The AI Effect: How startup funding is being redefined

As venture capital increasingly flows toward artificial intelligence, some investors note a growing trend of ‘AI-washing’ that is influencing startup narratives and shaping due diligence processes. Besides transforming businesses, artificial intelligence is also changing startup funding regulations.

In 2025, mentioning AI in a pitch is becoming increasingly important for startups seeking investor attention. For the first time, AI has accounted for more than half of venture capital funding, with $192.7 billion of the $366.8 billion invested globally this year going to AI businesses, according to PitchBook. In the most recent quarter, AI-led ventures received approximately 63% of all venture capital funding in the U.S.

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While marquee deals like Anthropic’s $13 billion Series F grab headlines, the broader funding landscape is narrowing. Only 823 venture funds have been raised globally in 2025, down from 4,430 in 2022. As PitchBook’s Kyle Sanford notes, the market is now “bifurcated — you’re in AI, or you’re not. You’re a big firm, or you’re not.”

AI has become a common expectation rather than a unique differentiator, influencing venture capital decisions through what is often called the ‘AI Effect’. In India, the emphasis is moving toward applied and agentic AI solutions that deliver measurable results, with sectors like SaaS, finance, and D2C also exploring AI integration. However, experts emphasize that long-term success will depend on defensibility and substance rather than just excitement or narrative.

AI as the New Default and the Price of Pretending

AI has moved from being a differentiator to a baseline expectation. Startups are expected to demonstrate how it contributes to efficiency, precision, or value, though the emphasis on appearing “AI-native” has led to concerns about credibility among investors.

According to Rahul Agarwalla, Managing Partner at SenseAI, “AI is not just an advantage, it’s the thesis. Every company we invest in must have AI as a core driver of value creation, not a marketing label.” Over the last 18 months, SenseAI has screened more than 1,700 startups across sectors, and “a large fraction were not AI-native but many pitched AI as a branding layer rather than as a core part of their value proposition.” Only about 207 passed their internal fundamentals test involving data, architecture, and technical diligence.

This phenomenon, often dubbed “AI-washing” has forced venture firms to sharpen their scrutiny. As Karthik Prabhakar, Managing Partner at PeerCapital, cautions, “AI is certainly table stakes when it comes to evaluating new investments, but it’s easy to be blind-sided in the current hype cycle. The opportunity lies in understanding how AI brings a sustainable advantage to the business in the medium to long term.”

Investors emphasise that AI should act as an efficiency multiplier rather than merely a buzzword. In a competitive market, startups that overstate their AI capabilities risk losing investor confidence.

India’s Edge in Applied and Agentic AI

India’s strength lies in applied and agentic AI, practical solutions focused on delivering measurable, scalable business outcomes efficiently, unlike the U.S. and China, which lead in foundational AI and deep-tech.

“India’s strength is in applied AI, building real-world tools, platforms, and enterprise applications that deliver tangible ROI,” says Prabhakar. He adds that the country still needs to “invest heavily in R&D to gain foundational depth” if it wants to compete globally in the long run.

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This practical focus leverages India’s strengths in scalability, problem-solving, and cost efficiency. According to Forbes India 2025, the country hosts the third-largest number of unicorns globally and ranks as the second-strongest startup ecosystem outside the U.S., positioning it to lead in AI-driven business models, including customer analytics, supply chain automation, and predictive insights.

Ashish Gala, Co-Founder at VentureSoul Partners, draws an important distinction, “AI investment can be split into two buckets, tech companies developing AI-based applications and those using AI as a tool. The first is niche and needs deep technical understanding, but for the second, AI has become almost a prerequisite to have smarter workflows and deliveries.” India, he says, is catching up quickly on the applications side, “but we are still far from having our native LLMs disrupt or replace global incumbents.”

Beyond AI: Traditional Sectors Are Adapting, Not Declining

With AI accounting for 53.2% of all money invested by global venture firms in the most recent quarter, as per PitchBook, India, however, the picture remains more balanced. Sectors like SaaS, D2C, and fintech still hold significant potential, even as the bar for innovation rises. Agarwalla observes that “pure-play SaaS or D2C pitches without AI integration find less attention than 12–18 months ago. But many are retrofitting AI layers, from customer segmentation to predictive churn to stay competitive.”

Prabhakar echoes this, noting that India’s consumer demographics are still maturing. “There’s still tremendous untapped opportunity in the D2C space and other non-AI segments,” he says. “Most AI investments in India are still a cross-border story, with revenue generation often tied to U.S. markets.”

The shift is not about abandoning non-AI sectors but about raising the bar of expectation. Founders now need to demonstrate how AI enhances performance, rather than simply being part of the tech stack.

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Speed, Scale, and the Moat Dilemma

AI startups are rewriting the speed of scale. Agarwalla notes that AI-led firms are growing “three times faster than SaaS,” with some hitting $1 million in ARR within two to four quarters compared to eight to twelve for traditional software companies. He adds, “many AI startups deliver measurable ROI from the very first deployment with higher productivity, more sales, reduced costs.”

However, both Agarwalla and Prabhakar warn that speed doesn’t equal defensibility. Without data loops, strong retention, and workflow integration, AI startups risk being easily replicated. As Prabhakar puts it, “Unless you’re building infrastructure-level AI, the defensibility is limited. What matters most is the ability to go to market fast and retain customers.”

Substance Over Hype: What Comes Next

For investors, the real challenge lies in separating meaningful innovation from market noise. As Gala points out, AI “will drive innovation and newer models,” but the winners will be those who treat AI as a tool for transformation, not as the transformation itself.

The future of venture funding is likely to favour startups that integrate AI seamlessly—making it invisible yet indispensable to their operations. While India’s venture ecosystem is clearly exhibiting an AI bias, it has not yet reached bubble levels. The market is maturing rather than overheating.

As the rush for AI-driven innovation continues, the next wave of standout startups will not be those who shout “AI” the loudest, but those that demonstrate its true value.