James Bell
Founder of Next Step Ventures. Applied AI consulting, training and implementation for private-markets teams.
James leads Next Step Ventures AI Consultancy, based in London and working with clients globally. His background brings together finance, data and AI, with experience increasing adoption and building working solutions inside private-markets finance firms and startups.
The work begins with the people doing the task: the tools they can use, the information they can access, the checks an experienced reviewer makes and the output the team actually needs. That can lead to a practical training session, a workflow proof or a wider implementation.
Alongside his private-markets work, James supports founders developing AI products and works with business owners as an AI operating partner, embedding tools into everyday operations. He is also developing The WaterWallet, his own fold-away water-container venture.
View James Bell’s professional profile on LinkedIn · Watch Applied AI demonstrations on YouTube
01How James works with a team
One named specialist works directly with the team. The starting point is the firm’s approved environment, including its data permissions, existing systems and review responsibilities. The method makes assumptions and uncertainty visible so the people responsible for the work can judge the result.
- AI training and literacy: practise useful workflows, recognise unreliable outputs and create reusable team material.
- AI hackathons and working sessions: turn recurring friction into specific, owned opportunities that can be tested.
- AI Workflow Planning: establish the case for one workflow, build a proof and reach a go, revise or stop decision.
- Implementation: connect the workflow to its sources, review process, operating owner and ongoing feedback.
02Selected writing and demonstrations
James writes the field notes on this site. They explain practical methods and implementation choices, with sources and examples where relevant. The guides below show the approach in more detail.
- What a three-hour AI crash course looks like - the session sequence, practice and follow-through.
- How to run a use-case hackathon that actually ships something - preparation, facilitation and ownership.
- How to score AI use cases before anyone builds anything - value, feasibility, risk and adoption.
- Shipping AI inside a regulated firm - the gap between a plausible demo and a dependable workflow.
- Watch the 30-minute AI working-session method - a short demonstration of data, process, judgement and output.
03Start with the work
For an initial conversation, bring one recurring task, who owns it, the approved tools and what a good output should look like. A fit call establishes the smallest useful next step and whether the necessary data, review and ownership are available.
Discuss a workflow with James or compare the available services.