Ganesan Karuppanaicker, Chief Technology Officer, Birlasoft.
The IT/IT-enabled services (ITeS) and business process management (BPM) sectors are undergoing a structural change, with several key trends emerging. Artificial intelligence (AI) is moving from pilots to real-world deployment, increasingly becoming embedded into everyday operations. Further, platform-based models are replacing fragmented systems, making it easier to scale services and integrate data, automation and intelligence. There is also a growing emphasis on governance, security and responsible AI, particularly as enterprises deal with more complex data environments and regulatory expectations.
Rather than replacing roles, AI is changing how work is done, pushing organisations towards more outcome-driven models. However, the path to scale is not without challenges, as legacy infrastructure, talent gaps and evolving security risks continue to slow down adoption. Ganesan Karuppanaicker, Chief Technology Officer, Birlasoft, shares his perspectives on the trends, challenges and priorities shaping the next phase of the IT/ITeS and BPM landscape…
What according to you have been the three key technology trends shaping the IT/ITeS sector?
From a technology leadership standpoint, the most significant shift shaping the IT/ITeS sector is the move toward AI‑native, AI-centric platforms, Agentic AI and outcome‑oriented enterprise architectures. Technology is no longer simply enabling business processes – it is increasingly becoming the execution layer itself. AI is now deeply embedded into enterprise workflows, autonomously managing incidents, orchestrating decisions, and driving real‑time outcomes across IT operations, supply chains, and customer value chains.
In parallel, enterprises are replacing fragmented, project‑based delivery models with integrated platforms spanning cloud, data, ERP, and AI, creating end‑to‑end visibility and faster decision cycles at scale. This AI-centric platform-led approach is also reshaping commercial models, with organisations shifting decisively toward outcome‑based, AI‑augmented services where success is defined by measurable business impact rather than effort. Together, these trends mark a clear transition away from labour‑arbitrage toward technology‑led differentiation, fundamentally redefining how value is created, delivered, and scaled across the IT services ecosystem.
How is AI transforming the way enterprises IT/ITeS sector operate? How are technologies such as AI, automation and platform-based systems reshaping operating models and workforce dynamics?
AI is reshaping enterprise operations in the IT/ITeS sector by evolving from a productivity accelerator into an active execution layer within the enterprise. Today, AI is embedded across IT operations, supply chains, and customer experience functions, enabling systems to autonomously sense, decide, and act. This is driving a shift from linear, human‑driven processes to AI‑orchestrated, continuously adaptive operating models that improve speed, resilience, and decision quality.
At the same time, enterprises are adopting platform‑centric architectures, tightly integrating cloud, data, automation, and AI layers to reduce process latency and enable end‑to‑end visibility across business functions. Operating models are increasingly designed around integrated platforms rather than fragmented services.
These changes are also reshaping workforce dynamics. The focus is moving from role‑based execution to human‑AI collaboration, where employees supervise, contextualise, and govern intelligent systems. At Birlasoft, Agentic AI orchestration platform such as Birlasoft Cogito formalise this model by defining clear agent responsibilities alongside human‑in‑the‑loop governance, reflecting a broader industry shift to AI as a co‑runner of the enterprise, not just a support tool.
How are you strengthening cybersecurity frameworks while adopting new-age technologies?
As AI moves deeper into enterprise execution layers, cybersecurity must evolve from static, perimeter‑based controls to continuous, embedded governance. The rise of agent‑based architectures and AgentOps frameworks underscores this shift. Security is no longer an afterthought, but an integral part of how AI systems operate in production.
At Birlasoft, we strengthen cybersecurity by embedding governance, security, and observability directly into AI‑led transformations. Every AI‑driven action is designed to be explainable, traceable, and policy‑aware, with controls enforced across cloud, data, and application layers. We align AI operations with enterprise intent and regulatory requirements through built‑in auditability, identity‑aware execution, and human‑in‑the‑loop checkpoints where risk is high.
This approach ensures that as enterprises scale next‑generation technologies, they do so with assured security, trust, and resilience.
What execution challenges or structural constraints have you encountered while adopting advanced technologies at scale?
One of the biggest challenges in scaling advanced technologies is not access to AI tools, but integrating them into complex enterprise environments. Fragmented legacy platforms make it hard to embed AI and automation seamlessly across end‑to‑end workflows, often resulting in pilots that show promise but fail to scale into enterprise‑wide impact.
Governance is another critical constraint. As AI moves from advisory roles to autonomous execution, the risk shifts from flawed insights to unintended actions, making accountability, traceability, and control essential. At the same time, enterprises must rethink operating models, moving away from rigid role‑based structures to cross‑functional, AI‑enabled teams with new skills and ways of working.
At Birlasoft, we address these challenges through AI‑first process reimagination framework, clearly defining human‑AI responsibilities and supporting them with validated agentic platforms and enterprise‑grade governance, recognising that scalable AI adoption is fundamentally a transformation of processes, platforms, and people, not just technology.
What major technology shifts do you anticipate in the IT/ITeS domain in the coming years? How will they help redefine your organisation’s systems?
The next phase of evolution in the IT and ITeS sector will be defined by the move toward AI‑native and increasingly autonomous enterprises, where intelligence is embedded across every operational layer. One of the most significant shifts is the rise of agentic AI – systems that go beyond copilots to autonomously orchestrate workflows, make decisions, and execute tasks across IT, business, and customer operations.
At the same time, the convergence of cloud, data, API infrastructure, and platform ecosystems will enable tightly integrated, real‑time enterprise environments, dramatically improving decision velocity and operational resilience. This will accelerate the shift from project‑centric delivery to platform‑led, outcome‑driven models.
For organisations like ours, these shifts are redefining systems into orchestrated, intelligent operating layers – designed for continuous adaptation, governed execution, and measurable business impact at scale.
