ServiceNow and NTT DATA have announced an expansion of their strategic partnership with an ambitious goal: accelerating enterprise transformation driven by artificial intelligence and making intelligent automation a cross-cutting capability for companies of all sizes and sectors. The agreement solidifies NTT DATA as a strategic delivery partner for ServiceNow’s AI solutions, while both companies co-create and commercialize AI-based applications and agents aimed at measurable business outcomes.
The partnership stems from a longstanding relationship — NTT DATA is a global integrator and partner of ServiceNow — and is based on an explicit approach of responsible and scalable AI implementation. On the ground, the move has two complementary directions: on one hand, NTT DATA will increasingly adopt the ServiceNow AI platform to boost productivity, efficiency, and customer experience in its global operations; on the other, ServiceNow will formally recognize NTT DATA as a strategic partner to deliver large-scale AI automation across multiple industries and regions.
“ServiceNow and NTT DATA are expanding access to AI-based automation across any industry and region, with the goal of creating tangible business impact at every stage,” says Amit Zavery, President, COO, and Product Officer at ServiceNow. “Together, we are transforming how the world’s leading companies operate — simplifying, optimizing, and making work more resilient through the ServiceNow AI platform.”
For Abhijit Dubey, President, CEO, and AI Director at NTT DATA, this announcement marks a further step in the corporate strategy: “Expanding our alliance with ServiceNow marks a key milestone in our mission to become the leading native AI services company. By combining ServiceNow’s Agentic AI platform with NTT DATA’s global scale and industry knowledge, we empower organizations to accelerate innovation, improve productivity, and achieve sustainable growth.”
What Changes with the New Phase of the Partnership
1) NTT DATA as Strategic Delivery Partner for ServiceNow AI
The formal designation as a strategic delivery partner places NTT DATA at the core of implementation, adoption, and scaling of ServiceNow’s AI automation. Practically, this means enhanced capacity to design, integrate, and operate agents and applications on the platform, with shared methodologies, accelerators, and templates that reduce timelines and lower risks in production.
2) A Joint Go-to-Market, From Idea to Run-Book
Both companies co-develop and co-market AI-driven solutions — including enterprise agents — that help transform how work gets done: from employee/customer support to IT operations, finance, procurement, field services, or risk and compliance. The focus is on reusable use cases (quick ROI) and high-impact projects (scaled optimization over multiple data domains and processes).
3) NTT DATA as Reference Client (“Lighthouse Customer”) for ServiceNow
Beyond integrator, NTT DATA will expand its own use of ServiceNow AI agents and capabilities like Global Business Services, among others. The dual aim is to drive internal transformation and accelerate delivery for clients based on real-world adoption lessons. The message is clear: lead by example to gain speed and confidence in industrialization.
4) New AI Deployment Models: From “Eternal Pilot” to Production Value
ServiceNow will work with NTT DATA on implementation mechanisms that bridge the gap between proof of concept and sustained value. This includes the Now Next AI program, which incorporates AI engineering capabilities directly into transformation projects with clients, with milestones, metrics, and governance from day one. The goal is to shift from isolated experiments to continuous improvement cycles oriented toward business results.
Why This Partnership Matters Beyond Headlines
1) From Task Automation to Decision Orchestration
The promise of enterprise agents is to go beyond the “ticket response bot.” Connected to the context of each process (catalogs, policies, historical data), these agents understand the what, explain the why, and recommend the next step — including automatic actions when rules and confidence allow. The intended outcome: faster cycle times, less friction for users, and better risk control.
2) From Isolated Projects to a Cross-Functional Platform
The agreement drives a vision of a single platform for AI automation, where data, processes, and experiences are governed consistently. This reduces integration debt (less “glue” between tools) and shortens the path to production: same identity, access control, and audit trail.
3) Productivity and Experience: Two Sides of the Same Coin
The expanded partnership emphasizes productivity (time savings, reduced repetitive tasks) and more seamless experiences (for employees and clients). In both cases, the framework is the same: AI agents that resolve with context and learn from operations to improve with each iteration.
4) Governance and Trust Built-In
The expansion isn’t about rushing to automate everything, but about a responsible adoption program. This involves privacy, security, explainability, and compliance embedded in each case. Above all, it requires metrics to measure return (time, quality, cost mitigation) and clear principles about what to automate, when, and at what level of human oversight.
Where Impact Can First Be Seen (Key Use Cases)
- Employee Support: agents that resolve IT, HR, or facilities requests, interact with users, complete forms, raise tasks, and close cases with evidence; less waiting, fewer escalations, more satisfaction.
- Customer Support & Field Operations: assistants that interpret incidents, consult installed base and SLAs, schedule visits, and anticipate needs; higher first-time fix rates and lower downtime.
- IT/FinOps & Security: agents that monitor service health and spending, recommend optimizations, and orchestrate traceable actions; less MTTR and better cost control.
- Procure-to-Pay & Order-to-Cash: automations that normalize data, verify conditions, and suggest exceptions to responsible parties; creating a more predictable environment and reducing operational errors.
Each organization will have its own priority map, but the pattern repeats: Interactivity, which today requires time and coordination, is simplified into a conversational flow with agents that “see” the context and act with permission.
What CIOs and Transformation Leaders Must Address to Capture Value
- Cases and Metrics: set clear objectives per process (e.g., reduce cycle time by 20%, cut ticket costs by 15%, or increase NPS). AI is a lever, not an end in itself.
- Data and Permissions: ensure trustworthy sources, access controls, and traceability; without proper governance, the agent risks losing accuracy or becoming siloed.
- Change & Adoption: train teams, adjust responsibilities, and explain what the agent automates and what remains human-controlled.
- Improvement Cycle: iterate with learnings (logs, feedback, metrics), adjust the scope, and only scale into new domains when value is proven.
Risks & Cautions: The Fine Print of Forward-Looking Statements
The announcement explicitly warns about risks and uncertainties inherent to initiatives of this scope: delays in execution or delivery, regulatory changes around AI, and doubts about whether sales will justify investments. Classic adoption factors such as data quality, resistance to change, security, and biases are also involved. The key lesson: start with narrow use cases, measure, and scale based on criteria.
Quick Keys from the Agreement (At a Glance)
- Designation: NTT DATA will be ServiceNow’s strategic AI delivery partner.
- Internal Adoption: NTT DATA will expand its use of the AI platform (agents, Global Business Services, etc.) across global operations.
- Joint Go-to-Market: Collaborative development and sales of AI-powered solutions for clients worldwide, focusing on measurable impact.
- Deployment Models: Collaboration on new implementation approaches — including Now Next AI — to industrialize AI in transformation projects.
Frequently Asked Questions
What does it mean for NTT DATA to be “ServiceNow’s strategic AI delivery partner”?
It means NTT DATA assumes a priority role in implementing and scaling ServiceNow’s AI platform, with access to methodologies, accelerators, and joint capabilities to reduce time to value and minimize risks in production.
What is Now Next AI, and how does it accelerate AI adoption in companies?
Now Next AI is a deployment model that integrates AI engineering into transformation projects from the start: it defines use cases, metrics, governance, and a continuous improvement cycle to move from pilot to value, avoiding the “Eternal Pilot.”
What do clients gain from ServiceNow and NTT DATA’s joint go-to-market?
Access to co-created solutions and coordinated teams that combine platforms and execution (consulting, integration, managed services). The expected benefits are shorter timelines, fewer ad hoc integrations, and more predictable return on investment.
What are common risks when scaling AI agents in critical processes?
The main ones include data quality, bias, security, and resistance to change. They can be mitigated with governance (permissions, audit, privacy), value metrics, controlled testing, and team training.