Choose a one-off AI training workshop when you need a shared starting point fast, your team already has the tools, and you have someone inside the firm who will keep the habits going afterward. Choose ongoing AI coaching when you need AI to change how specific work gets done, people are at very different levels, or earlier training faded within a few weeks.
Many firms end up using both: a workshop to get everyone to the same baseline, then a lighter rhythm of coaching for the teams where AI matters most.
Who this is for
COOs, heads of people, managing partners and team leads deciding how to spend an AI training budget, and weighing a single session against a longer program.
The short version
- A workshop is strongest at creating a common language, quick wins and momentum in a short time.
- Ongoing coaching is strongest at turning those first wins into everyday habits on real work.
- The deciding question is usually not the format. It is who keeps people practicing after the first session.
The two options at a glance
| One-off workshop | Ongoing coaching | |
|---|---|---|
| Typical shape | A single session or a short block, often half a day or a day | Shorter sessions spread over weeks or months, plus help between sessions |
| Usually strongest at | Shared baseline, awareness, momentum, a clear starting set of habits | Habit change, role-specific depth, working through real tasks as they come up |
| Time from people | Concentrated, then done | Smaller amounts, repeated |
| Cost shape | One fixed engagement | Recurring or staged |
| Main risk | Enthusiasm fades and usage drops back | Drifts into routine meetings without clear goals |
| Best measured by | Whether people try AI on real work in the following weeks | Whether specific workflows change and stay changed |
What a one-off workshop does well
A good workshop gets a whole team onto the same page at once: the same vocabulary, the same rules about what data they can use, and a few techniques they can apply the next day.
- It is easy to approve. One date, one budget line.
- It suits teams that are already fairly capable. If people use AI regularly and mainly need to tighten their habits and learn your firm’s rules, a single focused session may be all they need.
- It works well as a test. A workshop is a low-commitment way to see whether a trainer, and an approach, fits your firm.
Where a one-off workshop falls short
The common failure is the weeks after the session. Without follow-up, people go back to deadlines and old routines. A single session also struggles with a very mixed group, and it can only cover the tasks the trainer anticipated, not the awkward real cases people hit a week later.
If you have already run a workshop and usage dropped off, another workshop on its own is unlikely to fix that. See why your team isn’t using the AI tools you paid for.
What ongoing coaching does well
Ongoing coaching spreads the learning out and ties it to the memo, analysis, proposal or client email a team is working on that week.
- Habits have time to form. People try something, hit a problem, and get help before they give up.
- It adapts to the team. Sessions can go deeper for the people who are ready and slow down for the people who are not.
- It surfaces what to build. Repeated questions often reveal workflows worth standardizing or automating.
- It makes measurement realistic. You can track a few named workflows over time. See how to measure whether AI training worked.
Where ongoing coaching falls short
Coaching costs more in total and asks for repeated time from busy people. Without clear goals it becomes a standing meeting nobody prioritizes, and it is easy to keep it going longer than needed. The team should need less outside help over time, not more.
When each option tends to win
A one-off workshop is usually the better choice when:
- You need a fast, shared baseline across many people.
- Your team already uses AI and mainly needs your firm’s rules and better techniques.
- You have an internal owner, such as a team lead or operations person, who will run short follow-ups.
Ongoing coaching is usually the better choice when:
- You want specific workflows to change, not just awareness to rise.
- The team is mixed, with some heavy users and some who have barely started.
- A previous round of training faded.
- AI is tied to a business goal leadership will check on in a few months.
A simple way to decide
Work through these questions:
- What should be different in 90 days? If the honest answer is “people know the basics and our rules,” a workshop may be enough. If it is “these three workflows run differently,” plan for coaching.
- Who keeps people practicing afterward? If you can name someone with the time and standing to do it, a workshop plus internal follow-up can work. If not, build follow-up into the plan from the start.
- What happened last time? If earlier training faded, change the format, not just the trainer.
A practical middle path is a workshop, then a few short check-ins with the teams where AI matters most, then a decision on whether to continue.
Common mistakes
- Treating the workshop as the finish line. The session is where habits start, not where they are proven.
- Coaching without goals. Every coaching block should be tied to named workflows and a check-in date.
- Training everyone the same way. Different roles need different examples and depth.
- Skipping the rules. Either format should cover what data people can and cannot use. See how to write an AI acceptable use policy.
When you do not need us
If your team is already capable and you have a strong internal owner, a short workshop from anyone you trust, followed by your own check-ins, may be all you need. And if a single focused session solves the problem, more coaching is not the right answer.
How Ruby helps
We usually start with a short, hands-on session on your team’s real work, then recommend follow-up only where it will change specific workflows. Coaching tapers off as your people need us less, and connects to strategy and engineering when a workflow is worth building out.
To see how we teach, start with one practical hour of AI training.