NTT DATA Launches AI Agent for Managing Enterprise Infrastructure
NTT DATA announced the launch of an AI agent designed to manage infrastructure across multiple vendors and systems. The agent, embedded in NTT DATA's Software Defined Infrastructure (SDI) Services, works through natural language prompts to help enterprises monitor, optimize and govern their IT environments.
The system operates as a multi-agent orchestrator, continuously monitoring networking, data centers, cybersecurity and workplace environments. It combines live telemetry with historical data and policy rules to suggest or execute actions while keeping humans in control of decisions.
How It Works for Management
Unlike vendor-specific AI assistants locked into single platforms, this agent works across multivendor infrastructure. Managers can ask questions about system performance, resource utilization and costs using everyday language instead of navigating separate tools.
The agent reasons through data to predict problems before they occur and prioritize fixes based on business impact. It also tracks environmental costs of infrastructure operations, giving organizations visibility into sustainability metrics.
The Business Case
Organizations across the Middle East and Africa face pressure to scale digital systems while controlling costs and risk, according to Hani Nofal, head of technology solutions for NTT DATA in that region. The agent shifts operations from reactive firefighting to outcome-driven management focused on availability, efficiency and time to value.
IDC's Chris Barnard noted that traditional infrastructure services increasingly fail to meet the needs of AI-driven enterprises. "NTT DATA is differentiating itself through an innovative multivendor agentic service experience," he said.
What Managers Should Know
The agent functions as a digital twin for IT operational roles, meaning it learns how your infrastructure typically behaves and flags deviations. This reduces the need for staff to manually monitor systems across vendors.
For managers overseeing infrastructure teams, the practical benefit is clearer visibility into what's happening across complex environments. The system delivers persona-based insights, meaning a network manager sees different information than a security manager, both drawn from the same underlying data.
Learn more about AI Agents & Automation or explore an AI Learning Path for IT Managers to understand how these systems apply to your role.
Current Limitations
The agent operates within guardrails set by human policy makers. It doesn't make autonomous decisions outside defined parameters. Organizations must still decide what actions the agent can take independently versus what requires approval.
Implementation requires integration with existing infrastructure monitoring tools and systems. The agent's effectiveness depends on data quality from those underlying systems.
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