Everyone Thinks AI Will Destroy Adobe's Business. Here's Why It Could Flourish Instead.

Adobe shares have been hit by AI-driven pessimism—down about 21% since ChatGPT's debut and 23.5% year-to-date with short interest at an eight-year high—yet the company has posted consistent growth across key fundamentals: fiscal-year revenue rose from $17.61B (2022) to $23.77B (2025), net income climbed from $4.76B to $7.13B, and EPS increased from $10.10 to $16.70. Management is positioning Adobe as an AI beneficiary (CEO called it “the biggest opportunity for Adobe in decades”), citing strong AI integration across Creative/Document/Experience Clouds, record >$1M deal bookings in Q4 and a 25% increase in $10M+ ARR customers, while returning capital via >70M share repurchases since 2022 (410.5M shares outstanding). The piece argues the market may be overly pessimistic and presents Adobe as a contrarian, moderately attractive speculative opportunity given improving fundamentals, accelerating enterprise deals, and aggressive buybacks.

Analysis

Market structure: Adobe is benefiting from enterprise AI demand (AEP adoption ~70%, record >$1M bookings, +25% clients >$10M ARR) while smaller AI-native content substitutes face monetization and retention headwinds. Adobe’s aggressive buybacks (≈70M shares since 2022; ~17% of float) and rising ARR suggest tighter free float and sustained pricing power, supporting revenue-to-EPS conversion even with headline multiple compression. AI hardware/cloud winners (NVDA, cloud providers) also gain, so capital is rotating within tech from speculative consumer AI apps toward enterprise software + infra.

Risk assessment: Tail risks include copyright/regulatory rulings that constrain training-data use, rapid commoditization of basic creative tasks reducing ASPs, or a short-squeeze volatility spike given eight-year high short interest. Time buckets: days—high gamma and headline risk; weeks/months—earnings and AEP adoption metrics; quarters/years—structural ARR upside if Adobe converts enterprise spend into higher ARPU. Hidden dependencies: Adobe’s margins hinge on cloud compute costs and partner integrations (OpenAI/Anthropic deals), and buybacks amplify volatility.

Trade implications: Favor idiosyncratic long exposure to ADBE with volatility-aware option overlays and selective allocation to NVDA for infra exposure. Use collars/LEAPs to own upside while capping near-term downside; avoid unhedged longs in small-cap AI content firms. Sector tilt: overweight enterprise software and AI infra, underweight speculative consumer AI/small-cap content generators.

Contrarian angle: The market has priced in obsolescence but ignored measurable enterprise adoption (AEP, >$10M ARR clients +25% YY) and float shrinkage from buybacks—classic setup for mean reversion. Historical parallels: durable incumbents (MSFT in cloud, ADBE in creative suites) initially oversold in new tech cycles then re-rate as monetization proves out. Watch for unintended consequence: rapid third-party integrations (e.g., OpenAI partnerships) that both lower entry friction for competitors and expand Adobe’s platform moat by embedding AEP into enterprise stacks.

Key Decisions for Investors

• Establish a staged long position in ADBE equal to 2–3% of portfolio: deploy 50% immediately, add 25% if ADBE drops another 10% from current levels, add remaining 25% at -20%; target holding period 12–24 months and trim half on a +30% price move or if FY revenue growth decelerates by >300 bps versus consensus.
• Implement an options collar to own upside while limiting near-term downside: buy 12-month (Jan 2028) LEAP calls ~25–30 delta (e.g., Jan 2028 $330 calls) sized to fund upside exposure, and sell 3–6 month 20–30% OTM calls to finance; alternatively buy 6-month 10% OTM puts and sell 6-month 25% OTM calls to reduce cost if premium is high.
• Overweight NVDA (PCI to AI infra) by +1–2% while underweight speculative small-cap AI content names by -50% relative to benchmark; prefer capital allocation to enterprise software (ADBE) + infra (NVDA) versus consumer AI apps where monetization and retention are unproven.
• Use hard catalysts to adjust exposure: add 25% if next quarter shows AEP eligible-customer usage >70% and >20% YoY growth in clients with >$10M ARR; cut 50% if bookings of >$1M deals decline quarter-over-quarter or if regulatory action materially limits training-data usage within 60–120 days.