ADVERTISE | PODCASTS | EXECUTIVE’S PASS | B2B TRAINING | | | | Hey | Welcome to The AI Report — the #1 AI newsletter for business leaders. | You don’t need to be technical. Just informed. | • 1. 🤓 Understand the trends between consumers and AI with Adobe
• 2. ⚡️ Claude adds watermarks to AI text
• 3. 💼 Your Business Briefing
• 4. 🧭 Turn your AI roadmap into reality with ClickIT
• 5. 🤝 The Human & AI De Brief with Marie-Lou
• 6. ✍️ Today’s Policy Corner
• 7. 🗞️ The News Bulletin | Are you ready to launch AI transformation for your company? | |
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| TOGETHER WITH ADOBE | | AI Traffic to U.S. Websites Continues to Soar | | AI is rapidly becoming a primary interface between consumers and brands, as shoppers turn to LLMs to research specific products or locate deals. | Recent Adobe data highlights AI’s growing impact across major U.S. industries: | Retail: Between Oct 2024 and May 2026, AI traffic to retail sites (measured by consumers clicking on a link) grew a staggering 1,324%. In May, AI traffic also converted 54% better than non-AI channels like paid search or email. The categories that experienced the most growth included toys, baby and toddler products, apparel, pet products, home & garden and personal care products. Travel: AI-driven traffic delivered 21% higher engagement in May 2026, with visitors lingering longer and browsing more content on site. Hotels and car rentals were the top categories, with cruise brands only 2% behind car rentals. Financial Services: In May 2026, AI-referred visitors were 18% less likely to bounce compared to non-AI traffic. The dominant topics included banking recommendations for checking and savings accounts and understanding complex financial topics and products.
| AI-powered services are helping consumers shop with greater confidence. As it becomes the new battleground for attention, brands must ensure their products are visible and accurately represented across AI surfaces. | |
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| | Latest in AI | | | Claude adds watermarks to AI text | 🚨 Our Report | Anthropic is embedding machine-readable marks into text and images generated by Claude, a step toward complying with E.U. rules that require AI companies to label AI-produced content. The watermarks are invisible to humans but allow platforms and users to identify when content was created by Claude. | 🔓 Key Points | Text from supported Claude models carries an embedded watermark that travels with content when copied and pasted and may survive some degree of editing, according to Anthropic. For images, Anthropic is applying signed provenance metadata using the C2PA open standard, the same system used by Adobe, OpenAI, and Google for AI content labeling. The marking system covers Claude Platform (API), Claude, Claude Code, Claude Cowork, and Claude Tag, plus supported models running through AWS, Google Cloud, or Microsoft Foundry.
| 🔐 Relevance | The E.U. AI Act's Article 50(2) transparency requirements took effect August 2, with existing AI products carrying a four-month compliance grace period. For enterprise teams using Claude in customer-facing workflows, this changes the disclosure calculus. Watermarks could surface in client deliverables, marketing content, or internal documents if detection tools become widespread. Anthropic has cautioned the system is not fully conclusive: heavy editing, short passages, or format conversions can strip marks, and detected marks only signal content may have been processed by Claude, not authored by it. | |
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| | The AI Report Podcast | | |  | Find the People Who Already Believe in Your Idea |
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| | AN UPDATE ON OUR NEWEST PARTNER | | Hand Off What's Eating Your Week | | BlueMoso and CSMoso are live inside the AI Executives Pass, real people who handle the work that's eating your time, not another tool to manage. | Pass members get 10% off their first two months, priority matching, and free access to their Human in the Loop Playbook. | Plus, access to 23+ partner deals and resources. | $14,000 value for $199/yr. | | Already a member? Book a call here. |
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| | THE BUSINESS BRIEFING: IT & OPERATIONS (powered by Upscaile) | | Zipline (drone delivery, U.S. and Africa operations) was drowning in 100+ daily IT tickets with a lean support team. During high-volume periods like intern onboarding, that number hit 200. Tier-1 requests consumed hours as staff dug through past tickets and manually provisioned access across 30+ apps. They deployed Risotto to handle intake, autosolve routine requests, and grant access based on pre-approved Okta rules. | Tool used: Risotto -- Slack-native AI help desk that automates ticket resolution and access provisioning. | Result: 64% of IT tickets now autosolved or advanced by AI. 100% access grant automation rate. Thousands of hours saved in employee wait time. Team went live in 6 weeks. | The lesson: The IT lead was self-described "AI skeptic" who rejected vendors claiming near-100% automation. He chose a system with clear audit trails and human escalation paths. AI handled Tier-1; humans finished what AI couldn't. That division of labor is what made adoption stick. | Steal this: Identify your top 5 repetitive IT requests this week. Map each to a runbook with clear resolution steps. Start with one that has a binary outcome (password reset, access grant) and test AI automation there first. Build trust before expanding scope. | |
