🚨TRunpod hit $120 million in annual recurring revenue after bootstrapping from a Reddit post offering free GPU access, demonstrating that AI infrastructure outside hyperscalers can scale to meaningful revenue by solving developer pain points two years before the boom.

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They never sleep, never age, and never have a scandal. They're making $10,000 a month. And they're not real.

In 2026, a new class of celebrity is dominating your feed—and they were born in Photoshop, not a hospital. AI influencers are no longer a novelty; they're big business. The global virtual influencer market was valued at $6.06 billion in 2024 and is projected to hit $46 billion by 2030, growing at a staggering +41% CAGR.

Lu do Magalu has ~8.4 million followers on Instagram, making her the world's most-followed virtual influencer. Lil Miquela has 2.3 million followers and has worked with Prada, Calvin Klein, and Samsung. Aitana López, a 25-year-old virtual model with pink hair, earned up to €10,000 monthly for her creators at The Clueless agency in Barcelona.

But here's what's unexpected: As these pixel-perfect personalities flood social media, they're not replacing human connection. They're intensifying the craving for it.

How it works:

AI influencers are CGI characters built using artificial intelligence, 3D modeling, and machine learning. Unlike their human counterparts, AI influencers are available 24/7, can collaborate globally without limits, and bring a novel, futuristic edge to brand campaigns.

The creation process is getting democratized. With just a few steps, anyone can design a character, give it a unique voice and style, and launch it as a full-fledged Instagram personality. Platforms like InfluencerStudio, Glambase, and SynthLife have emerged specifically to help creators and brands build, grow, and monetize virtual influencers.

These digital personalities do everything human influencers do—post lifestyle content, review products, attend "events," advocate for causes. Virtual influencer Aitana Lopez "attended" an Oasis concert in London. They respond to comments. They have personalities, backstories, and opinions.

The technical sophistication is remarkable. AI and ML programs lend virtual human influencers a more realistic look as they interact with their followers. They can smile, laugh, or make funny faces. They respond with varying lengths of pauses, speech rate, and word length. Thanks to these programs, virtual influencers can establish contact with the audience and sustain the connection on an emotional level.

Why people follow them:

The motivations are surprisingly human. 27% of users follow virtual influencers for their content, 19% for the storytelling and 15% because they inspire them.

AI influencers appeal to younger audiences that value digital-first, experimental content. There's a novelty factor—the boundary-blurring between fiction and reality creates intrigue. Their appeal lies in consistency, creativity, and the novelty of seeing a character that blurs the line between fiction and reality.

For brands, the value proposition is clear: They are immune to scandals, controversies, and personal downtime. They produce 24/7 high-quality content with zero lag. With their ability to adapt instantly, they align perfectly with the latest trends.

The agency's founder, Rubén Cruz, shared that he developed the virtual character in response to unreliable creators, saying, "We started analysing how we were working and realised that many projects were being put on hold or cancelled due to problems beyond our control."

And it's working. 35% of consumers have purchased a product promoted by a virtual influencer. 35% of responders on average said they have already bought a product or service promoted by a virtual influencer.

The business model:

AI influencers generate revenue through the same channels as human creators: brand partnerships, sponsored content, product placements, and even their own product lines.

Creators are now building virtual influencer monetization models, using AI influencer subscriptions and exclusive behind-the-scenes content to generate $10,000+ per month in revenue.

Major brands have embraced them. Brands such as Calvin Klein, Prada, Samsung, YouTube and Balmain have all worked with AI influencers in recent years. Noonoouri has collaborated with Dior, Versace, and Marc Jacobs.

Virtual influencers offer brands a unique advantage in terms of consistency, control over content, and the elimination of human error or controversies that can often arise with traditional influencers. According to Forbes, 58% of respondents follow at least one virtual influencer, and 75% of Gen Z are particularly engaged with them.

Virtual Influencers have almost three times more engagement than real influencers. That means that followers are more engaged with virtual influencers' content.

The paradox:

But here's where it gets interesting. As AI influencers proliferate, they're not satisfying our need for connection—they're exposing how hollow digital relationships can be.

The result? A counter-movement is brewing.

While AI influencers rack up followers and engagement, there's a growing hunger for the one thing they can't provide: real human experiences. The same audiences following AI influencers are simultaneously craving in-person events, meet-and-greets, and tangible human moments.

Think about it: When asked about trust, 35-44-year-old users are the cluster of people who are the most trusting (6.5/10) and find virtual influencers relatable (6.2/10). Followed by the 25-34-year-old age group who are trusting at a 5.8/10 level and find them relatable at a 5.7/10 level. In third place, 18-24-year-olds are trusting on average 5.2/10, and relate to virtual influencers on average 5.6/10.

Translation: Even the people following AI influencers know something's missing.

