Beyond bolt-on AI: Indian enterprises move to agentic operations in 2026
Enterprises and financial institutions in India are shifting from add-on AI experiments to building operations that run on data, automation, and guardrailed autonomy. This shift centers on two moves: unifying fragmented content into intelligence and deploying agentic AI that can take action inside workflows.
Sunil Pandita, senior vice president at Newgen Software, put it simply: "As we move into 2026, enterprises and financial institutions are experiencing a fundamental transformation, not just adding AI, but reimagining how they operate."
From scattered documents to decision-ready insight
Content platforms are being used to consolidate documents, records, and interactions across the enterprise. The goal is fast, clean handoffs-where underwriting, service, risk, and finance work off the same source of truth.
This shift cuts rework, shortens approval cycles, and makes compliance easier to evidence. For operations teams, it means fewer manual checks and fewer swivel-chair moments between systems.
Agentic AI: autonomy with guardrails
Agentic AI is moving from pilots to production. Within clear boundaries, it classifies content, verifies data, updates records, triggers next steps, and escalates edge cases. Think customer onboarding, claims processing, loan servicing, reconciliations, and exception handling.
The payoff is instant service at scale without losing control. Human oversight stays in the loop for judgment calls and policy changes; machines handle the repeatable work.
Why this matters for operations leaders
India's BFSI sector serves massive customer bases while balancing turnaround time, cost, and access. Newgen notes that agentic operations are already delivering real-time intelligence across millions of transactions and service interactions.
There's a larger economic signal too. Projections suggest AI could add $1.7 trillion to India's economy by 2035. The advantage will go to firms that treat AI as an operating layer-data in, decision out-rather than a side feature.
What good looks like in 2026
- Unified content backbone: One platform for documents, records, and interaction data with strong access controls and audit trails.
- Guardrails by design: Clear policies for where agents can act, when to escalate, and how to log every step.
- Human-in-the-loop checkpoints: Tiered approvals for high-risk actions, with sampling and QA built into the flow.
- Real-time observability: Metrics for SLA, exceptions, model drift, cost per action, and customer effort score.
- Compliance-ready evidence: Versioned policies, explainability for decisions, and end-to-end traceability.
30-60-90 day action plan
- Days 1-30: Map top 3 workflows by volume and delay. Inventory documents, systems, and handoffs. Define success metrics (TAT, accuracy, cost per case).
- Days 31-60: Stand up a content platform pilot for one workflow. Add an agent to automate a contained step (classification, KYC checks, data extraction). Set guardrails and logging.
- Days 61-90: Expand to two adjacent steps. Wire into production data. Add monitoring for drift, exceptions, and SLA. Train ops leads on playbooks and escalation rules.
Leadership signals from Newgen
Pandita said organisations are rebuilding for a "frictionless, inclusive and AI-first" approach-connecting data, applying intelligence, and executing decisions quickly. He also noted Newgen's 2026 focus on global expansion, AI-driven learning across career paths, and workplace initiatives that support growth and inclusion.
Key takeaway for operations
This is bigger than automation. It's about orchestration-clean data, smart agents, and accountable controls working together so teams can move faster with confidence. Start small, measure hard, and scale what proves value.
Want to upskill your team on AI-in-operations? Explore practical programs for operations and BFSI roles at Complete AI Training.
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