Disruptive-innovation asset manager led by Cathie Wood; research team including Tasha Keeney, Sam Korus and Daniel Maguire
“ARK's research suggests that global autonomous ride-hail platforms will create $14 trillion in enterprise value, based on $4 trillion in revenue during the next five years.”
The five-year horizon runs to the end of 2027. Autonomous ride-hail revenue remains orders of magnitude below the $4 trillion implied by the forecast, but the deadline has not yet passed.
“ARK's price target for Tesla is $2,600 per share in 2029, with bear and bull cases valued between ~$2,000 and $3,100 per share; nearly 90% of Tesla's enterprise value and earnings will be attributed to the robotaxi business in 2029, while electric vehicles approximate a quarter of total sales and ~10% of earnings potential.”
Disruptive-innovation asset manager led by Cathie Wood; research team including Tasha Keeney, Sam Korus and Daniel Maguire
Resolves on Tesla's share price in 2029 against the $2,600 expected-value case (bear ~$2,000 / bull ~$3,100); the robotaxi-dominated earnings mix is a secondary check.
“AI training cost declines continued at an annual rate of 70%, the cost to train a large language model to GPT-3 level performance collapsing from $4.6 million in 2020 to $450,000 in 2022. We expect cost declines to continue at a 70% rate through 2030.”
Runs through 2030; ARK itself raised the assumed decline rate to ~75%/year in Big Ideas 2024.
“AI should increase the productivity of knowledge workers more than 4-fold by 2030. At 100% adoption, AI could increase global labor productivity ~$200 trillion, dwarfing the ~$32 trillion in total knowledge worker salaries.”
Resolves at the end of 2030; measured productivity gains to date are far below a 4x trajectory.
“Based on a 70% annualized drop in training costs and feedback loops, AI coding assistants like Copilot could increase the output of software engineers ~10-fold by 2030.”
Resolves at the end of 2030; ARK's own 2023 report put the then-current coding-assistant gain at roughly 2x.
“As companies generate profound productivity gains from artificial intelligence, we estimate that software spend per year could grow at a 42% compound annual rate from just under $1 trillion today to $14 trillion in 2030; propelled by AI software, total IT spend could increase 20% at an annual rate and surpass $20 trillion, four times the ~$5 trillion consensus estimate.”
Resolves at the end of 2030; ARK has since trimmed the figure to roughly $13 trillion of 2030 software spend in later research.
“The convergence of hardware and software could drive AI training costs down by 75% at an annual rate through 2030 — accelerated compute hardware reducing relative-compute-unit production costs by 53% per year while algorithmic enhancements lower training costs a further 47% per year.”
Runs through 2030; ARK has continued to cite roughly 75%-per-year training-cost declines in later Big Ideas editions.
“ARK's research suggests that autonomous ride-hailing platforms will generate more than $1 trillion in profits per year by 2030. In addition, automakers and fleet owners could enjoy profits of $250 billion and $70 billion, respectively.”
Deadline is 2030; as of 2026 autonomous ride-hail remains far from profitable at scale.
“In the data center, we believe accelerators, dominated by GPUs, will become the dominant processors for new workloads, growing 21% at an annual rate to $41 billion by 2030.”
Target year is 2030, but the estimate already looks far too low: Nvidia's data center revenue alone has run well above a $41 billion annual rate since fiscal 2024.
“If AI software companies were to generate revenue at a $14 trillion annual rate [in 2030] and a cash flow yield of roughly 30%, AI software could create more than $80 trillion in enterprise value, more than six times the $13 trillion in enterprise value created by the Internet since 1997.”
Asset manager; analyst research 'Productivity Gains Could Propel The AI Software Market To $14 Trillion By 2030'
Target year is 2030; ARK later raised the associated value estimates in Big Ideas 2023.
“According to our research, during the next eight years AI software could boost the productivity of the average knowledge worker by nearly 140%, adding approximately $50,000 in value per worker, or $56 trillion globally.”
Asset manager; analyst research 'Productivity Gains Could Propel The AI Software Market To $14 Trillion By 2030'
Deadline is 2030; ARK subsequently raised this to a more-than-4x productivity gain in Big Ideas 2023 (already tracked separately).
“In 2025, at ~$500 billion, annual investment in data center systems was nearly 2.5x the average from 2012 through 2023; this category of investment will continue to inflect and could triple to ~$1.4 trillion in 2030 (a ~30% compound annual growth rate).”
Resolves on 2030 global data center systems investment versus the ~$1.4 trillion forecast.
“As AI-driven compute demands grow, we expect custom silicon to grow as a share of compute spend: we believe custom ASICs could grow to over a third of the compute market by 2030.”
Asset manager; analyst research note "The State Of AI Infrastructure: Demand, Costs, And Custom Silicon"
Resolves on custom (non-GPU) accelerators' share of AI compute spend in 2030.
“Catalyzed by breakthroughs in artificial intelligence, the global equity market value associated with disruptive innovation could increase from 16% of the total to more than 60% by 2030. As a result, the annualized equity return associated with disruptive innovation could exceed 40% during the next seven years, increasing its market capitalization from ~$19 trillion today to roughly $220 trillion by 2030.”
Resolves in 2030 on the market capitalization of disruptive-innovation equities versus the ~$220 trillion / >60%-of-global-market-cap projection.
“Based on ARK's research, the enterprise value of companies focused on precision therapies could appreciate 28% at an annual rate during the next seven years, from ~$820 billion in 2023 to ~$4.5 trillion by 2030, as multiomic tools and technology reduce research and development spending per drug by more than 25%.”
