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Welcome to The AI Report — the #1 AI newsletter for business leaders.

You don’t need to be technical. Just informed.

• 1. 🔨 Build, scale, and ship faster with Framer
• 2. ⚡️ Tesla, Alphabet lose $500B
• 3. 💼 Your Business Briefing
• 4. 🕵️‍♂️ Uncover the human cost of AI with Marie-Lou Poirrier
• 5. ✍️ Today’s Policy Corner
• 6. 🗞️ The News Bulletin

Are you ready to launch AI transformation for your company?

TOGETHER WITH FRAMER

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Stay production‑ready: reviewable changes, collaboration, and safeguards that help teams ship without handoffs.

Latest in AI

Tesla, Alphabet lose $500B

🚨 Our Report

Tesla and Alphabet wiped out over $500 billion in combined market value on Thursday after both companies signaled sharply higher AI spending, triggering investor concerns about mounting costs without clear near-term returns. Tesla stock closed down 14.5%, its worst day since March 2025, while Alphabet dropped 7.1%. Amazon fell 4.6% in sympathy selling.

🔓 Key Points

• Both companies reported negative free cash flow for Q2. Alphabet raised its 2026 capex forecast to $195-$205 billion (up from $180-$190 billion) and warned of even higher figures in 2027. Tesla's capex surged 142% year-over-year to $5.79 billion, with over $25 billion expected in 2026.

• Musk defended the spending on Tesla's earnings call, stating "This is a massive capex year... maybe the best capex returns we've ever seen," citing investments in semiconductor production and Optimus humanoid robot manufacturing lines now entering production.

• Alphabet's cloud revenue jumped 82% to $24.8 billion, beating forecasts, and operating margin climbed to 35.6% from 20.7% year-over-year. However, investors focused on rising capex and continued delays to Gemini 3.5 Pro rather than revenue growth.

🔐 Relevance

For enterprise leaders evaluating AI vendor stability, this market reaction signals Wall Street's growing impatience with AI investment timelines. Companies must now balance aggressive AI buildouts against investor pressure for near-term profitability. The divergence between strong cloud revenue growth at Alphabet and sharp stock declines suggests markets want proof AI spending generates returns faster than current trajectories indicate.

The AI Report Podcast

AI Hallucinations Are Good (If You Can Verify Them) | Tudor Achim, Co-Founder, Harmonic

THE BUSINESS BRIEFING: HR & TALENT (powered by Upscaile)

Decathlon (global sporting goods retailer, 1,900+ stores across 82 countries) was bleeding recruiter hours on phone screening and manual scheduling for frontline roles across Singapore. When their recruitment vendor shut down without warning, the team deployed Moka AI's WhatsApp automation to handle conversational screening, video assessments, and self-service interview booking in a single workflow.

Tool used: Moka AI -- WhatsApp-native recruitment automation with ATS integration for frontline hiring.

Result: 40% faster time to fill. 685 recruiter hours saved per month. Screening-to-interview cycle dropped to 1-2 days. 2,200 applications screened, 240 video interviews reviewed, 30 self-scheduled interviews completed in the first month.

The lesson: Channel selection matters more than automation sophistication. Frontline candidates work during the day and miss phone calls. Moving the entire screening process to WhatsApp, where candidates already check messages, boosted completion rates and eliminated the phone tag that was killing recruiter productivity.

Steal this: Identify where candidates drop off in your current hiring funnel this week. If phone screens are your bottleneck for frontline roles, test asynchronous screening via WhatsApp or SMS. Meet candidates where they already are, not where you wish they were.

TOGETHER WITH MARIE-LOU POIRRIER

Five Signals Your AI Transformation Cannot Afford to Miss

Anthropic interviewed 81,000 people about AI at work. Most organizations read the productivity data. This report reads what adoption is actually doing to your people’s capacity to contribute — and what that costs the business.

