After a decade of investing in B2B/SaaS and discounting consumer investment, I’ve never been more excited about a paradigm shift than I am right now. The AI revolution is here, and it’s fundamentally transforming how humans interact with technology across every consumer vertical.
That’s why I’m thrilled to announce that Recursive Ventures is launching a $1M Consumer AI Program – 10 or more no hustle $100k checks – dedicated to backing the most promising consumer AI startups reshaping industries ripe for disruption.
Why Consumer AI? Why Now?
For the past decade, consumer technology has been dominated by incumbents who built their moats through network effects, data advantages, and customer acquisition expertise. Breaking into established markets required either massive capital to fund customer acquisition and challenge industry giants, or finding tiny, overlooked niches.
AI is rewriting these rules of engagement.
Gen AI is completely transforming Human-Machine interaction, enabling new user experiences. New UX have traditionally been a fertile ground for disruption in consumer (e.g. introduction of Mobile).
The democratization of foundational AI models has created an unprecedented opportunity for startups to build consumer experiences that are 10x better than what incumbents offer—without the need for billions in venture funding. AI’s ability to understand natural language, personalize at scale, and automate complex processes is enabling a new generation of consumer applications that feel fundamentally different.
But first, here are several consumer categories which I’m excited about in age of Consumer AI, and why:
Travel: Can we finally Disrupt the OTA Model?
The online travel agency (OTA) model has remained virtually unchanged for decades. Expedia, Booking.com, and others have merely digitized the travel agent experience without fundamentally improving it.
The consumer experience remains fragmented and cumbersome:
- Planning trips requires jumping between dozens of tabs and websites
- Comparisons are manual and time-consuming
- Personalization is shallow at best
- The booking-to-experience gap remains disconnected
AI is poised to transform this entire journey:
- Seamless Planning-to-Booking: AI agents that understand natural language can plan entire trips based on simple prompts like “Plan me a 10-day cultural tour of Japan with my family of four, staying in mid-range accommodations with easy access to public transport.”
- Hyper-personalization: By understanding preferences through conversation rather than form-filling, AI can recommend experiences that match your unique travel style.
- Dynamic Packaging: While OTAs offer basic flight + hotel bundles, AI can create comprehensive packages that include insider experiences based on your interests.
- Continuous Assistance: Unlike traditional OTAs that disappear after booking, AI companions can provide real-time support throughout the journey, handling everything from itinerary changes to local recommendations.
Companies building in this space are showing impressive early traction. Startups that combine LLMs with specialized travel knowledge are creating experiences that feel magical compared to the status quo.
Why has nobody disrupted OTA so far? Why is it ripe for disruption now?
First, OTAs have created a moat by integrating deeply into hospitality systems. This maot could now be disrupted by agents who can facilitate bookings over API, web-scraping, or other means without having to integrate into legacy systems. Second, OTA’s control online traffic, with Google reinforcing their position. This is again ripe for disruption because 1) Search is diminishing and LLMs are replacing 2) AI Agents can capture user’s attention before they actually book – much earlier, at the planning phase – basically pre-empting OTAs.
VCs have been ignore travel for a decade. Now could be the time to start looking again.
Shopping: Reinventing Discovery and Consideration
E-commerce has solved the transaction problem, but the discovery and consideration phases remain broken. Consumers still face:
- Overwhelming choice paralysis
- Generic and sponsored product recommendations
- Difficulty evaluating quality and fit
- Mistrust of reviews and sponsored content – the content is inherently adversarial, trying to convince you to buy vs. giving you the best advice for you
AI is revolutionizing this experience through:
- Intent-Based Discovery: Rather than browsing endless catalogs, AI shopping assistants can understand complex needs like “I need a waterproof jacket for hiking in the Pacific Northwest that packs small and weighs under 12 ounces.”
- Expert Consideration Support: AI can synthesize thousands of reviews, specifications, and use cases to provide nuanced comparisons that feel like talking to a category expert.
- Personalized Curation: By learning your preferences over time, AI shopping assistants can filter the infinite options down to the few that truly match your needs and style.
- Trust and Transparency: By providing objective analysis from multiple sources, AI can restore the eroding trust in online shopping recommendations.
The most exciting startups in this space are creating shopping experiences that combine the personalization of a personal shopper with the knowledge of a product expert—at internet scale.
