Introduction
Throughout history, wealth has followed a persistent trajectory, pooling in the hands of those who control the surplus of their era’s defining resources. From the fertile lands of ancient Mesopotamia, where kings and priests hoarded grain, to the industrial factories of the 19th century, where capital magnified profits for tycoons, the pattern has endured across civilizations. The digital age shifted this pool to data, concentrating riches with platform architects like Google and Meta, while today’s frontier of artificial intelligence funnels wealth to those mastering computational power—firms like Nvidia and OpenAI. In each phase, as explored in “The Shifting Pools of Wealth Through Time,” surplus emerges from a critical resource—land, capital, data, intelligence—and flows upward through mechanisms of control, be it territorial dominance, financial systems, network effects, or technological barriers. This dynamic, spanning millennia, reveals a timeless truth: wealth accumulates where surplus meets control, leaving most on the margins of its ascent.
Yet, the present moment hints at a disruption to this rhythm. We stand at the cusp of what may be termed an exponential age, a convergence of forces—cryptocurrency, artificial intelligence, robotics, and the promise of abundance—that scales surplus at a pace unprecedented in human history. Cryptocurrency, with a market capitalization of $2 trillion in 2025, is projected to reach $100 trillion by 2035, driven by logarithmic growth, state recognition, and global financial integration. Artificial intelligence promises a $13 trillion boost to global GDP by 2030, while robotics and renewable technologies edge toward a world of near-costless goods. Unlike the gradual transitions of past pools—from agrarian fields to industrial hubs, or dial-up networks to cloud servers—this surge unfolds in decades, not centuries, propelled by technological synergy and mass adoption. The sheer speed of this expansion raises a provocative possibility: it may outpace the ability of traditional power structures—states, institutions, and old money—to pool the resulting wealth as they once did.
This essay posits that in this exponential age, the rapid growth of surplus—exemplified by cryptocurrency’s potential $100 trillion market, AI’s economic transformation, and robotic abundance—creates a temporary window where ordinary individuals can accumulate wealth. Unlike lumbering institutions bound by bureaucracy or legacy wealth tethered to slower systems, “normal” people, acting reflexively with modest investments like $100 in crypto or leveraging accessible intelligence such as AI skills, can front-run these giants. Data from 2025—300 million crypto users, early adopter windfalls, and AI’s diffusion—suggest this shift is underway, with projections to 2035 indicating it could scale further. Building on the historical framework of wealth concentration, this analysis explores how speed disrupts control, offering a shot at accumulation to those outside the elite. Through a neutral lens, it examines the mechanisms, evidence, and limits of this opportunity, asking whether the exponential age bends the age-old pattern—or merely accelerates its next iteration.
Section 1: The Exponential Age – Defining the Surge
The exponential age marks a departure from the historical pools of wealth—land, capital, data, and intelligence—by the sheer velocity and scale at which it generates surplus. Where past eras saw surplus emerge gradually, tied to physical limits or incremental technologies, the current convergence of cryptocurrency, artificial intelligence (AI), and robotics accelerates economic value creation on a geometric trajectory. This section delineates this phenomenon, contrasting its rapid ascent with the slower transitions of prior phases and grounding it in contemporary data from 2025. By projecting forward to 2035, it establishes the foundation for a central claim: the speed of this surplus may temporarily overwhelm the mechanisms that have historically concentrated wealth, offering a window for broader participation.
Cryptocurrency stands as a flagship of this exponential surge, its market capitalization climbing from negligible value in 2009 to $2 trillion by March 28, 2025. Analysts plotting its growth on a logarithmic scale observe a pattern of explosive leaps—$1 billion in 2013, $800 billion in 2021, and now $2 trillion—suggesting a potential rise to $100 trillion by 2035, a 50-fold increase in a decade. This trajectory is not mere speculation; it aligns with tangible drivers. State recognition, such as El Salvador’s adoption of Bitcoin as legal tender in 2021 and the United Arab Emirates’ crypto-friendly policies by 2024, signals a shift toward mainstream acceptance. The International Monetary Fund’s (IMF) evolving stance—hypothetical inclusion of crypto transfers in its Balance of Payments Manual (BPM7)—could further legitimize cross-border flows, potentially channeling trillions into the asset class. Unlike land, which grew wealth through centuries of cultivation, or capital, which scaled over decades of industrialization, crypto’s ascent compresses exponential growth into years, fueled by global connectivity and decentralized protocols.
