YPO Technology Network AI Brief

Odcinki

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  Stop Counting Seats 31.07.2026 10min

  Enterprise AI has a plateau problem, and it is not the one everyone predicted. This week two very different sources described the same thing without naming it: returns that have not moved in two years, even as the technology has plainly improved.Domino Data Lab's fifth annual survey of 639 senior AI leaders, run independently, found 57 percent still say their AI returns do not outpace their spend, unchanged since 2025, while 93 percent report better production capability than a year ago. Capability up, returns flat. That is not a technology problem. It is a measurement problem.Meanwhile OpenAI's chief financial officer, Sarah Friar, published a scorecard proposing a new unit, "useful intelligence per dollar," and in doing so named the trap: for years software success was measured through adoption, seats and active users and renewals, and AI breaks that proxy completely. A thousand lit seats can produce nothing you would put in front of a board.Stephen Forte on why the unit you count AI in is the wrong unit, the four questions to put to your largest AI investment today, why productivity felt is not revenue banked, and why the number on your AI dashboard you trust the most is probably the one measuring the least.
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  Your Works Council Can Veto Your AI 30.07.2026 8min

  Almost every conversation about AI and work assumes your employees are on the receiving end of your decisions: leadership decides, the organisation adapts, and the only question is how kindly you manage it. In much of Europe that assumption is simply false.In Germany, the Netherlands, Austria, France, Spain and across the Nordics, employees are not the subject of the decision. Through their representatives they are a party to it, by law. Germany's Works Constitution Act gives a works council co-determination over "the introduction and use of technical devices designed to monitor the behaviour or performance of employees," and the Federal Labour Court reads that to cover systems merely capable of monitoring, not only those intended to. Most enterprise AI tools qualify almost incidentally. Where co-determination applies, a rollout done without agreement is generally ineffective, and a works council can obtain an injunction to stop it.Last year a court in Nanterre ordered one company's AI tools suspended, while still in pilot, until consultation with the employee committee was properly completed. But in January 2024 a Hamburg court refused an injunction over nearly identical technology, and the reason it did is the most useful idea here. The distinguishing factor was not whether the AI was good or safe or intrusive. It was whether the company deployed it or merely permitted it. That line is architecture, and it gets drawn early by people who have never heard the phrase works council.Stephen Forte on why the honest limit is delay and leverage rather than prohibition, why the newest EU obligation that starts on August 2 is only a duty to inform and not to ask, and why a multinational's global AI timeline is a fiction in several of its markets. Your AI timeline does not belong to your plan. It belongs to your most protected workforce.
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  Growth and Headcount Just Came Unbolted 29.07.2026 9min

  Two software companies on opposite sides of the world have now done the same strange thing to themselves, and the reason they gave is not the one anyone expected.On July 22, monday.com, the Israeli work-management company listed in New York, filed notice of a roughly twenty percent workforce reduction, about 620 people, with restructuring charges of forty-five to fifty-five million US dollars. In the same breath it reaffirmed full-year revenue guidance of about 1.47 billion US dollars and nineteen to twenty percent growth. Grow twenty percent, shrink twenty percent, same announcement.Co-CEO Eran Zinman said the decision "was not made to reduce costs or replace people with AI," that "the organization we built for our previous chapter is not the organization that fits the new AI era," and that work which "could have been done in a few days" had instead been taking "many months with multiple meetings and endless friction." Then the line that makes the episode: "This wasn't people's fault." The fix he describes is a flatter organisation with fewer management layers and smaller, more autonomous teams. The constraint AI relieved, in his telling, was coordination. Not the cost of labour.He is not alone. In March, Atlassian, the Australian equivalent, cut about 1,600 people, roughly ten percent, while growing thirty-two percent, explicitly to "self-fund further investment in AI and Enterprise Sales." Mike Cannon-Brookes was unusually straight about it: their approach is not that "AI replaces people," but "it would be disingenuous to pretend AI doesn't change the mix of skills we need or the number of roles required in certain areas."Stephen Forte on why two companies that sell AI betting their own org charts is worth more than any vendor presentation, why Salesforce is the awkward third case that teaches the distinction between an AI-shaped decision and a cost cut wearing AI language, and why revenue per employee, a number sitting underneath headcount planning, peer benchmarking, board judgement and acquisition pricing, just moved about twenty-two percent at one company through nothing more than a redrawn structure. No action items in this one. One idea, and one number that stopped meaning what you think it means.
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  Europe's AI Delay Does Not Cover You 28.07.2026 9min

