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. Dr Ritwik Batabyal, CTO and Innovation Officer, Mastek share his perspectives on the trends, challenges and priorities shaping the next phase of the IT/ITeS and BPM landscape…
What are the three key technology trends shaping the IT/ITeS sector?
At Mastek, we are seeing three key shifts shaping the IT/ITeS sector:
- Agentic AI moving from pilots to production: The conversation has shifted decisively from “should we use AI?” to “how do we govern autonomous AI agents?”. At Mastek, we are deploying multi-agent orchestration frameworks that enable AI systems to plan, delegate and execute tasks with minimal human intervention.
- AI governance as a competitive moat: Organisations investing in responsible AI frameworks, covering explainability and accountability, will command greater enterprise trust. This is becoming a key procurement criterion, particularly in regulated industries. Mastek has embedded AI governance reviews into its delivery lifecycle, treating them as a design requirement rather than a post-deployment step.
- Data mesh and federated intelligence: Centralised data lakes are giving way to domain-owned, federated data products, bringing AI closer to business context. For IT/ITeS firms handling multi-client, multi-geography data, this enables more efficient and context-driven AI deployments without central bottlenecks.
How is AI transforming the way enterprises in the IT/ITeS sector operate? How are technologies such as AI, automation and platform-based systems reshaping operating models and workforce dynamics?
The shift we are witnessing is not AI replacing people, but redefining what organisations choose to solve. At Mastek, this is visible in four ways:
From task automation to outcome ownership: Earlier, automation focused on eliminating steps in a process. AI-driven systems are now being designed to own outcomes. For instance, AI agents can manage end-to-end workflows, such as resolving support issues, by identifying root causes, coordinating internally and closing the loop autonomously.
Rise of the AI workflow architect: The workforce is being restructured around roles that design, supervise and improve AI-driven workflows. At Mastek, there is growing demand for roles such as AI pipeline designers and prompt-ops engineers, making reskilling a delivery imperative.
Platform-based delivery over bespoke builds: Client engagements are increasingly shifting toward platform-centric models with pre-built AI accelerators, reusable data connectors and modular components. This allows teams to focus more on business outcomes rather than infrastructure.
Accountability gaps in automated decision chains: As AI begins to take decisions such as pricing, resource allocation and risk scoring, accountability becomes critical. Organisations need clear human override protocols and governance frameworks to manage associated risks.
How are you strengthening cybersecurity frameworks while adopting new technologies?
Cybersecurity at Mastek is embedded into every technology adoption decision. The expansion of AI has introduced several new challenges:
- Securing the AI layer: Large language model-specific vulnerabilities such as prompt injection and data leakage have created a new attack surface. At Mastek, we have developed review protocols for AI model inputs, outputs and integration points, treating the model pipeline as a security perimeter.
- Regulatory impact and data protection: The Digital Personal Data Protection Act is reshaping how organisations handle data. At Mastek, this has led to systematic audits of data flows across our delivery platforms, particularly where AI models interact with client data, requiring close alignment across legal, data and security functions.
- Third-party AI and supply chain risks: As enterprises rely more on external AI platforms, supply chain risks are increasing. We mandate vendor AI security reviews as part of our procurement and architecture approval, focusing on data handling and auditability.
- Shift to continuous threat intelligence: Periodic audits are no longer sufficient in a rapidly evolving threat landscape. Mastek has moved toward real-time threat intelligence integration and automated security posture management to detect misconfigurations and anomalies continuously.
What execution challenges or structural constraints have you encountered while adopting advanced technologies at scale?
Scaling advanced technology is less a technical issue and more an organisational challenge. Key constraints include:
- AI readiness gap in legacy systems: The bottleneck is often the underlying data infrastructure. Many of our clients operate on legacy systems that cannot support clean, real-time data. This requires upfront investment in data modernisation before AI can scale effectively.
- The AI KPI problem: Enterprises often rely on technical metrics such as model accuracy rather than business outcomes. At Mastek, we emphasise defining business-level success criteria early to ensure that AI initiatives move beyond pilot stages.
- Organisational trust deficits: AI adoption is often constrained by the lack of trust and clarity around AI outputs. We address this by making AI systems interpretable and practically useful at the point of decision.
- Governance without bureaucracy: As AI deployments scale, governance can become a bottleneck if not designed carefully. The focus is on building lightweight, embedded governance frameworks that scale without becoming a bottleneck.
- Talent building for roles that do not have a hiring market yet: Critical roles such as AI solution architects and data product managers lack established talent pipelines. We are addressing this by building capabilities internally through structured trainings and cross-functional rotations.
What major technology shifts do you anticipate in the IT/ITeS domain in the coming years? How will they redefine your organisation’s systems?
The shifts are not incremental upgrades but architectural resets. At Mastek, we are positioning for the following changes:
- Multi-agent AI systems redefining service delivery: Delivery models will increasingly rely on orchestrated networks of AI agents, handling end-to-end service workflows, with human oversight focused on exception handling and strategic decisions. For Mastek, this shifts our role toward designing orchestration logic, guardrails and escalation frameworks.
- Sovereign AI and localisation: Demands are rising for AI systems that operate within enterprises or national boundaries due to regulatory and data sovereignty requirements. This is driving a shift toward private model deployments, with Mastek investing in capabilities to architect and manage these environments.
- AI-native enterprise systems: Legacy ERP systems are giving way to composable, AI-driven platforms that can adapt dynamically based on operational data, reshaping enterprise system design and modernisation approaches.
- Continuous intelligence: Enterprises are moving from periodic reporting to always-on, AI-driven decision making, with real-time insights enabling faster and more responsive operations. Mastek is embedding intelligence layers into its managed services to support this shift.
- Post-quantum cryptography readiness: While large-scale quantum computing is still evolving, enterprises need to start preparing their encryption frameworks for future risks. This is emerging as an important long-term priority for organisations handling sensitive data.
Mastek is focusing on building adaptive systems that enable clients to integrate and scale emerging technologies faster. The emphasis is shifting from implementation to continuous evolution, ensuring organisations respond quickly to new technology shifts.