Artificial intelligence amplifies this trend, transforming data into a resource of unprecedented economic potency. The McKinsey Global Institute estimates AI could add $13 trillion to global GDP by 2030, a figure that, if extended with current adoption rates, might reach $20–30 trillion by 2035. This projection rests on AI’s ability to automate tasks—from logistics optimization to medical diagnostics—and refine decision-making across industries. The computational leap from models like GPT-4 in 2023 to anticipated successors suggests a 10-fold increase in processing power every five years, a pace that dwarfs the gradual mechanization of the industrial era or even the internet’s two-decade spread. By 2025, firms like Nvidia, with a market cap exceeding $2 trillion, and OpenAI, valued at $80 billion, illustrate this surge, yet open-source frameworks such as TensorFlow hint at a diffusion beyond corporate silos. This rapid scaling generates surplus not just for elites but across ecosystems, outstripping the slower consolidation of past technological shifts.
Robotics and the promise of abundance complete this triad, redefining the production of physical goods. By 2025, renewable energy exemplifies this potential: solar power costs have plummeted 89% since 2009, according to the International Renewable Energy Agency (IRENA), nearing $0.01 per kilowatt-hour. Robotics follows suit—pilots in Japan deploy humanoid assistants in eldercare, while vertical farming experiments in urban centers promise food at pennies per unit. Projections suggest that by 2035, these technologies could render energy, shelter, and nutrition near-costless, a stark contrast to land’s finite yields or capital’s coal-driven factories. This abundance generates surplus at a scale and speed unimaginable in agrarian or industrial societies, where growth was tethered to seasons or steam. The exponential decline in production costs—mirroring Moore’s Law in computing—positions robotics as a multiplier of economic value, potentially flooding markets before traditional gatekeepers can fully harness it.
Data from 2025 underscore this exponential character. Cryptocurrency boasts 300 million users worldwide, a figure that could climb to 5 billion by 2035 if adoption mirrors the internet’s curve from 1990 to 2010. AI’s integration into daily life—smartphones, supply chains—parallels this, with computational advancements accelerating its reach. Robotics, though nascent, shows exponential uptake in pilot regions, from China’s factory bots to Europe’s renewable grids. Unlike the linear progression of wheat harvests or the decades-long rise of steel empires, this surge compresses surplus creation into a tight timeframe, outpacing the gradual layering of control seen in prior eras. The exponential age, then, is defined not just by its magnitude—$100 trillion in crypto, trillions in AI and robotics—but by its velocity, setting the stage for a potential disruption of wealth’s historical pooling.
Section 2: The Lag of Large Pools – Institutions and Old Money
The exponential age, with its rapid surplus generation—cryptocurrency’s projected $100 trillion market cap, AI’s $13 trillion economic boost, and robotic abundance—challenges the historical mechanisms that have concentrated wealth. Across past pools, from land to intelligence, control aligned with surplus over time: feudal lords taxed harvests, industrial magnates secured patents, and digital platforms locked in user data. Yet, each consolidation required a period of adaptation—decades or centuries—during which established powers adjusted to new realities. This section argues that the unprecedented speed of the current surge outstrips the reflexive capacity of large pools of wealth—states, institutions, and old money—leaving a temporary lag where surplus flows beyond their immediate grasp. Evidence from historical patterns and contemporary trends as of March 28, 2025, supports this, highlighting a structural slowness that contrasts with the agility of individual actors.
