In the past two decades, Artificial Intelligence (AI) and Machine Learning (ML) have rapidly evolved, gaining substantial momentum in recent years due to significant investments. Once obscure concepts, these technologies are now widely accessible for various applications, spurred by events like the self-driving car movement and the launch of Chat GPT by OpenAI. Established tech giants lead the AI wave, yet startups find niches in infrastructure provision and process automation. Investor interest in AI startups has grown, with Indian funding increasing threefold from 2020 to 2022. Despite global economic pressures, AI startups receive support from government initiatives, although talent shortage remains a challenge. While early-stage AI funding thrived, recent data signals a decline, reflecting evolving investment patterns and potential challenges ahead.
Over the last two decades, cognitive technologies like Artificial Intelligence (AI) and Machine Learning (ML) have been evolving at a rapid pace. But it is in recent years that they have taken groundbreaking strides in terms of investments to propel growth. First emerging as obscure tools meant for a distant future, the technologies are now widespread and available to the masses for a variety of use cases. There have been two pivotal moments that have accelerated the adoption and investments into AI. The first is the self-driving car movement, and the other is the launch of Chat GPT by OpenAI. These two events have led to the belief that AI is now primed for everyday production, and no industry can afford to ignore investing in it. In this article, we will explore the investor opportunity for ventures building upon AI and the macro challenges that may impact the sector.
Startups are catching the AI wave
Unlike the internet boom of the 90s and the 2000s, where multiple new entrants came into the fold, the AI wave is being pioneered by established tech giants, as significant upfront investment is required to develop the technology. Yet, while the chunk of spearheading AI lies with the behemoths, startups can also find niches to operate in.
Broadly speaking, these startups can support two important business needs: first, many companies require third-party infrastructure providers to implement AI in their products; while the second opportunity lies in application work involving automating business processes. These are typically back-office administrative and financial activities, which help marketing and support departments within enterprises.
There are numerous examples of AI-based applications in the global market and many businesses are capitalizing on their capabilities to automate support queries or generate marketing content through AI. Closer home, in India too, one can witness the growing adoption of AI in various industries — from finance to healthcare, and education to e-commerce. Examples include chatbots for customer support, medical image analysis for healthcare, and personalized learning tools for education.
Investor interest in AI startups
Given their potential to transform various industries, there is growing investor interest in ventures building upon the capabilities of AI. According to Tracxn data, funding into these startups in the Indian market has increased threefold from 2020 to 2022, growing from $1.76 billion to $5.28 billion. Compared to the global context, Indian startups in the sector are becoming more prominent to investors, ranking the 3rd highest in terms of funds raised in 2022, according to Tracxn data. This places India ahead of the United Kingdom, Israel and France, pushing the country closer to becoming a global hub for AI applications development. Investors are eager to capitalize on the opportunities presented by AI and democratizing services that have hitherto been inaccessible, especially for smaller businesses.
Despite the contraction in private market funding globally, as well as in India, investment into AI-based ventures continues to flow. In Q1 CY23, there have been 50 funding rounds which have deployed capital to these startups. Online investing platform, Mensa Brands raised $36.3 million in debt funding, while machine vision player, Mad Street Den raised the largest equity deal in the period through a $30 million Series C round. However, the activity in funding is far less pronounced compared to Q1 CY22, where 133 funding rounds took place and the largest deal size was $400 million raised by conversational AI player Uniphore in a Series E round.
Inflows from private entities have been decreasing due to global macroeconomic pressures, but startups in this sector are continuing to receive significant support through government-led initiatives falling under Prime Minister Narendra Modi’s Startup India program. This fact becomes more salient when we see that leading investors in AI-based ventures in terms of portfolio count are T-Hub, a startup incubator created by a Public-Private-Partnership (PPP) fostered by the Government of Telangana, and Startup Karnataka, another state-level incubation program. Furthermore, initiatives like the National AI Strategy, the National Programme on AI, and the AI for All program, along with tax incentives for startups and investors, are expected to create a favourable environment for AI startups in India.
Growing investor interest notwithstanding, a challenge for AI-based startups lies in the fact that India’s tech ecosystem is still relatively new, resulting in a shortage of senior technical and PhD-level talent compared to more established tech hubs. This limits the number of startups founded by highly educated candidates. However, with the maturing of the tech ecosystem in the country, more senior technical talent is expected to stay, which will foster the emergence of more such companies in the future.
Private market investments will always go through cycles of extreme highs and lows and we are currently in the midst of a bear market. As highlighted earlier, Q1 CY2022 did see 133 funding rounds occur in the Artificial Intelligence space in India, receiving a total of $2.36 billion in funding. The sector was burgeoning with many new ventures, as the majority of funding rounds were dedicated to seed capital (75), followed by series A (15) and angel (13) rounds. This is not surprising as although the global startup ecosystem is experiencing a funding crunch that began in Q4 CY2021, early-stage deals did not lose momentum in 2022 and actually grew by 5.8% compared to the previous year. Investors are lowering their valuation metrics and are taking a more patient approach with late-stage deals, looking to fund ventures that portray clear paths to profitability.
Across sectors, startups in the early phases of growth have fared better in comparison to those raising late-stage capital. However, the current scenario for these nascent ventures Yet, as the development of AI-based applications is seeing phenomenal growth in India, supported by the launch of GPT and other large language models (LLMs), the verdict is still out on the sector’s resilience as compared to others.may not be as promising as it was in 2022. According to Tracxn data, total funding in Indian early-stage deals fell by 72% in Q1 CY2023 compared to Q1 CY2022. Moreover, AI startups’ total funding across early and late-stage rounds has reached a total of $308 million Q1 CY2023, which means they have gone through a steep decline of 87% YoY, where average funding amounts have fallen from $20.5 million to $8.34 million. With the recent collapse of SVB, Credit Suisse’s rescue by UBS, and proposed changes to the Angel Tax provision, the funding winter may be further exacerbated.