BofA thematic research: AI, robotics, quantum, eVTOL, drones, space, and fusion are entering the commercialization validation stage

Overview

This is a BofA global thematic research report titled "Come with me, and you’ll see,a Transforming World of pure innovation," dated July 22, 2026. Based on BofA’s recent Transforming World Conference, more than 20 field research and expert events, and presentations from over 40 companies and speakers, the report reviews commercialization progress across themes such as AI, robotics, quantum computing, electric vertical takeoff and landing aircraft, autonomous driving, drone delivery, the space economy, fusion, and nuclear energy. The core conclusion is that multiple frontier technologies are moving from the proof-of-concept stage into phases that are deployable, certifiable, and commercially viable, and that investment discussions are shifting from “does the technology work” to “can it scale economically.”

Core views

The report argues that AI is expanding into the physical world, with robotics, autonomous driving, and drones benefiting from model capability improvements, falling hardware costs, and data accumulation; quantum computing is unlikely to replace traditional computing, but rather will form hybrid architectures alongside CPUs and GPUs; eVTOL could expand the market beyond helicopters in urban air mobility, airport shuttle, medical, cargo, and defense scenarios; the space economy benefits from falling launch costs and government demand; and fusion and advanced nuclear are viewed as long-term energy solutions in the context of rising AI electricity demand. At the same time, fact verification, legal liability, and social trust issues arising from AI-generated content may determine the speed and business models of the next phase of AI applications.

Analysis framework

The report adopts a thematic investing and conference-notes-style research approach, linking together company presentations, expert interviews, live demonstrations, and field research to compare how different technologies differ in their progression from vision to commercialization. Rather than focusing on traditional single-company financial forecasts, the analysis emphasizes cross-theme synthesis around scalable markets, technology maturity, regulatory pathways, cost curves, customer adoption, data moats, and potential beneficiaries across the value chain.

Methodology notes

• thematic investingTransforming World thematic framework

  From proof of concept to commercial reality

  The report uses BofA’s Transforming World conference series and field research as an observation window to assess whether frontier technologies have moved from the lab or prototype stage into commercial deployment, certification, customer expansion, and unit-economics validation.

• technology commercializationscaling economics assessment

  Economics of scaling

  The report emphasizes that the investment debate is shifting from whether technology is feasible to whether it can scale, including hardware costs, utilization, reliability, certification, regulation, infrastructure, and customers’ willingness to pay.

• AI governancetruth and accountability lens

  Truth, verifiability, and legal liability

  The Steve Rosenbaum section emphasizes that hallucinations and synthetic content from generative AI may erode the ability to verify facts objectively, while legal liability and market demand may push models to place greater weight on source attribution, factual reliability, and verifiable answers.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• QUANTUM COMPUTING INC / QUBT

  The report discusses QCI’s photonic quantum computing path, which is mapped through entity recognition to QUBT.US.

  Strengths

  The company emphasizes thin-film lithium niobate, room-temperature operation, lower power consumption, and reduced cooling requirements, and showcases the cloud-based Dirac quantum machine for complex optimization tasks.

  Weaknesses

  Commercialization remains at an early stage, and the report emphasizes that quantum usability and miniaturization still need to be proven over the next 3-5 years.

  Comparison

  Compared with Rigetti’s focus on the superconducting path, QCI emphasizes the potential advantages of photonic quantum computing in energy consumption, cooling, and miniaturization.

  Risks

  There remains uncertainty around the pace of quantum commercialization, customer adoption, competition among technology paths, performance verifiability, and integration with classical computing architectures.

• Rigetti

  Appears in the report as a case study of quantum computing commercialization.

  Strengths

  Focused on superconducting quantum computing; the report says it benefits from most of the industry’s R&D investment, as well as gate-speed and scalability advantages, and targets commercial progress in about three years.

  Weaknesses

  Quantum advantage still needs to be demonstrated in commercial applications with clear ROI.

  Comparison

  Unlike QCI’s photonic path, Rigetti represents the superconducting quantum path.

  Risks

  Government and private-sector funding, qubit quality, system scaling, ROI in application scenarios, and competing technology paths could all affect outcomes.

• KraneShares Global Humanoid Robotics and Physical AI Index ETF / KOID

  The report discusses humanoid robotics and physical AI investment themes through KraneShares.

  Strengths

  The theme spans value-chain segments such as AI computing power, semiconductors, sensors, actuators, and precision engineering, with near-term deployment scenarios concentrated in industrial environments.

  Weaknesses

  Consumer-grade humanoid robots remain a longer-term opportunity, while model reliability, data, and safety are still bottlenecks.

  Comparison

  The report believes nearer-term value is more likely to emerge in controlled industrial deployments and key components, rather than immediate adoption of general-purpose household robots.

  Risks

  Safety, regulation, social acceptance, model reliability, and insufficient real-world data may slow adoption.

• Vertical Aerospace

  Appears in the report as a case study of eVTOL commercialization and certification pathways.

  Strengths

  The VX4 aircraft is positioned as a quieter, safer alternative to helicopters, with applications including airport shuttle, regional travel, cargo, and defense.

  Weaknesses

  Commercialization depends on airworthiness certification, infrastructure, batteries, economics, and utilization.

  Comparison

  The report views eVTOL as a new transportation layer between ground transport and traditional aviation, rather than simply a helicopter replacement.

  Risks

  Certification targets for 2028-2029, charging infrastructure, noise standards, hybrid-power range, and customer adoption all carry execution risk.

• Wayve

  Appears in the report as a case study of the end-to-end AI autonomous driving approach.

