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‘We have Evolved from a Market Leader in Robotic Process Automation into a Pioneer in Agentic Process Automation’: Sanjay Rohatgi, SVP & GM – APJ, Automation Anywhere

By: APAC Media

and
  • Anannya Saraswat
by APAC Media
June 4, 2026
in important, Interviews
Reading Time: 6 mins read
‘We have Evolved from a Market Leader in Robotic Process Automation into a Pioneer in Agentic Process Automation’: Sanjay Rohatgi, SVP & GM - APJ, Automation Anywhere

‘We have Evolved from a Market Leader in Robotic Process Automation into a Pioneer in Agentic Process Automation’: Sanjay Rohatgi, SVP & GM - APJ, Automation Anywhere

Summarize with:

As enterprises move beyond traditional automation and embrace the transformative potential of generative and agentic AI, the focus is increasingly shifting toward intelligent, end-to-end workflow automation. In this interview, Sanjay Rohatgi, Senior Vice President and General Manager – APJ at Automation Anywhere, discusses with Anannya Saraswat, Correspondent at APAC Media and CXO Media, how the company is evolving from its roots in robotic process automation (RPA) to pioneering Agentic Process Automation (APA). 

Could you provide an overview of Automation Anywhere’s current portfolio and how it is evolving in the era of generative and agentic AI? What differentiates your platform from other automation and AI players in an increasingly crowded market?

Automation Anywhere has evolved from a market leader in Robotic Process Automation (RPA) into a pioneer and a category creator in Agentic Process Automation (APA).

Today, our platform combines RPA, AI agents, orchestration, document automation, and conversational AI to automate complex enterprise workflows end-to-end.

What differentiates us is our platform-first approach. While many players focus on AI within isolated enterprise systems, we orchestrate workflows seamlessly across the enterprise stack.

By combining AI agents, deterministic automation, and enterprise-grade governance, we enable organizations to operationalize AI securely, at scale, and with measurable business outcomes.

Most recently, we acquired AISERA, the leader in conversational AI for IT Service Management (ITSM) and HR Services Help Desk. This completely transforms the business economics of IT Services Help Desk and HR Services Help Desk by proactively resolving 70-80% of the tickets even before we go to the ITSM or Human Resource Management (HRM) tool. This is a game-changer.

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From a Robotic Process Automation player, how has Automation Anywhere evolved into the era of GenAI and agentic AI?

Our evolution into GenAI and Agentic AI is built on the strong foundation of RPA.

Enterprises continue to depend on deterministic automation for consistency, compliance, and scale. What has changed is the need for systems that can reason, interpret unstructured data, and adapt dynamically.

That is where Agentic Process Automation (APA) comes in. APA combines RPA, AI agents, orchestration, and human oversight into a unified execution model. RPA handles structured processes, while AI agents bring intelligence, context, and adaptability.

Together, they enable enterprises to automate workflows end-to-end with speed, governance, and resilience.

What are the key pillars of Automation Anywhere’s GTM strategy for India?

India is one of our most strategic growth markets globally.

Our GTM strategy is anchored on three priorities:

  • Deep vertical focus across BFSI, manufacturing, public sector, conglomerates, and GCCs
  • Ecosystem-led growth through partners, hyperscalers, and GSIs
  • Accelerating the shift from traditional automation to Agentic Process Automation (APA)

India is rapidly emerging as a global AI innovation hub, and we are seeing strong demand for AI-led workflow transformation across enterprises and government institutions.

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How is your partner network structured, and what dynamics define it?

Our ecosystem spans global system integrators, consulting firms, hyperscalers, and regional partners.

We work closely with leading organisations, including Accenture, Deloitte, EY, PwC, Infosys, TCS, and Wipro, to scale enterprise AI transformation initiatives across industries.

What differentiates our approach is that partners are not simply deploying automations – they are helping customers build long-term, AI-driven workflow transformation capabilities.

As enterprises prioritize ROI, scalability, and faster time-to-value, the partner ecosystem becomes critical to scaling AI adoption.

How are you integrating AI agents into your automation ecosystem to deliver end-to-end enterprise workflows?

We view enterprise AI across three layers: infrastructure, models, and applied AI. Automation Anywhere operates in the applied AI layer.

Our platform is model-agnostic and integrates with leading AI ecosystems, including OpenAI, Microsoft, Google, Anthropic, and AWS, to name a few.

Enterprise workflows typically span multiple systems—from SAP and ServiceNow to Salesforce and Microsoft environments.

Our platform orchestrates these workflows through a unified execution layer that combines AI agents, RPA, and governance, enabling secure, scalable, end-to-end enterprise automation. 

What are the most common use cases or industries where your solutions are seeing the strongest traction today?

We are seeing strong momentum across BFSI, manufacturing, telecom, the public sector, and shared services. Key use cases include:

  • KYC and Anti-Money Laundering (AML) workflows
  • Loan processing and customer onboarding
  • Intelligent document automation
  • Invoice processing and finance operations
  • Procure-to-pay and order-to-cash workflows

Public sector adoption is also accelerating as governments and utilities modernize citizen services and operational efficiency through AI-led automation.

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Across industries, enterprises are focused on improving speed, compliance, and operational efficiency.

What are the biggest risks enterprises face when deploying AI agents, and how can they mitigate them?

The first major risk is “agentic sprawl.” As AI agent development becomes easier, enterprises risk deploying disconnected agents without governance, cybersecurity, or scalability.

This is why a platform-led approach matters. Enterprises need centralized orchestration, auditability, compliance, and policy enforcement to scale AI responsibly.

The second major risk is cybersecurity. AI introduces new attack surfaces across infrastructure, models, datasets, and workflows. Guardrails must exist across every layer of the AI stack.

The winning approach combines AI agents, deterministic automation, governance, and human oversight to drive innovation without losing control.

India and the broader APJ region are seeing rapid adoption of agentic AI. What are the key factors driving this momentum?

AI has democratized enterprise innovation globally.

India’s adoption patterns increasingly mirror markets such as Australia, Singapore, Japan, and the US, where enterprises are focused on measurable business outcomes and ROI.

Organisations are adopting Agentic AI to improve efficiency, accelerate workflow automation, reduce operational costs, and drive faster time-to-market.

In India, BFSI, GCCs, and digital-first enterprises are leading adoption, supported by strong government momentum around AI and digital transformation.

What are your key priorities for growth over the next 12–24 months?

Our priority is accelerating the transition from traditional automation to Agentic Process Automation (APA) and solving customer business process challenges.

For existing customers, this means evolving from siloed automation to enterprise-wide AI-led transformation. For new customers, it means enabling AI-first automation from day one.

We are focused on expanding across high-growth sectors, including BFSI, manufacturing, public sector, and GCCs, while strengthening our ecosystem across partners, hyperscalers, and AI providers.

At the core of our strategy is delivering measurable business value through secure, scalable, AI-driven automation.

Summarize with:

Tags: Agentic AIAutomation AnywhereEnterprise AI AdoptionWorkflow Automation
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