What’s changed about investing in shopping? Why is it ripe for disruption now?
With the entire shopping experience moving from e-commerce to agents increasingly shopping on our behalf, e-commerce could increasingly become more of a deep technical area than just a pure DTC one.
The entire eco-system around shopping is “adversarial”. Ads, sponsored content, influencers funneling leads, etc. Agents can actually deal effectively with “adversarials” content and work through the noise. Agents could be best positioned to really understand customers’ needs, wants, and guardrails to pick the best product, not the one that paid the most to get featured.
For most VCs, investing in e-commerce has been challenging unless it’s a DTC brand that charges a premium (e.g. Eight Sleep). This has been pretty much the case since mid 2000’s when VCs wrote their last checks to companies like NextTag.
AI opens up an entire universe of possibilities and business models, including consumer subscription models (e.g. would a soon to be mom pay $10/month to have her personal shopper buy everything that her baby needs?). That put shopping potentially back on the map for VCs.
Personal Finance: Beyond Robo-Advisors
The first wave of fintech disruption brought us robo-advisors and mobile-first banking. But these innovations merely digitized traditional financial services rather than fundamentally reimagining them.
Personal finance remains:
- Generic rather than truly personalized. Even today you need a full-fledged family office or advisor to build a portfolio
- Reactive rather than proactive
- Fragmented across multiple platforms
- Limited in its ability to optimize complex financial decisions
AI is enabling a new generation of financial services that are:
- Truly Personalized: Moving beyond basic demographic profiles to understand your unique financial philosophy, risk tolerance, and life goals.
- Proactive Optimization: Continuously analyzing your financial activity to identify optimization opportunities, from debt restructuring to tax planning.
- Holistic Management: Integrating across investments, banking, insurance, estate planning, and taxes to optimize your entire financial picture.
- Democratizing Expertise: Providing the kind of sophisticated analysis and strategy previously available only to the ultra-wealthy through family offices.
The most promising startups here are creating AI financial advisors that combine the strategic thinking of a CFP with the analytical capabilities of a quant analyst—accessible to everyday consumers.
Are there opportunities for Consumer FinTech VC in this new AI age?
One of the holy grails of the pioneers of FinTech was to disrupt on-the-ground financial advisors. It hasn’t happened yet.
Yes, we have seen the rise of robo-advisors (e.g. Wealthfront, Betterment) and other approaches, but non had the ability to be fully customized and personalized to the needs of individual investors. Basically, we couldn’t replicate the work an investment advisor was doing in the real world.
With AI we can.
And this presents a massive opportunity for VC to back the next generation of investment advisor and wealth management tools. At a scale we haven’t seen before.
Education: The AI Tutor Revolution
Education technology has largely digitized traditional educational models without solving the fundamental problems of personalization and scalability. Even the best teachers cannot:
- Adapt to each student’s unique learning style
- Provide unlimited patience and repetition
- Be available 24/7 for questions
- Customize curriculum to individual interests
AI tutors are changing the game through:
- Infinite Patience: Unlike human tutors who get frustrated with repetition, AI tutors can explain concepts as many times as needed, in different ways, until it clicks.
- Learning Style Adaptation: Identifying whether you learn better through visual, auditory, or conceptual explanations, and adapting accordingly.
- Personalized Curriculum Pacing: Moving faster through concepts you grasp quickly and slowing down for challenging areas, unlike the one-size-fits-all classroom.
- Interest-Based Engagement: Connecting learning to your specific interests to increase motivation and retention.
The education startups showing the most promise are creating AI tutors that make learning feel like having a world-class teacher dedicated entirely to your success.
Personal Healthcare: From Reactive to Proactive
Healthcare remains one of the most broken consumer experiences, with:
- Limited access to expertise
- Reactive rather than preventive care
- Poor information continuity
- One-size-fits-all approaches to wellness
AI is enabling a transformation to:
- Continuous Monitoring: Using consumer devices and inputs to monitor health markers continuously rather than at infrequent doctor visits.
- Personalized Guidance: Creating wellness plans based on your unique genetics, microbiome, lifestyle, and goals rather than generic recommendations.
- Early Intervention: Identifying potential health issues before they become serious through pattern recognition across multiple data points.
- Knowledge Integration: Connecting fragmented health information across providers, research, and personal data to provide comprehensive guidance.