  Strengths

  Foundation models, large-scale driving data, low-cost hardware, and integration with mass-produced vehicles could improve scalability.

  Weaknesses

  Commercial deployment still needs to prove reliability, utilization, regulatory approval, and safety performance.

  Comparison

  The report distinguishes Wayve’s end-to-end AI approach from traditional rule-based robotaxi systems.

  Risks

  Data moats, simulation effectiveness, safety liability, regulation, and business models are all key uncertainties.

• Matternet

  Appears in the report as a case study of autonomous drone delivery networks.

  Strengths

  The report says drones can cut delivery times by as much as 94% and reduce end-customer costs by at least 40%; a full technology stack helps integration and cost reduction.

  Weaknesses

  Scaling remains highly dependent on regulatory changes and network deployment density.

  Comparison

  Similar to autonomous driving, drone delivery is also moving from technical validation toward network deployment.

  Risks

  FAA Part 108, BVLOS rules, urban operating safety, customer density, and unit economics are the main variables.

• Helion

  Appears in the report as a case study of the fusion commercialization pathway.

  Strengths

  The report highlights direct electricity generation, a smaller footprint, lower complexity, supply-chain control, and iterative prototype development, with a long-term cost target of $1 per watt.

  Weaknesses

  The commercial power plant target and manufacturing scale-up still need to be validated.

  Comparison

  Compared with large reactor complexes, Helion places more emphasis on fusion generators and direct electricity capture.

  Risks

  Regulation and public acceptance, intellectual property, resource supply chains, technological differentiation, and intensifying competition are the main risks.

Key data

• Conference and research coverage>40 companies and speakers, around 20 field visits, expert calls, and the Transforming World ConferenceThe report uses these activities to showcase commercialization progress in technologies across mobility, computing, industry, energy, and space.
• AI fake citation riskIn 2026, more than 4,000 fabricated medical references appeared in about 3,000 biomedical papersThe report uses this data to illustrate factual reliability issues with generative AI in high-risk knowledge domains.
• Share of papers with fabricated citationsThe proportion of medical papers containing at least one fake citation rose from below 5% before mid-2024 to about 60% in the first quarter of 2026This data supports the report’s discussion of AI hallucinations and academic integrity risks.
• eVTOL time savingsA 120-minute car trip could become a 10-minute flightThe report positions eVTOL as a new layer of transportation between ground transport and traditional aviation.
• AI cost declineAI costs could fall to 1% of current levels within two yearsThe report believes falling costs will further drive AI penetration in knowledge work and automation scenarios.
• Robot deployment efficiencyRobot deployment in unstructured environments can be shortened from 3.5 months to 12 hours, a speed increase of more than 200xThis data reflects the potential change in deployment efficiency enabled by physical AI.
• U.S. drone delivery potentialBy 2030, U.S. drone delivery could reach 3 million to 5 million deliveries per day, versus roughly 3,000 to 5,000 per day currentlyThe report believes regulatory frameworks and BVLOS capability are key to scaling drone delivery.
• Rigetti quantum targetsTargeting 1,000 qubits, 99.9% fidelity, and advancing quantum commercialization over the next three yearsThe report says Rigetti is focused on the superconducting path and believes quantum advantage may gradually emerge in commercial applications.
• Helion long-term cost target$1 per watt, with a goal of advancing the first commercial power plant with Microsoft in 2028The report views fusion as a potential long-term solution to structural power shortages and growing AI electricity demand.

Impact & implications

For investors, the report suggests that frontier technology themes are moving from a narrative-driven phase into a commercially validated phase. Potential beneficiaries include not only individual OEMs or application companies, but also AI computing power, semiconductors, sensors, actuators, precision engineering, data systems, regulatory compliance capabilities, energy infrastructure, and software platforms with verifiable data moats. At the same time, technological progress does not equal certain investment returns; whether companies can build reliable products, obtain certification, lower costs, secure regulatory approval, and win repeat customers will determine how quickly thematic investing turns from vision into cash flow.

Risks

• Generative AI hallucinations and synthetic content may weaken fact-verification capabilities, affecting adoption in high-risk industries.
• Technologies such as AI, autonomous driving, robotics, and drones face constraints in commercialization from safety, regulation, legal liability, and social acceptance.
• Physical AI and humanoid robots remain limited by real-world data, model reliability, generalization in complex environments, and deployment costs.
• The timing of quantum computing commercialization and investment returns remains uncertain, with competition across different technology paths.
• eVTOL and drones require airworthiness certification, airspace rules, infrastructure, and unit economics to all align.
• Fusion and advanced nuclear face challenges in manufacturing scale-up, supply chains, regulation, public acceptance, and technological differentiation.

What to watch

• Whether AI models shift from pursuing engagement to stronger source attribution, factual reliability, and verifiable answers.
• Whether courts and regulators expand legal liability for platforms over AI-generated content, search results, and social media harms.
• Customer expansion, deployment cycles, accident rates, and ROI for humanoid robots in factories, warehouses, and logistics scenarios.
• Whether quantum computing companies can deliver repeatable, measurable ROI in optimization, pharmaceuticals, cryptography, or financial services applications.
• Certification progress for eVTOL around 2028-2029, charging infrastructure buildout, and defense/medical/airport shuttle orders.
• Whether rules such as FAA Part 108 drive scaled commercial BVLOS drone delivery in the U.S.
• Utilization, reliability, hardware costs, and regulatory approval as autonomous driving moves from pilot projects to commercial deployment.
• Whether AI electricity demand continues to rise, thereby reinforcing the investment case for fusion, advanced nuclear, and power infrastructure.