In this exclusive conversation with Express Computer, Amir Durrani, Global Head, Applications and Business Process Services at NTT DATA Inc., outlines how the company is accelerating an AI-first transformation to empower enterprises globally. With a strong focus on innovation, next-gen talent, and responsible adoption of AI, Durrani shares how NTT DATA is uniquely positioned to enable organisations to thrive in a digital-first era.
The conversation runs on from the way Agentic AI and generative AI are being infused into enterprise ecosystems to the company’s investments in India as a central engineering hub and organizational vision for reconciling innovation with governance.
You have set an ambitious target of generating $2 billion in revenue from agentic AI by 2027. What is the core vision driving this transformation, and how does the Smart AI Agent Ecosystem redefine enterprise automation compared with conventional AI or RPA approaches?
Our vision of agentic AI is to radically transform how businesses utilise automation. We recognise AI as a transformative shift, arguably even more profound than the internet revolution. The Smart AI Agent Ecosystem is designed to go far beyond the limitations of conventional AI or RPA, which are often confined to task-specific automation or linear processes. By contrast, agentic AI enables autonomous, context-aware decision-making. Our ecosystem integrates consulting, transformation, operations, global connectivity, and data centres to provide a full-stack pathway for clients’ AI journeys. It is not just about automating repetitive tasks but also building intelligent agents that can learn, adapt, and work alongside people to achieve tangible business results at scale. This revolution is an evolution in enterprise automation, from static bots to dynamic, intelligent digital workers who can work across multiple systems and domains in tandem.
Your patented plug-in technology enhances legacy RPA bots into autonomous, smart agents without requiring full system redesigns. Can you give an example of a recent implementation where this has pushed transformation forward and provided quantifiable returns on investment?
One of the strongest features of our proprietary plug-in technology is that it can extend the value and shelf life of current RPA investments without having enterprises go through the expensive or intrusive process of overhaul. A recent implementation with a global insurance company illustrated this effect quite clearly. By integrating our plug-in, we re-engineered their legacy bots into autonomous agents that could handle end-to-end claims handling with minimal touch. Strengthens end customer satisfaction by almost 40% and lessens claims cycle times by almost the same percentage. The plug-in seamlessly converts static scripts into intelligent, self-learning entities that deal with varied systems. Customers value the quick ROI here, quantifiable returns were realised within a few months, while at the same time laying groundwork for the organisation’s future AI-powered scalability.
The EPAS model – Evangelise, Pilot, Adopt, Scale – offers a structured pathway for AI adoption. How is this partnership with Salesforce enabling faster deployment and industry-specific impact for your clients?
Our EPAS framework is a proven methodology that helps clients build confidence with AI adoption by breaking it down into digestible phases. By evangelising the possibilities, piloting targeted use cases, scaling successful pilots, and then adopting AI across the enterprise, organisations are able to transform at a sustainable pace. Partnering with Salesforce has been critical in this journey. Through Salesforce’s AgentExchange – one of the largest AI agent ecosystems for enterprises – clients gain access to hundreds of pre-built templates, validated MCP servers, and industry-specific solutions. This enables faster deployment, reduced security concerns, and immediate impact. Together, we are co-developing sector-specific applications, in BFSI, healthcare, retail, manufacturing ensuring the benefits of agentic AI translate into measurable outcomes for each industry.
India is already among your top ten revenue-generating markets, with a target to break into the top five within three years. How are India’s talent pool, innovation capacity, and partner ecosystem contributing to NTT DATA’s global AI leadership?
India plays a central role in our global strategy, not only as a high-growth market but also as the largest hub for our delivery, talent, and innovation. Since 2011, we have invested more than $3 billion in India and are committing $1.5 billion annually over the next three years. These investments encompass expanding infrastructure, building state-of-the-art data centres, and enhancing our employee base. With over 40,000 skilled professionals powering delivery centres in AI-led transformation, cybersecurity, application management, and BPS, India is not just supporting but driving global AI leadership for NTT DATA. Additionally, India is the nucleus of our co-innovation efforts with global tech giants such as Salesforce, Google Cloud, and Microsoft, as well as with emerging startups. By embedding their AI-driven innovations into our Business Outcomes Solutions and Services (BOSS) framework, we ensure that every service line is AI-enabled, placing India firmly at the heart of our worldwide AI journey.