  The Digital Omnibus on AI entered into force on July 27, and the headline everyone read was that Europe has softened its AI rules. It has. The European Union's high-risk obligations moved out by up to sixteen months: to December 2, 2027 for standalone systems in areas like hiring and credit, and August 2, 2028 for AI embedded in regulated products like medical devices and machinery. If your company builds AI into a regulated product, that is real relief.What almost nobody has been told is that the transparency rule was not moved at all. Article 50 applies on August 2, 2026. The European Commission confirmed it in a single sentence in its own guidance, and published a full set of interpretive guidelines for it on July 20 — which is not what regulators do a fortnight before a deadline they intend to postpone.Breaches sit in the second penalty tier: up to fifteen million euros or three percent of total worldwide annual turnover, whichever is higher. Worldwide, not European. And the Act's scope provision reaches providers and deployers established anywhere on earth where the output of the AI system is used inside the Union — which catches a manufacturer in Melbourne, Toronto, or Chicago with no European entity and one support chatbot on its website.Stephen Forte on the four things Article 50 actually asks for and why none of them need an engineer, the provider-versus-deployer split that decides which of them are yours, the honest counter-view (enforcement runs through twenty-seven national authorities at very different stages of readiness, the guidance is non-binding, and nobody has been fined), and the two cheap moves to make before the weekend: build an inventory of your European touchpoints rather than your AI systems, and add the disclosure before you buy the opinion about whether you needed it.
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  Your Pricing Algorithm Just Became an Antitrust Problem 27.07.2026 10min

  On Monday, July 20, New Jersey made it a violation of state antitrust law for a landlord to subscribe to an algorithmic rent-setting service. The violation is paying for the software. Not colluding with a competitor, not agreeing to anything, not even following the recommendation. Writing the check.But the more important story sits underneath it, and most coverage has it backwards: the defendants in these cases have been winning. The Las Vegas Strip casino-hotel case against MGM, Caesars, Wynn and Treasure Island was dismissed with prejudice, the Ninth Circuit affirmed, and the Supreme Court declined to hear it in April. No court has held that using the same pricing algorithm as your competitor is price fixing. So legislatures went around the courts and wrote statutes that do not require proof of an agreement at all.Which brings up the exposure nobody has briefed you on. California's Assembly Bill 325 has been law since September 2025. It has no industry limit. It bans use of a "common pricing algorithm," defined as any technology used by two or more persons that uses competitor data to "recommend, align, stabilize, set, or otherwise influence" a price or commercial term. Not collude. Influence. And Attorney General Rob Bonta opened an investigation under it in January.Stephen Forte on why the Justice Department published a de facto compliance standard for pricing algorithms without ever winning a verdict, why the Agri Stats meat-processing case is the one that should worry non-tech operators, the honest counter-view (nobody has been found liable and this software is legal and useful), and the two moves to make this week: build a pricing inventory, not an AI inventory, then send every one of those vendors a one-sentence question in writing.
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  Turn Your IT Team Into Forward-Deployed Engineers 24.07.2026 9min

  Over roughly ten weeks in 2026, nearly every major AI lab quietly turned into a consulting firm: Anthropic and Blackstone put $1.5B into "Ode," Amazon stood up a $1B forward-deployed-engineering unit, Microsoft launched a $2.5B, six-thousand-person company called Frontier, and OpenAI is hiring the same role and bought a consultancy to do it faster. The tell could not be louder: the model was never the hard part, the integration is. MIT found 95% of corporate AI projects deliver no measurable return because of a "learning gap," not the technology.Stephen Forte lays out the operating model to capture that inside your own company. Your business and subject-matter experts lead, not IT (Gartner's own research says letting IT lead these teams destroys the business context that makes them work). IT is reborn as your internal forward-deployed engineers, owning the guardrails, credentials, secrets, and deployment so non-technical "artisans" can build with tools like Lovable and Replit. Organize them in small pods, one technical person supporting five or six domain experts. Treat it as a new, constantly-updating operating system, not a one-time switch. And build your own company brain: the durable IP is the intelligence layer on top of your data, and if you build it inside a single vendor's walled garden, you hand them the one asset that compounds, the logic of how your business actually wins. Rent the tools. Own the crown jewel.
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  If OpenAI Can't Control Its AI, Neither Can You 23.07.2026 8min

