My PM software uses AI to predict our finish date, but it’s consistently optimistic. We’ve missed three milestones in a row that the "Dashboard" said were on track. Is the problem with my data entry, or is predictive planning just hype?
3 answers
The AI is only as good as the "Quality" of the data it’s fed. Most teams suffer from "Optimism Bias" during data entry. If your developers are marking tasks as "90% done" for two weeks straight, the AI thinks progress is being made. You need to implement "Binary Progress Tracking" (it’s either 0% or 100% done). Also, check if your AI is only looking at internal data. In 2026, the best predictors also ingest external data—like vendor delays or global supply chain indices. If your AI isn't aware that your hardware supplier is backlogged, it will always be optimistic.
How do we convince the team to be "Honest" with the data if they feel that a "Red" status on the dashboard will lead to a reprimand?
Use "Reference Class Forecasting." Compare your current project plan to a pool of 100 similar past projects. It’s the best reality check for AI.
Totally agree, Gary. History is a much better teacher than a local algorithm that’s only looking at a two-week sprint.
Richard, that’s a "Psychological Safety" issue, not a tech issue. To answer your point, I changed my dashboard's name from "Performance Tracker" to "Risk Support Tool." I told the team: "The earlier the dashboard turns red, the faster I can get you more resources or move the deadline." Once they saw that "Red" meant "Help is coming" rather than "You're in trouble," the data quality improved overnight, and our AI predictions became 90% accurate.