a16z Growth State of Markets September 2026 is a 90-page investor-grade market review covering the tech-driven equity cycle, the multi-trillion-dollar AI capex buildout, the rotation from software (bits) to hardware and infrastructure (atoms), the so-called SaaSpocalypse, private-market value creation, the post-ZIRP startup landscape, and the macro signals now coming from private company data. Every page pairs a bold editorial headline with sourced charts from S&P Capital IQ, Bloomberg, JPMAM, Goldman Sachs, Morgan Stanley, PitchBook, Carta, OpenRouter, Stripe and a16z portfolio companies.
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a16z Growth State of Markets September 2026 is a 90-page investor-grade market review covering the tech-driven equity cycle, the multi-trillion-dollar AI capex buildout, the rotation from software (bits) to hardware and infrastructure (atoms), the so-called SaaSpocalypse, private-market value creation, the post-ZIRP startup landscape, and the macro signals now coming from private company data. Every page pairs a bold editorial headline with sourced charts from S&P Capital IQ, Bloomberg, JPMAM, Goldman Sachs, Morgan Stanley, PitchBook, Carta, OpenRouter, Stripe and a16z portfolio companies.
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Cover slide with the a16z Growth wordmark, the title State of Markets in metallic serif capitals and the date September 2026 over a moody teal cityscape.
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Legal disclaimer stating the deck is informational only, not investment advice, with notes on third-party data and the tech-universe methodology.
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Eight numbered sections: Tech Is The Everything Cycle, AI Is A Generational Platform Shift, Capex Is Working, Atoms Are So Back, SaaSpocalypse? More Like SaaS-Prove-It, Take a Walk On The Private Side, It's A Brave New World For Startups Too, PrivateCos Telling The Macro Story.
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Section divider for part one.
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Thesis narrative that tech has left the cottage and is now the prime mover of the economy, paired with a chart showing tech is now 55% of all U.S. capital spending.
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Two stacked bar charts showing tech is roughly 35% of the Global 100 by count and roughly 60% by market cap, rising steadily since 2010.
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Three charts: tech is nearly half of S&P 500 profits, tech earnings have grown about 3.8x more than non-tech, and tech contributed about 76% of earnings growth.
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Three charts showing S&P 500 margins at historic highs near 17.5%, margin expansion for tech and non-tech, and tech profit margins far above the rest.
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Tech and energy lead EPS growth but growth is broad-based, with a record 93.6% of S&P 500 companies meeting or beating estimates.
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Earnings per share surge while P/E multiples compress, and tech profits grow 71% year over year off an already high base.
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Table decomposing year-to-date sector returns into EPS growth and multiple change, plus a bar chart showing tech P/E roughly 20% below its five-year average.
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Rest of tech, not the Mag 7, has carried the year as hyperscalers pour profits into the AI buildout.
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Momentum factor swings and leveraged ETF assets reaching $192B show retail piling into consensus themes.
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Section divider for part two.
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Hyperscaler capex approaching $800B in 2026 and over $1T annually from 2027, and every compute cycle is bigger than the last.
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Capex is near the peaks of past cycles as a share of GDP, and hyperscaler capex estimates keep being revised upward every year.
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Hyperscaler capex rising to about $1.18T by 2028 while free cash flow as a share of sales drops sharply before recovering.
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Hyperscaler and Nvidia investment-grade debt issuance spikes above $300B in 2026, and AI borrowing is adding long-duration supply to the market.
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Hyperscaler ROIC near 20% remains well above cost of debt and WACC, which is why lenders are comfortable.
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Data centers have driven a surge in construction and skilled-trades hiring and pay a large premium on wages for the same job titles.
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Scatter plot shows the largest price increases came with the largest demand decreases, with a research quote estimating rates fell 6% where capacity grew 160%.
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Section divider for part three.
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OpenAI and Anthropic ARR ramping toward $150B, and labs added more revenue in 2026 than all public software combined.
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Cloud revenue backlogs have doubled year over year, and consensus expects hyperscaler free cash flow to come roaring back by 2030.
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CoreWeave and other neoclouds are scaling quarterly revenue faster than AWS, Azure and GCS did at the same stage.
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GPU rental prices and residual values are climbing or holding steady even for older chips, undermining the depreciation bear case.
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Companies reporting quantifiable AI impact are rising, yet 69% of the S&P 500 cite a live deployment while only 2% disclose a tracked metric.
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Grid of ten earnings-call quotes on AI ROI from Amazon, Meta, Shopify, ServiceNow, Affirm, Lemonade, Chime, Snowflake, Microsoft and Walmart.
