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AI can produce a confident, polished answer in seconds. But before you act on it or put your name to it, you need to know whether you can trust it.
In this course, you’ll learn to spot inaccurate information, invented details, missing context and overconfident claims in AI-generated content. You’ll build a practical process for checking facts, tracing citations to their original sources and deciding how much verification is needed based on the potential risk.
You’ll also learn to use AI to support goal-setting, prioritisation and decision-making—while keeping judgement and accountability firmly with you. You’ll finish with an AI Risk and Verification Plan and an AI-Supported Planning and Prioritisation Analysis based on your own work.
This TSIBA course is delivered in partnership with Alwin Education Ltd. Alwin Education is a UK based digitally native network of locally accredited higher-education institutions that focus on expanding access, strengthening quality, and aligning every programme to labour-market demand. This course is aimed at giving working professionals a practical, career-focused learning experience underpinned by rigorous academic standards.
An AI Risk and Verification Plan for a real task, covering checks, safeguards and human accountability, plus an AI-Supported Planning and Prioritisation Analysis showing what comes first and why. Both are yours to keep.
The warning signs that matter — unsupported claims, unverifiable detail, overconfident language, missing context, contradictions, an answer that does not quite address the task — and how to judge whether something is fit for purpose, needs checking, or should not be used as it stands.
How much verification a task actually warrants, and why two tasks carrying similar risk can still need different checks depending on whether the output is the deliverable or only a thinking aid.
Use practical frameworks to set goals, prioritise competing demands and make decisions with incomplete information. Learn to brief AI with the right context while keeping judgement, trade-offs and accountability firmly with you.
Your team is producing content faster, but you remain accountable for its accuracy and quality. You need a reliable way to check AI-generated work before it reaches a client or decision-maker.
Whether you work in finance, compliance, HR, engineering or law, a confident but inaccurate answer carries real consequences. You need a practical verification process—not simply a reminder to “check the output.”
You want to use AI to organise competing deadlines, requests and team needs while keeping the final judgement, trade-offs and accountability in your hands.
Orientation module + 2 modules. Each module runs one week at 2-4 hours.
You start by learning why AI outputs go wrong and how reliability varies by task. You then learn a practical verification routine: checking the original source, following a citation back and confirming it actually supports the claim, cross-checking against independent sources, and testing whether an output fits the original task and context rather than assuming factual accuracy makes it usable. You’ll then match the level of checking and human oversight to the risk and consequences involved.
Output: an AI Risk and Verification Plan for a workplace task.
You work through goal-setting and prioritisation, using the Eisenhower Matrix alongside strategic centering — one clear organisational priority acting as a filter when several important demands compete — and the practical responses available when deadlines conflict: negotiating, escalating, delegating or reframing. You then practise briefing AI with enough real context to be useful, examine its suggestions for missing context and questionable assumptions, and apply decision-making frameworks that treat AI-generated information as an input to a decision rather than the decision itself.
Output: an AI-Supported Planning and Prioritisation Analysis for a real workload.
An AI Risk and Verification Plan and an AI-Supported Planning and Prioritisation Analysis.
| Item | Detail |
|---|---|
| Total course fee | R990 |
| Included | All course materials |
| Group / employer enrolment | Price determined by group size |
Build on the foundations of the two-week course with a deeper, six-week programme. Assess the risks, create a verification plan and develop a complete, evidence-based AI Business Case—ready to support a decision to proceed, revise or stop a real AI application.
This course is launching soon. Leave your details and we'll let you know as soon as it's open for enrolment.
By submitting this form, you consent to TSIBA processing your information in accordance with POPIA and our Privacy Policy.AI is already in your organisation whether or not anyone approved it, and the risk is not the tool. It is that nobody has agreed what gets checked, by whom, or how carefully — so the same scrutiny gets applied to a throwaway internal draft and to something a client will act on, usually by accident. The cost arrives as a single traceable mistake in work that carried somebody’s name.
Talk to Us About CohortsEach participant produces an AI Risk and Verification Plan for a real task — the risks they identified, the checks they chose, the safeguards and review points they would build in, and where they say accountability must stay with a person — plus a prioritisation analysis showing their reasoning.
2 to 4 hours a week, fully online, across two weeks. No travel, no days out of the business, no cover to arrange.
Because the work is done on live tasks rather than case studies, outputs start getting verified properly during the two weeks, not after them.
Anytime - this is a self-paced micro course with no fixed intake dates. Enrol and begin your orientation module whenever suits you.
2-4 hours a week across 2 weeks, plus an orientation module. Fully online.
Yes - cohorts can be enrolled for a team. Group pricing determined by group size.
