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AI agents now redesign core business processes

AI agents now redesign core business processes

Key takeaway

  • AI agents are moving from supporting tasks to leading business processes. NTT DATA shows real cases: knowledge transfer, faster surveys, and quicker product concepts.

  • The trend shifts customer contact designs toward AI agents. Companies should redesign workflows, not just add AI.

  • Security, data, and ongoing improvement remain key.

3 Key Points

  1. What happened

    NTT DATA is moving AI use from simple efficiency tools to transforming core business processes. Examples include passing on expert knowledge at Kawasaki Heavy Industries and shortening a 9-month product concept task to 150 seconds for a major overseas food maker.

  2. Why it matters

    AI agents can now handle larger parts of business workflows, including customer contact points and internal operations. This shift means companies must rethink processes around AI, not just add it to existing tasks. The article highlights outcomes like cutting a survey period from 1.5 months to 0.5 days using AI-generated consumer personas.

  3. What to watch

    NTT DATA is applying AI in stages, starting with low-risk tasks and expanding as accuracy improves. They also offer services like LITRON Marketing, LITRON CORE, and LITRON Builder, and emphasize building an AI-ready data foundation, continuous improvement, and security governance.

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Context & Analysis

The article marks a shift from pilot projects to full-scale AI adoption, with NTT DATA presenting examples where AI is embedded in core business processes. The Kawasaki Heavy Industries case shows how interview and tutor agents turn tacit expert knowledge into reusable assets for younger staff. The Kao case demonstrates using AI-generated consumer personas to cut survey periods dramatically. These examples support the argument that AI agents are not just tools but catalysts for redesigning how work gets done.

A key theme is the changing nature of customer interaction. The article predicts that personal AI assistants will represent customers, so companies must design information that AI agents can understand and select, rather than only optimizing for human web visitors. This implies a shift in information architecture and content strategy, though the article does not provide concrete details on implementation.

The practical guidance centers on three pillars: an AI-ready data foundation, continuous improvement, and security governance. The staged approach—starting small and expanding based on risk and validation—reflects a cautious yet progressive strategy. The article emphasizes that AI should augment human capabilities, not replace them, with humans focusing on decision-making and creativity while AI handles routine tasks. Overall, the message is that successful AI transformation requires both technological infrastructure and organizational change, with NTT DATA positioning its services like LITRON and Smart AI Agent as enablers.

FAQ

How much faster did the food maker's product concept work become?
The work that used to take nine months was reduced to 150 seconds using multiple AI agents with specialized knowledge.
What is NTT DATA's approach to implementing AI agents safely?
They start with low-risk tasks, let AI handle checks and minor corrections, while humans verify results for high-risk areas. They gradually expand AI responsibility as accuracy and safety are confirmed.
What does 'Client Zero' mean in NTT DATA's AI strategy?
It means treating themselves as the 'zeroth customer' — using AI in their own operations first, then applying the learned insights to customer services.
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