Empowering Enterprises with AI: NTT DATA’s Success Using Microsoft Copilot & Power Platform

AI is fundamentally reshaping modern enterprise operations, promising leaps in productivity, efficiency, and innovation. Yet, the journey from experimentation to large-scale real-world deployment comes with intricacies that many organizations underestimate. For global technology services giant NTT DATA, the challenge was clear: how to harness advanced AI to automate and transform both internal workflows and client-facing services—without compromising security, speed, or compatibility with existing infrastructure.

How NTT DATA Approached Enterprise AI Adoption​

NTT DATA is no stranger to digital transformation. With notable expertise in cloud infrastructure, managed services, and digital modernization, its teams recognized that integrating AI at scale requires more than just algorithmic prowess. It demands a platform agile enough to slot into complex technology stacks, robust enough to satisfy strict security constraints, and intuitive enough for rapid adoption by employees and customers alike.
“We needed an agentic AI solution that was fast to deploy, seamlessly integrated with our existing tech stack, and highly secure,” explains Aishwarya Singh, SVP Global Head of Digital Collaboration Services at NTT DATA. Notably, the company’s service portfolio is vast and diverse, spanning sectors from healthcare to financial services. This breadth meant their AI platform not only had to optimize efficiency and automation for end clients but also be adaptable and customizable at every layer of delivery.
After evaluating available options, NTT DATA placed its confidence in the Microsoft AI ecosystem, specifically leveraging Microsoft Copilot Studio and Power Platform as the foundation for its agentic AI services. The rationale: these tools offer an extensive set of features for AI-powered automation, collaboration, and secure integration—all core to meeting diverse client requirements at scale.

Leveraging Microsoft Copilot Studio and Power Platform​

Microsoft Copilot Studio stands out as a generative AI solution crafted for enterprise scenarios. It empowers organizations to create automated agents capable of handling everything from customer inquiries to internal support tickets. Paired with the Microsoft Power Platform—a suite that includes Power Apps, Power Automate, and Power BI—NTT DATA’s teams have access to an end-to-end toolkit for designing, deploying, monitoring, and refining AI workflows.

Why Microsoft? Integration, Security, and Comprehensiveness​

A key catalyst for this selection was NTT DATA’s deep, long-standing partnership with Microsoft, as one of the world’s largest Operator Connect and Teams Phone partners. Their workforce—from engineering to sales—already operated within the Microsoft ecosystem, offering a stable foundation for further innovation without the steep learning curves or integration headaches that can accompany third-party or bespoke platforms.
The Microsoft AI stack’s seamless integration capability proved valuable not only for accelerating deployment but also for unifying data, security policies, and user management across disparate business units. Security and compliance, heightened concerns for global service providers, are deeply embedded within Azure and Microsoft 365, allowing NTT DATA to meet both strict client regulatory requirements and internal governance demands.
Moreover, the extensiveness of Microsoft’s toolset enables NTT DATA to implement automation and AI use cases that would otherwise require assembling—and maintaining—a patchwork of vendors and solutions. This unification serves as a significant operational win, reducing complexity while maximizing value from existing investments in identity, collaboration, and analytics infrastructure.

Concrete Results: Efficiency, Speed, and Performance Gains​

NTT DATA’s focus on “agentic AI”—where autonomous agents perform complex sequences of tasks without constant human oversight—distinguishes its approach from basic chatbot implementations or narrow machine learning projects.
Early results, according to Singh, include:

• Accelerated Deployment: The ability to go from concept to production in a fraction of the time compared to previous manual or hybrid processes.
• Process Automation: Back-office tasks, document processing, and customer service workflows now run with reduced human intervention, freeing staff to concentrate on higher-value activities.
• Enhanced Collaboration: Teams report instant access to insights, data visualizations, and intelligent assistance within familiar environments like Microsoft Teams and Outlook.
• Security and Compliance: Built-in controls and continuous monitoring via Azure protect sensitive client information, while simplifying audits and regulatory reporting.

Though some outcome metrics are still emerging, pilot deployments reportedly led to double-digit efficiency gains in service desk operations and significant reductions in manual workload for IT and HR support teams. Such figures broadly align with wider industry findings: Forrester and Gartner cite process automation with generative AI yielding between 15% and 40% efficiency improvements in administrative-heavy functions.

Critical Analysis: Strengths and Differentiators​

Deep Ecosystem Integration​

One notable strength in NTT DATA’s AI adoption strategy is its insistence on deep platform integration over isolated, bolt-on solutions. By staying within the Microsoft ecosystem, the company leverages not just the technical capabilities of Copilot Studio but also the collaborative superpowers of Teams, the analytics of Power BI, and the security backbone of Azure Active Directory.
This holistic integration manifests as smoother user experiences, faster incident resolution, and more agile responses to business changes. Custom connectors, shared security policies, and native compatibility with existing business applications mean upgrades and new features propagate quickly and predictably.

Accelerated Time to Value​

Organizations often cite slow ramp-up or cumbersome change management as major barriers to AI-driven transformation. By utilizing tools frequently already in use by employees (such as Teams), NTT DATA sidesteps much of the friction associated with new software rollouts. Power Platform’s low-code nature further empowers non-developers to build and tailor solutions, decentralizing innovation and making it accessible to more business units.