Historically, the pooling of wealth followed a predictable arc: surplus emerged, then control caught up. In the land-based era, agricultural surplus from Mesopotamia’s irrigation or Europe’s feudal estates took generations to fully centralize; kings and lords imposed tribute systems only after territorial dominance stabilized, a process spanning centuries by 3000 BCE or the 11th century CE. The capital phase saw a faster but still gradual alignment—Britain’s Industrial Revolution unfolded over decades, with the 1844 Companies Act formalizing corporate control nearly a century after steam engines proliferated. The data era compressed this further; the internet’s open 1990s gave way to platform dominance by the 2010s, as firms like Google and Meta harnessed network effects over two decades. In each case, institutions—governments, banks, corporations—adapted slowly, leveraging bureaucracy, legislation, or infrastructure to pool surplus after its initial spread. The exponential age, however, shrinks this timeline to years, testing the limits of such inertia.
Contemporary institutions exhibit this lag starkly in the face of cryptocurrency’s ascent. By 2025, crypto’s $2 trillion market cap reflects a 15-year rise from obscurity, yet major banks trailed this wave. JPMorgan Chase, dismissive of Bitcoin in 2017, launched crypto trading desks only in 2022, five years after its price breached $10,000. Institutional investment vehicles, like BlackRock’s $10 billion Bitcoin ETF in 2024, entered after retail adoption hit 300 million users, a decade-plus behind early miners who turned $100 into millions. This slowness stems from structural constraints—board approvals, risk assessments, and regulatory compliance—delaying pivots that individuals execute in minutes via a smartphone app. The data suggest a gap: while institutional holdings grow (e.g., Grayscale’s $40 billion in Bitcoin by 2025), they follow, not lead, the exponential curve that could reach $100 trillion by 2035, leaving early surplus unpooled.
States, too, struggle to match this velocity. Regulatory responses to cryptocurrency lag its growth by years—sometimes deliberately, sometimes by necessity. The U.S. Internal Revenue Service began tracking crypto transactions in 2024, 15 years after Bitcoin’s genesis, while China’s policy oscillated from a 2021 ban to partial acceptance by 2025, a four-year flip-flop. The IMF’s potential inclusion of crypto in its Balance of Payments Manual (BPM7), still hypothetical in 2025, trails actual cross-border flows already reshaping remittances and trade. These delays reflect the deliberative nature of governance—consensus-building, legal drafting, enforcement—processes that span half-decades, not months. By contrast, crypto’s projected 50-fold increase to $100 trillion by 2035 compresses into a decade, a pace that outruns policy cycles and leaves surplus momentarily uncontained.
Old money—traditional wealth pools like oil, real estate, and legacy stocks—fares no better, tethered to linear growth ill-suited to exponential shifts. In 2025, the Forbes billionaires list still features pre-crypto titans—Buffett, Walton—whose fortunes grow at 5–10% annually, a fraction of crypto’s 1000x leaps or AI’s trillion-dollar surges. These pools missed the 2010s crypto boom, with oil magnates and property barons largely absent from Bitcoin’s early $1-to-$60,000 climb. Even as new elites emerge—Musk’s Tesla and Zhao’s Binance ride the wave—old money’s inertia, rooted in physical assets or slow markets, lags the digital and computational speed of the exponential age. The data highlight this mismatch: traditional sectors trail crypto’s 300 million users and AI’s $2 trillion market caps (e.g., Nvidia), unable to pivot as surplus scales geometrically.
This lag creates a critical disparity. The exponential pace—crypto’s 50x in a decade, AI’s 5-year compute leaps, robotics’ cost drops—outstrips institutional reflexes, which operate on cycles of 5–10 years or more. By 2025, retail adoption (300 million crypto wallets) and early gains (e.g., $100 to $60,000 in Bitcoin) outpace institutional ETFs ($100 billion total) and state taxes, which remain nascent. Whale concentration—27% of Bitcoin in 0.01% of hands—shows control adapting, but slower than the user base, suggesting a window where surplus spreads before pooling tightens. Historically, control eventually aligned; today, the data indicate speed may delay that alignment, scattering wealth beyond large pools’ immediate reach.
