growth-memo.com/p/validation-click a lot. That’s classic search behavior, but it doesn’t carry over to AI chatbots. - Writing style, token budget, and technical factors matter for agents. If you want to be present in AI Search and agentic recommendations, you need to lead with unique information https://www.growth-memo.com/p/why-proprietary-data-is-your-most , write in a direct, easy-to-understand way https://www.growth-memo.com/p/the-science-of-how-ai-pays-attention , remove fluff and keep your site technically fast and easy to access. AEO/GEO is a brand channel disguised as a performance channel. AI recommendations shape demand not citations . The unit of optimization is whether AI names, trusts, and recommends your brand. The grAIpes are sour November 2025 was a pivotal turning point in AI. Claude’s Opus 4.5 was the first model that was perceived as reliable and robust enough for agentic workflows. A month later, Peter Steinberger went viral with Clawdbot, which led to millions of installs https://openclawvps.io/blog/openclaw-statistics , long lines in China https://www.cnn.com/2026/03/29/business/china-openclaw-ai-anxiety-intl-hnk-dst , and Nvidia building a Nemoclaw clone. Then, things got even crazier. Shopify, Uber, Meta, and many other tech giants built token leadership boards that incentivized engineers to light as many tokens on fire as possible. “Let me give you a thought experiment. Let’s say you have a software engineer or AI researcher, and you pay them $500,000 a year. At the end of the year, I’m going to ask him how much did you spend in tokens. And if that person said $5,000, I will go ape something else. —If that $500,000 engineer did not consume at least $250,000 worth of tokens, I am going to be deeply alarmed.” Jensen Huang A Meta engineer created an internal leaderboard dubbed “ Claudeonomics https://www.reddit.com/r/GenAI4all/comments/1uriom3/meta employees consumed 737 trillion ai tokens in/ ” that ranked over 85,000 employees by the number of AI tokens they burned. It led to massive waste as employees left AI agents running on idle or useless tasks just to climb the ranks and earn titles like “Token Legend”. Reportedly, Meta engineers consumed 73.7 trillion tokens in just 30 days. I wonder how much of OpenAI’s and Anthropic’s growth was ignited just by workslop. Good times. But in April, CFOs pumped the brakes after discovering that employees had burned through their annual token budget in 4 months. TokenMAXXXING shifted to valueMAXXXING. Meta’s leaderboards were shut down in April along with leaderboards at other companies , but not before the 1 user on the board averaged 281 billion tokens, which would cost over $1.4 million at standard API rates. But what remains from the all-you-can-eat token craze is a step change in productivity that we cannot yet measure. As I wrote, AI changed my work. And yours, too https://www.growth-memo.com/p/ai-changed-my-work-and-yours-too : I have used AI to raise my impact by a magnitude. - I designed landing pages end-to-end for a major travel brand that made it into production. - I automated topic prioritization, SEO testing, and SEO reporting for my clients with full-blown apps. - I built an array of useful applications for myself, from automating the SSI SEO Site Index found in the bimonthly Growth Intelligence Briefs https://www.growth-memo.com/t/growth-intelligence-brief to Openclaw agents that help me with research and charts. One outcome of the token tsunami is that a lot more people started using Claude, which in return fired up the growth engines for AI infrastructure companies that Claude recommended, like Supabase. SaaS bloodbath In February 2026, as a consequence of the Opus 4.6 release and Claude Cowork, the software-as-a-service industry saw a severe market downturn that wiped out hundreds of billions of dollars in market cap over just a few trading sessions. The SaaS vertical saw a steep annual decline of +30% in the markets. Valuations for high-growth software companies collapsed, with revenue multiples shrinking dramatically compared to their pandemic highs. If you’re working in B2B, you’ve probably felt the impact in the form of lower conversion rates, longer sales cycles, and softening brand searches. The Brand Tax Calculator https://www.growth-memo.com/i/191197367/5-premium-brand-tax-calculator-and-3-tests-to-run-before-your-next-budget-review gives you the dollar figure for the gap between branded paid spend and reported ROAS, and the AI SEO Budget Reallocation Planner