Innovation Platform Identification Criteria (Wright's Law Screen)
Three-filter test to find genuine multi-decade platforms before they're priced in
ARK Invest's Innovation Platform Identification Criteria is a three-filter screening methodology developed to separate genuine multi-decade investment platforms from hype cycles. It was designed to answer the question most investors get wrong: confusing 'interesting technology' with 'investable platform.' The framework anchors on Wright's Law — the empirical observation that costs decline at a predictable rate for every doubling of cumulative production — as the primary signal of platform legitimacy.
The three criteria operate as sequential gates. A technology must pass all three to qualify as a platform worth concentrating in: it must follow a demonstrable Wright's Law cost curve; it must cut across multiple economic sectors rather than serving a single industry; and it must function as a launchpad for technologies that don't yet exist. Technologies that pass all three are not just companies — they are the enabling infrastructure for the next generation of platforms.
ARK's five current qualifying platforms are Robotics, Energy Storage, Artificial Intelligence, Blockchain Technology, and Multi-omic Sequencing. The framework also highlights convergence — when multiple platforms combine (e.g., robotics + energy storage + AI enabling both robo-taxis and humanoid robots), each platform's cost decline accelerates the others, creating a compounding effect that further widens the investment moat.
- Wright's Law cost-decline rate is the primary signal — not market size projections or revenue forecasts
- Single-sector technologies do not compound the same way as multi-sector platforms; cross-sector proliferation is a prerequisite
- The highest-value platforms enable technologies that do not yet exist, multiplying the investment thesis beyond the original platform
- Convergence between qualifying platforms accelerates each platform's individual cost curve, creating non-linear compounding
- Technology is inherently deflationary — costs fall over time and are passed through as lower prices or better performance
- Apply the Wright's Law Cost Curve filterMeasure how fast costs decline with cumulative production. A genuine platform shows costs halving at a consistent rate as production scales. If the cost-decline slope is absent or flat, the technology fails the primary filter regardless of narrative appeal.Pro tipFocus on cumulative production units, not calendar time — the cost curve is production-driven, not time-driven. AI inference costs halving roughly annually is an example of a steep, qualifying slope.WarningRevenue growth is not a proxy for Wright's Law compliance. A technology can grow revenues while costs remain sticky — that is not a platform.
- Test for cross-sector proliferationAssess whether the technology can apply to more than one industry or customer group. Multi-sector technologies create reflexive demand loops — each adopting sector drives costs further down the curve, enabling the next sector to adopt.Pro tipAsk: which three industries not currently using this technology will be transformed by it within a decade? If you cannot name three, the platform likely fails this filter.
- Test for launchpad effectDetermine whether the platform enables technologies that do not yet exist. DNA sequencing, for example, was a prerequisite for CRISPR gene editing. This criterion is what separates a platform from a merely large market — it captures the options value of unknown future technologies.Pro tipLook for 'prerequisite' relationships, not just adjacent markets. The launchpad effect generates value from platforms that haven't been invented yet.WarningThis step requires speculative judgment. Ground it in analogues — ask which prior platforms (internet, mobile, cloud) enabled their own successor technologies.
- Map convergence between qualifying platformsOnce two or more platforms pass all three filters, assess whether they are converging. Convergence compounds cost curves across platforms simultaneously. Robo-taxis and humanoid robots both require robotics, energy storage, and AI — each advance in one of the three benefits both end markets.Pro tipConvergence points are where ARK concentrates most aggressively because the cost-curve compounding becomes multiplicative rather than additive.
ARK identified DNA sequencing as a qualifying platform early because it passed all three criteria: demonstrable Wright's Law cost decline (sequencing costs fell from $100M to under $1,000 per genome in roughly 15 years), cross-sector application (diagnostics, agriculture, pharmaceutical R&D), and launchpad effect — base-level sequencing was a prerequisite before CRISPR gene editing could be developed.
By 2025, ARK identified that robo-taxis and humanoid robots share the same three underlying platforms: Robotics, Energy Storage, and AI. Each advance in any of the three benefits both end markets. Tesla, positioned at the intersection of all three, became ARK's largest conviction holding — with 90% of ARK's $2,600 Tesla price target attributed to the robo-taxi platform alone.
Cathie Wood founded ARK Invest in 2014 with the explicit mission of identifying disruptive innovation platforms before mainstream adoption. The Wright's Law Screen emerged from her observation that traditional financial analysis — built around DCF models and sector-specific benchmarks — systematically failed to capture the compounding value of platforms that reinvent cost structures across industries.
The framework draws on the work of economist Theodore Wright, who in 1936 observed that airframe production costs fell 15% for every doubling of cumulative units produced. ARK generalised this to all technology platforms: the cost-decline slope, not market size projections, is the most reliable predictor of long-run platform value. By 2025, ARK had applied this framework publicly for over a decade, accumulating a documented track record across DNA sequencing, electric vehicles, and AI inference cost curves.