AI to enhance SaaS offerings, help extract more value from software: LeadSquared COO

The enterprise Software-as-a-Service (SaaS) landscape has seen significant transformations over the past few years, driven by the widespread adoption of cloud-based software and the shift from one-time Capital Expenditure (CapEx) purchases to subscription-based operating expenses (OpEx) models. As businesses increasingly rely on SaaS solutions for critical functions, Artificial Intelligence (AI) is emerging as a key enabler, enhancing software capabilities and improving customer outcomes. 

Founded in 2011 in India, LeadSquared offers sales and marketing automation solutions to help businesses optimise customer relationship management and sales processes. 

In a conversation with TechCircle, Prashant Singh, COO and Co-Founder, discusses the evolution of SaaS buying behavior, the growing impact of AI in sales and Customer Relationship Management (CRM), and trends shaping the industry’s future. Edited Excerpts:

What major shifts have you observed in enterprise SaaS buying behavior, especially in India, over the past two to three years? 

There’s been a clear shift from perpetual licences to SaaS. SaaS is now a common option for enterprises buying software. 

Deployment has also moved from on-premise to cloud-based SaaS. It took time for enterprises to trust that SaaS could meet business needs while also offering the level of security expected from on-prem solutions. Over time, enterprises, SaaS vendors, and cloud providers have all learned and adapted. 

Now, even sensitive applications like those in financial services can be securely hosted in the cloud. Not all SaaS vendors meet high security standards, but many do. 

This shift includes changes in mindset, deployment architecture, and security capabilities. Regulatory bodies like Reserve Bank of India (RBI), Securities and Exchange Board of India (SEBI), Insurance Regulatory and Development Authority (IRDAI), and the Mutual Funds Association of India have introduced frameworks that help SaaS vendors standardise and stay compliant. 

Earlier, software purchases were treated as one-time CapEx investments with annual maintenance. Now, CFOs are more comfortable with SaaS as an OpEx model, paying on a subscription basis without owning the software Internet Protocol (IP). 

The SaaS ecosystem is maturing. Alongside cloud adoption, AI, especially generative AI is emerging as a key enabler. It’s expected to enhance SaaS offerings and help customers extract more value from their software. 

What trends are you seeing in the consolidation or fragmentation of the SaaS ecosystem, particularly in sales and CRM technology? 

CRM is a crowded space, both globally and in India. Most players haven't scaled significantly. There's heavy competition at the lower end of the market, with many small companies offering CRM solutions. However, many of them struggle to gain traction and grow. Some of these companies will eventually shut down or get acquired by mid-size or larger SaaS firms. 

Among mid-size players, consolidation hasn’t happened yet, but it's likely in the next few years. Right now, each company is focused on its own strategy. Some will succeed, others may not. Companies that don't perform well or face investor pressure to exit could become part of consolidation activity. 

Currently, most growth-stage companies are focused on execution and reaching profitability. Over time, factors like investor exits, performance issues, or market and technology shifts may drive more consolidation. 

Where do you think AI is delivering real RoI in sales and CRM? 

One clear area where AI delivers return on investment (RoI) is in improving salesperson productivity. It can handle routine tasks, like executing workflows or entering data, on their behalf, based on pre-set rules or intelligence. 

The second area is sales intelligence. AI can score leads and opportunities, helping salespeople prioritise the ones with the highest chance of closing. It can also guide conversations with prospects, suggesting what to say and what actions to take next. 

Overall, AI contributes to better productivity and conversion rates. It’s already showing measurable results in these areas. Another use case is reactivating old or inactive leads using AI chatbots or voicebots. These bots can engage contacts and then pass qualified leads to human salespeople.

Improving the end customer’s experience across sales, service, and marketing is also a key area. The focus here is less on supporting the salesperson and more on ensuring a smoother, more relevant experience for the customer. AI can help significantly. 

Beyond these, there are common AI applications like generating content for emails, marketing campaigns, landing pages, and replies to service tickets. These are widespread and evolving fast. 

There is value in applying AI to all these areas. However, there’s also a lot of hype, especially around AI replacing entire companies. That might be partly true, but it’s too early to tell. Time will show how it really plays out.

Do you think Indian SaaS companies are building foundational AI, or is most innovation focused on leveraging existing Large Language Models (LLMs) or application binary interfaces (ABIs)? 

Most of the work in AI today involves modifying existing models and integrating them into application layers. A McKinsey paper describes three types of players in the AI space: makers, shapers, and takers. Makers are those who develop foundational models, usually large tech companies with the necessary resources for deep research and development. Shapers focus on adapting these models to specific domains or use cases. Takers simply consume AI through Application Programming Interfaces (APIs) without making changes to the underlying models. Most Indian tech and SaaS companies operate as shapers or takers. There are a few makers, but so far, they haven’t produced any notable results. 

What are the key differences you've noticed in sales processes and digital adoption between India and other markets? 

Yes. Indian clients are generally okay with compromising on functionality or user experience (UX) as long as the product meets their goal and fits their budget. Given a choice between a high-end software with excellent performance and UX, and another that simply gets the job done, they might choose the latter if it’s more cost-effective. 

In contrast, global clients, especially in the US and Europe, prioritise quality. If a product lacks in that area, they’re less likely to stay loyal. Quality is a key factor in their decision-making. When it comes to adoption, international users usually prefer self-serve software. They expect the product to be intuitive and don’t want to rely on support or training. They’re typically low-touch users. 

In India, it’s the opposite. It’s a high-touch market where people expect personal interaction both during and after the sales process. They often want someone available, on call or in person, for support or questions. Also, Western clients are more willing to pay for services, while in India, there’s usually less willingness to pay for added service or support. 

These are some of the core differences in how software is evaluated, adopted, and supported across markets. 

What’s next for your company in terms of product innovation, market expansion, or acquisitions? 

AI is helping us and others improve existing systems to deliver better outcomes, whether in sales, cost, or customer experience. That’s where most of our innovation is focused. We're also building an analytics platform powered by AI that generates actionable insights from both our own and third-party data. Turning insights into actions is a key driver of business performance. 

On acquisitions, nothing is planned right now, but we’re open to opportunities that align with our roadmap or speed up execution. We have a strong balance sheet and a clear appetite to acquire the right kind of assets, though we’ll remain selective.