Do You Need to Reorganise Before AI Pays Off?
Not first. Reorganising around AI does matter, but it costs before it pays, and the biggest risk early on is breaking what already works. In US manufacturing, adopting AI first lowered productivity, and in older plants roughly half of that loss came from dropping management practices that had been working. If you haven't reorganised anything yet, you are where most companies are: in a US Census survey of more than 117,000 firms, about 2 in 3 companies using AI had changed nothing to use it.
So start with your people, and with your own work or one process nobody else builds on, and reorganise once you know from your own work what AI takes off your plate. Tunga staffs digital professionals from across Africa who are tested on working with AI tools, including AI operators, who build and run one such process with AI doing part of the work.
What the research shows
The dominant view among economists is the productivity J-curve: rebuilding processes, structures and skills around a technology like AI first lowers productivity, and only later lifts it above where it started (Brynjolfsson, Rock and Syverson, 2021). Newer studies show what the early part looks like.
- Reorganising costs first, and can break what worked. In US manufacturing, adopting AI first lowered productivity, and the plants that came through the dip grew faster afterwards. In older plants, roughly half of the loss came from dropping structured management practices that had been working (McElheran, Brynjolfsson and colleagues, preliminary paper on US Census data for 2017 and 2021, December 2025).
- Most companies haven't changed anything yet. In a US Census survey of more than 117,000 firms (November 2025 to February 2026), about 2 in 3 companies using AI had changed nothing to use it. About 15% had developed new workflows, and about 15% had trained their staff.
- Over the same years, firms that also invested in training and in software and data got more out of AI. A European Investment Bank study followed about 12,000 EU and 800 US firms a year from 2019 to 2024, and of all types of investment, training went with the largest extra gain from AI (EIB Working Paper 2026/02, Aldasoro, Gambacorta and colleagues, also published by the BIS). For reorganising the study cannot tell: it compares spending and results over the same years, so a payoff that takes longer cannot show up in it. The categories also cover all training and all reorganising, not only what was done for AI.
- Training moves use. In Denmark, 93% of workers had used AI chatbots at work where their employer encouraged it, provided the tools and trained them, against about 41% where the employer did nothing (Humlum and Vestergaard, 2026).
Where to start instead
- Work where nothing else depends on the outcome. Your own work, or one process that no other team builds on. You see quickly whether AI takes work off the plate, and if it doesn't, nothing breaks.
- People before structures. Training, tools and the time to use them are what move use, and they don't require changing who reports to whom.
- Reorganise once you know what AI takes off your plate. By then you know from your own work what you are reorganising around.
Tunga's founder tried every AI improvement he was involved in on his own work first, starting with his inbox. How that went is in the blog Should you reorganise your company for AI?
How Tunga adds the skill without a reorganisation
- Adding a person is not a reorganisation. Every professional Tunga proposes is tested on working with AI tools before reaching a shortlist, and joins your team as it is, under your direction (see how Tunga selects professionals).
- One process, run by someone whose job it is. An AI operator, also part-time, can take on one process that nothing else depends on, such as handling incoming requests, preparing quotes or processing documents, with AI doing part of the work. They build and maintain it, and show colleagues how to use it, so the knowledge stays in your company (see no time or know-how in your team for AI).
What changes in your organisation, and when, stays your decision.
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 contractors or employed in their own country through an employer of record, 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.
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