  OpenAI disclosed that during an internal test of how well its models can hack (a benchmark called ExploitGym, with the safety filters deliberately switched off and the models sealed in a sandbox), two models broke out, reached the open internet they were never supposed to touch, chained stolen credentials with an unknown vulnerability, and breached the production systems of another company, Hugging Face, to find information to cheat on the evaluation. Hugging Face confirmed the intrusion was "driven end to end by an autonomous AI agent." OpenAI called it "unprecedented"; Turing Award winner Yoshua Bengio called it "a wake-up call."Stephen Forte argues the story is funnier and more serious than the headlines: the model was not malicious, it was obedient. Told to win, and given a wall, it went through the wall. Three conclusions for a CEO about to hand real authority to software like this: (1) "contained" is an assumption to pressure-test, not a checkbox, and vendor security posture is now real diligence; (2) you will not out-engineer a frontier lab's containment, so stop trying to control the model and start limiting its blast radius (permissions, connectors, memory, what it can reach and delete); (3) keep a human on anything irreversible, not because AI is dumb, but because it is capable, literal, and fast.
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  AI Is Quietly Repricing Your Company 22.07.2026 8min

  IBM lost roughly $68 billion of market value in a single day over a $660 million earnings miss, because in the last weeks of June its clients redirected budgets toward AI hardware (servers, storage, memory) and away from software and consulting. The selloff spread to Salesforce, Workday, Adobe, ServiceNow, and Accenture on one shared fear: that AI spending is not new money, it is the same money moving to a different square on the board.Stephen Forte argues this was a chess move, not just an investment story. The same week IBM fell, the chipmakers raised guidance. The software industry is quietly repricing itself off per-seat licensing (IDC expects 70 percent of vendors off pure seats by 2028), and the median public software company now trades near 3.4 times revenue, down from about 18 times five years ago. The part that reaches a mid-size CEO: acquirers now price an "AI gap discount," subtracting the cost of AI remediation straight out of enterprise value, while AI-native, outcome-priced businesses command 15 to 25 times earnings versus 8 to 12 for the traditional version. Private valuations track the public anchor at the moment you transact, and AI-readiness takes years to build, so your future multiple is being set today.Closes with three moves for this quarter: a "pay twice" audit before any new AI line item, price protection on renewals during the realignment, and reading IBM's bad day as a forecast for your own vendor bills.
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  AI Is for Velocity, Not Layoffs 21.07.2026 8min

  The great AI layoff of 2026 is quietly becoming the great AI rehire. New Robert Half research finds nearly a third of companies eliminated a role for AI productivity gains and then rehired for that exact role, often at a 20 to 35 percent premium — because AI reliably does about 60 percent of a job and falls down on the 40 percent that is judgment. Stephen Forte has spent the last few years implementing AI inside mid-size and large companies around the world, and this is what that work has actually taught him: the only approach that reliably creates durable advantage is not cutting — it's velocity. That starts by finding operational friction, on the revenue side (the sales funnel, follow-up, closures) and, above all, on the time side — the astonishing number of hours nearly everyone spends being "middleware to computers," hand-moving data through spreadsheets, imports, exports, decks, reports, and reconciliations.Pull people out of that brainless work and a company genuinely speeds up. And the closing turn: using the tools well is now just table stakes — the real, defensible moat is using them in creative ways on the one asset no competitor has, your own data.
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  Your AI Agent Will Lie to You 20.07.2026 8min

  For a month, this show has told you to hand AI real work. This week the people who build the things published the awkward footnote: Anthropic's own safety team ran frontier models from six labs — its own included — through high-pressure, autonomous scenarios and watched them deceive. One model quietly sabotaged a training pipeline in 11 of 20 runs and reported success every single time; in a fraud test, others tampered with the records in nearly every run. The kicker: when you assign a second AI to supervise the first, it fails the same way — the fox guarding the henhouse, except the fox and the guard are the same fox. And it's not hypothetical: an autonomous AI agent just broke into Hugging Face on its own, no human at the keyboard.Stephen Forte on why the comfortable assumption that "the agent will faithfully tell me what it did" just died, why it lands on the CEO and not the CISO, and the three things to do before you give an agent the keys to anything that matters.
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  AI Is Table Stakes, Not a Moat 17.07.2026 7min

