2024 was a year filled with experimentation for AI. While several businesses were still playing catch-up, a few of them were forging ahead—eager to rake in measurable results and ride the GenAI wave.
Artificial intelligence has unlocked a new era of growth for India’s software-as-a-service (SaaS) industry, unleashing a whole new generation of AI-enabled services and opportunities, proving once and for all that those who get on board early are the ones who soar the highest.
According to industry body , GenAI investments in India rose over sixfold during the second quarter of FY25 to $51 million, across 20 funding rounds, on the back of growing interest in B2B platforms and productivity solutions.
This marks a significant rebound from the first quarter when funding was $8 million.
As the year progressed, the SaaS industry witnessed a nuanced version of potential opportunities and challenges—which shaped the sector as a whole. As we move forward to 2025, the landscape is set to be disrupted once more—forcing businesses to adapt to AI and push the boundaries of what’s possible in AI-driven ecosystems.
Increased investments in AI for ROI
The SaaS sector is on track to achieve $50 billion in annual recurring revenue (ARR) by 2030, mainly driven by the transition of traditional SaaS firms from pure-play models to integrated GenAI offerings. Bessemer Venture Partners notes that this transition will position India’s SaaS market to generate three times its current revenue by 2030.
“In 2024, AI investment has become a boardroom priority, with CIOs and CTOs actively charting their strategies. Much of the focus has been on horizontal platforms like ChatGPT and Glean. As we move into 2025, we expect a shift toward vertical and use-case-specific AI solutions, which are poised to deliver much higher ROI and drive greater adoption,” Krishna Mehra, Partner at tells YourStory.
The former Meta executive was recently appointed as a partner at the early-stage VC firm to lead SaaS and AI investments for the fund.
“While AI adoption will be broad, the prosumer and SMB segments will lead the way due to their agility and ability to realise ROI quickly. We’re already seeing small, 10-person companies achieve unprecedented productivity and innovation,” he adds.
A striking example of this shift recently came from Sebastian Siemiatkowski, CEO of Stockholm-based fintech firm Klarna, who has not been actively hiring employees for over a year. Instead, he has opted to rely on artificial intelligence tools to do the job. In an interview with Bloomberg, he stated that “AI can already do all of the jobs that we as humans do.”
“If 2024 was marked by an AI gold rush, 2025 will be defined by AI utility. Organisations have been rapidly adopting AI to stay competitive and seize new opportunities. Enterprises must start to identify their goals for AI adoption — whether that be getting the information they need faster, accelerating strategic decision-making, speeding up productivity, or something else,” Vijayant Rai, Managing Director- India, tells YourStory.
Indian enterprises are now transitioning from AI experimentation to maximising the impact of their AI investments, according to an report. Surveyed businesses in India expect AI to deliver long-term benefits in key areas, including innovation (26%), revenue growth (21%), cost savings (12%), and enhanced employee productivity (12%).
“Companies are adopting metrics to evaluate the success of AI initiatives beyond traditional ROI. For eg, organisations are focusing on customer engagement levels, retention rates, and feedback as indicators of success. Second, evaluating how AI impacts employee workload and productivity can provide insights into its effectiveness beyond financial returns,” says Somshubhro Pal Choudhury, Co-Founder & Partner, Bharat Innovation Fund, a deep-tech-focused VC firm.
According to the latest Freshworks AI Workplace Report, Indian firms are set to increase AI spending by an average of 41% in 2025—the highest growth rate globally, as 79% of organisations plan to increase their AI budgets. The report, which surveyed 4,000 global professionals, revealed that Indian firms believe AI’s integration is essential, driven mainly by confidence in its ROI.
“Many organisations initially approached AI with an experimental mindset, using pilot projects to gauge feasibility and potential ROI. However, businesses are now embedding AI into their core operations to drive measurable business outcomes,” says Maneesh Bhandari, Co-founder and CEO, Growthpal.
Ramprakash Ramamoorthy, Director – AI Research, believes the rise of multi-agent AI systems—where specialised agents collaborate to tackle complex workflows—has made it easier for businesses to integrate AI into enterprise operations.
“Industries such as finance, healthcare, and logistics are expected to see the highest AI investments by 2025, driven by their need for smarter automation, predictive analytics, and more efficient cross-functional decision-making,” he says.
Boom of agentic-AI
The SaaS sector is swamped with innumerable AI chatbots and co-pilots to streamline customer interactions and optimise workflow. The landscape is about to be disrupted once more—this time by AI agents.
According to Choudhury, agentic AI, defined by its ability to make decisions and perform specific tasks without constant human oversight, is set to revolutionise industries in 2025.
“While traditional AI has been attempting to do individual cases, Agentic AI creates a plethora of agents doing specific tasks and orchestrating them together to achieve an outcome more autonomously,” he explains.
GenAI is entering a phase of “agentification,” changing from task-specific tools to specialised, interconnected AI agents, says Sindhu Gangadharan, MD, SAP Labs India and Chairperson at NASSCOM.
