Practical AI training for private-markets teams
Practical, role-based AI literacy that helps investment and operating teams use approved tools well, recognise failure, protect sensitive information and turn learning into repeatable work.
Led by James Bell, based in London and working globally through on-site, remote and hybrid engagements.
AI literacy is the ability to use AI with judgement - not simply the ability to write a prompt. In private markets, that means understanding what a model can and cannot infer, how confidential information should be handled, when sources must be checked, where professional judgement enters a workflow, and what a trustworthy output looks like.
Next Step Ventures designs training around the firm’s approved tools and the work people already perform. Sessions can use Microsoft 365 Copilot, ChatGPT Enterprise, Claude, Gemini, local tools or a mixed environment. The objective is consistent capability that survives after the session, not a list of tricks people forget.
01What good AI literacy covers
| Capability | What the team learns | Why it matters |
|---|---|---|
| Model judgement | How models generate answers, where they fail and how to test uncertainty. | Teams stop treating fluent output as verified analysis. |
| Data judgement | Which information is approved, how access works and when sources or citations are required. | Confidential investment and client information is handled consistently. |
| Workflow design | How to define the input, process, output, review and success test for a repeated task. | One-off prompting becomes repeatable work. |
| Tool fluency | How to use the features available in the firm’s actual stack. | Learning transfers directly into Monday-morning work. |
| Responsible use | How to apply human review, escalation, disclosure and auditability. | Useful adoption can grow without weakening accountability. |
02Training formats
- Leadership briefing: a focused view of capability, risk, operating choices and what implementation requires.
- Practical team workshop: hands-on work using relevant documents, scenarios and approved tools.
- Role-based programme: different learning paths for investment professionals, operations, investor relations, finance, legal and compliance.
- Train-the-champion: reusable material, office hours and facilitation support for one or two motivated internal champions per team.
- Training plus build: a session that turns selected workflows into reusable skills, artefacts or lightweight automations.
For a private-equity-specific session, see AI training for private equity teams. The broader literacy programme is designed for mixed investment organisations and cross-functional groups.
03How the content stays relevant
Before the session, participants or workflow owners provide an approved data sample, an example of the desired output and a walkthrough of the current process. That preparation allows exercises to reflect the firm’s real environment without requiring sensitive material to be placed into an unapproved tool.
The session makes professional judgement explicit. Participants identify what an experienced reviewer checks, which omissions matter, when an answer should be rejected and where the model needs evidence. This is particularly important in investment work, where the decisive quality rule may exist in a person’s experience rather than a written procedure.
04What the team should leave with
- a shared language for discussing AI capability and risk;
- safe working habits for approved tools and data;
- role-relevant workflows people have practised themselves;
- reusable prompts, skills, checklists or artefacts where appropriate;
- a shortlist of opportunities that deserve a test;
- named owners and a plan for follow-up, measurement and reinforcement.
05Choose a useful starting format
The right session depends on the work participants need to do afterwards. Start with one team, a clear capability gap and an approved set of examples.
On a small screen, scroll the comparison sideways to see each format and its outputs.
| Starting point | Practical format | Evidence to take away |
|---|---|---|
| Licences are available, but usage is uneven | A focused three-hour AI workshop using familiar tasks | Practised workflows, saved prompts or skills and a named next action |
| Different teams have different needs | Role-based sessions for investment, operations, finance, investor relations, legal or compliance | Examples and review checklists matched to each role |
| People have ideas but need to try them | Training followed by an AI hackathon | A prioritised backlog, prototype evidence and workflow owners |
| One workflow needs a build decision | The AI Workflow Planning | A working proof, acceptance tests and a go, revise or stop decision |
For scoping, share the participants’ roles, approved tools, current experience and one or two representative tasks. Agree the session format and follow-up before delivery. London is the base; sessions can be delivered on site, remotely or in a hybrid format for teams internationally.
For the underlying adoption problem, read The AI rollout has happened. The training has not.
06AI literacy FAQs
Is AI literacy the same as prompt training?
No. Prompting is one component. AI literacy also covers model limitations, data handling, source checking, professional judgement, workflow design, human review and responsible use.
Can the training use our existing tools?
Yes. Training is adapted to the approved tools and permissions participants actually have, rather than assuming access to a particular model or enterprise product.
Can legal, compliance and investment teams attend together?
Yes. Mixed groups are often valuable because they surface different quality, risk and approval requirements around the same workflow.
Related reading: what a three-hour AI crash course looks like and the AI literacy and implementation game plan.