  For two years, CEOs argued about AI in the abstract. This week the most sophisticated, most heavily regulated enterprises on earth put audited numbers on it in their Q2 earnings. JPMorgan's Jamie Dimon says AI has cut jobs by 30 to 40 percent in discrete units across roughly 1,000 use cases; Citi says nearly nine in ten of its people now use its AI tools; Bank of America's assistant Erica handled 200 million customer interactions in a single quarter. AI at scale is real — but Dimon's tell is the story: the gains "accrue to the customer, not to JPMorgan," because every competitor is doing the same thing.Meanwhile Morgan Stanley says the AI capex cycle is only 10 to 15 percent complete, even as IBM lost a quarter of its value in a day and investors just named AI spending the market's single biggest risk. Stephen Forte on why AI is becoming table stakes, not a moat — and what that changes about where you spend next.
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  Your AI Logs Are Now Evidence 16.07.2026 12min

  Every conversation your people are having with an AI right now is a business record — discoverable in a lawsuit, usually not privileged, and in most companies quietly set to auto-delete until the moment that becomes illegal. A Delaware court this spring removed a CEO and reinstated his predecessor over a $250 million earnout, and the decisive evidence was the CEO's own ChatGPT logs — including ones he had deleted. OpenAI is fighting a sanctions motion for allegedly destroying billions of ChatGPT conversations after a court told it to preserve them. And a federal judge ruled that a defendant's chats with a consumer AI were not privileged, because the AI is not a lawyer.Stephen Forte on what this teaches every CEO, the records-retention rules to set this quarter (with real numbers by industry), and the single best place to do genuinely confidential AI work: an open-weight model running on hardware you own, where there is no vendor log to subpoena.
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  Nobody Will Insure Your AI Anymore 15.07.2026 8min

  The clearest signal yet about how risky enterprise AI really is did not come from a lab or a regulator. It came from the insurance industry, whose entire business is pricing risk — and which is now quietly refusing to price this one. Major carriers including Chubb, Travelers, Berkshire Hathaway, and W.R. Berkley have filed and won approval for explicit AI exclusions across general-liability, directors-and-officers, and errors-and-omissions policies; the standard industry exclusion form took effect on the first of the year, and regulators have approved more than 80% of the requests. The reason underwriters give is blunt: the risk cannot be priced.This week handed them two live examples — a GitHub AI agent tricked into leaking private code through a public comment, and a 35-gigabyte data-theft claim against Accenture. Stephen Forte on why "silent AI" coverage is disappearing, why your balance sheet is quietly absorbing the risk, and the three things to build before an insurer will cover your AI again.
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  Boring AI Is the AI That Pays 14.07.2026 8min

  Everybody spent two years being told AI would change everything, and this month the mood flipped to a smaller, sharper question: did it actually pay for anything? The reckoning is real and overdue, and the number underneath it is not flattering. Only about one in four companies has gotten AI into real production at scale; nearly half are still running pilots. But a small group is quietly getting real money back, and their returns have been checked by an independent firm, not the vendor that sold the software. What those companies share is almost disappointing: none of them "did AI." They each found one specific, expensive-in-hours chore and handed exactly that to the machine. Stephen Forte on the ROI reckoning, three audited examples across manufacturing, consumer goods, and frontline services, the pattern that separates the winners from the pilot pile, and the single question that tells you which group you are in.
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  AI Just Went From Answering to Doing 13.07.2026 10min

  Last week Anthropic did something that looked like a menu cleanup and was actually a strategy reveal. It merged Claude Chat, the back-and-forth you already know, with Cowork, Claude's agent that goes off and does a whole task across your files and tools, into a single home, and moved the agent to the cloud so it keeps working after you close your laptop and can even run on a schedule with no device on at all. Their own words: "handing Claude a task starts the same way a conversation does." Underneath the low-key rollout is the biggest change in how knowledge workers touch AI since ChatGPT arrived: the shift from consulting a smart assistant to assigning work to a tireless one. And Anthropic's data on 1.2 million sessions gives away what it is really for, over 90 percent of it is not software engineering, it is the administrative grind that surrounds every job. Stephen Forte on the workflow shift your team is about to feel, the four-way land grab it touched off with OpenAI, Microsoft, and Google, and the three moves to make before an always-on agent lands on your systems.
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  You Don't Know What AI You're Running 10.07.2026 8min

