‘I am not a fan of AI’: as Apple continues its push into artificial intelligence, its co-founder says the tech is not up to scratch

Steve Wozniak, Apple co‑founder, publicly said he is "not a fan" of current AI (e.g., ChatGPT/Claude), criticizing reliability and lack of emotional understanding, putting him at odds with CEO Tim Cook. Apple launched "Apple Intelligence" in summer 2024, but several flagship features remain delayed two years on, highlighting execution risks that may modestly weigh on investor sentiment toward Apple's AI roadmap.

Analysis

Wozniak’s public rejection of contemporary LLMs is a sentiment accelerant more than a technology inflection; expect a short-lived headline-driven repricing in AAPL equity and options around near-term product events (WWDC, September iPhone cycle) as investors re-evaluate timing risk on Apple Intelligence features. The meaningful second-order effect is confidence: developers, enterprise partners and some high-frequency search/assistant advertisers may pause integrations until Apple demonstrates reliability, extending monetization lag by quarters rather than days.

Competitive dynamics favor cloud-first LLM incumbents (Alphabet/Microsoft) in the next 3–12 months because delivered capability and developer mindshare compound quickly; conversely, Apple’s bet on on-device models and stricter quality thresholds benefits semiconductor fabs and SoC integrators if Apple doubles down on performance-per-watt to avoid hallucination vectors. That shift increases near-term capex intensity for upstream suppliers (TSMC, advanced packaging vendors) and could lift ASPs of higher-margin hardware SKUs if Apple ties exclusive features to new silicon.

Key tail risks: a high-profile hallucination or security incident from Apple Intelligence would amplify regulatory and litigation risk and truncate services upside for 12–24 months; the reversal scenario is also clear — a demonstrably superior, reliable on-device model shipped within 6–9 months would re-rate AAPL quickly because it preserves Apple’s ecosystem monetization leverage. Watch adoption signals (SDK uptake, third-party app integrations, enterprise pilots) over the next 2–6 quarters for confirmation.

The market consensus frames this as an Apple problem; the contrarian view is that elevated standards and slower rollout could increase stickiness and long-term differentiation, benefitting hardware suppliers and margins beyond a 12–24 month horizon if Apple keeps AI local and reliable.

Key Decisions for Investors

• Pair trade (3–9 months): Long GOOGL vs Short AAPL, equal $ exposure. Rationale: capture re-rate of cloud LLM leadership while hedging idiosyncratic Apple execution risk. Target asymmetric return: 15–25% upside if Google continues to win share with limited downside if Apple resolves issues; size to max 2–3% portfolio delta.
• Options hedge for AAPL (3–6 months): Buy AAPL puts (protective) or a put spread to limit cost. Rationale: hedge event risk around WWDC/iPhone announcements where feature misses compress services growth; cost should be <2–3% of notional to keep hedge efficient.
• Long NVDA or NVDA call spread (6–12 months): Capture accelerated inference and datacenter demand as AI workloads tilt toward accelerators. Use call spreads to define risk — fund with short OTM calls if comfortable with upside cap; position size 1–2% portfolio.
• Supply-chain play (12 months): Long TSM — structural beneficiary if Apple pivots to higher-performance on-device models requiring leading-node capacity and packaging. Treat as a core, lower-volatility exposure sized 2–4% with monitoring of Apple-specific tape-outs and foundry bookings.