This development highlights the expanding influence of AI across industries and the intense competition shaping its future
The artificial intelligence (AI) landscape is witnessing rapid shifts, with the recent emergence of DeepSeek as a formidable challenger to ChatGPT. Developed at a fraction of the cost of its competitors, DeepSeek’s success is a testament to how AI innovation continues to evolve beyond the traditional reliance on massive computing power.
This development highlights the expanding influence of AI across industries and the intense competition shaping its future. As businesses increasingly integrate AI-driven solutions to maintain a competitive edge, venture capitalists (VCs) are closely monitoring startups that bring fresh innovation to the sector. However, while investor interest in AI is at an all-time high, caution remains over the long-term viability of these technologies.
VCs Assess Longevity Of AI Startups
Speaking to Business Today, Ankit Anand, Founding Partner at early-stage VC firm Riceberg Ventures, notes that DeepSeek has overturned the traditional belief that solving large-scale AI problems requires ever-growing computing resources.
“DeepSeek challenged the conventional wisdom that you just ‘throw more compute’ at large-scale AI problems. By applying a novel architecture, they lowered costs and improved performance, proving that true breakthroughs can still happen even in today’s fast-moving AI landscape,” he says.
Anand adds that VCs are now evaluating AI startups based on their long-term strategies rather than just short-term technical achievements. “In this landscape, usually VCs measure how the team intends to stay ahead as AI evolves. If they have a clear vision for ongoing R&D and a track record of technical execution, that indicates real staying power rather than a one-off innovation,” he explains.
Challenges In Betting On AI
Despite the excitement surrounding AI investments, the sector presents significant risks. A major challenge for startups comes from Big Tech giants like Microsoft and Google, which can rapidly incorporate AI capabilities into their existing products, making many niche solutions redundant.
Sahil Chopra, VP, Growth & Marketing at Gurugram-based Inflection Point Ventures, highlights additional hurdles such as high computing costs, regulatory uncertainty, and the risk of obsolescence.
“The key is to support businesses with good execution, agility, and a well-defined monetisation plan. With the appropriate team and a clear route to product-market fit, these risks may be transformed into substantial possibilities,” he says.
Investment trends in AI are also shifting. While early funding rounds often focused on core AI models, attention is now turning towards applications and infrastructure. This shift is driven by the realisation that while developing foundational AI models demands significant resources and faces intense competition, applications and infrastructure firms provide long-term value by enabling AI adoption across industries.
However, the surge in AI valuations has led to concerns about overvaluation. Startups without a strong technical advantage may struggle to secure follow-on funding, particularly if larger companies enter their space.
Need For Continuous R&D & Smart Engineering
Bruce Keith, Co-founder and CEO of Bengaluru-based AI investment firm InvestorAi, believes DeepSeek’s success underscores the power of smart engineering over brute computing force.
“What DeepSeek has done is shown what smart engineering can do and reminded everyone that the race is never won after the first lap,” he says.
For AI startups, Keith stresses the importance of sustained investment in research and development (R&D). “For us as a startup, we continue to spend a substantial portion of our budget on R&D—it is 15-20 per cent of our headcount. It is important to keep experimenting, but to do it with a clear end goal on what you are solving for. In the applications space, being vertical and having deep domain knowledge is a key input into AI coding and engineering,” he adds.
As AI innovation accelerates, both startups and investors will need to navigate an industry that is still evolving—where today’s groundbreaking advancements could quickly become obsolete. The challenge will be identifying which technologies will endure and which will fade, making strategic foresight crucial in the fast-moving AI ecosystem.