https://www.growth-memo.com/i/178497248/scenario-based-budget-planning-is-the-seo-survival-move turns it into 5 growth-priority scenarios in under 7 minutes. Both live in the Premium Resource Library https://www.growth-memo.com/p/exclusive-growth-premium-resources . It turns out not all software was or is forsaken. It’s the bottom quartile of software companies that pulls the market down. Interestingly, the decline is purely associated with how “the market” views a company’s AI robustness . Company valuation drops are not related to performance, but rather to whether people think AI will disrupt their product. Over the last 30 trading days, both the top quartile and median IGV stock have outperformed the ETF as a whole — it’s the bottom quartile which include some of the largest companies that’s pulling down overall performance. So, if you’re in B2B and either forced or privileged to take a new job, pick a company the market is optimistic about. AI washing in the labor market You might have read or heard this recently: “We’re laying off x% of our workforce due to AI.” It’s the narrative du jour . Challenger, Gray & Christmas https://www.challengergray.com/wp-content/uploads/2026/06/Challenger-Report-May-2026.pdf reported that AI was the leading cited reason for May 2026 job cuts and had been cited in 87,714 cuts year-to-date, equal to 22% of all 2026 announced layoffs through May. And don’t get me wrong. Layoffs are real: - Tech layoffs up ~66% year over year, toward 150K - Oracle cut 21,000 citing AI - Challenger lists AI as the top cited reason ~87,700 YTD by May - Block cut 40% and its stock rose Bloomberg’s “AI washing” framing The only problem is that AI is not the cause . I’ve written extensively https://www.growth-memo.com/p/stop-trying-to-replace-people-with about the Big Labs using AI replacement as a marketing narrative. But it hasn’t come true yet. A lot of AI layoffs were really to offset capital expenditures, pandemic overhiring, and economic turbulence. We can all imagine a future in which AI is so good that it makes certain roles obsolete, but that time is not now. A year ago, in the H1 2025 report https://www.growth-memo.com/p/ai-halftime-report-h1-2025 , I predicted that AI layoffs were a PR stunt. And I was right: Despite clear productivity gains from AI, the recent waves of layoffs show no indication https://www.growth-memo.com/p/stop-trying-to-replace-people-with of AI being the underlying cause. In fact, companies using AI as a reason to lay employees off are rehiring them https://www.fastcompany.com/91571824/the-great-ai-layoff-is-turning-into-the-great-ai-rehire . The agent market fragmented Google is now the most likely player to win the AI consumer market, and ChatGPT has lost its significance in AI Search to Google: - ChatGPT still has ~1.1B users, but OpenAI refocused on an enterprise pivot and shut down Sora, dropped video in ChatGPT and killed Instant Checkout. Enterprise makes up ~40% of revenue https://www.cnbc.com/2026/04/08/openai-ipo-sarah-friar-retail-investors.html , heading to ~50% ahead of a potential IPO. I’m skeptical that we’ll be able to buy OpenAI stock. According to Ed Zitron, OpenAI spends $2.8 billion USD every month to make $1.1B. - Anthropic’s fight with the Pentagon pushed Claude to No. 1 among free apps on Apple’s U.S. App Store. A few months later, users seem less sure if Anthropic can resist attacks from open-source models. - The Big Labs massively subsidize tokens. SemiAnalysis found a $200 USD plan of the frontier models gives you 8-14K USD worth in tokens https://x.com/SemiAnalysis /status/2064815044085318040 . Lately, open-source models like Kimi K3, GLM 5.2, or Deepseek V4 have put pressure on the big US labs because of those subsidies. Open-weight and open-source models also show that the model itself becomes commoditized, while the harness and application layer gain more importance. Forward-deployed-engineer job postings rose 800% https://www.salesforce.com/news/stories/forward-deployed-engineers-making-ai-jobs-more-human/ in the first 9 months of 2025 and were still up 729% year over year https://www.businessinsider.com/forward-deployed-engineer-jobs-in-demand-2026-5 in April 2026. Frontier Labs now pays more than $500,000 in total compensation https://www.reuters.com/technology/artificial-intelligence/artificial-intelligencer-hottest-job-ai-right-now-2026-02-26/ for people who can turn a model demo into a working system inside a customer’s business. Never have marketers faced a faster evolving environment with more platforms to measure… which is