The most innovative healthcare AI startups are creating experiences that feel like having a physician, nutritionist, and wellness coach continuously monitoring and guiding your health.
Productivity & Knowledge Work: Amplifying Human Capability
Knowledge work tools have barely evolved beyond the digital equivalent of paper. Most productivity software still requires humans to:
- Manually organize information
- Format documents and presentations
- Perform repetitive tasks
- Remember connections between disparate pieces of information
AI is creating new interfaces that:
- Automate Mundane Tasks: Handling everything from scheduling to summarization to data entry, freeing humans for higher-value thinking.
- Context-Aware Assistance: Understanding your workflow to provide relevant information and suggestions without disrupting your flow.
- Creative Amplification: Helping generate ideas, refine writing, and visualize concepts based on simple prompts.
- Knowledge Synthesis: Connecting information across sources to identify patterns and insights you might miss.
The most exciting productivity AI startups are creating tools that feel like having world-class executive assistants, researchers, and collaborators at your fingertips.
Entertainment & Media: Personalized Experiences at Scale
Despite the streaming revolution, media consumption remains relatively passive and generic:
- One-size-fits-all content libraries
- Limited personalization beyond basic recommendations
- Passive consumption experiences
- Generic content creation
AI is enabling:
- Dynamic Storytelling: Interactive narratives that adapt to your preferences and responses in real-time.
- Ultra-Personalization: Content recommendations based on contextual factors like mood, time of day, and recent interests rather than just viewing history.
- Participatory Creation: Tools that allow consumers to become creators through AI-assisted content generation.
- Immersive Experiences: Combining AI with spatial computing to create responsive, intelligent environments.
The startups showing the most promise here are creating entertainment experiences that blur the line between consumption and creation.
What I’m Looking For
At Recursive Ventures, we’re committing a minimum $1M to this thesis, writing ten or more $100K checks to consumer AI startups that demonstrate:
- A product that feels magical: Using AI not as a feature but as the core of an experience that’s fundamentally better than what exists today.
- Early signals of product-market fit: This doesn’t necessarily mean revenue—it could be retention, engagement, or enthusiastic user feedback.
- Domain expertise + AI understanding: Teams that deeply understand both their vertical and how to leverage AI’s capabilities properly.
- Consumer empathy: A clear vision for how AI improves the consumer experience, not just technology for technology’s sake.
If you’re building something that reimagines consumer experiences through AI, I want to hear from you. Comment on this post with a short description of your startup, or get an introduction through someone in my network.
The next wave of generational consumer companies will be built on AI, and I’m excited to partner with the founders creating them.
Opportunity for VC and LPs
Over the last 10-15 years it’s been really hard for VCs to invest in consumer. Many have scaled back their Consumer investment practices.
With a few exceptions, it’s been the land of have and have nots – most Consumer companies weren’t funded unless they had traction, and once the company has had traction all the VCs would flock to it. Chicken and egg.
This old dynamic is now in flux. The ability to create decent consumer experiences at a fraction of the cost it used to cost (hello Vibe coding), the abundance of LLM models (and the introduction of new UX paradigms), and AI tools enabling rapid experimentation, are all creating a new generation of Consumer AI companies.
Today, consumer companies can figure out if they have a winner or not in a friction of the time and effort it used to take. How will Venture Capital adopt?
One approach, which is the approach we are taking, is to write much smaller checks against a bigger set of opportunities, to see what sticks. We no longer need millions to validate if an B2C idea has traction. Sub <$1m can do the trick.
Once we find a winner with real traction we can increasingly fund it to put more gas on the flame, build big brands, and acquire users with reasonable cash recovery cycles.
Why This Matters
Beyond the investment opportunity, I believe Consumer AI represents something profoundly important: technology that adapts to humans, rather than forcing humans to adapt to technology.
For too long, we’ve accepted clunky interfaces, fragmented experiences, and one-size-fits-all solutions as the cost of digital convenience. AI has the potential to reverse this pattern, creating technology that feels natural, personalized, and truly empowering.
The companies that succeed in Consumer AI won’t just generate venture returns—they’ll fundamentally improve people’s lives by making technology more human.
And that’s an investment thesis I can get behind.
If you’re building in Consumer AI, I’d love to hear from you. Recursive Ventures is writing ten no-hustle $100k checks to Consumer AI companies. Apply by commenting on this post or even better – get a warm intro through my network.