By Jasjit Kang
The business process services (BPS) industry was once celebrated for cost efficiency through standardised processes, large-scale transitions and SLA-driven outcomes. Today, we stand on the verge of a deeper shift from doing things right to knowing what’s right to do next. Early automation focused on bots handling repetitive tasks to reduce manual effort and improve turnaround. Robotic process automation (RPA) served well but was task-driven, not thinking-driven. Now, augmented intelligence enables AI to learn, reason and recommend.
Once behind the scenes, BPS has moved to the frontline of decision-making. Financial planning and analysis (FP&A) teams don’t just report variance; they explain causes and simulate future outcomes. Healthcare operations help predict fraud or patient behaviours before they happen. BPS has shifted from execution to interpretation, transforming its role.
Generic AI has limits; leaders differentiate via domain-specific intelligence. AI must understand pharma regulatory cycles or procurement contracts. In pharma, AI detects adverse event patterns and accelerates pharmacovigilance. In financial services, AI flags compliance breaches before escalation. Domain-trained AI asks smarter questions, generating sharper insights. We have progressed from SLAs to outcome-based models, now advancing to foresight.
AI predicts likely scenarios, prescribes actions, and personalises responses. Imagine a BPS partner warning three months ahead of a margin shortfall and offering three proactive levers to adjust course. This foresight is already expected.
As AI reshapes BPS, talent will define the pace and scale of transformation. Success hinges on a workforce that blends deep domain expertise with digital fluency. Organisations must invest in cross-skilling and develop professionals who can interpret, adapt and lead in AI-driven environments. Training must evolve to prepare teams for a future where humans and machines co-create value. True differentiation will come from talent that thrives in ambiguity, asks the right questions, and leads with empathy.
Future BPS won’t depend on org charts or manuals but on intelligent, interconnected workflows. AI squads combining domain, design, and data expertise, with continuous learning feedback loops, will replace rigid structures with adaptive operating systems. Success hinges not only on technology but on managing change and preparing clients.
BPS players evolving from execution partners to intelligence partners will lead; others will fade behind AI-native competitors. Leadership is defined by embedding intelligence, insight and innovation deeply into every client touchpoint. Winning means investing holistically in people, perspective, and purpose not just platforms. We must stop asking, “How can we automate this process?” and start asking, “What intelligence does this process hold, and how can we unlock it at scale?” The future of BPS is purpose-led, not process-led. It’s about knowing more and doing what truly matters.