Resolves in 2030 on the aggregate enterprise value of precision-therapy companies versus the ~$4.5 trillion projection.
“Informed by Wright's Law, we estimate that AI-relative compute unit (RCU) production costs could decline at a 39% annual rate and that software improvements could contribute an additional 37% in cost declines during the next eight years. In other words, the convergence of hardware and software could drive down AI training costs by 60% at an annual rate by 2030.”
Investment management firm; 'Big Ideas 2022' annual research report, Artificial Intelligence chapter
Target year 2030 is still in the future; ARK later revised this same forecast upward to 70% annually (Big Ideas 2023) and 75% annually (Big Ideas 2024).
“Disruptive innovation could command more than two-thirds of the global equity market, compounding at a 38% rate through 2030, as breakthroughs in artificial intelligence, autonomous mobility and humanoid robots turbocharge productivity.”
Investment management firm; 'Big Ideas 2025: Unlocking Exponential Growth Through Disruptive Innovation' annual research report
Target year 2030 is still in the future; this is the 2025 restatement of ARK's recurring disruptive-innovation market-share forecast (the 2024 edition put it at more than 60% by 2030 at a 40% annual rate).
“Global real GDP growth will accelerate to 7.3% by 2030 — roughly 4 percentage points above the IMF's forecast — as five AI-centered innovation platforms converge ('The Great Acceleration').”
Investment management firm; 'Big Ideas 2026: The Great Acceleration', 10th annual flagship research report
Target year 2030 is still in the future; ARK frames 7% real growth as a conservative step-function increase from the ~3% historical trend.
“Based on our updated assumptions on pricing, ARK estimates that autonomous logistics revenue could scale from nearly zero today to $1-2 trillion by 2030.”
Autonomous delivery revenue remains negligible as of early 2026; ARK itself cut the figure to ~$900 billion by 2030 in Big Ideas 2024, so the 2030 outcome is still open.
“Digital wallets, powered by AI purchasing agents, could represent 72% of all e-commerce transactions by 2030.”
Part of ARK's AI Agents big idea, which also forecasts ~$9 trillion of AI-facilitated global gross online consumption by 2030; resolvable against global e-commerce payment-method share data in 2030.
“AI purchasing agents could generate global revenue between $40 billion and $200 billion for digital wallet platforms in 2030.”
ARK valued digital wallet platforms (e.g. Block, Robinhood, SoFi) at ~$1,800 per user at the time; the wide 5x range makes this a weak but still checkable 2030 revenue forecast.
“According to ARK's research, autonomous delivery revenues could scale from essentially nil today to $900 billion in 2030.”
ARK breaks the 2030 figure into roughly $440 billion of robot/drone last-mile delivery fees plus autonomous trucking; autonomous delivery revenue today is still negligible. Tracks alongside, but is distinct from, ARK's 2023 $1–2 trillion autonomous-logistics estimate.
“Based on the radical productivity gains that we expect AI to deliver, businesses could increase spending on software 47% at an annual rate during the next six years, from $1.1 trillion this year to $13 trillion in 2030.”
ARK later framed this as the top end of a range — its July 2025 research gave a $3–13 trillion 2030 software-spend scenario band with a $7 trillion midpoint — so the $13 trillion figure represents its rapid-mass-adoption case.
“According to ARK's research, robotaxi platforms could redefine personal mobility and generate $28 trillion in enterprise value during the next five to ten years.”
Horizon runs to 2034 (the far end of ARK's stated five-to-ten-year window); global robotaxi platform enterprise value today remains orders of magnitude below $28 trillion.
“Deep learning could create 3x the value of the internet: the internet captured 15% of the globe's equity market capitalization over 20 years; if deep learning were to achieve the same rate of adoption, it would add $30 trillion to global equity market capitalizations in the next 20 years.”
Horizon runs to 2039; ARK reaffirmed the $30 trillion figure in its 2020 and 2021 Big Ideas reports, and AI-linked equity value has grown sharply since 2019.
“ARK has grown increasingly confident that Tesla will launch a robotaxi service soon. Our updated Monte Carlo model includes a range of launch dates, with late 2024 as the weighted average of all cases.”
Asset manager; open-source Tesla valuation model, 'ARK's Expected Value For Tesla In 2027: $2,000 Per Share'
Tesla launched no robotaxi service in 2024; its first limited robotaxi pilot began in Austin in June 2025 with in-car safety monitors, missing ARK's weighted-average late-2024 launch assumption by more than half a year.
“AI training costs have dropped roughly 10x every year. In 2017 the cost to train an image recognition network like ResNet-50 on a public cloud was ~$1,000; in 2019 the cost dropped to ~$10. At the current rate of improvement, the cost should fall to $1 by the end of this year [2020].”
Asset manager; analyst research note 'AI Training Costs Are Improving at 50x the Speed of Moore's Law'
The Stanford AI Index 2021, using DAWNBench data, put the cost of training an ImageNet image-recognition system to 93% accuracy at about $7.43 in 2020 (down ~150x from ~$1,100 in 2017), and the 2022 AI Index put it at $4.60 in 2021 — the ~10x-per-year pace stalled and the $1 threshold was not reached by end-2020.
“Enterprise value for autonomous [ride-hail] platform operators could scale to $3.8 trillion by 2025.”
Autonomous ride-hail was still pre-scale at the end of 2025: Waymo was the only meaningful US operator (valued in the low hundreds of billions at most), GM shut Cruise down, and Tesla's robotaxi service was limited to small supervised fleets — aggregate enterprise value for autonomous platform operators was orders of magnitude below $3.8 trillion.