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Only 20% of organizations cite cost as a constraint, most sectors plan to increase AI spend, and cloud reached only 4% of IT budgets in year two.
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Gen Z business applications surge and GitHub shows an explosion of merged pull requests, commits and new repos.
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High-intensity AI adopters increase entry-level headcount share, and AI-related white-collar hiring in the U.S. is running above trend.
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Adoption is wide but shallow; a tiny share of power users drive growth, and AI natives generate far more revenue at the tail.
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The top 1% of AI spenders outspend the top 10% by roughly 8x, and frontier firms' token output has pulled far ahead of typical firms across industries.
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The price of intelligence has fallen as much in three years as PCs did in fifteen, while H100 rental prices rise even as token prices fall.
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Agents now consume 7.3 trillion tokens on OpenRouter, far more than humans, and over 85% of agentic token burn comes from cached prompts.
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Open models are growing quickly but remain a tiny slice of spend, while frontier labs capture about 70% of spend on 35% of tokens.
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Price per token is falling and older models keep share, yet GPU rental prices keep rising even for older accelerators.
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Households paying for AI and their monthly spend keep rising, retention curves smile, and paid consumer subscriptions are up roughly 5x since 2025.
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Search referral traffic is declining while AI referrals remain tiny compared with direct, paid and social channels.
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Meta's Muse app rapidly captured a share of U.S. downloads against ChatGPT, Instagram, Threads and Claude in mid-September.
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In the mobile internet cycle semiconductors led, then infrastructure, then software; the AI cycle is repeating the pattern.
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Section divider for part four, noting AI has led to a broader rotation from bits to atoms.
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Hardware has taken center stage as hyperscaler free cash flow effectively becomes semiconductor free cash flow, with EVs, grid, defense, rockets and robots adding to the atoms cycle.
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U.S. investment was a software story until hardware and data center spending recently turned up, and a Sankey diagram traces $100 of AI capex across the supply chain.
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Roughly $90T of global infrastructure investment is needed by 2040, with U.S. funding gaps in water, roads, power and transit.
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U.S. manufacturing PMI, new orders and production are back in expansion, and output in semiconductors and electrical equipment is running ahead of capacity.
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Electricity demand growth comes from EVs, buildings and industry as much as data centers, and utility capex is set to exceed $1T by 2030.
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Launch costs have fallen to about $3,868 per kg while payload mass soars, and commercial operators now own most launched objects.
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Annual robot sales forecasts rise sharply, humanoids need the most actuators per unit, and earnings calls show a new automation wave.
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Waymo reached half a million weekly rides with a timeline of city launches, and robotaxi weekly active users are climbing.
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Global defense budgets as a share of GDP are rising again, and U.S. defense new orders and shipments are on the march.
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After a decade of capital-light dominance, asset-heavy businesses are outperforming asset-light, with the AI supply chain as the winning trade.
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Semis and storage have nearly doubled year to date, and NAND and DRAM memory prices have spiked to multi-year highs.
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Chipmaker forward multiples sit well below what their expected earnings growth would predict, suggesting the cycle may not be like past ones.
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GPUs arrive on time but substrates, HBM, DRAM, optics, transformers and gas turbines all have unusually long lead times.
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Section divider for part five, subtitled Software's Selective Selloff as SaaS enters a prove-it era.
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SaaS has re-rated to reflect a shift from growth to profitability, but fundamentals remain stronger than returns suggest.
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Cyber and observability is the runaway software winner year to date and commands the premium multiple versus vertical and horizontal SaaS.
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Median EV to revenue has compressed across segments, with horizontal software at 2.7x, while high-growth multiples have normalized rather than collapsed.
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Software revenue growth has slowed but stabilized across percentiles, and operating leverage measures are stable or improving.
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High-growth SaaS has become rare while high-margin SaaS is common; about 75% of software is profitable but only about 30% grows 20% plus.
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Historical analogue showing newspaper stocks sold off five years before consensus earnings collapsed.
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Capital-light businesses carry great ROE expectations near 25% versus capital-intensive ones in the mid-teens.
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Section divider for part six.
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VC-backed exit value hit a new high watermark of $2,188B in 2026 year to date versus modest venture capital raised.
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$3-4T of value is accruing on the private side, and the five largest private companies are worth more than the past decade of tech IPOs combined.
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Value accrues to private markets as time to IPO lengthens, and active U.S. unicorns at $5.34T have lapped the Russell 2000.