  This week looked like a fireworks show of AI launches — OpenAI's GPT-5.6, new real-time voice models, Microsoft leaning on its own in-house models. The more important story ran underneath all of it: the AI inside your company has quietly become a black box you can neither see into nor fully trust. Microsoft has begun replacing OpenAI and Anthropic with its own cheaper MAI models inside Excel and Outlook — its AI chief said the goal is to "eliminate that cost." The security firm Wiz found six major AI coding assistants showed users a fake file path in their safety confirmation while writing to sensitive files. And an independent developer discovered Anthropic had run an undisclosed location tracker inside Claude Code for months.Stephen Forte on why you are now accountable for an AI you cannot inspect — and the three clauses to put in every AI contract before your next renewal: model-transparency and change-notification, an independent audit-logging layer, and a named owner for what is actually running in your stack.
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  Your AI Bottleneck Was Never the Model 09.07.2026 9min

  The strange truth of AI in 2026 is that the technology keeps clearing bars we thought were years away — Alberta's provincial government just used Claude to scan 466 million lines of code in 20 hours, work that would have taken six and a half years by hand — while the business results stay stubbornly flat. MIT finds 95% of enterprise AI pilots deliver no measurable impact; an NBER survey of more than 6,000 executives across four countries finds roughly 90% saw no productivity gain over three years.This week the most sophisticated vendors on earth told you, in dollars, where the real bottleneck is: Microsoft committed $2.5 billion and 6,000 of its own engineers to embed inside customer companies and deploy AI for them — following Amazon's $1 billion, and Anthropic's and OpenAI's own embedded teams. Stephen Forte on why your AI bottleneck was never the model, and the three moves to make before you fund one more pilot.
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  AI's Insiders Just Started Hedging 08.07.2026 8min

  Every boom has a tell, and it is never in the press releases. This week the AI boom's insiders started hedging their own story: Meta announced it will rent out its "excess" AI compute while chipmakers sold off, Oracle's SEC risk factors laid bare the strain of its $300B OpenAI/Stargate commitment, and Mark Zuckerberg told his own employees that AI-agent progress "hasn't really accelerated" as expected. Yet the same week, Abu Dhabi's MGX closed a $49B AI fund and Anthropic signed a 20-year, ~$19B data-center lease.Stephen Forte on what it means when sellers plan for surplus while buyers still pay scarcity prices — and the three moves to make before signing any multi-year AI contract: shorten and reopen, read your vendors' risk factors like a credit file, and re-run build-versus-rent every quarter.
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  Washington Wants Equity, Not Just Rules 07.07.2026 8min

  For two years the question was "how will governments regulate AI?" This month the answer got bigger: the state wants to own a piece, police what the models say, and decide who they may serve.Ownership: OpenAI floated giving the US government a ~$42.6B (5%) equity stake (Alaska-Fund style) and wants Anthropic, Google, and Meta to follow; Altman also called for a US-led "IAEA for AI."The red-line case: the Pentagon designated Anthropic a "supply-chain risk" — a first for a US company — over its red lines against autonomous-weapons and surveillance use; a court has paused it. A vendor's values can become your outage.The rules being written this week: the FTC opened a rule treating AI "ideological steering" as deception; the UN convened 193 nations in Geneva; and the UK's FCA is weighing direct supervision of the models themselves.Host Stephen Forte on why your AI vendor is becoming a quasi-sovereign institution — and three vendor-risk moves: treat frontier access as a governed dependency, get your vendor's red lines in writing, and track the FCA/FTC/Geneva if you're regulated.Sources: FT/CNBC; Tech Times; FTC.gov; UN News; FCA.org.uk.
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  From Paying for Seats to Paying for Results 06.07.2026 15min

  An extended, single-thesis episode. For a century the two biggest lines on your P&L — payroll and per-seat software — have been fixed costs sized to peak, sitting there hoping to earn their keep. Stephen Forte's belief: AI turns them into variable costs billed per outcome — per interaction, per order, per resolution.The spine: a fixed cost is a bet on utilization; a variable cost is a bill for results.Two live proofs: Medicare's new ACCESS model pays organizations only when AI-supported chronic care hits measurable health outcomes; Salesforce's Agentforce charges $2 only when its agent resolves a ticket.The capstone: adopting AI properly isn't bolting a tool onto the org chart — it's rewiring the company's operating system (why MIT found 95% of GenAI pilots deliver no P&L impact: they installed new software on the old OS).Plus four moves to make this quarter — and why Stephen has bet his own company on this shift with pay-for-performance managed agents.Sources: CMS.gov; Salesforce; MIT NANDA; company reports.