What’s Ahead - Alien Processes, Domains, and Data Models

2025-11-05 · Source: Practical Data Modeling · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Emerging Technologies & Innovation · Depth: Intermediate, short

Summary

The article speculates on the future impact of AI agents on business processes, domains, and data models, suggesting changes that will appear "alien" to human understanding. Drawing a parallel to AlphaGo's unexpected mastery of Go in 2015, it posits that as AI agents become more integrated and numerous within organizations, they will develop their own optimized processes and even "machine tacit" knowledge. This evolution will shift the focus of data modeling from merely recording "what" happened to understanding "why" and "how" AI-generated processes operate. The author anticipates the emergence of new, potentially incomprehensible data formats, such as high-dimensional vector spaces or dynamic ontologies, leading to a "Mixed Model Arts" environment where human and machine-invented structures coexist.

Key takeaway

For Directors of AI/ML evaluating future enterprise architecture, recognize that AI agents will not merely automate existing processes but will invent entirely new ones and associated data models. Your teams should begin exploring how to integrate and manage these "alien" machine-generated structures, shifting focus towards understanding AI's operational logic rather than solely defining its inputs and outputs. Proactive planning for "Mixed Model Arts" environments is crucial to avoid being outpaced by autonomous agent evolution.

Key insights

AI agents will soon create "alien" processes and data models, fundamentally altering human-machine interaction in business.

Principles

• AI agents will develop "machine tacit" knowledge.
• Data modeling will shift from "what" to "why" and "how."

In practice

• Prepare for AI-generated processes and domains.
• Anticipate new, non-traditional data model formats.

Topics

• AI Agents
• Business Process Modeling
• Data Model Evolution
• Machine Tacit Knowledge
• Mixed Model Arts

Best for: AI Engineer, Data Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Practical Data Modeling.