Enterprise AI: Golden Age or existential crisis for India SaaS?

Klarna’s decision to dump Salesforce, or Marc Benioff blasting Microsoft co-pilot as being inferior to Salesforce agents (surprise!) are just a couple of headlines in the jostling to influence the direction of enterprise AI adoption.? While it may take another 18 months to firm up, trend lines are pretty clear.?

With AI, the lines between software and services are blurring.? This evolution is going to force SaaS and services companies to rethink their business models, moving beyond the traditional separation of standardized products and customized consulting services toward a unified, AI-driven approach that offers greater value to customers. ?For India SaaS start-ups this shift represents huge opportunity as well as extinction risks.

Past technology shifts have reshaped market leadership?

Every decade or so new technology stacks have offered massive opportunities for enterprises to drive higher growth and efficiency. From main frames to AS/400 to client-server to SaaS.? These shifts have been pretty monumental in value creation as well as destruction.? A handful of incumbent vendors evolve while many disappear into the pages of history. During each shift a new set of market leaders prospered but in turn could never escape their own tryst with an inevitable new technology inflection point.

I started my career as an equity analyst covering software companies in the mid-nineties. ? It was the time of client-server architectures and a new rapidly growing breed of enterprise software companies – such as SAP, Oracle, Peoplesoft at the app layer and many more in middleware and data management layers such as BMC software, Citrix, Informatica, etc.? These companies focused on building products —enterprise software that could address a wide array of business functions. These solutions were robust but required significant customization and support. Accenture and similar consulting firms seized this opportunity, providing the services needed to tailor, implement, and maintain these systems. The distinction between software products and service providers was clear and formed the foundation of enterprise IT.

The emergence of SaaS began to somewhat shift this dynamic. Solutions like Salesforce provided software that was hosted in the cloud, requiring less infrastructure investment and fewer technical resources on the part of the customer. These solutions reduced complexity by integrating some elements of the service, such as automatic updates and cloud hosting, into the core offering. Yet, even SaaS companies like Salesforce still needed consulting firms and in-house experts to handle customization and integration into broader enterprise ecosystems.

?The SaaS era did not fundamentally disrupt the traditional swim lanes.?? Enterprise SaaS companies focused on building “one to many” offerings that were architected for standardization and easy.? For SaaS companies customization is viewed as suicidal and a major barrier to rapid growth.? From a enterprise stand point while SaaS is indeed easier to implement it did not completely solve for ensuring a set of solutions that addresses the need for company specific complex business flows.? This again worked well for the PWC, Accenture, and later India IT majors like Infosys, TCS among others.? Each generation of enterprise software created legacy that needed consultants and services to operate seamlessly.?For services companies customization was the core value proposition that allowed them to engage clients on multiyear projects well after the software vendor made the original sale.

AI in the enterprise will force convergence at a rapid pace

?AI is fundamentally changing this model of separation between products and services. AI has the potential to enhance both the software itself and the process by which it is customized, deployed, and maintained, creating opportunities for convergence in several key ways.

?1. Automated customization and deployment: AI can make enterprise software more adaptable to individual customer needs. Through machine learning, software can analyze customer data, business processes, and operational environments to automatically adapt its features and workflows. This AI-driven customization reduces the need for intensive, manual configuration by consulting firms, allowing businesses to deploy software faster with solutions that are already tailored to their needs.

?2. Integrated AI agents for process automation: AI can provide proactive and predictive support that blurs the line between product and service. AI-driven software is moving towards offering built-in assistants that help automate business processes. These AI agents can perform tasks traditionally managed by consultants, such as configuring workflows, analyzing data for insights, and offering recommendations based on user behavior. Instead of having a consultant analyze reports and suggest process optimizations, the software itself becomes the consultant, learning from historical data and industry best practices to suggest improvements.

?3. End-to-End solutions: The rise of AI is also leading to the development of platforms that offer end-to-end solutions by integrating AI capabilities with both products and services. For example, ServiceNow and Salesforce are increasingly leveraging AI to not only automate workflows but also provide built-in intelligence that guides customers through the deployment and optimization processes. This end-to-end approach allows these platforms to offer a complete solution that spans software, deployment, support, and optimization.

?Business models will change to reflect customer expectations

?The current landscape, where SaaS companies focus on providing standardized software while service companies handle customization and consulting, may not be tenable for long.? As customers demand more integrated, personalized experiences that require both technology and deep business expertise, SaaS and services companies must rethink their business models in several ways:

?1. Unified product and service offerings: SaaS companies will need to expand their scope to include more built-in services. This means developing products that come with embedded AI-driven consulting capabilities, providing tailored experiences that traditionally required separate service engagements. The aim is to create seamless offerings where the customer doesn’t need to look for third-party consultants for deployment and optimization.

?2. AI-enhanced consulting models: Service providers like Accenture will rethink their role in the AI era. Instead of merely focusing on deploying and customizing software, they must leverage AI to provide higher-value, strategic advisory services. AI tools can automate much of the repetitive, labor-intensive work involved in system customization, allowing consultants to focus more on helping customers extract strategic value from their data and technology investments.

?3. Outcome-based models: Both SaaS and service providers are likely to move towards outcome-based pricing models, where they are compensated based on the results they deliver rather than merely the software or hours worked. AI makes it easier to track and optimize for outcomes, enabling providers to deliver measurable value—whether that means higher productivity, better customer satisfaction, or increased revenue.

?India has a unique advantages with the new hybrid model

?As AI becomes more deeply embedded in enterprise solutions, the distinction between products and services will increasingly disappear, replaced by platforms capable of delivering outcomes as a seamless, integrated experience.? In this new landscape, traditional SaaS and service firms must either evolve towards hybrid models or risk being left behind by more agile competitors.

Market shifts like this represent significant opportunities and risks.? It is especially challenging for young SaaS companies to feel their way around a shifting landscape.? However a hybrid model leverages two of India’s strengths – SaaS product builders and a very strong core of experienced services companies.? There are budding hybrid companies looking to rethink large verticals entirely with a new set of outcome based offerings.? While the near term may be rocky, it is clear that change is coming.? While some incumbents will survive and thrive, history suggests that big market shifts create a new wave of companies building on a fresh canvas.?? This is the mega opportunity for India’s best software and services minds.?