Only 23% of U.S. adults trust how generative AI is being used in social media, and another 39% said they would trust influencers less if they increased their use of AI.

The more brands deploy flawless, 24/7, never-tired AI personalities, the more consumers notice what's absent—messiness, vulnerability, spontaneity, humanity.

This is creating unprecedented opportunities for human creators who lean into their realness. Events are selling out. Pop-ups are packed. Conferences, workshops, and IRL experiences are commanding premium prices because they offer what no AI can: you had to be there moments.

The influencers winning in 2026 aren't choosing between digital and physical—they're mastering both. They use AI for scale and consistency (AI-generated content, automated responses, personalized videos at scale), but they double down on irreplaceable human touchpoints: live events, in-person meet-ups, surprise appearances, intimate workshops.

What brands are learning:

While AI creators offer scalability, cost savings and creative freedom, they raise concerns around authenticity, representation and regulatory compliance. In the future, campaigns will likely blend the flexibility of AI influencers with the relatability and emotional depth of human influencers.

Some brands are even creating hybrid strategies: AI influencers for consistent content production and baseline engagement, paired with human ambassadors for emotional storytelling and event-based activation.

What's next:

2026 won't be remembered as the year AI influencers replaced humans. It'll be remembered as the year we learned what only humans can do.

The prevalence of virtual influencers is rising with no signs of slowing down. These influencers have already become key players in social media, crypto, and similar industries and possess the potential to rival human content creators in influence in the coming years.

52.8% of marketers believe AI influencers have a significant impact on the future of marketing and entertainment.

But the smartest marketers aren't betting on one or the other. They're recognizing that AI influencers create a peculiar emotional void—one that makes genuine human experiences more valuable, not less.

The irony is perfect: The rise of AI influencers isn't ending the creator economy. It's clarifying what part of it was always about technology (reach, consistency, production) and what part will always be human (trust, emotion, shared experiences).

Expect to see this play out everywhere in 2026: More AI influencers on your feed. And more sold-out human experiences in your city.

The businesses that understand this duality—that scale and soul aren't opposites, they're complements—will own the next decade of influence.

BTW: A 2022 survey found that 58% of respondents followed at least one virtual influencer, and 35% had purchased a product based on a recommendation from one. But when asked about attending events? Human creators still own that category entirely. No one's camping overnight for an AI influencer's pop-up shop. Yet.

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The Recap: Sequoia Capital is joining Anthropic's $25 billion funding round at a $350 billion valuation—more than double its $170 billion valuation from four months ago—despite already backing both OpenAI and Elon Musk's xAI, shattering the decades-old VC taboo against investing in direct competitors. The move is particularly fraught given that OpenAI CEO Sam Altman testified under oath that investors with access to confidential information would lose that access if they made "non-passive investments in OpenAI's competitors," calling such restrictions "industry standard."

Unpacked:

Bottom line: Sequoia's move signals that AI has reached such scale that traditional VC rules no longer apply—when funding rounds hit $25 billion and valuations exceed $350 billion before IPO, firms can't afford to pick wrong. The "hedge across all winners" strategy makes financial sense for Sequoia's LPs, who get exposure to whichever foundation model emerges dominant. But it fundamentally changes what venture capital means, transforming it from high-conviction bets with deep strategic support into diversified portfolio construction where information barriers and conflict management become the primary skills.

Runpod reached $120M ARR serving 500,000 developers after bootstrapping from a Reddit post, proving AI infrastructure can scale outside hyperscalers by solving developer pain points with repurposed Ethereum mining rigs turned into GPU hosting.

ClickHouse raised $400 million at a $15 billion valuation with 250%+ ARR growth, challenging Snowflake and Databricks as open-source data infrastructure captures enterprise value faster than incumbents expected.

Threads surpassed X with 141.5 million daily mobile users versus 125 million, demonstrating Meta's cross-platform distribution and regulatory immunity beats product quality when platform dominance is infrastructure-level.

Moxie Marlinspike launched a privacy-first ChatGPT alternative, betting that data privacy concerns will fragment foundation model markets as cryptography expertise meets AI infrastructure design.

Big Tech successfully lobbied for EU digital rights rollbacks, suggesting market power converts into political influence that could reshape global AI governance as regulatory capture accelerates.

Amazon ended inventory commingling by March 31, revealing pressure to compete with AI-native logistics players forces even the most powerful platforms to reshape fulfillment economics.

Nvidia contacted Anna's Archive for training data access, exposing AI companies' willingness to exploit gray markets when licensing costs exceed utility—risking legal foundations of model training.

Wikipedia launched community-led AI content cleanup, admitting even crowdsourced platforms cannot outpace AI generation without structural governance changes to maintain quality.

Best of AI™ Team

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