Section 3: The Reflexive Advantage – Normal People Front-Running the Wave
The exponential age’s rapid surplus—cryptocurrency’s potential $100 trillion market cap, AI’s $13 trillion economic boost, and robotic abundance—creates a fleeting misalignment where traditional pools of wealth lag, as established in the prior section. This lag opens a window for ordinary individuals, unbound by the inertia of institutions or the legacy of old money, to capture a share of this wealth. Unlike states requiring policy cycles or corporations needing board approvals, “normal” people can act reflexively—making swift decisions with minimal resources—and leverage accessible intelligence to front-run the consolidation that historically follows surplus growth. This section examines how such individuals, armed with modest investments like $100 in crypto or skills honed through freely available tools, can seize this opportunity, drawing on 2025 trends and echoing patterns from past wealth pools.
Reflexivity, in this context, refers to the capacity for rapid, adaptive action, a trait individuals possess in contrast to the deliberative pace of large entities. Where a bank might take months to launch a crypto fund—JPMorgan’s 2022 pivot came five years after Bitcoin’s $10,000 milestone—an individual can buy $100 in Bitcoin or Ethereum via a smartphone app in minutes, reacting to market signals shared on platforms like X or price dips tracked on CoinMarketCap. This agility mirrors the speed of the exponential age itself: cryptocurrency’s projected 50-fold rise to $100 trillion by 2035 demands decisions measured in days or weeks, not years. By 2025, 300 million users worldwide have embraced crypto, a grassroots swell that outpaces institutional adoption—exchange-traded funds hold $100 billion, a fraction of the $2 trillion market. This reflexive edge allows normal people to enter early, positioning them to benefit as surplus scales before control tightens.
Crypto ownership exemplifies this advantage, offering a direct means to capture wealth as the asset class grows. In 2025, a $100 investment in Bitcoin, priced at a hypothetical $10,000 during a dip, buys 0.01 BTC; if Bitcoin reaches $500,000 by 2035, as a $100 trillion market might imply, that stake becomes $5,000—a 50-fold return unattainable in traditional savings. Ethereum, at $2,500 in 2025, could climb to $25,000, turning $100 into $1,000. Decentralized finance (DeFi) amplifies this: staking $1,000 in a platform like Uniswap or Aave at 5–20% annual yields compounds to $2,600–$6,700 by 2035, even without price appreciation. By 2025, DeFi’s total value locked stands at $200 billion, a pool driven by retail users, not banks, who lagged until 2023. These gains echo historical front-runners—homesteaders claiming land before feudal enclosure or merchants investing in the Dutch East India Company before its dividends soared—where early, small stakes reaped outsized rewards as surplus expanded beyond initial control.
Leveraging intelligence further enhances this opportunity, as the exponential age democratizes access to high-value skills. Free resources—Coursera courses on AI, YouTube tutorials on crypto trading—enable anyone with internet access to master tools that tap into surplus flows. By 2025, AI-related skills command premiums of 50–100% over other tech roles, according to Glassdoor, with prompt engineers or dataset curators earning $150,000 annually without needing to own the infrastructure controlled by firms like Nvidia. In the crypto sphere, intelligence manifests in niche strategies: a coder builds a smart contract on Ethereum for free using open-source tools, selling it for $10,000, or a trader spots an altcoin at $10 that rises 10-fold in a year. The 2021 NFT boom offers a precedent—artists minted digital works on OpenSea, some earning $50,000 with no gallery backing, a feat rooted in quick learning rather than capital. These examples parallel scribes in ancient Egypt, who gained wealth managing records, or engineers like Brunel, who profited from industrial design—skills bridging surplus to reward without elite status.
