Artificial intelligence (AI) is transforming the workplace in myriad ways, from acting as a digital assistant and automating repetitive workflows to shifting employee focus towards higher-value tasks. It powers e-learning too, drafting training outlines, generating knowledge checks and summarising regulations.
The pace at which AI can carry out tasks would have seemed impossible just a few years ago. However, speed doesn’t equate to security and reliability.
Support artificial intelligence with technical and operational controls, including SSO for approved AI platforms, user access logs and retention policies.
When it comes to compliance teams, the stakes are unusually high. Training content influences regulatory outcomes, audit evidence, employee behaviour and organisational culture. For example, an inaccurate explanation of anti-money laundering (AML) obligations, a misleading conduct scenario, or an AI-generated policy summary that omits a critical legal requirement can lead to breaches and fines.
Indeed, we’re aware that some businesses using AI-led compliance solutions have found they don’t always deliver the expected accuracy, consistency or governance assurance.
That doesn’t mean artificial intelligence has no place in the workplace or compliance training. Rather, the key is reliable, governed and secure AI use.
Below, this guide explains how to develop practical controls for AI use in the workplace, with a focus on compliance training.
Why does AI reliability matter in compliance training?Because an AI mistake can result in:
Reliability has two dimensions that should be addressed together:
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When incorporating artificial intelligence into the workplace, the first step is to distinguish low-risk support activities and high-risk compliance ones.
The following are generally permitted within an approved AI environment:
The common feature? AI is assisting human work, not making decisions or independently creating content.
The following typically require specialist review or remain prohibited:
Uploading confidential contracts/files or internal audit reports to public AI tools.
Useful AI in the workplace ruleIf the output in question could reasonably be relied upon as official guidance, artificial intelligence shouldn’t be the sole author or decision-maker. |
One of the biggest risks in workplace adoption of artificial intelligence is employees entering sensitive information into public AI services. With that in mind, we highlight some pointers below.
Companies should prohibit inputting the following:
To help you decide, refer to the following table:
| Classification | Examples | Public AI allowed? |
| Public | Published policies, marketing content, public regulations | Yes |
| Internal | Routine operational procedures, non-sensitive communications | Only in approved enterprise AI tools |
| Confidential | Customer data, financial records, employee files | No |
| Restricted | Legal privilege, investigations, security information | Strictly prohibited |
Alongside the above, train your employees to classify data before opening an AI tool, not afterwards.
AI governance fails when responsibility is unclear, so put a system in place.
| Activity | Approver |
| Use of approved enterprise AI tool for routine drafting | Line manager |
| New AI tool procurement | IT and information security |
| AI use involving personal data | Data protection officer / Privacy team |
| AI-generated compliance training content | Compliance and learning & development (L&D) |
| AI use affecting regulated processes | Compliance, legal and risk |
Occasionally, you may need or want to justify an exception. In which case, document a record, including:
Mitigating controls applied
This creates an audit trail and prevents informal workarounds from becoming permanent practice.
Alongside approval rules, policies should specify what staff must do, not just what to avoid.
Employees should:
Given employees should treat all artificial intelligence-generated output as unverified draft material, they must:
Staff should know how to report the following:
Make this information as visible as procedures on topics such as information security or whistleblowing.
Below, we outline sample rules for acceptable use, prohibited inputs and escalation paths for privacy incidents.
Employees can use approved AI tools to assist with drafting, summarising, formatting, translation and administrative support activities. However, they must ensure confidential, personal or legally privileged info isn’t entered.
Employees must not enter customer personal data, employee records, confidential commercial information, legal advice, investigation materials, security credentials, or any information that’s classified or restricted, into public or unapproved AI tools.
AI-generated outputs must be reviewed and approved by a suitably qualified employee before being relied upon for compliance, legal, regulatory or customer-facing reasons.
Report suspected exposure of personal or confidential information via an AI tool immediately to the Information Security team and your data protection officer.
Practical situations are more effective than abstract rules, so we’ve created a few examples.
A support employee wants to paste a complaint containing the customer's name, account number and transaction history into a public AI chatbot to obtain a summary.
Correct response: Prohibited. The information contains personal and financial data and should not be entered.
A compliance manager asks a permitted enterprise AI assistant to rewrite an already approved policy announcement in plain language.
Correct response: Permitted, provided the source policy is approved, and no additional confidential information is introduced.
A learning designer uses artificial intelligence to build a complete anti-money laundering training module and publishes it to employees without compliance review.
