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SoftBank to launch AGENTIC STAR 3.0 on Oct 26, 2026

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SoftBank to launch AGENTIC STAR 3.0 on Oct 26, 2026

3 Key Points

  1. What happened

    SoftBank will offer AGENTIC STAR 3.0 from October 26, 2026, adding a project feature that designs and manages multi-step workflows mixing AI-agent work with human judgment, records execution history, and visualizes completion and failure counts and processing time.

  2. Why it matters

    Corporate AI users increasingly want agents embedded in ongoing processes and measurable results, so the version is positioned to support cost-effectiveness evaluation rather than chat-only assistance, though adoption outcomes are not yet shown.

WHO IT HITSCorporate teams deploying AI for multi-step operations, such as those needing human sign-off steps, can design and monitor agent workflows with quantitative metrics. IT and operations managers evaluating AI ROI are the most direct users.

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Context & Analysis

SoftBank frames AGENTIC STAR around a shift from using AI in chat to entrusting it with work. The 3.0 release extends that idea from individual chat assistance to continuous execution and management of business processes.

The company cites growing corporate demand for embedding AI agents into multi-step processes, not just single tasks. It also points to the need to quantify processing time and completion status to evaluate AI's cost-effectiveness.

To meet that, the new version records agent execution history and surfaces completion counts, failure counts, and processing time. These features are presented as a way to connect AI introduction to continuous process improvement, though the announcement does not provide customer results or adoption figures.

FAQ
When will AGENTIC STAR 3.0 be available?
SoftBank will provide it starting October 26, 2026.
What new capability does the project feature add?
It lets users design and manage multi-step workflows that combine AI-agent execution with human judgment and confirmation steps.
How does it help measure AI adoption results?
It visualizes completed and failed task counts and processing time, so teams can verify cost-effectiveness using metrics such as man-hours and quality.
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