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Published: 16 November 2022



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  • 多くの既存ソフトウェア・プラットフォームが、コンポジット人工知能 (AI) のトレンドによって、既に拡張・改良されている。コンポジットAIは、意思決定インテリジェンス・プラットフォームの先駆けである。

  • 意思決定モデリング機能によって、データ/アナリティクスとプロセス管理ソフトウェアの間にある従来の境界線が曖昧化しつつある。

  • 単一のAI手法 (例えば、機械学習、ルール、最適化) のみに焦点を合わせたプラットフォームは例外となる。

  • AIソフトウェアは、自律型システムとソフトウェア・エージェントに向かいつつあるため、社内全域にわたって意思決定モデリングを合理化することは、AIソフトウェアの次なる段階への準備になる。



  • トレーサビリティ、再現性、妥当性、信頼性の向上を目的とした原則を用いてモデルを構築することにより、組織横断的な意思決定を持続可能なものにする。

  • 意思決定の際は、各状況の要件に合わせて意思決定手法の選択を調整することで、特定領域の専門家、AIエキスパート、ビジネス・プロセス・アナリストとのコラボレーションを加速させる。

  • 意思決定インテリジェンス・プラットフォームを選択する際は、「意思決定フローの設計」「オーケストレーション」「意思決定フローの実行」「コンポジション」「意思決定の監査」の能力に優先順位を付けることで、意思決定のモデル化/実行の成功度を高める。

  • 新旧の分析的・記号的手法についてスタッフの専門知識を高めることで、あらゆる意思決定モデリング・ユースケース (意思決定の支援/拡張/自動化) に対処する。

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Kimihiko Iijima

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