AndTech to Host Seminar on AI Agent Social Implementation and R&D/Product Development Acceleration on July 21st
AndTech will host an expert-led Zoom seminar on July 21, 2026, focusing on the social implementation of AI agents and R&D DX. The session will cover practical integration processes and real-world case studies from industry leaders.
📋 Article Processing Timeline
- 📰 Published: May 29, 2026 at 22:40
- 🔍 Collected: May 29, 2026 at 13:48
- 🤖 AI Analyzed: May 29, 2026 at 13:48 (0 min after Collected)
AndTech, Inc. (Headquarters: Kawasaki, Kanagawa; President: Masao Suyama) has announced a professional Zoom seminar titled 'AI Agents' as part of its R&D support program, addressing the rising interest in this field.
The seminar will cover the latest trends in AI agents and Physical AI—the next frontier after generative AI—along with practical insights into the 'field-led AI agent implementation process' and case studies using AI agents and knowledge graphs for product development.
Date and Time: July 21, 2026 (Tue), 13:00-16:35
Registration Fee: 55,000 JPY (tax included)
Format: Live streaming via Zoom
Program Overview:
- Part 1: What comes after Generative AI? R&D DX strategy in the AI agent/Physical AI era (Speaker: Shiho Mukada)
- Part 2: From tool implementation to structural transformation: AI agent implementation at DNP, its retention process and insights (Speaker: Tsuyoshi Wada)
- Part 3: NEC's product development cases using AI agents, and accelerating materials development using knowledge graphs and generative AI (Speakers: Noritaka Shimura, Noboru Yoshida)
Key Learning Objectives:
- Overview of AI agents and Physical AI
- Latest trends in AI in R&D and materials development
- Relationships between AI agents, MI, digital twins, and autonomous experiments
- Reasons why AI projects remain at the PoC stage and how to overcome them
- Importance of AgentOps and operational design
- How research organizations will change over the next 3-5 years
- Approaches for organizational adoption and process redesign for generative AI
- Field-led implementation processes for AI agents
- Application cases of knowledge graphs and generative AI in product and materials development
The seminar will cover the latest trends in AI agents and Physical AI—the next frontier after generative AI—along with practical insights into the 'field-led AI agent implementation process' and case studies using AI agents and knowledge graphs for product development.
Date and Time: July 21, 2026 (Tue), 13:00-16:35
Registration Fee: 55,000 JPY (tax included)
Format: Live streaming via Zoom
Program Overview:
- Part 1: What comes after Generative AI? R&D DX strategy in the AI agent/Physical AI era (Speaker: Shiho Mukada)
- Part 2: From tool implementation to structural transformation: AI agent implementation at DNP, its retention process and insights (Speaker: Tsuyoshi Wada)
- Part 3: NEC's product development cases using AI agents, and accelerating materials development using knowledge graphs and generative AI (Speakers: Noritaka Shimura, Noboru Yoshida)
Key Learning Objectives:
- Overview of AI agents and Physical AI
- Latest trends in AI in R&D and materials development
- Relationships between AI agents, MI, digital twins, and autonomous experiments
- Reasons why AI projects remain at the PoC stage and how to overcome them
- Importance of AgentOps and operational design
- How research organizations will change over the next 3-5 years
- Approaches for organizational adoption and process redesign for generative AI
- Field-led implementation processes for AI agents
- Application cases of knowledge graphs and generative AI in product and materials development
FAQ
AndTechが開催するAIエージェントセミナーの開催日時と形式は？
2026年07月21日(火) 13:00-16:35に、WEB会議ツール「Zoom」を使用したライブ配信形式で開催されます。
このセミナーではどのような専門的な知見が学べますか？
AIエージェント・Physical AIの概要、研究開発におけるAI活用の最新動向、AI導入をPoC止まりにさせない運用設計、知識グラフと生成AIを組み合わせた材料開発の高速化事例などが学べます。
セミナーにはどのような講師陣が登壇しますか？
MISTEM合同会社 向田志保氏、大日本印刷株式会社 和田剛氏、日本電気株式会社(NEC)の志村典孝氏および吉田登氏が登壇します。
セミナーの参加費用はいくらですか？
参加費は55,000円（税込）で、電子資料の配布が予定されています。
AIエージェントの社会実装において、このセミナーが解決を目指す課題は何ですか？
AI導入がPoC（概念実証）止まりになる原因の対策、暗黙知の言語化、業務の分解・実装プロセス、そしてAIガバナンスと人間がボトルネックにならない体験設計などを解決の課題としています。