Just "Figure It Out" Is Not a Training Strategy

When I made the move into the corporate world after 15 years of teaching in public education, one of the things that confounded me the most was the corporate response to training. It was as if many organizations had never really engaged with research on how people learn.

You could see it in how new initiatives were introduced. Tools would be rolled out, expectations would be set, and employees were often left to figure things out on their own. That same pattern is showing up again with AI.

At some point over the last few years, many organizations adopted a similar approach. They gave their teams access and expected them to figure it out. No structure. No shared language. No clear expectations for what “good” looks like.

On the surface, it sounds reasonable. Most professionals are capable, experienced, and used to learning new tools. The assumption is that, given enough time, they will naturally incorporate AI into their workflow. In practice, that rarely happens.

In my work, I see this play out regularly. Teams are introduced to AI tools with enthusiasm, but a few weeks later, usage becomes inconsistent. A handful of people experiment with it. Most fall back into familiar habits. The tool becomes optional rather than essential.

It is not a motivation problem. It is a training problem.

What the Research Has Been Telling Us for Years

This is not unique to AI.

A 2022 workplace learning study found that traditional, instructor-led training still produces the highest levels of effectiveness. When learning shifts to a purely self-directed digital format, effectiveness drops. When structure is reintroduced through a hybrid approach, outcomes improve again.

A 2025 retrospective cohort study on professional development showed similar results. When learners went through structured courses with clear instruction and progression, their performance improved significantly. Post-assessment scores exceeded 85 percent accuracy, and variability between learners decreased. The training did not just increase knowledge, it made performance more consistent.

That consistency matters in just about every business setting.

Even decades earlier, large-scale research pointed in the same direction. The Project Follow Through study found that Direct Instruction outperformed other models across multiple measures. Learners who received clear, structured teaching consistently achieved higher results than those expected to discover the material on their own.

None of this is new. We have known for a long time that structure improves learning outcomes.

Why AI Makes This Gap More Obvious

AI introduces a different kind of challenge.

It is not a static tool with a fixed set of steps. It is flexible, responsive, and open-ended. That makes it powerful, but it also makes it difficult to learn without guidance.

When someone is told to “figure it out,” they are not just learning a tool. They are trying to develop a way of thinking. Without structure, most people default to surface-level use. They try a few prompts, get mixed results, and struggle to connect the tool to their actual work. Over time, they either abandon it or use it in limited, inconsistent ways.

From the outside, it can look like the tool is not delivering value. In reality, the thinking behind its use has never been developed.

The Role of Curriculum

A curriculum does more than organize information. It provides a path, defines what someone needs to understand, how they should approach problems, and what effective use actually looks like in real situations. It creates a shared standard across a team, which is what allows a tool to move from individual experimentation to consistent application.

Without that structure, every person is left to invent their own approach.

Some will figure it out. Most will not.

Even among those who do, the approaches will vary, which makes it difficult for an organization to scale results.

Where This Shows Up in Real Work

You can see the difference fairly quickly.

In teams without structured training, AI use tends to be sporadic. Outputs vary widely in quality. People are unsure when to trust the results or how to refine them. The tool feels unpredictable.

In teams with structured training, the experience changes. There is a common way to approach tasks.

People know how to guide the tool, evaluate what it produces, and improve the outcome. The results are not only better, they are more consistent. That consistency is what creates leverage.

A Different Approach

In my work, I teach AI as a thinking process, not just a tool. The focus is on building a repeatable way to approach problems so that the tool can be used effectively across different situations.

It is less about memorizing prompts and more about understanding how to move from an initial idea to a refined, usable output.

When that process is in place, the tool becomes more predictable. People spend less time guessing and more time improving.

The Shift Organizations Need to Make

Access is no longer the barrier. Training is.

Organizations that treat AI as something employees will “pick up over time” tend to see uneven results. Those that invest in structured learning build capability that compounds.

The difference does not come from the tool itself. It comes from how people are taught to use it.

Closing Thought

If your team has access to AI but has not been trained on how to think with it, you are not seeing the full value of what is available.

The next step is not more tools or more experimentation. It is a clearer, more intentional way of learning how to use what is already in front of you.

That is the role of a curriculum. And it is the difference between hoping your team figures it out and knowing they can.

References

Project Follow Through / Direct Instruction: National Institute for Direct Instruction. (2026, February 26). Project Follow Through. https://www.nifdi.org/what-is-di/project-follow-through.html

2022 Workplace Training Study Emergn. (2022). The pursuit of effective workplace training: Emergn survey report 2022. https://www.emergn.com/wp-content/uploads/2022/10/Emergn-Survey-Report-2022-The-Pursuit-of-Effective-Workplace-Training.pdf

2025 Professional Development Study: Effectiveness of a continuous training program on knowledge retention and professional growth among health care professionals. (2025, May 19). PMC. https://pmc.ncbi.nlm.nih.gov/articles/PMC12090590/