Historical echoes reinforce this reflexive advantage. In the land era, settlers grabbed unclaimed territory before lords fenced it; in the capital era, small traders bought stocks in nascent firms like the VOC, reaping 18% annual dividends before monopolies solidified. The data era saw bloggers and YouTubers monetize attention in the 2000s, earning millions before platforms like Meta dominated ad revenue. Each phase offered a window where agility and insight outpaced pooling—decades for land, years for capital, months for data. Today, the exponential age compresses this to a decade or less: crypto’s 300 million users beat banks to $2 trillion, early Bitcoin buyers turned $1 into $60,000 by 2025, and DeFi’s $200 billion TVL reflects retail stakes outrunning institutional funds. The data suggest a pattern—normal people, acting fast and smart, capture surplus in the gap before control catches up.
This advantage hinges on the speed of the exponential surge. If cryptocurrency hits $100 trillion by 2035, with 5 billion users as adoption scales, a $100 stake averages $2,000—modest but significant, outpacing old money’s pivot from linear assets. AI’s diffusion—open-source tools reaching millions—spreads skills faster than patents can lock them, while robotics’ abundance promises gains (e.g., tokenized supply chains) accessible via crypto. By 2025, retail reflexes lead: 300 million wallets dwarf ETF volumes, early crypto gains (1000x since 2013) outstrip bank returns, and skill premiums reflect intelligence’s edge. This window, though finite, positions normal people to front-run the wave, leveraging the lag of large pools to claim a slice of the exponential age’s surplus.
Section 4: Limits and the Pattern’s Pull
The exponential age’s rapid surplus—cryptocurrency’s projected $100 trillion market cap, AI’s $13 trillion economic boost, and robotic abundance—offers ordinary individuals a window to front-run institutional control, as argued in the prior section. Yet, this opportunity is neither boundless nor immune to the historical dynamic traced in earlier eras: wealth pools where surplus meets control. While the speed of this surge temporarily scatters surplus beyond the grasp of states, institutions, and old money, the mechanisms of concentration—market dominance, regulatory capture, and elite adaptation—tend to reassert over time. This section explores these limits, assessing the risks to normal people and the resilience of the pattern, grounded in 2025 trends and projections to 2035. The analysis remains neutral, weighing feasibility against the pull of history.
Concentration, a hallmark of past wealth pools, shows signs of reemerging even amidst the exponential age’s velocity. In cryptocurrency, early adopters and large holders—known as whales—already skew the distribution: by 2025, 0.01% of Bitcoin addresses control 27% of the supply, per Glassnode estimates, while 1,000 wallets hold 40% of Ethereum. If the market reaches $100 trillion by 2035, a plausible scenario suggests 70%—or $70 trillion—could pool with these entities, leaving the remaining $30 trillion split among 5 billion users, averaging $6,000 each. Institutional players amplify this trend: Grayscale’s $40 billion in Bitcoin holdings and BlackRock’s $10 billion ETF in 2024 signal a shift from retail pioneers to corporate giants. This mirrors the data era, where the top 1% of U.S. firms captured 36% of profits by 2017 (World Inequality Database), or the intelligence era, where Nvidia’s $2 trillion market cap dwarfs smaller players. Speed scatters surplus initially, but scale favors those with resources to consolidate.
Risks to retail participants further constrain this window, echoing vulnerabilities seen in prior surges. Volatility, a crypto hallmark, wiped $2 trillion from the market in 2022, hitting latecomers hardest—those buying at 2021 peaks lost 80% by 2023, while early whales cashed out. Scams compound this: Chainalysis reported $7.7 billion lost to crypto fraud in 2021, a figure likely to scale with the market by 2035, disproportionately affecting less-savvy normal people. Late entry poses another hazard; a $100 stake in Bitcoin at $60,000 in 2025 yields $833 at $500,000 by 2035, a modest 8-fold gain compared to the 1000x returns of 2010s buyers. These risks parallel capital’s stock market crashes or data’s ad-revenue lockouts, where timing determined winners. The exponential age’s speed offers a shot, but not a guarantee—reflexivity falters without foresight or resilience.
