Better AI Software Stock: Figma vs. Adobe

Adobe has folded AI into its stack (Firefly plus integrations with 25+ models), driving a 15% YoY rise in monthly active users in FY2025 and record fiscal Q4 revenue of $6.2 billion (from $5.6 billion) with net income of $1.9 billion (vs. $1.7 billion). Figma, newly public, is embedding AI via Figma Make, the Weavy acquisition and a ChatGPT partnership, producing Q3 revenue of $274.2 million (+38% YoY) but a $1.1 billion net loss largely from IPO-related stock-based compensation; 30% of customers with ≥$100k ARR use Figma Make weekly. Given Adobe's stronger profitability, large-account booking growth (>25% YoY in $10M+ ARR customers) and a materially lower price-to-sales multiple than Figma, the piece argues Adobe is the more attractively valued and fundamentally resilient software investment despite AI disruption risks.

Analysis

Market structure: Incumbent platform owners with enterprise contracts and proprietary training data (ADBE) are the primary near-term winners; they can package AI as a sticky value-add and upsell larger ARR customers (Adobe reported >25% YoY growth in >$10M ARR customers). Fast-growth pure-play design SaaS (FIG) benefits from viral developer & API channels (OpenAI tie‑ins) but faces higher valuation risk as generative models commoditize point tools. Cross-asset: stronger large-cap software earnings tighten IG spreads and lower skew in ADBE options while keeping FIG implied vol elevated; GPU/semiconductor names (NVDA) remain a positive lever for compute scarcity and margin pressure on smaller AI incumbents.

Risk assessment: Key tail risks are regulatory (EU/US suits over model training/copyright within 3–18 months), antitrust (resurgence of merger scrutiny), and margin squeeze from rising compute costs (NVDA pricing) that could compress software gross margins by 200–500bps over 12–24 months. Short-term (days–weeks) moves will be earnings/feature-driven; medium-term (3–12 months) depends on enterprise renewals and ARR expansion; long-term (1–3 years) hinges on who owns customer workflows+data. Hidden dependency: reliance on third‑party models (OpenAI) and on-prem/cloud GPU supply chains are single points of failure for product road maps.

Trade implications: Favor capital-efficient, asymmetric exposure: bias long ADBE (durable cashflows, cheaper P/S) and short FIG on relative valuation; express via dollar-neutral pair trades or ADBE call spreads versus FIG short-dated puts if FIG vol is rich. Size positions to risk: initiate 2–4% net long ADBE exposure, 1–2% short FIG or equivalent notional, hold 6–12 months, trim on +20% move. Use 12–18 month call spreads on ADBE to capture re-rating while selling near-term FIG calls to harvest vol.

Contrarian angle: Consensus underestimates the pace at which enterprise procurement votes; Adobe’s enterprise tenures and $1M+ bookings create higher switching friction than retail AI demos suggest — the market may be over-penalizing ADBE. Conversely, Figma’s premium P/S assumes rapid margin expansion and profitable scale; if stock-based comp or customer churn persists, downside could be 30–50% from current levels. Historical parallel: incumbent re‑rating after platform AI upgrades (Microsoft in cloud era) — winners were those who monetized enterprise workflows, not the flashiest apps. Unintended consequence: regulatory action that limits model training sets would advantage companies with licensed/owned assets (ADBE) and punish open‑data reliant players (some FIG workflows).

Key Decisions for Investors

• Establish a 2–4% portfolio long in ADBE within 2 weeks, targeting a 12‑month upside of ~20–30%; add another 1–2% on any >12% pullback; set a tactical stop-loss at 12% below average cost and reassess if quarterly net retention falls >300bps.
• Implement a dollar‑neutral pair: long ADBE (2.5% notional) and short FIG (1.5% notional) to exploit valuation gap, hold 6–12 months; unwind if FIG reports sequential revenue acceleration >5% QoQ or if ADBE net new ARR growth decelerates >200bps.
• Buy a 12–18 month ADBE call spread sized to 1–2% of portfolio (buy LEAP call, sell higher strike to fund cost) to express asymmetric upside from AI monetization while avoiding outright delta risk; target >2x payoff, cap loss to premium paid.
• Trim or avoid funding additional exposure to FIG until one of: (a) FIG reports two consecutive quarters of positive EBITDA/CFO conversion, or (b) FIG P/S falls below 10x LTM sales (a ~30–50% valuation compression from current); re-evaluate on those triggers.
• Monitor regulatory catalysts: track EU/US copyright/regulation developments and any FTC/EC inquiries over the next 60–180 days—if formal investigations into model training are opened, increase ADBE sizing by 50% and reduce FIG exposure by 50% within 2 weeks of announcement.