Correct response: Not permitted. Compliance subject matter experts (SMEs) must validate the accuracy, completeness, jurisdictional relevance and regulatory precision of the content before release.
A manager uploads a confidential internal audit report to an external AI summarisation tool to prepare a board presentation.
Correct response: Prohibited unless the tool is specifically approved for confidential data processing and the appropriate security and privacy controls are in place.
Our guidance is only credible when supported by the following technical and operational controls.
Firms should implement:
You should maintain logs of the following:
Doing this helps identify unusual usage patterns, such as bulk copying of internal documents into AI systems.
Companies should define:
Additionally, establish how retention aligns with the General Data Protection Regulation (GDPR) and organisational record management policies.
If you use an enterprise AI provider, assess data residency, encryption standards, model training practices, subprocessors, breach notification obligations, and independent security certifications.
A common mistake? Publishing a 20-page artificial intelligence policy and assuming employees will read it. Instead, effective AI compliance training should be short, bite-sized, role-based and reinforced regularly.
Examples of permitted and prohibited prompts
Quick classification exercises
Managers should receive additional guidance on:
| Audience | Frequency |
| All employees | Annually |
| High-risk functions (compliance, HR, finance, customer operations…) | Every six months |
| Managers | Annually plus significant policy changes |
| New joiners | During onboarding |
Microlearning reminders, short videos, scenario-based quizzes and fast-track pre-course assessment solutions are often more effective than repeating the same full e-learning course every year.
Now we’ve established a way to carry out your AI compliance training, what about using AI to develop the learning content itself? The recent surge in this area has encouraged some businesses to build modules internally at a lower cost than outsourcing.
However, at Skillcast, we’ve noticed something: some firms that initially chose AI-led content generation have returned to more structured, expert-led approaches.
Why?
They experienced issues with quality, relevance, or regulatory confidence – or a combination.
In practice, reliable compliance training requires much more than content creation, such as:
AI can accelerate parts of the workflow, but it doesn’t remove the need for human-led governance, expertise and quality assurance.
That’s why many early adopters have encountered difficulties. Automatically generated modules may appear impressive, but companies often discover problems with inconsistent terminology, outdated regulatory references, superficial scenario design, or insufficient audit defensibility.
Using AI for compliance training: a more sustainable approachInstead of relying on artificial intelligence, consider AI-assisted, expert-governed compliance training that:
Skillcast's approach combines technology-enabled delivery with compliance expertise, structured governance, robust reporting and secure learning management controls. This helps you benefit from innovation without compromising reliability, auditability or regulatory confidence. Ultimately, AI can support the work it takes to build a compliance training programme – it cannot replace it. |
Before allowing AI to assist with compliance training programmes, ask the following.
Has the information been classified?
Has the appropriate manager or control function approved the activity?
Are exceptions documented?
Will a qualified human review the output?
Are authoritative sources available for validation?
Has IT and security approved the AI tool?
Are access, logging, retention and monitoring controls in place?
If any answer is no to any of the above, pause the activity until the risk is investigated and resolved.
AI is likely to become a permanent feature of workplace learning and compliance operations. The question is no longer whether to use artificial intelligence, but how to safely and reliably leverage it. For compliance training, it depends on five principles:
Treating AI as an uncontrolled content generator risks inaccurate training, privacy issues and regulatory uncertainty. But using the technology as a governed assistant within a secure framework can improve efficiency while maintaining the trust, integrity and auditability effective compliance training demands.
For information about the services Skillcast offers, contact us or request a demo.
Encourage transparency, so managers, reviewers and colleagues know when AI has contributed to a document, analysis or communication.
Yes, because artificial intelligence tools can produce insecure code, misleading links or inaccurate technical instructions, so outputs should be reviewed before use.
Yes, it can help identify potential areas for revision or create draft updates, but SMEs should confirm, particularly across aspects such as regulatory references.
Our Essentials Library contains e-learning content designed to help organisations meet fundamental compliance requirements. If you’re looking for focused training, browse our courses, where we offer a complete solution for your compliance programme. Our artificial intelligence topics include:
Our e-learning courses are designed to engage employees, including our microlearning library, which was created to support knowledge retention.
Our Compliance Portal also features a range of tools to digitise and automate your compliance learning. These include our:
If you’d like to access leading insights and compliance tips, you can browse our free resources by topic to find guides, modules, compliance bites and more.
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