Elite adaptation, both old and new, reinforces the pattern’s pull. Traditional wealth—oil, real estate—lags, but new elites born of the exponential age scale rapidly. Elon Musk’s Tesla, with Bitcoin holdings since 2021, and xAI, launched in 2023, ride crypto and AI waves to a $1 trillion-plus valuation by 2025. Startups like OpenAI, valued at $80 billion in 2024, capture intelligence’s surplus faster than old money pivots, yet still concentrate it—venture capital poured $50 billion into AI firms in 2024 (Crunchbase), dwarfing retail stakes. These players adapt reflexively, like normal people, but with deeper pockets and broader reach, echoing industrial tycoons who outscaled early traders. By 2035, if crypto hits $100 trillion, such elites could claim a lion’s share—$50 trillion or more—leaving normal people with significant but secondary gains, much as data’s moguls overtook bloggers.
The data reflect this tension between opportunity and concentration. By 2025, 300 million crypto users outpace institutional ETFs ($100 billion), and early gains—$1 to $60,000 in Bitcoin—favor retail agility. DeFi’s $200 billion total value locked shows normal people staking ahead of banks, while AI skill premiums (50–100%, Glassdoor) reward intelligence over capital. Yet, whale dominance, institutional buy-ins, and state interventions—U.S. taxes by 2030, China’s regulatory shifts—suggest control catching up. If 5 billion hold crypto by 2035, $20 trillion might spread to retail—a real transfer—but 70% pooling with elites aligns with history: land’s lords, capital’s magnates, data’s platforms. Speed opens a window; the pattern narrows it.
This feasibility remains tempered. A $100 stake in 2025 growing to $5,000 by 2035 is meaningful—outpacing savings or stocks—yet modest against billionaires’ billions. Reflexivity and intelligence give normal people a shot, but not parity; exponential growth scatters surplus, not equality. The data nod yes to the window—2025 trends show retail leading, 2035 projections suggest scale—but no to a full break. Control lags, then adapts, as it always has, tempering the “greatness” of this transfer with the weight of precedent.
Conclusion
The exponential age—marked by cryptocurrency’s potential $100 trillion market cap, artificial intelligence’s $13 trillion economic boost, and robotic abundance—ushers in a surge of surplus unprecedented in its speed and scale. This essay has argued that this velocity disrupts the historical pattern of wealth concentration, where surplus meets control, creating a temporary window for ordinary individuals to accumulate wealth. Unlike the slow-moving institutions, states, and old money that historically pooled riches—from Mesopotamia’s granaries to Silicon Valley’s server farms—normal people, acting reflexively with modest stakes like $100 in crypto or leveraging intelligence through accessible skills, can front-run this consolidation. Data from 2025 affirm this shift is underway, with projections to 2035 suggesting it could scale further, offering a shot at wealth accumulation that bends, though does not fully break, the enduring dynamic of pooling.
The evidence synthesizes a compelling case. By March 28, 2025, cryptocurrency’s $2 trillion market cap and 300 million users outpace institutional ETFs at $100 billion, while early adopters turned $1 into $60,000, showcasing retail agility over corporate lag. DeFi’s $200 billion total value locked reflects normal people staking ahead of banks, and AI’s diffusion—open-source tools and skill premiums of 50–100% (Glassdoor)—spreads surplus beyond elite silos. Projecting to 2035, a $100 trillion crypto market with 5 billion users could distribute $20 trillion to retail, averaging $4,000 per stake, while AI and robotics amplify this through economic growth and abundance. These trends echo historical front-runners—homesteaders, early traders, bloggers—who seized surplus before control solidified, but the exponential age compresses this window from decades to years, amplifying its reach. The speed of this surge—50-fold crypto growth, AI’s 5-year leaps—outstrips the reflexive capacity of large pools, scattering wealth outward before it pools upward.
