Artificial intelligence / 13 September 2026
A practical path to AI adoption for Zambian organisations
A grounded guide to choosing, testing, and governing useful AI in a Zambian organisation without starting with an oversized technology programme.
01
Begin with a real task
Artificial intelligence is most useful when it improves a specific part of work. A first use case might help staff search approved documents, prepare a draft from structured information, classify incoming requests, or summarise routine reports. Start by describing the task, the person responsible for it, the information it uses, and the decision that follows. That gives the organisation something concrete to evaluate.
Avoid choosing a tool before the problem is clear. A fashionable product can create more steps, move sensitive information into an unsuitable service, or produce output that nobody is accountable for checking. A useful candidate has a measurable burden today, enough good information to work from, and a person who can judge whether the output is correct. Keep the first scope narrow enough to stop or revise quickly.
02
Set responsibility before the pilot
Zambia's National Artificial Intelligence Strategy places ethical use, privacy, fairness, skills, infrastructure, and governance alongside innovation. For an organisation, that translates into a short operating rule before a pilot begins: who owns the use case, what information may be entered, which outputs require human approval, how errors are reported, and when the tool must not be used. These decisions belong to management and the people who understand the work, not only the IT team.
Treat personal, financial, health, employment, customer, and confidential business information with particular care. Check where a service processes and stores data, how long it keeps prompts and files, whether the provider uses them for model training, and what access controls are available. Existing contracts, sector rules, and Zambia's data protection requirements still apply when an AI feature is involved. Obtain appropriate legal or compliance advice for a regulated use case.
03
Test usefulness, accuracy, and failure
Build a small evaluation set from representative tasks. Include straightforward examples, unusual cases, incomplete inputs, and cases where the correct response is to ask for more information. A subject specialist should compare the AI-assisted result with the organisation's accepted standard. Record errors and the time needed to review them. A faster first draft is not a saving if staff must reconstruct the answer or cannot explain its source.
The pilot should also test how failure is handled. Users need an obvious way to correct an output, return to the normal process, and report a recurring problem. When an answer depends on organisational material, the interface should identify the source where possible. For higher-impact decisions, keep a meaningful human review step and an audit trail. The goal is dependable assistance within a defined boundary, rather than automation for its own sake.
04
Prepare the people and the information
AI readiness often depends on work that is valuable even without AI. Current policies need clear owners. Documents need consistent names, permissions, and retention rules. Customer and operational records need agreed definitions. Staff need examples of acceptable use and a channel for questions. These foundations reduce the chance that a tool confidently repeats outdated, duplicated, or unauthorised information.
Training should match each role. A user needs to know how to frame a request, verify a result, protect information, and recognise common limitations. A manager needs to understand risk, cost, provider terms, and how performance will be reviewed. Technical staff need to manage access, integration, logging, and changes to the service. Short practice sessions around the selected use case are more useful than generic demonstrations.
05
Scale only after evidence
At the end of the pilot, compare the result with the original workflow. Look at quality, turnaround time, staff effort, user confidence, exceptions, operating cost, and any new risks. Decide whether to expand, change the approach, or stop. Keep the evidence and the decision together so that a later review can see why the organisation adopted the tool and what conditions were attached.
A sensible AI programme can begin with one useful workflow and a small group of accountable people. That approach aligns innovation with the governance and continuous learning emphasised in Zambia's strategy. It also gives leadership a clearer view of value before committing more data, budget, or critical operations. The best next use case should earn its place through the same disciplined process.
Sources
Official references
This ONBRD editorial article draws on the following primary sources. The practical recommendations are ONBRD's interpretation for organisational planning.