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The top 1% of exits account for 84% of exit value and the top 10% for 94% in the first half of 2026.
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Tender subscription rates are at highs, tender discounts are rare and small, and secondary trades show no discounts to last round.
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Top 30 VC portfolios have appreciated far more than the top 10 public companies, and venture NAV is concentrated at a crowded top.
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VC IRR dispersion by vintage has never been wider, and a table of net IRR, TVPI and DPI by percentile shows it pays to be top decile.
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Section divider for part seven.
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Startups traded growth for profitability after ZIRP, but those that recently raised still grow at or above peak-ZIRP pace.
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AI-related deals now capture 86% of U.S. VC deal value in 2026, with concentration masking a mix-shift into services and capital-intensive verticals.
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New unicorns are getting younger with a 37% decline in median age, and most unicorns are profitable but growing 20% or less.
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Post-AI startup vintages are on a roughly 3x steeper revenue curve, and top AI apps grow about 5x off a small base and 2.5x off a larger base.
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Section divider for part eight, noting private techcos increasingly generate the leading signal on key economic questions.
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Weekly tokens on OpenRouter reached 126.2T in September 2026, about 27x year over year and doubling roughly monthly.
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OpenAI data shows 95% of power users adopt plugins and 93% adopt skills versus 21% and 19% at frontier firms and single digits at typical firms.
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Databricks Smart Router solves 92.3% of coding tasks at $2.13 per task, 35% cheaper and 1.3 points better than the best single model.
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Kalshi prediction markets price the forward cost of Nvidia B200 compute per hour, making compute price a tradable KPI.
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Private inference providers added about three quarters of the revenue of Snowflake plus Datadog in 2026 at about one fifth of the equity value.
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Stripe payment data shows SaaS revenue growth accelerated into 2026 for both mature and young companies, contradicting the SaaSpocalypse narrative.
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Protege data shows in-system mortality per 100k patients falling faster in health systems adopting ambient AI fastest.
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EliseAI voice localization lifted tour conversions 5.28% and caller engagement 7.8%, with a quote describing the ElevenLabs and Cartesia collaboration.
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Infographic shows how many new-entrant munitions one legacy round buys, from 3x to 8x cheaper alternatives.
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Flock license plate readers reduced motor vehicle theft, shortened recovery times and increased arrest clearance rates.
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Pokemon card prices beat technology stocks, and Pokemon sales rise alongside Whatnot weekly active users as live auctions take flight.
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Seven forward-looking opportunity areas: Heavy-use consumer, Robotics, Autonomy, AI x Bio, Personal Health, Diffusion into the Enterprise beyond Coding, and a New era of American Dynamism.
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It is a 90-page market review from Andreessen Horowitz's growth team covering the tech-led equity cycle, the AI capex buildout, the rotation from software to hardware and infrastructure, the state of SaaS, private-market value creation, startup fundraising conditions, and macro signals from private company data.
Venture and growth investors, public equity analysts covering tech and AI, startup founders benchmarking growth and profitability, corporate strategy and IR teams, and students or journalists who want a sourced, chart-driven view of the 2026 market.
The deck pairs a cream background with dark green and black sidebars, serif editorial headlines, and white chart cards with source footnotes. The section divider, sidebar-plus-chart, two-chart, three-chart and logo case-study layouts are all easy to adapt for your own market or LP update.
No. It argues it is hard to call a bubble because earnings are growing off a high base while multiples have compressed, hyperscaler returns exceed their cost of borrowing, and demand for compute still exceeds supply. It does flag debt, concentration and retail leverage as risks to watch.
It reframes the software selloff as a prove-it era rather than an apocalypse. Cyber and observability outperformed, vertical SaaS held up better than horizontal, fundamentals and operating leverage stayed stable, and Stripe data shows SaaS revenue actually accelerated into 2026.
Charts cite S&P Capital IQ, Bloomberg, FactSet, JPMAM, Goldman Sachs, Morgan Stanley, BofA, PitchBook, Carta, Indeed, Ahrefs, SensorTower, OpenRouter, Stripe, Kalshi, and a16z portfolio companies such as Databricks, Protege, EliseAI, Anduril, Flock and Whatnot, with source lines on every chart.
The closing slide names seven untapped areas: heavy-use consumer AI, robotics, autonomy, AI x bio, personal health, diffusion of AI into the enterprise beyond coding, and a new era of American Dynamism including defense and manufacturing.
Yes. Use the section structure and chart-card layouts as a reference, then generate your own slides from your data or documents with 2Slides AI to match a similar editorial, chart-first style.
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