What differentiates Indian operations when it comes to delivering AI value at scale?
Our Indian operations stand out due to the comprehensive transformation journey undertaken under the leadership of Abhijit Dubey, President and CEO of NTT Data. Inc., outside of Japan. Unlike many markets where AI adoption is piecemeal, India has enabled us to operationalise agentic AI across all service lines. From horizontal functions such as Contact centres, Application Management Services, and Technical Debt remediation to vertical industries like insurance, banking, healthcare, and manufacturing, every service line is now Advance AI-enabled. This ability to marry cutting-edge technology with deep domain knowledge allows us to consistently deliver superior business outcomes at scale. The sheer scale of Indian operations, combined with our culture of innovation, positions us uniquely to showcase what AI-enabled enterprise reinvention can achieve globally.
From healthcare and BFSI to automotive and logistics, which sectors do you anticipate will see the fastest returns on investment from agentic AI adoption over the next two years, and why?
Digital labour is already proving to be a competitive differentiator across industries. In healthcare and life sciences, AI agents are transforming patient management and driving better outcomes. In BFSI, our Agentforce solutions are enabling Life Insurance-as-a-Service and Contact Centre-as-a-Service, cutting operational costs and improving efficiency. Application Management Services are being agentified to seamlessly integrate with observability and service management ecosystems, delivering immediate value. Beyond these, real estate, vendor management, marketing automation, recruitment, and governance are sectors where AI adoption is showing rapid ROI. Each example demonstrates not just efficiency gains but also strategic advantages in speed, accuracy, and scalability
Are there any unexpected industries starting to adopt AI faster than you projected?
Yes, we are observing quicker-than-expected adoption in utilities and manufacturing. Traditionally viewed as slower to adopt emerging technologies, these sectors are now embracing AI due to the tangible productivity gains and operational resilience it offers. Utilities, for example, are leveraging AI to better predict demand and manage infrastructure, while manufacturing is adopting AI for predictive maintenance, quality control, and supply chain optimisation. These use cases highlight how agentic AI is extending its influence beyond the traditionally expected sectors.
With $1.5 billion in planned annual investments in India, which areas—AI research and development, delivery excellence, client co-innovation, or partner enablement—will be the key beneficiaries?
The annual $1.5 billion investment will fuel several strategic areas: expanding our hyperscale data centres, advancing AI research and development, scaling talent, and driving co-innovation with clients. We are also committed to building regional innovation hubs, such as our Bengaluru centre, which will serve as the nucleus of next-gen experimentation and client collaboration. Each of these investments is aimed at strengthening our ability to deliver AI-enabled business outcomes consistently and at scale.
As agentic AI takes on more complex workflows and decision-making, what is your perspective on workforce reskilling, and how is NTT DATA helping enterprises prepare for this shift?
We see workforce reskilling as a central pillar of AI adoption. Rather than replacing roles, agentic AI is augmenting human capabilities, enabling employees to focus on higher-value, strategic tasks. At NTT DATA, we are heavily investing in internal training programmes, reskilling platforms, and hands-on exposure to AI for our employees. Our mission is to accelerate client success and positively impact society through responsible innovation. We provide employees with access to training tools and co-innovation opportunities, ensuring they not only adapt but thrive in this new environment. We extend the same opportunities to our clients, supporting them with consulting expertise and domain knowledge to embed AI into their operations responsibly. It’s about equipping the workforce for transformation rather than dimension less disruption.
What are your priorities for the rest of 2025?
Our top priorities revolve around strengthening valuable partnerships and creating ecosystems where clients and partners thrive together. We are accelerating transformation by leveraging alliances with Microsoft, AWS, Google Cloud, Cisco, Salesforce, and SAP, co-developing platforms in AI, cloud, cybersecurity, and enterprise tech. A major focus is also on our dedicated Google Cloud Business Unit for GenAI. In essence, 2025 is about building ecosystems of collaboration, scaling AI adoption responsibly, and driving outcomes that matter to businesses and society.