🚫 The AI "Blacklist": Where Generative AI has no place in Project Management I’ve been diving deep into the structural mismatch between Generative AI and professional standards (like PMI-PMP). Here is the reality:AI does not lie because it has no duty to tell the truth.It generates coherent text, not verified facts. In a world governed by traceability, accountability, and ethical truthfulness, here are the tasks where using raw AI output isn't just risky—it’s a violation of professional due diligence. 1. Financial Baselines & EVM Calculations
The Risk: AI can't account for real-time market volatility or proprietary constraints.
The Reality: If the math is wrong, the AI won't feel the "guilt" of a budget overrun. You can delegate the typing, but you can’t delegate the audit risk.
2. Safety & Compliance Documentation
The Risk: AI cannot physically inspect a site or understand engineering tolerances.
The Reality: Safety isn't a "word prediction" game. Using AI for OSHA or ISO plans creates physical and legal exposure that an LLM isn't built to catch.
3. Legal Clauses & Contract Language
The Risk: Jurisdictional nuances and current case law are often "hallucinated" or outdated in AI training sets.
The Reality: AI doesn’t understand the consequences of a bad indemnity clause. It optimizes for "sounding legal," not for "being legal."
4. Technical Specifications & Engineering
The Risk: An AI might suggest a material that looks correct in a sentence but violates the laws of physics or safety margins.
The Reality: AI lacks "professional judgment." It cannot verify its own logic or guarantee that its output is reproducible in the real world.
5. Ethics & Conflict of Interest Assessments
The Risk: Transparency requires a logic process you can explain. AI is a "black box."
The Reality: PMI standards require honesty and accountability. Presenting unverified AI data as a "factual disclosure" is a failure of professional integrity.
The Bottom Line:AI is a "Search Assistant," not a "Subject Matter Expert." It is optimized forspeed and synthesis, not fortruth and rigor. If your task requires evidence, verification, or accountability, keep the AI out of the driver’s seat. Use it for the draft—never for the decision Saving Changes...
