Can India's Startups Tap Into Generative AI Opportunity? Experts feel that the opportunity for Indian businesses offering these tools will depend on the size and maturity of the market

ChatGPT has brought significant attention to the generative AI (artificial intelligence) space. The opportunity for generative AI startups in both domestic and global markets is huge as it is a particularly exciting area of innovation within the broader field of AI. These tools can be used to transform everything from art and design to data analysis and decision-making. It can be used in software code, test cases, and concepts; help automate creative tasks and explain errors; and even create entirely new content such as stories, scripts, images, videos, and music. It has numerous potential applications, ranging from assisting artists and writers in the production of new works to aiding businesses in the development of more effective marketing campaigns.

According to a recent report, the global market for generative AI is anticipated to increase from $11.3 billion in 2023 to $51.8 billion in 2028 at a CAGR of 35.6% over the course of time. Prominent global startups in the space such as Jasper, Runway, Lightricks, and Stability AI have collectively raised over $500 million in funding showcasing the potential.

In terms of the domestic market, India has more than 4226 AI startups. But, so far there has not been any huge innovation in the generative AI space that can match up to OpenAI's ChatGPT or Google's Bard. That's why experts feel that the opportunity for businesses offering these tools will depend on the size and maturity of the market in question. "It will also depend on the specific needs and demands of customers within that market. In some cases, there may be significant demand for generative AI solutions within a particular industry or application area, while in others, the market may be less developed or more competitive," said Kavit Sutariya, general partner, CapFort Ventures.

Having said that, there is surely a growing demand for generative AI solutions on the domestic market as businesses seek innovative methods to reach their target audience.

Prominent business models in B2B and B2C

There are a variety of business models in the space such as subscription-based, pay-per-use/pay-as-you-go, customization, and licensing services. Within subscription-based services, which provide fixed subscriptions with unlimited usage, we have the global example of Canva, which uses generative AI to suggest design elements and layouts based on the user's content. There are also companies like Jasper chat and Artomatix, which provide generative AI tools. In the domestic space, we have startups like AlphaSense, that use generative AI to automatically extract key points and summaries from millions of documents so its users can quickly understand the most important information when analyzing earnings, prepping for earnings, or doing SWOT analyses. Companies such as Instoried and Pepper Content have been using generative AI to analyze customer data, identify patterns, and create personalized content for their clients. This has allowed these companies to improve their content quality, reduce costs, and increase efficiency. Bengaluru-based fintech startup Velocity has introduced an Indian version of ChatGPT, which offers users a personalized experience integrated into its existing analytics tool.

Besides fixed subscription models with unlimited usage, we also have the pay-as-you-go model, offered by OpenAI or a similar API-based service that lets you use their API and charges for the tokens used.

Both business-to-business (B2B) and business-to-consumer (B2C) startups are using generative AI, but B2B startups tend to be more common in this space. In the B2B space, generative AI startups are often focused on solving problems in specific industries, such as healthcare or finance, or for strategic use cases. These solutions may use generative AI to help automate processes, improve decision-making, or generate new insights. In the B2C space, generative AI startups are often focused on creating new forms of content, such as images, videos, or music. But since they have wider use cases or applications, they tend to run into accuracy issues.

Some companies may also add generative AI to a product or service already on the market. "Since the market for creative AI is still new and changing quickly, there isn't a single company that has a lot of power. There are startups that do well in both the B2B and B2C markets, as well as those that have added an incremental layer of generative AI to an established product or service. Each of these categories may be more or less common depending on the industry or application in question, as well as the startups' target market and business plan," said Sunil Shekhawat, CEO, Sanchiconnect.

There are a few startups facilitating the distribution and sale of generative AI works created by artists and designers. For instance, sportswear manufacturers Nike and Adidas are utilizing generative AI to let users build their own items.

Manikandan Thangarathnam, senior director, platform engineering, Uber for Deeptech spoke about how finding a differentiator is going to be the key for most companies, by quoting ChatGPT as an example, at Entrepreneur India's Tech & Innovation Summit 2023. "A few years ago, when software companies were developing software, just building a large-scale distributed system, software itself was a differentiator. That was when very few companies were able to handle petabytes of data.. When all these cloud platforms like AWS or Oracle Cloud came in, people felt that ..Oh, my differentiator is gone," he said while comparing generative AI being in the same place today.

Bhargavi V, partner, Java Capital who closely tracks sources such as a reputable blog that shares AI tools globally sees a minimum of 15 new additions daily. "In terms of use cases, B2B and B2C applications have been steadily emerging. The trends highlight the widespread adoption of generative AI in various industries," she said.

Sectors that have the most use cases

Generative AI has numerous applications across various sectors and experts expect to see more innovative applications of this technology in the future to solve complex problems.

• Content creation: The sector has been one of the earliest adopters of this technology and presents the most obvious use cases. Videos, blogs, advertising content, and other types of published content are now being created using generative AI.
• Healthcare: In healthcare, generative AI can help analyse medical imaging data, identify patterns in patient data, and generate synthetic data for training machine learning models. It is being used to generate personalized treatment plans, analyze medical images, and predict patient outcomes.
• Music & art: In the creative industry, designers can leverage generative AI tools to automate tasks and enhance their creative process and musicians can better create unique and personalized pieces.
• Finance: Many finance firms have begun using generative AI to create synthetic data for training machine learning models that can detect fraud more accurately. It is used to analyze market trends, make investment decisions, and manage risks. This technology can also detect fraudulent transactions and identify potential trading opportunities.
• Advertising and marketing: Generative AI has been used in marketing and advertising to make personalised content and improve ad targeting. This is one space which has seen fastest adoption of generative AI making it mature faster than ever before.
• Gaming and entertainment: Generative AI has been used to make virtual worlds, game content, and even improve the performance of game characters. AI-generated virtual characters and worlds can adapt to the player's behavior, making the game more engaging.
• Education: Personalised learning experiences and smart teaching systems have been made with the help of generative AI.
• Retail: Generative AI is being used in retail to personalize customer experiences, optimize inventory management, and improve supply chain efficiency. AI can analyze customer data to make personalized product recommendations and identify trends and patterns.

Going ahead experts expect to see collaborations in terms of mergers and acquisitions between startups and large companies. "Startups often focus on developing niche solutions that meet specific customer needs, which can be challenging for larger companies to replicate. But on the other hand, larger companies have the resources and reach to scale these innovations and bring them to market. Ultimately, both start-ups and larger companies have a role to play in the development and adoption of generative AI," said Raj Neervannan, co-founder and CTO, AlphaSense Technologies.

"Startups play a significant role in making generative AI more accessible, and user-friendly, and build solutions for specialized use cases. The collaboration between large companies and startups fosters innovation and accelerates the adoption and application of generative AI across various industries," added Bhargavi.

Experts expect to see many tech startups entering the generative AI space. But, the differentiating factor will be building something that others cannot replicate.