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| | | | THE HUMAN & AI DE BRIEF | | My team is using AI to collaborate. So why does something feel off? | | Sara and Tom were working on a shared project across time zones and professional languages. AI made it possible to move fast. It also made it possible for them to never actually meet — not in the way that matters. | What disappeared wasn’t the collaboration. The collaboration functioned. What disappeared was the shared pride of building something together. And neither of them noticed until it was already gone. | The smoothness is the problem. This week on the AI Report blog, what happens when we optimize away the friction that makes work feel like something worth doing together — and what it’s actually costing your teams. | |
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| | THE POLICY CORNER | | Colorado's new AI disclosure law takes effect January 1, 2027, replacing the controversial 2024 Colorado AI Act. | Governor Polis signed SB 26-189 on May 14, 2026, repealing the original Colorado AI Act and creating an entirely new compliance framework for automated decision-making. Any business using AI to "materially influence a consequential decision" in employment, housing, financial services, insurance, or health care must now disclose that use with a clear, conspicuous link next to the user action. When AI contributes to an adverse outcome, you have 30 days to notify the affected consumer and provide a human appeal option where "commercially reasonable." | Deadline: January 1, 2027. Businesses using AI for covered decisions should have disclosure systems ready by Q4 2026. | Risk: Documentation requirements now extend to ADMT developers, not just deployers. Failure to provide human appeal pathways or proper disclosures exposes businesses to enforcement actions under Colorado's consumer protection authority. | Your move: Audit every customer-facing workflow where AI influences decisions in covered areas. Map each to the new disclosure requirements and identify where human review processes need to be built or formalized before year-end. | |
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| | AI News | | 🎵 Spotify labels AI-generated artists, bans them from recommendations: Starting mid-September, "AI Persona" badges will flag fake artists and exclude their music from editorial and algorithmic playlists unless users explicitly follow them. FULL STORY 🌍 Google's Gemini app hits 1 billion monthly users: The fastest-growing product in Google's history now generates 150M+ images daily and sees 63% of users interacting via voice. FULL STORY 💰 OpenAI completes $7B employee tender offer at $852B valuation: The buyback provides liquidity without an IPO, signaling the company may delay its public debut while focusing on enterprise growth. FULL STORY ✈️ Ryanair signs five-year Google Cloud deal for AI-powered operations: Europe's largest airline will deploy Gemini and DeepMind models for crew scheduling, maintenance planning, and weather decisions across 35,000 employees. FULL STORY
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| | *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? | |
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| | The Money: Mega-rounds flow to AI infrastructure, not models | | Two of the week's largest AI investments bypassed foundation models entirely. Capital is clustering around companies solving enterprise deployment bottlenecks: training customization and security governance. As agentic AI moves into production faster than controls can keep up, investors are backing the picks-and-shovels layer. | Deals to know: | River AI (Seed/Series A, $1.1B) -- Neocloud for enterprise RL and LoRA fine-tuning on open models. Promises complex training runs in 15-20 minutes with no infrastructure team. Investors: General Catalyst, AMP PBC, Nvidia, AMD Ventures, Y Combinator, Temasek Team8 Fund III (Fund close, $365M) -- Early-stage AI-native enterprise companies across cybersecurity, infrastructure, and fintech. Survey of 111 CISOs found 80% running AI agents in production while security confidence averaged 2.32/5. Investors: Institutional LPs
| Signal: Smart money sees the next constraint isn't model capability. It's enterprise readiness: training customization for non-AI teams and governance controls for production agents. |
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