Dr Muhamad Hariz Muhamad Adnan (drhariz.com), HRD Corp certified AI trainer and Senior Lecturer at UPSI, delivers AI training for law firms, accounting and audit firms, tax practices and consultancies in Malaysia. The training centres on confidentiality and PDPA-aware use, document drafting and review, research workflows with proper verification, and a written firm AI policy, so professionals gain speed without risking client trust.
Professional services firms sell expertise and judgement, and much of their time goes into reading, drafting, summarising and checking documents. That makes them natural users of Generative AI tools such as ChatGPT, Microsoft Copilot and Google Gemini. It also makes them unusually exposed: a single confidential document pasted into the wrong tool, or an AI-invented citation in a submission, can damage a client relationship and a firm’s reputation. AI training for these firms therefore has to balance productivity with discipline. This guide explains what that training should cover.
Why professional services need a different kind of AI training
General corporate AI workshops often encourage people to “paste your document in and ask for a summary”. In a law or accounting firm, that instruction can breach client confidentiality, engagement terms or data protection obligations. Professional services training starts from the opposite direction: first decide what may be used with which tool, then practise techniques within those rules. It also places heavy emphasis on verification, because AI tools can produce confident, well-written text that is factually wrong, including non-existent cases, provisions or figures.
Confidentiality and PDPA-aware use
Every session begins with data rules. Participants learn to classify information (public, internal, confidential, client-privileged, personal data), which AI tools and account types the firm approves for each class, and how to anonymise or abstract a matter so they can still get help from AI without exposing client details. The Personal Data Protection Act 2010 (PDPA), client engagement terms and each profession’s own confidentiality duties all shape these rules. For the broader governance picture in Malaysia, see AI governance in Malaysia.
Practical use cases covered
Drafting and first drafts
AI is useful for first drafts of routine documents: engagement letters, client update emails, internal memos, meeting summaries, proposal sections and standard clauses. Participants learn to give the tool a clear role, audience, structure and length, and to treat every output as a draft that a qualified professional must review.
Document review and summarisation
Using approved tools, staff practise summarising long documents, extracting key dates, parties and obligations into tables, comparing two versions of a document, and producing issue lists. Training shows how to ask the AI to quote the exact passage it relied on, which makes checking far faster.
Research workflows
AI can help structure research questions, suggest search terms and summarise material that the professional has already found. It should not be trusted as a source of law, standards or figures on its own. Training covers a verification routine: every case, provision, standard or number must be checked against the primary source before it appears in client work.
Spreadsheets and financial analysis
For accounting, audit and advisory teams, AI assistants in Excel and Google Sheets can explain formulas, build reconciliations, flag anomalies and draft commentary on variances. Participants learn to validate results and document how AI was used in working papers where the firm requires it.
Client communication and marketing
AI can help turn technical updates into clear client alerts, articles and social posts, in Bahasa Melayu or English, while partners keep final approval.
Building a firm AI policy
A short, written AI policy is one of the most valuable outcomes of the partners’ session. It usually covers approved tools and accounts, data classes that may never be entered, mandatory human review, verification of citations and figures, disclosure to clients where appropriate, record-keeping, and who to ask when unsure. The policy then becomes the basis for onboarding new staff.
Suggested programme
| Session | Audience | Focus |
|---|---|---|
| Partners and managers briefing | Partners, principals, practice heads | Risks, opportunities, firm AI policy |
| Foundations workshop | Associates, executives, support staff | Prompting, data rules, verification routine |
| Practice-specific workshop | Legal, audit, tax or advisory teams | Drafting, review and analysis on sanitised firm examples |
| Follow-up clinic | All participants | Questions from real use after two to four weeks |
How this differs from AI training for banks and financial institutions
Banks and insurers operate under specific regulatory expectations and usually have in-house risk, compliance and technology teams driving AI adoption. Professional services firms are typically smaller, partner-led and client-matter based, so training focuses on individual practitioners’ daily work and a practical firm policy. Financial institutions should read AI training for banks and financial services in Malaysia.
HRD Corp claimable
Law firms, accounting firms and consultancies registered with HRD Corp can claim approved AI training against their levy, provided the grant is approved before the training. See HRD Corp Claimable AI Training Courses in Malaysia.
About the trainer
Dr Muhamad Hariz Bin Muhamad Adnan is a Doctor in Artificial Intelligence, Senior Lecturer at the Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris (UPSI), and an HRD Corp certified AI trainer focused on AI-driven digital transformation in the workplace and in education. He delivers corporate AI training in Malaysia on-site or live online, in Bahasa Melayu, English or bilingually. Professional schools and faculties can also see AI for education in Malaysia. To plan a session for your firm, contact Dr Hariz.
Frequently asked questions
It can be, if the firm decides which tools and accounts are approved, never enters confidential or personal client data into unapproved tools, and requires a qualified professional to review and verify every AI output.
Data classification and PDPA-aware use, drafting and document review techniques, a verification routine for citations and figures, spreadsheet analysis, client communication, and a written firm AI policy.
AI can help frame questions and summarise material already found, but it can invent cases, provisions or numbers. Every reference must be checked against the primary source before it is used in client work.
Yes, for firms registered with HRD Corp, as long as the grant is approved before the training starts.
Yes, using sanitised or anonymised versions agreed with the firm in advance, so exercises reflect real work without exposing client information.