Yet, the pattern’s pull remains formidable. Concentration reasserts as whales claim 27% of Bitcoin and institutions like Grayscale hold $40 billion, a trend that could see 70% of $100 trillion—$70 trillion—pool with elites by 2035. Risks—volatility wiping $2 trillion in 2022, scams costing $7.7 billion in 2021—and elite adaptation, from Musk’s $1 trillion empire to OpenAI’s $80 billion valuation, temper this window. Control lags but catches up, as it did with land’s lords, capital’s tycoons, and data’s moguls. A $100 stake growing to $5,000 is real—outpacing traditional assets—but modest against billionaires’ billions, suggesting a bend, not a rupture, in the historical arc. The data nod yes to opportunity—retail leads in 2025, scale looms by 2035—but no to egalitarianism; speed opens a door, not a new paradigm.
Looking forward, the exponential age’s trajectory remains fluid. If decentralization endures—crypto’s protocols resisting capture, abundance spreading via robotics—the window widens, potentially scattering surplus further as 5 billion wallets or AI-skilled workers claim their share. Conversely, if states tax heavily or elites consolidate faster, it narrows, reverting to the familiar upward flow. History favors the latter, yet the speed and synergy of these forces—crypto, AI, robotics—hint at a race redefined. For normal people, the shot lies in acting now: a $100 stake or a learned skill in 2025 could ride the wave to 2035, front-running the inevitable pull. The exponential age does not erase the pattern, but its velocity reshapes who runs—and who wins—in its early laps.
References
Chainalysis. (2022). The 2022 crypto crime report. Retrieved from https://www.chainalysis.com
(Supports data on $7.7 billion in crypto scam losses in 2021, with trends suggesting escalation by 2035.)
Crunchbase. (2024). AI startup funding report 2024. Retrieved from https://www.crunchbase.com
(Cites $50 billion in AI startup investments in 2024, reflecting elite adaptation.)
Glassnode. (2025). Bitcoin on-chain analytics: Holder distribution 2025. Retrieved from https://glassnode.com
(Provides estimate of 0.01% of Bitcoin addresses controlling 27% of supply in 2025.)
International Renewable Energy Agency (IRENA). (2025). Renewable power generation costs in 2024. Retrieved from https://www.irena.org
(Documents solar cost drop of 89% from 2009–2025, underpinning robotic abundance projections.)
McKinsey Global Institute. (2021). The future of work after COVID-19. Retrieved from https://www.mckinsey.com
(Estimates AI’s $13 trillion GDP impact by 2030, extended to $20–30 trillion by 2035 in projections.)
Milanović, B. (2016). Global inequality: A new approach for the age of globalization. Harvard University Press.
(Frames historical wealth concentration in capital era, relevant to institutional lag discussion.)
OpenSecrets. (2024). Lobbying data summary 2024. Retrieved from https://www.opensecrets.org
(Notes $80 million in U.S. tech lobbying in 2024, indicating elite influence in AI and crypto.)
Scheidel, W. (2017). The great leveler: Violence and the history of inequality from the Stone Age to the twenty-first century. Princeton University Press.
(Provides historical context on land and capital-era concentration, supporting pattern’s pull.)
Statista. (2025). Number of cryptocurrency users worldwide 2025. Retrieved from https://www.statista.com
(Reports 300 million crypto users in 2025, with projections to 5 billion by 2035 based on adoption curves.)
World Bank. (2020). Remittance prices worldwide 2020. Retrieved from https://www.worldbank.org
(Cites average 7% remittance fees, contrasted with crypto’s lower costs in 2025 trends.)
World Inequality Database. (2017). World inequality report 2018. Retrieved from https://wid.world
(Documents top 1% of U.S. firms capturing 36% of profits in data era, paralleling crypto concentration risks.)
Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.
(Details data-era platform dominance, providing a benchmark for institutional adaptation.)