The Planning Paradox
Stanford University’s AI’s Index Report shows an alarming trend: artificial intelligence is advancing at an extraordinary pace, transforming workplace capabilities, accelerating adoption, and changing the skills employees need faster than traditional training models can keep up.
Why it matters: The rate of change is so rapid that planning an AI learning curriculum - or any curriculum for that matter - that is longer than six months is turning into a fool's errand.
For example, let’s look at the pace of change in AI-related training
2023: Organizations introduced employees to LLMs and the fundamentals of writing effective prompts.
2024: Training expanded to analyzing documents, interpreting data and incorporating AI into everyday workflows.
2025: AI agents introduced new possibilities for automating tasks and managing complex workflows.
2026: Organizations increasingly need employees who can supervise AI agents, evaluate their recommendations and exercise sound judgment about when humans should intervene.
2027: TBD.
Imagine having developed a comprehensive, two-year AI training curriculum in 2023. How much of it would still address your employees' most pressing needs today?
Yet many organizations continue to build rigid, annual or multi-year training calendars.
What if we stopped trying to predict every learning need and started planning for the unexpected?
Introducing the 100–75–50–25 Planning Paradox
At Wronski Associates, we're proposing a different approach to working with clients: establish long-term learning goals while deliberately leaving room to adapt.
Here's how it works:
3 months: 100% planned. Commit to specific learning priorities, programs and experiences that address immediate business needs.
6 months: 75% planned. Establish a clear direction while reserving capacity for emerging challenges and opportunities.
12 months: 50% planned. Identify the capabilities employees will need, but leave half the specific learning activities open to adjustment.
24 months: 25% planned. Commit to strategic outcomes without pretending we can predict exactly which training programs will be needed two years from now.
The twist: These percentages don't represent how much training we'll deliver. They represent how much of the future we're willing to lock in today.
And this isn’t AI-focused; it’s all topics and the entire curriculum for any long-term engagement.
We aren’t viewing change as a disruption; it's now the strategy.
Rather than developing something that’s fixed, we fully expect and plan for change.
With that in mind, imagine taking an hour every 30 to 60 days to ask:
What's changed? What new technologies, business priorities or workplace challenges have emerged?
What matters now? Which employee capabilities will have the greatest impact on performance?
What should we change? Which learning experiences should we keep, expand, redesign or eliminate?
A planned leadership workshop might evolve to address managing AI-enabled teams. A new technology might require entirely different skills. An emerging business challenge might take priority over a program scheduled months earlier.
And that's not a failure of the plan. It's the plan working exactly as intended.
Organizations still need a clear, long-term vision for developing their people. Leadership, communication, collaboration, and critical thinking remain essential capabilities that deserve sustained investment.
But the specific learning experiences required to build those capabilities will evolve.
The Planning Paradox: The more uncertain the future becomes, the more important planning is, and the less rigid our plans should be.
At Wronski Associates, we believe the best learning strategy isn't one that survives two years unchanged.
The bottom line: The biggest risk in long-term learning isn't that your training plan will change. It's that it won't.
