AI Funding Surge Reshapes Diligence Practices

The recent surge in investment for artificial intelligence (AI) startups is prompting significant changes in how the Big Four accounting firms conduct their due diligence. With an influx of capital, investors are increasingly focused not only on the founders’ credentials and market potential but also on the intricacies of AI technology itself. This shift has led firms like PwC and Deloitte to broaden their review processes to include detailed examinations of data sourcing, model training, and product effectiveness.

According to a report, Indian AI startups raised $832 million in 2025, with another $633 million in the first quarter of 2026 alone. This rapid growth has attracted a variety of investors, including private equity firms that typically demand more rigorous scrutiny than venture capitalists. As a result, Big Four firms are increasingly involved in these evaluations, moving beyond traditional financial diligence to assess technical capabilities and governance structures.

Raunak Bhinge, founder of Infinite Uptime, noted that as his company evolved, investor expectations shifted dramatically. Initially, his pitch revolved around digitizing factory equipment; however, as funding rounds progressed, investors began to demand clarity on how the technology functions and delivers value. This change illustrates a broader trend where the diligence process is no longer just about financial metrics but also about understanding the underlying technology.

As the diligence landscape evolves, the Big Four are adapting their methodologies. They are incorporating specialized teams that focus on AI, ensuring that they can provide comprehensive insights into the technology’s reliability and the company’s ability to scale. This proactive approach is crucial, especially as investors seek to navigate the complexities of AI-driven businesses.

This proactive approach is crucial, especially as investors seek to navigate the complexities of AI-driven businesses.

Investor Expectations Drive Deeper Scrutiny

The expectations of investors have significantly changed in light of the AI funding boom. Investors now demand a deeper understanding of how AI models are constructed and how they perform in real-world applications. This shift has led to a more rigorous evaluation process, with firms like Elevation Capital routinely involving third-party experts to assess the technology before making investment decisions.

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Krishna Mehra, an AI partner at Elevation Capital, emphasized that diligence now includes a thorough examination of the entire tech stack. Investors want to know how workflows are divided, which models are being utilized, and the training processes behind them. This level of scrutiny helps differentiate genuinely innovative products from those that merely repackage existing technologies.

Moreover, the Big Four firms are now tasked with verifying claims related to data usage and model efficacy. Siddharth Vishwanath, an advisory markets leader at PwC India, explained that their diligence now assesses not only the product but also the governance and compliance aspects of AI technologies. This holistic approach is essential in ensuring that investments are sound and sustainable.

Wider Implications for the Tech Industry

The implications of this shift in diligence practices extend beyond individual startups and investors. As Big Four firms engage more deeply with AI technologies, they are also influencing industry standards and best practices. This evolution is crucial as it sets benchmarks for new entrants in the AI space, ensuring that they adhere to rigorous standards from the outset.

Furthermore, the increased focus on governance and compliance may lead to a more structured approach to AI development. As companies navigate the complexities of AI integration, they will need to establish robust frameworks that address ethical considerations, data privacy, and regulatory compliance. This shift may also encourage startups to prioritize these aspects from their inception, fostering a culture of responsibility within the tech industry.

As companies navigate the complexities of AI integration, they will need to establish robust frameworks that address ethical considerations, data privacy, and regulatory compliance.

In the broader economic context, the growing investment in AI startups signals a shift in market dynamics. With significant capital flowing into this sector, it is likely to spur innovation and competition, driving advancements that could reshape various industries. As AI technologies become more prevalent, businesses across sectors will need to adapt to stay relevant.

This transformation presents both challenges and opportunities. While startups must navigate heightened scrutiny, they also have the chance to differentiate themselves through innovation and transparency. The evolving landscape of AI funding and diligence practices will undoubtedly shape the future of technology and investment.

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The current landscape raises questions about the sustainability of this investment boom. Will the increased diligence lead to more robust and reliable AI solutions, or will it stifle innovation by imposing excessive barriers? As the industry continues to evolve, these questions will be critical in determining the future trajectory of AI startups and their role in the global economy.