TRIZ is famous for helping teams think beyond the obvious.
Here’s the paradox: can TRIZ itself become a box?
The contradiction matrix, 39 parameters, 40 principles—powerful tools, yes. But if we treat only those as the front door to every problem, we risk swapping one box for another.
Important context (for practitioners)
TRIZ is far more than the matrix. Modern TRIZ includes ARIZ, Su-Field analysis, Trends/TESE (Trends of Engineering System Evolution), Function-Oriented Search (FOS), Anticipatory Failure Determination (AFD), and OTSM (a generalization of TRIZ for networks of contradictions). My point isn’t to dismiss TRIZ—it’s to prevent teams from under-using modern TRIZ and over-relying on the matrix.
Where TRIZ Becomes a Box (in practice)
Structural limits (when teams start only with the matrix):
- Two-parameter framing for problems with 5–20 interacting constraints
- Category ambiguity across domains (“ease of operation” in software ≠ in manufacturing)
- Static catalogs that can lag modern materials, digital, and field-based effects
- Mapping outcomes that vary by who frames the contradiction
Cognitive traps (human factors):
- Premature convergence once the matrix suggests a path
- Anchoring to the first recommended principle
- Quiet framework worship (“if it’s not in TRIZ, it’s not systematic”)
Modern TRIZ already mitigates these issues—if you use the full toolkit.
Expanding the TRIZ Box with AI (extension, not replacement)
What AI adds to modern TRIZ:
- Dynamic parameters (beyond 39): extract problem-specific features from reports, lab notes, and patents
- Multi-constraint reasoning: analyze multi constraints simultaneously, not just a two-parameter snapshot
- OTSM-style navigation: map and prioritize networks of contradictions, not isolated pairs
- AFD at scale: auto-suggest failure scenarios/hypotheses from similar cases and literature
- Continuously learning knowledge base: update with your experiment history + new patents/papers, not mid-century only
- Bias checks: force multiple solution pathways to avoid anchoring on the first idea
A Pragmatic Workflow (TRIZ + AI + Domain Expertise)
- Frame with TRIZ (ARIZ steps: define system, contradictions, resources).
- AI expands the canvas (surface hidden parameters, cluster similar cases, suggest TESE moves).
- Generate solution pathways (Su-Field transforms, field substitutions, FOS cross-domain ideas).
- AFD pass (anticipate & design out likely failures).
- Domain filter & rapid tests (short DOE around the highest-leverage gates).
Outcome: the rigor of TRIZ + the breadth and recency of AI + the feasibility lens of your experts.
The Meta-Lesson
Every innovation tool eventually becomes a constraint—unless we evolve it.
Classical TRIZ gave us structure.
Modern TRIZ (ARIZ, Su-Field, Trends/TESE, FOS, AFD, OTSM) broadened that structure.
AI-TRIZ lets us personalize, scale, and continuously update the structure with our own data.
👉 Have you seen a framework quietly become the box? Share a story. I’m collecting cross-industry patterns to publish a summary.
About the author: Innovation & SR&ED advisor | I help IT and manufacturing teams turn constraints into breakthroughs—and tax credits—using AI + modern TRIZ.