Enterprise-Grade Security and Compliance​

For any service provider—especially one operating in heavily regulated sectors—the risk of data breaches or compliance lapses can be existential. Microsoft’s robust security guarantees, spanning encryption, threat detection, identity management, and auditability, minimize these risks. Furthermore, NTT DATA’s global delivery model is supported by Microsoft’s extensive compliance certifications, from ISO to GDPR to HIPAA, providing a baseline of regulatory assurance for customers worldwide.

Scalability and Flexibility​

A common pitfall for many AI deployments is rigidity: solutions may work in the pilot stage but falter when requirements change or when expansion is needed across geographies or business lines. Here, both Copilot Studio and Power Platform—cloud-native and designed for global scale—support rapid ramp-up and customization. Integrations can be tailored and automations extended or retired as needed, ensuring the platform remains aligned with business objectives over time.

Potential Risks and Cautions​

Despite the strengths, several areas merit close scrutiny as organizations consider similar approaches:

• Platform Dependency: Relying heavily on a single vendor for automation and AI can introduce lock-in risk. While deep integration with Microsoft’s ecosystem brings tangible advantages in speed and manageability, it can also make future migrations or multi-cloud strategies more complex and costly.
• Transparency and Explainability: As generative AI systems become more autonomous, the “black box” nature of certain algorithms raises valid concerns about explainability—especially critical in industries where decision rationale must be auditable.
• Change Management and Workforce Impact: Even with best-in-class tools, true transformation depends on user acceptance and a willingness to adapt to new workflows. Organizations must invest in training, change management, and open communication to avoid resistance or underutilization.
• Data Privacy and Cross-Border Compliance: Multinational operations introduce unique challenges around data sovereignty, cross-border data transfers, and local regulations that may not always be fully addressed by cloud providers—even those with extensive compliance certifications.
• Measuring ROI: While initial efficiency gains appear promising, long-term value realization requires continuous measurement and fine-tuning. Over-optimistic projections or incomplete baselining can lead to missed expectations.

Real-World Use Cases: Automation in Action​

The impact of NTT DATA’s agentic AI services can be felt across a range of operational domains:

Service Desk Automation​

Multi-level support requests—from password resets to more complex troubleshooting—are now triaged by AI agents, which analyze historical tickets, recommend resolutions, and escalate only the most complex issues to human technicians. This not only improves first-call resolution rates but also slashes average handling times and reduces burnout among support staff.

Intelligent Document Processing​

Automated workflows routinely extract, classify, and route information from invoices, contracts, and forms. The platform’s integration with Power Automate allows for the orchestration of these tasks across disparate data sources, minimizing manual entry and reducing the potential for human error.

HR and Employee Services​

Employee onboarding—a traditionally paperwork-heavy, fragmented process—benefits from AI-powered bots that answer common HR questions, schedule orientation sessions, and prompt new hires for required documentation, creating a smoother experience while ensuring compliance with internal policies.

Customer Experience Digitization​

Externally, client-facing virtual agents utilize Microsoft Copilot’s natural language processing capabilities to guide customers through product selection, account management, and post-sale support in real time, 24/7, across multiple channels.

How NTT DATA’s Example Informs Broader Enterprise AI Strategy​

NTT DATA’s success story underscores the importance of three fundamental principles for any enterprise seeking to scale AI and automation:

• Platform Alignment: Maximize value from established vendor relationships and existing technology investments by choosing platforms already embedded in business processes.
• Holistic Integration: Prioritize end-to-end workflows that cross departmental and data silos, rather than isolated optimizations in single business units.
• Continuous Optimization: Treat AI deployment as an iterative journey—one that evolves with business needs, user feedback, and technological advances, rather than a fixed, one-off project.

For organizations navigating similar choices, the lesson is clear: technology alone is not a panacea. Success depends on aligning tools with strategy, preparing for ongoing transformation, and investing in the cultural shifts necessary to fully realize AI’s promise.

Outlook: Next Steps for AI-Driven Business Transformation​

Looking forward, the trend is clear: agentic AI, with the autonomy to orchestrate multi-step processes and continuously adapt to evolving business requirements, is poised to redefine not only back-office efficiency but the entire value proposition of service delivery. As AI systems mature, enterprises should anticipate:

• Greater Personalization: Tailored automation that responds to individual user needs and historical patterns, rather than relying on one-size-fits-all processes.
• Augmented Human Intelligence: Rather than replacing human workers, generative and agentic AI will increasingly support complex decision-making, surfacing insights and recommendations within existing workflows.
• Stronger Governance: As reliance on AI grows, mechanisms for governance, bias mitigation, and responsible deployment will become ever more critical—demanding transparency from both platform vendors and adopters.
• Expansion Beyond IT: While early wins frequently come in IT and operations, functionality is expected to rapidly extend across finance, marketing, sales, and client-facing departments.

NTT DATA’s journey with Microsoft Copilot Studio and Power Platform offers an instructive case study: with careful selection of tools, a willingness to modernize, and a dedicated focus on security, enterprises can unlock transformative value from AI while managing risk. But as with any powerful new capability, success relies not just on adopting technology, but on reimagining how people, processes, and platforms work together to shape the future of business.

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Source: Microsoft Q&A: NTT DATA trusts Microsoft AI to enhance automation and transform operations | Microsoft Customer Stories