No Time or Know-How in Your Team for AI? How to Add the Capacity
For smaller companies, know-how is the main obstacle to using AI, more than money, and the people who could learn it are busy running the business. There are four usual routes: free up and train your own people, hire an agency for a defined project, hire a freelancer for a short task, or add someone to the team who already works this way. Tunga calls that last role an AI operator: someone who runs processes with the help of AI, and builds and maintains those processes. Through Tunga you can add one, also part-time.
Why AI work stalls in smaller companies
- Know-how, more than money. In the Netherlands, for example, 71.6% of micro companies that had considered AI named lack of expertise as the reason they didn't use it in 2025, up from 56.5% in 2023; cost fell from 30.9% to 20.3% (CBS).
- The people who know the processes are running them. The colleague who knows how quotes or support tickets work is the one handling them all day.
- AI processes need looking after. Models change, instructions stop working as they did, and output needs checking. A tool that is built once and handed over tends to stall after a few months.
The options
- Free up and train your own people. This builds the most knowledge inside the company, and it takes time you may not have: someone else has to take over part of their work.
- An agency or consultancy for a defined project that is handed over at the end. This suits one tool that can be fully specified up front, as long as someone on your side can maintain it afterwards.
- A freelancer for a short, well-defined task.
- Someone in your team who already works this way. This suits a stream of smaller processes and improvements, where most of the value comes after the first version, and the way of working spreads to colleagues.
What an AI operator does
At Tunga, an AI operator is a professional who runs processes with the help of AI, and builds and maintains those processes:
- runs a process such as handling incoming requests, preparing quotes or processing documents, with AI doing part of the work;
- connects AI models and agents to the tools you already use, such as your CRM, email, documents and ticketing system;
- writes and tests the instructions the processes run on, checks the output, and fixes them when the results drift;
- documents how each process works and shows colleagues how to use it, so the knowledge stays in your company.
An AI engineer goes deeper into the software: AI features in your product, data pipelines, testing how well a model performs. In practice the two roles overlap, and the right profile depends on the work.
Are these skills available?
Building with AI is new for professionals everywhere, in Amsterdam as much as in Lagos. Tunga's professionals use the same tools as their peers elsewhere. Some examples from their public profiles on tunga.io:
- Ronnie (Kampala, Uganda) built an autonomous coding agent that takes tasks from Slack and opens pull requests across more than 10 microservices.
- Henok (Addis Ababa, Ethiopia) builds Python pipelines on Azure that use OpenAI for document parsing, with tests and CI/CD as the check on the output.
- Toluwani (Ibadan, Nigeria) ships client projects with Claude Code as his main development tool, directed through custom skills and project configurations.
What you need on your side
- Someone who knows the process and can say what should change and whether the result is good.
- Access to the systems and data the processes need, under your own rules.
- Time from the people involved, a few hours in the first weeks to explain how the work is done now, and later to learn the new way of working.
When it doesn't work
- Nobody can say which process should change, or judge whether the result is good. An AI operator can build and run, but cannot decide what is worth doing.
- One fully specified tool with no follow-up. An agency or freelancer usually fits better.
Where Tunga fits
Tunga takes the staffing side off the plate of companies that need digital professionals: software engineers, AI operators, product managers and other digital roles, from across Africa. The client directs the work. Tunga handles finding and vetting, contracts, payments and compliance, onboarding, keeping people, and replacing them when someone leaves or it isn't working. The professionals are independent freelancers contracted by Tunga and work remotely from their own country; the client has one contract, with Tunga, and a delivery manager who checks in with both sides. In 2025, about 1 in 56 placements ended because the professional left for another job. Founded in 2015; 3,500 professionals across 38 African countries and 300+ client companies, as of September 2026.
Tunga is not the right fit when the role has to be on site, when the work means talking to your clients in a language other than English or French, or when saving on cost is the main reason you're looking.
Need capacity now?
Tell us what you're looking for. We'll get back to you within one working day.
Tell us what you need