Backlog-funded AI capacity, deep bundles and trust position the company to double enterprise value by 2030 if execution sustains. Custom silicon and regulation are the swing factors.

Leaning into the compute flywheel, Microsoft can compound Azure + Copilot + Security into a larger recurring platform by 2030, monetizing AI at scale through distribution, bundling and backlog-driven capacity while protecting trust and margins.

Owns distribution, trust, and hyperscale compute to monetize AI where cognition commoditizes; strong network capital and backlog-funded capacity.

Method: revenue. Inputs: FY25 revenue 281,700; 2025 IT TAM ≈ 5.45T; assume 2030 TAM 8.0T and MSFT penetration 8.8% → 2030 revenue 700,000. Revenue bridge (USD-m): 281,700 → Azure scale +200,000 → price/mix (AI services) +60,000 → new SKUs (Copilot/Security/Windows AI PCs) +90,000 → new segments/geos +30,000 → partnerships/JVs (incl. OpenAI-led demand) +35,000 → other +3,300 = 700,000. Assume 2030 EV/Rev 12× (below today’s ~13× given scale; peer anchors AMZN/GOOGL high-single-digit). EV_2030 = 8,400,000. Current EV ≈ market cap 3,820,000 + net debt (debt–cash) −51,400 = 3,768,600. Implied 8,400,000 / 3,768,600 ≈ 2.2× by 2030.

Key risks: sustained capex intensity vs ROI; custom-silicon delays; regulatory constraints on bundling/OpenAI; GPU/energy supply bottlenecks; inference cost curve; hyperscaler competition. Offsets: backlog visibility, distribution, and integrated security/AI bundles.