As client expectations evolve, IT firms are moving beyond traditional business process outsourcing (BPO) to embrace platformisation – provision of wider services under a common platform. Enterprises today are no longer satisfied with siloed services. They seek integrated, intelligent solutions that deliver automation, agility, and measurable business impact.
This shift is not just strategic but necessary. The $3.3 billion acquisition of WNS by Capgemini in July 2025 reflects a growing market demand for end-to-end digital transformation capabilities that extend far beyond implementation. Similarly, Infosys launched Cobalt as a cloud-first, AI-enabled suite for companies and clients to accelerate digital transformation.
Technological and Financial Necessity
Varun Goswami, global head of product and AI at Newgen Software, emphasised that being product-native has become central to how modern platforms create value. He said, “Product-native approach creates two key advantages: firstly, from a go-to-market lens, it enables the delivery of ready-to-deploy, industry-specific solutions that address real-world challenges, and secondly, from a technology perspective, it ensures performance, scalability, and resilience, without over-reliance on the shifting landscape of native AI stacks.”
To Goswami, being AI-first and product-native is no longer a choice; it is what organisations need to drive meaningful, future-ready transformation.
M&As Reshape the IT-SaaS-BPO Landscape
The convergence of BPO, SaaS and large IT services firms is picking up pace as enterprises shift how they consume technology and transformation services.
According to Goutham Parcha, vice president, application development, Pegasystems India, this shift is driving a new era of strategic mergers, where SaaS and BPO companies are increasingly becoming integral components of global IT services offerings. He noted that this trend is only set to intensify. “In the coming years, we can expect this trend to deepen further. Strategic acquisitions, ecosystem alliances, and even co-innovation models will become more common, as firms look to accelerate time-to-value for clients and defend margins.”
A key factor accelerating this evolution is the emergence of intelligent agents, which have the potential to upend traditional BPO models. SaaS companies, Gautham believes, are in a strong position to lead this disruption by offering automation solutions driven by intelligent agents.
Sarat Varanasi, practice leader – insurance analytics, AI services and platforms at EXL, echoed a similar sentiment.“Domain expertise is becoming critical for deploying AI and agentic AI solutions effectively. As a result, domain-rich BPOs are increasingly attractive to IT giants seeking to enhance workflow IP, GenAI capabilities, and operational depth,” he said.
Varanasi added that going forward, SaaS providers are likely to build their own delivery arms, while BPOs will work to embed AI more deeply into their workflows further blurring the traditional boundaries between these sectors.
Backward Integration Isn’t the Future
With regard to this growing trend and its impact, Parcha noted, “Backward integration of SaaS platforms into traditional outsourcing models is unlikely to align with market trends. Instead, value will come from platforms that are intelligent by default and resilient by design, reducing reliance on labour intensive processes.”
He said that SaaS platforms are expanding their capabilities by embedding automation, workflow orchestration, and predictive AI directly into the product, minimising dependence on people-heavy service models while ensuring consistent, high-quality outcomes.
The Big IT Bottleneck
Big IT firms are navigating multiple hurdles as they shift from services-led models to product-native and AI-driven operations.
Varanasi outlines the key roadblocks as “legacy models, talent gaps/upskilling, lack of product IP, ecosystem limitations, data preparedness for AI adoption, and change management.”
Many firms are still tied to outdated contracts that slow progress. As he noted, “We believe we will have people working on AI or with AI. However, leading pure-play IT firms can be constrained by legacy IT contracts that need to be cannibalised to enable AI adoption. This has resulted in a slower pace of innovation.”
In contrast, domain-led digital operations firms are moving faster. “With their domain expertise,” he added, “they’ve enabled faster implementation of AI/GenAI, accelerated product development, and reduced time-to-market.”
Parcha pointed out the strain on old systems: “These systems are difficult to replace, expensive to maintain, and do not easily connect with modern technologies.” This complexity increases cost and delays, while also creating “technical debt, so companies get stuck using most of their resources keeping them running instead of moving forward.”
Beyond infrastructure, internal collaboration is another critical barrier. “Another challenge is that teams often work in silos, making collaboration and integration of new tools difficult. It slows decision-making and the need for rapid product innovation,” said Parcha. Security is also emerging as a serious concern: “Older platforms can be more vulnerable to cyber threats and are harder to keep compliant with fast-changing regulations.”
Strategies for AI- first Startups
The most successful AI-first startups will be those that build deep, domain-specific solutions, rather than relying on generic tools. Varanasi emphasised, “The real opportunity lies in moving beyond generic tools to deliver workflow-embedded, domain-specific solutions.” As horizontal SaaS models become increasingly commoditised, startups will need to differentiate by delivering measurable business impact.
“As horizontal SaaS rapidly commoditises, the future belongs to IP-rich platforms that directly enhance client KPIs and deliver measurable business value,” he noted.
While many emerging startups are focused on areas like data annotation, customer service, or call centre automation, lasting value will come from embedding AI into core operational workflows.
In this context, digital operations providers have a built-in advantage. “Digital operations providers hold a distinct advantage due to their domain expertise and process knowledge, positioning them well to co-create verticalised, AI-native SaaS models,” said Varanasi.
He also pointed out a critical industry dynamic. “AI commoditises faster than service delivery changes. Winners will own use-case outcomes (claims processing, billing, underwriting).” The edge, he suggested, lies in mastering outcomes that align directly with client business goals.
The post How Product-Native IT Models Are Reshaping Enterprise Tech appeared first on Analytics India Magazine.
