Generative AI Gets a SaaSy Touch Tapping into the current Generative AI opportunity are India's leading SaaS companies, who are investing in it like never before

The buzz around Generative AI continues unabated. But, it is no longer just a new kid on the block, it is a new reality that no one wants to shy away from. In fact, it won't be incorrect to say that Generative AI (artificial intelligence) has stolen Web3's thunder. There is also a heightened realization that the opportunity for generative AI startups in both domestic and global markets is enormous and that the bus can't be missed.

The global Generative AI market size was valued at USD 8.2 Billion in 2021, and is projected to reach USD 126.5 Billion by 2031, growing at a CAGR of 32% from 2022 to 2031. In India, investors are also riding the wave. According to Venture Intelligence's data, the share of VC investments in AI startups stands at 15 per cent of the total VC funding in the first five months of 2023 (January-May) compared to a corresponding 10 per cent share commanded by AI startups in 2022.

Although pure-play Generative AI startups are not that common yet in India, with only few players such as Rephrase.ai, Blend, ProbeAI, Fasthr.AI, the technology has set foot in many industries such as healthcare, music and art, finance, advertising and marketing, gaming and entertainment, among others. This has opened up huge opportunities for the SaaS (software as a service) sector.

Tapping into this market are India's leading SaaS companies, who are following the footsteps of global software giants like SAP, Salesforce, and IBM and investing in Generative AI like never before. According to a report by Stellaris Venture Partners and IFC, Indian SaaS startups that harness AI could achieve a $500-billion market value by 2030. And, Generative AI is a particularly exciting area of innovation within the broader field of AI.

We spoke to some of the SaaS companies to get a sense of the ground reality of its application in the SaaS space.

Making the Best Use of the Opportunity

Given SaaS giant Zoho's technical expertise and know-how focus over the years, it has been working on its AI stack for the past twelve years, with a significant chunk of its profits being invested in R&D across tech stacks. Over the years, the Sridhar Vembu-founded company has incorporated a few generative AI use cases across its apps as well.

However, most of them in use are outside the medium-sized models' category - including but not limited to translation, grammar error correction/detection, Natural Language Q&A in BI tool, etc. "We have also identified cases in our broad product suite utilizing Generative AI. For instance, to not only help sell better using Zoho CRM but also resolve customer support faster by collating and gathering information from the knowledge base, past interactions, transcribing our meetings and generating actionable insights etc," said Ramprakash Ramamoorthy, director - AI Research, Zoho Corp.

In the short term, the company has integrated with Large Language Models (LLMs) available in the market. In the medium term, it will deploy more LLM capabilities across the board in its offerings, and in the long term, it will own all Large Language Models in the Zoho Cloud, thereby offering privacy and value to its customers. Currently, its R&D wing is working on an LLM that can do Summarisation, Paraphrasing and Deep nested conversations.

"We are also noticing increasing interest from our customers for AI features, not just in the large language models space. We see our existing AI feature usage increase by a significant margin, thanks to all the noise around AI. This is also an affirmative sign for the adoption of this technology," said Ramamoorthy.

Other prominent SaaS companies are also investing heavily in Generative AI. Freshworks recently unveiled Freddy Self-Service, Freddy Copilot and Freddy Insights to make AI more accessible to every workplace. The new predictive and assistive generative AI capabilities embedded within Freshworks solutions and platform are said to go beyond content generation and help support agents, sellers, marketers, IT teams and leaders become more efficient with a revolutionary new way to interact with their business software.

"We have been helping customers run more efficient businesses with AI for half a decade and know they don't need a billion apps to do so. Every department could benefit from a workplace assistant that maximizes productivity, and that's what Freddy AI can do – for the support agent, salesperson, marketer, IT manager, HR professional, developer and more," said Girish Mathrubootham, founder and CEO, in a statement.

This technology allows SaaS to solve several key challenges for its customers. Ranging from finding information efficiently and accurately, to generating high-quality content when crafting responses.

RFPIO, is another SaaS company that recently announced that it would offer Generative AI capabilities within its software to help marketing, sales, finance and security professionals create and edit proposals, questionnaires and other responses that play a vital role in revenue growth and risk mitigation for their organizations. The response management SaaS company caters to Adobe, Atlassian, Google, Microsoft, Tenable, Zoom Video and others.

RFPIO believes Generative AI has enormous potential to help response teams automate simple and repetitive tasks while freeing more time for strategy, creativity and customer engagement. "There is no question that GPT will help businesses embrace large language models to drive greater workplace productivity," said AJ Sunder, Chief Product Officer and CIO, RFPIO. He believes that Generative AI will help response teams draft responses, perfect the response language with easy writing aids, and provide complete, compliant responses every time. "In short, this new capability can help responders to be even more effective and efficient with their work," he said.

Bengaluru and California-based SaaS company Zendesk has also been partnering with LLM providers like OpenAI to extend its core offering and create personalized and valuable customer conversations. "With our AI-powered solutions, businesses are able to start using our solutions in minutes, without specialized developer skills required, costly training or expensive integrations. This increases time to value and ensures a positive return on investment in AI for businesses," said Vasudeva Rao Munnaluri, RVP, India & SAARC, Zendesk

When done right, AI can be a force multiplier for CX teams, enabling consistency, and helping them better understand customers with actionable insights and that is why the company continues to invest in AI, including generative AI, to explore new ways to support our customers in deploying AI that's built on trust, security and reliability.

However, almost all experts agree that it is still a long way to go before we resolve all the challenges that come in the way of scaling up.

Hurdles Faced by SaaS Companies

Experts say that even though the market for creative AI is still new, it is changing quickly and moving at an incredible speed. Thus, keeping pace, and being able to change course with new developments can be challenging. The second challenge is also related to how new the technology is. "There are a lot of unknowns, a lot of information being thrown, some accurate, some not so accurate. Understandably some of our customers are a bit apprehensive and are taking a cautious approach," said AJ Sunder.

There are a lot of unknowns regarding the privacy implications of these models as well. "As a privacy-conscious company, this is one of our major concerns. It is indispensable to have sufficient guard rails to ensure that the model does not let out any sensitive information during hallucinations," said Ramamoorthy.

Further, in the case of larger models, it would require a larger training data set, and the availability of such huge datasets is a challenge. "Open-source datasets are trying to bridge this gap, but they still have a long way to go," he added.

While building LLMs, the lack of availability to compute is another difficulty that is encountered. "GPU (Graphical Processing Units) has multi-threading capabilities and these models need such intensive levels of computing," Ramamoorthy further added.

Role of SaaS Startups in Accelerating Adoption

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.

Can SaaS startups play a key role in making generative AI more accessible and fool-proof? "There are endless possibilities with a technology like Generative AI. Startups may lack the resources of large enterprises but can make up for that by being nimble, willing to experiment, fail and learn quickly," said Sunder.

Startups have always been known to push the barriers to developing and adopting new technologies and there's a massive opportunity for startups to make generative AI solutions more accessible. "Startups have the potential to amplify the value of generative AI solutions and given the SaaS boom, their generative AI solutions can allow businesses to rapidly adopt AI-driven solutions without traditional software infrastructure, thereby making AI more accessible than it is now," said Munnaluri.

As someone watching this space closely, Ramamoorthy feels that the current ecosystem is yet to solve the privacy, data and compute-hungry problems and it would need the nimbleness of a startup and the resources of a mega-corporate to bridge the gaps.