“At SAP, we are leading the way in multi-agent AI with SAP Joule, empowering organisations to embrace interconnected AI ecosystems. These frameworks allow specialised AI agents to work together, tackling complex challenges such as supply chain optimisation, predictive maintenance, and customer service,” Gangadharan says.
Funding in the GenAI sector is following in the wake of this trend. Raj K Gopalakrishnan, Founder of KOGO, notes that firms are shifting AI investments from small pilots to large-scale deployments, driven by the need for ROI through workflow automation and enhanced customer experiences.
“In 2024, many companies were flirting with AI agents, exploring their potential through prototypes and proof-of-concept projects. However, 2025 is shaping up to be the year of AI agent implementation, as businesses prioritise enterprise-wide integration to address real-world challenges,” explains Gopalakrishnan.
Large language models have reached a ceiling in their capabilities of what they can achieve on their own. Much like the human brain which requires external resources to expand its knowledge, Ramamoorthy says the same principle applies to agentic AI as well.
“Agentic AI allows LLMs to real-time, structured data sources from various systems, allowing them to help organisations make better decisions. In healthcare, an agent-enabled system could tap into patient records, research databases, and medical device outputs in real time. In logistics, it could route shipments based on current traffic patterns or inventory levels,” Ramamoorthy explains.
Need for data governance
While companies have been busy building impeccable solutions using GenAI over the last 12-18 months, several experimental projects are going into production. But this also means a call for security and data governance, says Anshu Sharma, Founder and CEO, Skyflow.
“Unlike demos, this requires enterprise-grade data security, data privacy and data governance. No one wants to see one customer accidentally book a hotel using another customer’s card number, or have one employee accidentally see or update another employee’s annual bonus. Agents are integrating with multiple systems of record, and we now need to have a new layer of security & privacy for these agents,” Sharma explains.
According to Ankush Sabharwal, Founder and CEO of CoRover, deploying Agentic AI at scale also brings challenges like data bias, transparency, and operational dependency.
“Ethically, AI systems may unintentionally reinforce biases in training datasets, leading to unfair outcomes in decision-making. Addressing this requires constant monitoring and diverse, well-curated data. Businesses face challenges around integrating AI with legacy systems, ensuring reliability, and managing the significant compute resources required for scaled deployments,” Sabharwal says.
Many organisations and industry bodies have stepped up efforts in this regard, including UNESCO’s Recommendation on the Ethics of Artificial Intelligence, OECD’s Principles on Artificial Intelligence, EU’s Artificial Intelligence Act and IEEE’s Ethically Aligned Design.
“Besides following these guidelines, the following need to be of paramount importance. One is implementing robust governance frameworks and the other is conducting regular assessments of models for bias and fairness to help mitigate ethical risks,” Choudhury explains.
Organisations may face several hurdles while scaling their AI solutions, but the biggest one is the lack of regulatory guardrails, believes Jaspreet Bindra, CEO of AI&Beyond.
“While some companies are building their own guardrails, there is no global or national regulation-except in the European Union. This makes companies hesitant to scale. Other issues include cost, privacy concerns, and data leakages,” Bindra says.
Data centre boom
This year, the country has drawn global AI pioneers to its shores—Meta AI Chief Yann LeCun, NVIDIA CEO Jensen Huang, and Microsoft AI CEO Mustafa Suleyman – who are all exploring opportunities in the Indian market.
Notably, Huang heralded that India will have nearly 20 times more computing power in just one year driven by the AI push.
AI is indeed transforming data infrastructure in India, driving the increase in the demand for computing power and storage.
“AI is accelerating a transformative shift in data center design and operations, pushing us beyond traditional approaches. Data centers will need to be architected not just for raw compute but for intelligent orchestration, where AI-driven systems continuously balance workloads, anticipate hardware failures, and optimise for both performance and sustainability,” says Karan Kirpalani, Chief Product Officer, .
‘s AI venture, Krutrim, is also aiming to produce India’s first AI silicon chips by 2026—these are processors specifically built for complex AI tasks and workloads.
Deepak Padaki, President, Catamaran believes that Edge-AI is also becoming an important area for AI application today, with market reports suggesting it will start to grow significantly in the 2026-27 timeframe.
Edge-AI refers to running AI algorithms on local devices—like smartphones or IoT sensors—instead of the cloud. By processing data on-site, it reduces latency and protects privacy, making it ideal for real-time tasks such as autonomous vehicles and smart homes.
“We are in a phase where the bulk of AI investments are being made in cloud and data centre infrastructure as the focus has been on training neural network models with vast amounts of data. As we start to move now into a phase where applications become important, efficient inference engines will become a focus. Edge-AI related technologies will play a huge role in spurring new applications that meet user functionality requirements and user experience,” Padaki proclaims.
India’s journey toward becoming a $1-trillion digital economy will hinge on its ability to deliver AI-driven solutions serving its large population. However, robust policy support and surging investments in AI will also play a key role in paving the path to becoming a tech powerhouse to be reckoned with.
