Introducing Charting Disruption: Outlook for 2027 and Beyond

Innovation is moving from experimental promise to commercially scalable growth across five connected stages, creating equity opportunities beyond the largest AI companies.

• Innovation has accelerated its path to scale: the internet took about 15 years to reach 1 billion users, while ChatGPT took about three years.
• AI agents' task length at 50% reliability doubled about every seven months from 2019 to 2025, while GPT-3.5-class token prices are forecast to fall roughly 1,000-fold through 2026.
• Falling costs are expanding adjacent markets: humanoid robot costs fell about two-thirds to roughly $50,000 between 2023 and 2026, launch costs to low Earth orbit could reach $500 per kilogram by 2030, and AI-assisted drug discovery could cut preclinical selection time by 30% to 50% and costs by up to 50%.
• Physical constraints are becoming investment themes: critical resource and water supply could require more than $2 trillion by 2040, data centers could reach 20% of U.S. electricity demand by 2035, and mined demand could exceed supply by 17% to 22% across copper, lithium, and magnet rare earths in 2035.
• Market exposure remains concentrated, with the 10 largest S&P 500 constituents representing about 37% of index weight, while overlap is only 2.6% for U.S. Infrastructure Development, 2.1% for U.S. Electrification, 1.7% for Defense Tech, 1.1% for Cybersecurity, and 0.1% for Space Tech.

Takeaway: Investors can look beyond leading AI companies by targeting the resources, infrastructure, enabling technologies, and applications supporting innovation, while accounting for capacity constraints, capital intensity, and differences in theme maturity.