Why Ghana’s AI Skills Push Needs a “Transfer Test” Before Training Counts as a Success

Ghana has no shortage of reasons to invest in AI skills. At the Ghana Chamber of Mines human-resource conference in Accra today, industry leaders described a mining future that will become more automated, remote and intelligent. Chamber CEO Kenneth Ashigbey stressed that success will depend on people with the skills and capacity to manage and improve the technology, while Telecel Ghana CEO Patricia Obo-Nai urged employers to treat continuous digital-skills development as essential.

That is the right direction. But training can still fail even when employees finish the course, understand the software and feel confident using it.

The missing question is whether the skill transfers into everyday work.

A company can put 100 employees through AI training and still discover three months later that only a handful have changed how work gets done. Some employees return to familiar habits. Others use the tools for low-value tasks. A few become internal experts, but the workflows they build depend so heavily on their personal knowledge that nobody else can operate them.

That is why employers should add a transfer test before they count an AI training programme as successful.

For 30 days after training, each participant or team should apply the new capability to one real workflow. It might involve preparing a report, reviewing maintenance information, analysing customer requests, drafting a proposal, organizing field data or handling a recurring administrative task. The goal should be specific enough that managers can compare the old process with the new one.

Then test four things.

First, did the workflow produce a measurable improvement? Faster output alone is weak evidence if employees spend the saved time checking, correcting or reopening the work. The relevant measure is the business result after verification and repair are counted.

Second, can the employee explain where AI should stop? A future-ready worker needs more than prompting skill. The employee should know when missing data, unusual circumstances, financial consequences, safety concerns or contradictory information require human judgment.

Third, can another person reproduce the workflow? This is the most overlooked part of AI adoption. If the process works only because one enthusiastic employee remembers the right prompt, knows where the source files live and understands a collection of undocumented exceptions, the organization has created a dependency rather than a capability.

The original user should teach the workflow to a colleague who did not build it. If that second person can reproduce the outcome, handle common exceptions and explain the escalation rules without constant coaching, the skill has begun to transfer.

Fourth, does the workflow survive after the excitement of training fades? Repeat the test several weeks later. Sustainable adoption should become part of ordinary work rather than a demonstration employees perform immediately after a workshop.

This matters because Ghana is already investing in skills at scale. The Youth Employment Agency recently reported training more than 3,000 young people, with digital tracks that include coding and robotics, artificial intelligence and drone assembly. The agency also emphasized monitoring whether beneficiaries actually use what they learned.

That same principle should guide employer-led AI training.

Accra Street Journal has recently argued that digital literacy has become a core workforce and business skill. The next step is to measure that literacy through evidence of changed work.

A transfer test also improves training itself. When managers see where employees repeatedly struggle, they can revise the learning programme around real exceptions. When a workflow depends on undocumented tricks, they can fix the documentation. When a tool produces impressive demos but weak business outcomes, they can stop spending time on it.

Ghana needs more AI capability, especially as industries such as mining become more automated. But course completion should be the beginning of measurement rather than the end.

The organizations that benefit most from AI will be the ones that can prove a worker learned the skill, applied it to a real problem, understood its limits, and transferred the process to someone else. That is how training becomes organizational capacity instead of a certificate.

———————————————-

Gleb Tsipursky, PhD, a behavioral scientist, CEO of Disaster Avoidance Experts, and author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026). https://disasteravoidanceexperts.com/aibook

Last Updated on October 3, 2026 by Samuel Kwame Boadu

Samuel Kwame Boadu

Samuel Kwame Boadu is a Ghanaian media entrepreneur and storyteller with a passion for amplifying urban voices and uncovering everyday truths. He is the Editor-in-Chief and Founder of Accra Street Journal, a dynamic digital platform dedicated to capturing the pulse of Ghana’s capital—its people, culture, challenges, business, sports and innovations.

accrastreetjournal.com/