why understanding what platforms matter most for your audience is important. But from an execution perspective, model availability has become a business risk, as we can see at the hand of Fable 5. Having options is good. Publishers and the law I predicted up to 70% of 2024 organic traffic could be gone by 2026, but that was overeager. In the end, the numbers land at ~33% referral loss year over year https://pressgazette.co.uk/publisher data/publisher-traffic-ai-overviews/ , with 68% of Google searches now ending without a click https://sparktoro.com/blog/in-2026-less-than-one-third-of-google-searches-still-send-a-click/ . Still, as a result, publishers are moving the fight to the courts and regulators. USA Today CEO Mike Reed explained https://www.therebooting.com/podcast/s/the rebooting show/why usa today co might quit google : “We’re getting close now to the point where we’ll block Google as well and abandon the traditional search traffic that we get today.” https://www.therebooting.com/podcast/s/the rebooting show/why usa today co might quit google Here are just a few lawsuit-related highlights: - A court in Munich ruled Google liable for false statements https://www.dw.com/en/german-court-holds-google-liable-for-fake-ai-answers/a-77527661 generated by AI Overviews June 2026 . - 400 newspapers sued OpenAI and Microsoft https://www.courthousenews.com/newspapers-sue-openai-microsoft-for-mass-copyright-infringement/ over unauthorized content use June 2026 . - The UK CMA ordered Google to give publishers greater control and transparency https://www.reuters.com/world/google-required-open-up-ai-search-engine-rivals-under-eu-mandated-changes-2026-07-16/ over how content is used in AI search including opt-outs from AI Overviews, AI Mode, and Discover summaries , along with clearer attribution and improved reporting on how content appears in AI-generated results. Google responded by adding an impression-based AI report in Search Console. In response to the intense publishing landscape changes, Parallel AI and Cloudflare are both trying to build publishing marketplaces for content owners and AI companies. “Assume there’s no search. You have to have your businesses planned as if search is zero.” — Conde Nast CEO Roger Lynch Publishers are trying to replace the content-for-traffic bargain with a content-for-training https://library.growth-memo.com/p/training-data market. This leaves several open questions: - Who sets the price and how? - How can you prove that an article contributed to an AI agent’s answer or purchase? - Do publishers have negotiation power? - Are smaller publishers even needed by AI labs? Dig in: Full list of Growth Memo research completed in H1 2026 Dig deeper into the patterns covered in this halftime report below: - User behavior studies: - Data analyses: The Consensus Gap https://www.growth-memo.com/p/the-consensus-gap The ghost citation problem https://www.growth-memo.com/p/the-ghost-citation-problem Reasoning lift: What happens to AI visibility when AI thinks harder https://www.growth-memo.com/p/reasoning-lift-what-happens-to-ai The science of how AI pays attention https://www.growth-memo.com/p/the-science-of-how-ai-pays-attention The science of how AI picks its sources https://www.growth-memo.com/p/the-science-of-how-ai-picks-its-sources The science of what AI actually rewards https://www.growth-memo.com/p/the-science-of-what-ai-actually-rewards Shorter, Focused Content Wins in ChatGPT https://www.growth-memo.com/p/shorter-focused-content-wins-in-chatgpt GSC data is 75% incomplete https://www.growth-memo.com/p/gsc-data-is-75-incomplete Organic rankings vs. product grids: The new e-commerce divide https://www.growth-memo.com/p/organic-rankings-vs-product-grids The AI skills salary premium https://www.growth-memo.com/p/the-ai-skills-salary-premium Where AI agents get stuck on your site https://www.growth-memo.com/p/where-ai-agents-get-stuck-on-your Why most original data never gets cited https://www.growth-memo.com/p/why-most-original-data-never-gets As we pass the halfway point in the year, a big thanks to my editorial and research partners, Amanda Johnson https://www.linkedin.com/in/amanda-b-johnson/ and Eric van Buskirk https://www.linkedin.com/in/vanbuskirk/ . And an extension of gratitude to my data partners who make these analyses possible: Semrush, AirOps, Gauge, Citation Labs, Siteline, SalaryGuide, and AudienceKey. This post first appeared on the author’s website and is republished here with permission. 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