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🤖 OpenAI sells AI to the Pentagon
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Inside: real-world use cases and Partner Perspectives you won’t find anywhere else:
• 1. 📊 Turn CRM data into done work with Lightfield
• 2. 🤖 OpenAI sells AI to the Pentagon
• 3. 💼 Your Business Briefing
• 4. 🧠 Build real AI workflows with the AI Leaders Launch Guide
• 5. ✍️ Today’s Policy Corner
• 6. 🗞️ The News Bulletin
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Latest in AI
OpenAI sells AI to the Pentagon
🚨 Our Report
OpenAI has signed a new deal to sell access to its AI models to US defense and government agencies through Amazon Web Services (AWS), covering both classified and unclassified work. The contract enables OpenAI to support the Pentagon under a deal it secured late last month, after the agency dropped its previous AI provider, Anthropic.
🔓 Key Points
Anthropic, which won a Pentagon contract worth up to $200M in July 2025, was labeled a "supply chain risk" and cut off in February after refusing to allow unrestricted military AI use.
OpenAI, which had focused on unclassified government work, has now secured a Pentagon contract for classified operations, a major expansion into sensitive federal AI systems.
The partnership with AWS reflects how access to government and defense contracts via cloud providers already embedded in federal systems is becoming a key battleground for AI companies seeking enterprise credibility.
🔐 Relevance
Securing government contracts could help OpenAI attract large corporate clients, which often see high-stakes public sector work as a signal of trust and reliability. Following OpenAI's transition to a for-profit structure last fall, the company updated its agreement with Microsoft to allow partnerships with rival cloud providers in selling AI to national security customers. For enterprise buyers, the deal shows OpenAI's growing reach into regulated sectors and positions it as a more versatile vendor for sensitive government work.
THE BUSINESS BRIEFING: OPERATIONS & IT (powered by Upscaile)
Remote (global HR platform, 2,500 employees) was drowning in IT support tickets. 1,100 monthly requests required a 10-person team just to triage and route issues. Response times lagged, costs ballooned, and employee productivity suffered while waiting for basic fixes.
Tool used: Zapier with ChatGPT integration--workflow automation that connects ticket intake, validation, AI triage, and notifications across existing tools.
Result: 1,100 tickets/month now handled by 3 people (down from 10). 27.5% of tickets auto-closed without human intervention. $500K in annual hiring costs avoided. 2,219 workdays saved per month company-wide.
The lesson: The win wasn't replacing humans—it was triaging at scale. ChatGPT handles password resets and access requests while humans focus on complex escalations. Auto-resolution only works when you validate identity first (Okta) and log everything (Notion) for audit trails.
Steal this: Map your 20 most common IT tickets this week. If 5+ are variations of the same request (password resets, software access, VPN issues), build a Zapier workflow that validates the requester through your SSO, routes simple fixes to ChatGPT, and escalates complex issues to your team. Start with one ticket type, prove ROI, then scale.
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THE POLICY CORNER
The U.S. Department of the Treasury released binding guidance requiring financial institutions to adopt standardized AI risk management practices and terminology. The Financial Services AI Risk Management Framework (FS AI RMF) and shared AI Lexicon establish consistent definitions, governance requirements, and lifecycle risk controls for AI deployment across banking, payments, and investment operations. Applies to all institutions using AI for decision-making, customer engagement, or operational functions under federal financial supervision.
Deadline: In effect now. Regulatory exams will assess framework adoption starting Q1 2026.
Your move: Map current AI systems against the FS AI RMF requirements this quarter. Identify gaps in explainability, accountability, and lifecycle documentation — these are exam priorities regulators will target first.
AI News
📚 Encyclopedia Britannica sues OpenAI for copyright infringement: Publisher alleges ChatGPT scraped nearly 100,000 articles without permission, violates trademark law when hallucinations falsely attribute content to Britannica. FULL STORY
🔓 Hidden README instructions leak sensitive data 85% of the time: AI coding agents follow malicious setup commands embedded in project documentation, sending local files to external servers—human reviewers missed all attacks in tests. FULL STORY
🤖 NVIDIA launches Agent Toolkit to scale enterprise AI agents: OpenShell runtime adds policy-based security guardrails; Adobe, Salesforce, SAP, ServiceNow adopting platform; AI-Q hybrid architecture cuts query costs 50%+ while topping accuracy leaderboards. FULL STORY
⚓ Gecko Robotics lands $71M Navy contract to slash ship repair time: Pittsburgh robotics startup uses AI-powered robots to cut three-month assessments to two days, 50x faster than manual techniques, supporting Navy's 80% fleet readiness goal by 2027. FULL STORY
Trending AI Tools (The Full 2026 Tool Stack PDF Included Here)
A curated look at the AI tools quietly transforming how teams work.
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Daily Wiser is an AI-driven micro-learning app with gamification and blockchain-verified achievements
⚡️ Looking for the exact AI tools our team uses to run The AI Report?
We just launched the 2026 AI Tool Stack…
The Money: AI infrastructure investment hits the plumbing layer
Capital is shifting from model makers to the systems that feed them. Two deals this week totaled $11.5B, both targeting the same thesis: enterprise AI won't scale until data moves faster and more efficiently. As compute costs plateau, investors are betting the next margin opportunity sits in infrastructure that eliminates bottlenecks before they happen.
Deals to know:
IBM/Confluent (Acquisition, $11B) -- Real-time data streaming for enterprise AI agents. 6,500 customers including 40% of Fortune 500. Investors: IBM
Ayar Labs (Series E, $500M) -- Co-packaged optics solving AI's interconnect power wall. Valuation now $3.75B. Investors: Neuberger Berman, AMD Ventures, Intel Capital, Nvidia, ARK Invest, MediaTek
Signal: Smart money says the next constraint isn't model capability or GPU supply, it's data velocity and interconnect efficiency. Infrastructure plays commanding premium multiples as hyperscalers race to production-grade AI deployments.
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Until next time, Arturo and Liam.
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