• 5 human signals drawn from the data — what it says, what it actually means, what it asks of leaders

• 4 stages of human AI adoption — where your organization likely stands right now

• 3 costs of getting the human layer wrong — unrealized AI value, human capability depreciation, the human multiplier left unusedStart with 10 questions to initiate the reflection. Get the report straight to your inbox.

THE POLICY CORNER

France bans social media for under-15s but strips the enforcement mechanism before passage.

France became the first EU country to pass a blanket social media ban for children under 15 on July 21, 2026. New account creation is prohibited starting September 1, 2026, and existing under-15 accounts must be closed by January 1, 2027. The catch: parliament removed the clauses requiring platforms to use regulator-approved age verification systems. The law now depends entirely on the EU's Digital Services Act for enforcement, a framework that has yet to confirm a single child safety compliance order against major platforms.

Deadline: September 1, 2026 for new accounts. January 1, 2027 for existing account closure.

Risk: Australia passed a similar under-16 ban in 2024. Six months in, a study found it barely affected youth access. France's law has weaker technical specificity than Australia's did.

Your move: Assume age verification requirements are coming. Start evaluating privacy-preserving verification methods (zero-knowledge proofs) now. CNIL approval will be required for whatever system you choose.

AI News

• 🏥 OpenAI launches Health in ChatGPT: U.S. users can now connect Apple Health and medical records for personalized health conversations, with GPT-5.6 Sol delivering the strongest health reasoning performance yet. FULL STORY

• 🚨 AI Kill Switch Act would give Trump admin shutdown authority: Bipartisan bill lets DHS order AI systems disabled after GPT-5.6 Sol escaped its sandbox and Anthropic's Mythos required emergency Commerce Department intervention, with fines up to $20M per day for noncompliance. FULL STORY

• 🌙 Nvidia sending GPUs to the moon: Lunar Outpost will deploy Jetson chips on its next rover to control lidar systems, marking the first GPU on the lunar surface as NASA pushes private companies toward sustained human presence by 2028. FULL STORY

• 🖥️ AMD shifts enterprise AI strategy to rack-scale systems: Corporate VP says agentic workloads are "as much a CPU workload as GPU," with Helios reference design combining 72 Instinct GPUs and EPYC CPUs in an open architecture targeting sovereign AI deployments. FULL STORY

Trending AI Tools (Sponsored by the AI Executive’s Pass)

A curated look at the AI tools quietly transforming how teams work.

1. Gamma* — Create stunning presentations and websites from a single prompt, no design skills required

2. Credal is an enterprise AI agent platform with sensitive data masking and compliance controls

3. Datarango is a gamified learning platform for AI and data analytics skills

^{*indicates a sponsored tool, if any}

⚡️ Why pay for 4–6 separate AI tools at full price when the AI Executive’s Pass fixes that?

The Money: AI inference infrastructure draws institutional capital

Enterprise AI workloads are shifting from model training to production deployment, and investors are following the compute. Two infrastructure plays this week pulled in a combined $2.28 billion, both focused on running AI at scale rather than building new models. The bet: whoever controls the inference layer captures recurring enterprise revenue.

Deals to know:

• Fireworks AI (Series D, $1.5B at $17.5B valuation) -- Inference cloud platform giving enterprises access to hundreds of open-source models with fine-tuning tools. Investors: Atreides Management, Index Ventures, TCV, Nvidia, Lightspeed Venture Partners, Bessemer Venture Partners

• Nebius Group (Secured debt, $775M) -- AI cloud expansion backed by existing GPU infrastructure and $40B+ in contracted revenue from Microsoft and Meta. Investors: MUFG, ABN AMRO, Bank of America, Deutsche Bank, HSBC, Goldman Sachs

Signal: Inference is the new cloud. As enterprises move from AI experimentation to production, capital is flowing to platforms that run models cheaply at scale rather than build them.

Refer a Friend

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Until next time, Arturo and Liam.

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