export default function AiInvestmentViewPointsPage() { const highlights = [ { emoji: "🎯", title: "From Story to Proof", desc: "The market now asks for monetization, ROI, and durable moats, not AI slogans." }, { emoji: "⚖️", title: "Clearer Winners and Losers", desc: "AI beneficiaries are separating from thin software layers with weak defensibility." }, { emoji: "🔁", title: "Business Model Rewrite", desc: "Software is shifting from seat pricing to agent and outcome-based economics." } ]; const crossConferenceSignals = [ "AI spending is judged by payback, not by narrative momentum.", "Compute is treated as productive capacity tied to token and inference revenue.", "Coding remains the strongest early enterprise AI use case with visible ROI.", "The path is moving from copilots to autonomous agents, then to physical AI.", "Durable value is moving toward workflow ownership, proprietary data, and trust." ]; const companyTakeaways = [ { company: "Anthropic", thesis: "Model progress is still accelerating; coding is the enterprise beachhead.", investorRead: "Capability growth and real demand suggest runway for monetization." }, { company: "NVIDIA", thesis: "Agentic adoption is fast, and compute is directly linked to revenue creation.", investorRead: "Infrastructure is becoming productive capital, not pure IT expense." }, { company: "Microsoft", thesis: "Work is moving toward a headless, agent-driven operating model.", investorRead: "Value can scale beyond seat count through workflow orchestration." }, { company: "Meta", thesis: "AI is already improving ad performance with a disciplined infra strategy.", investorRead: "Real monetization now, while LLM use is deployed selectively." }, { company: "Alphabet", thesis: "AI is expanding Search engagement while broadening platform bets.", investorRead: "Massive capex is defended by scale, utilization, and ecosystem growth." }, { company: "AMD", thesis: "AI hardware demand is broadening where efficiency and TCO matter.", investorRead: "Alternative compute supply is valuable as AI deployment diversifies." }, { company: "SAP", thesis: "Enterprise AI compounds inside systems of record and core workflows.", investorRead: "Incumbents with mission-critical data can defend and extend moats." } ]; const winners = [ "Frontier labs with enterprise traction", "Compute and infrastructure leaders", "Hyperscalers turning capex into platform revenue", "System-of-record software firms embedding AI into operations", "Platforms controlling data, workflow, and distribution" ]; const risks = [ "Thin interface-only software layers", "Products built on mostly public information", "Seat-based SaaS with weak AI adaptation", "Offerings without proprietary workflow or data advantage", "Low-integrity tools in high-trust enterprise domains" ]; const timeline = [ ["Phase 1", "Copilots improve human productivity."], ["Phase 2", "Agents execute tasks with less manual interaction."], ["Phase 3", "Physical AI extends into robotics and industrial workflows."] ]; return (

AI Investment Lens

2026 TMT Signal: AI enters the prove-it era

This page distills the article into one practical question for investors: which companies can convert AI capability, infrastructure, and workflow control into durable earnings power?

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Cross-conference signals

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Company-by-company takeaways

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Likely winners

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Most exposed

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Adoption sequence

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