AI in Accounting & Finance : Governance, Risk and Compliance

Introduction and AI Opportunity in Accounting 

• Welcome, session objectives, and current state of AI adoption in the profession (drawing on 2026 ICAEW insights into trends, skills focus, and productivity potential).
• Overview of how AI drives innovation: automating data processing, reporting, audit support, tax compliance checks, and client insights.
• Balancing excitement with responsibility: key risks (bias, hallucinations, confidentiality breaches) and the need for professional judgment.

Due Diligence on AI Suppliers and Tools

• Critical questions to ask vendors: data handling/security, transparency of models, output reliability, compliance certifications, and alignment with ethical/professional standards.
• Evaluating enterprise vs. public tools: protecting client confidentiality (e.g., never inputting real data into non-secure platforms).
• Practical checklists and red flags, informed by ICAEW best practices and ICO expectations on accountability.

Regulatory Requirements and Guidance

• ICAEW expectations: ethical principles (integrity, objectivity, competence, confidentiality), PCRT guidance for AI in tax, and professional conduct updates.
• ICO priorities: data protection compliance, fairness/transparency in AI, and accountability obligations.
• EU AI Act overview and implications for accountants/SMEs: risk classifications (e.g., high-risk in credit/risk assessments), deployer obligations, transparency rules, and support measures like sandboxes/guidelines (phased application relevant in 2026).

Developing Organisational AI Guidelines

• Essential elements to include: acceptable use policies, oversight roles, documentation requirements, ethical frameworks, and integration with existing governance (e.g., risk registers, CPD).
• Tailoring for accounting contexts: client data protection, output review protocols, and human-in-the-loop for high-stakes work.
• Examples from ICAEW resources and real-world firm approaches to ensure responsible adoption.

AI DPIAs: When, Why, and How

• Triggers for conducting an AI-specific Data Protection Impact Assessment (DPIA): innovative/novel AI use, high-risk processing, or per ICO lists (often applicable to AI in professional services).
• Key contents: risk identification (bias, accuracy, rights impacts), mitigation strategies, stakeholder consultation, and ongoing monitoring.
• Practical templates and steps aligned with ICO guidance and 2026 updates on agentic AI.

AI Interactions with Emerging Technologies

• How AI complements blockchain (e.g., enhanced traceability, smart contract auditing, trustworthy ledgers in finance).
• Quantum computing horizons: potential disruptions to encryption/complex modeling and early preparation strategies.
• Strategic considerations for accountants: where synergies create value and where risks amplify.

Strengths and Limits of Machine Learning 

• Core strengths: pattern recognition, predictive analytics, efficiency in large datasets.
• Practical limits: lack of true understanding, potential for errors/bias/hallucinations, dependency on training data quality.
• Best practices for mitigation: always verify outputs, maintain professional skepticism, and use AI as an "auxiliary brain" (per ICAEW 2026 skills advice).

Interactive Scenarios, Wrap-Up, and Q&A 

• Real-world case studies/hypotheticals: applying AI in tax advisory, audit sampling, client reporting, or practice management while addressing risks.
• Group discussion: sharing firm experiences, overcoming barriers, and planning next steps.
• Key takeaways, resources (ICAEW GenAI Accelerator, ICO tools), and actionable roadmap for implementation.
• Open Q&A on 2026-specific challenges (e.g., evolving guidance, agentic AI implications).

This schedule ensures a balanced, progressive structure: building knowledge from evaluation to governance, then tools and foresight, with strong interactive elements to reinforce learning. The content remains UK/accountant-centric, assuming basic digital familiarity while delivering immediate, implementable strategies amid 2026's rapid AI developments in the profession.

Redcliffe's course trainer has been advising clients on Data Protection for over a decade and founded Digital Law in 2014 to provide legal & compliance advice to organisations about their activities in the Digital arena. Digital Law has clients across the UK, Europe, Middle East, North Africa, Asia and the United States rand advises on Data Protection, GDPR, & Cyber Security compliance along with e-commerce, website compliance, software licensing, AI, blockchain, privacy and Freedom of Information Act matters. He has advised clients in the creative, digital and retail sectors as well as working with clients in the banking, insurance and financial services who are engaged in the supply of goods and services using digital technology.

He is co-author of the Cyber Security Toolkit for the Law Society of England and Wales, a practical compliance guide for law firms, and is co-author of a GDPR practical compliance manual for law firms. He regularly speaks at Conferences and presents Webinars and Podcasts for different organisations. A regular speaker at Conferences around the world, he has spoken at LegalTechTalk, the Nordic Privacy Arena,  the European Legal Security Forum, the Lawyer2050 Conference in Tunisia, Legal Geek and the British Legal Technology Forum. He also produces the regular Digital Law Podcast. 

The trainer is a member of the Expert Advisory Board for the Security, Privacy, Identity, Trust and Engagement Network +  (“SPRITE+”) and is a past Chair of the GDPR Working Group of the Law Society of England and Wales.  He is also a past chair of the Law Society’s Technology and Law Committee.

• Due diligence – questions to ask of an AI supplier
• Regulatory requirements – what do the ICAEW, FRC and the ICO look for?
• The application and reach of the EU AI Act
• What should be included in your organisation's AI guidelines?
• When to carry out an AI DPIA and what should it contain?
• AI and how it will interact with other technologies including blockchain and quantum computing
• The strengths and limits of machine learning

• Strong, integrated regulatory and compliance focus tailored to UK accountants' obligations
  • The course dedicates significant time to navigating ICAEW expectations (ethical principles, PCRT January 2026 topical guidance on AI in tax work, professional competence/confidentiality), ICO data protection requirements (fairness, accountability, and AI-specific DPIAs for processing personal data in accounting contexts), and the EU AI Act's practical implications (risk classifications, deployer duties, transparency rules, and SME-friendly measures like sandboxes/simplified obligations, especially relevant for cross-border clients or EU outputs from August 2026 onward).
  • It provides combined, actionable clarity on the full UK/EU regulatory triad—helping participants avoid ethical breaches, ICO scrutiny, or non-compliance risks amid 2026's evolving landscape (e.g., HMRC transparency expectations for AI in tax software).

• Practical governance and risk-management toolkit emphasis
  • It goes beyond hype or basic tool demos by prioritising due diligence on AI suppliers (critical questions on transparency, security, reliability), developing organisational AI guidelines (acceptable use, oversight, human-in-the-loop protocols), and knowing when/how to conduct AI DPIAs (triggers, contents, mitigation). This "governance-first" approach equips practice leaders, compliance roles, and tax specialists to build firm-wide policies - addressing a common gap where professionals experiment with AI but lack structured controls, especially post-PCRT updates and ICO guidance on agentic AI.

• Forward-looking technology intersections
  • Unique coverage of AI's interactions with blockchain (e.g., traceability in ledgers, audit enhancement) and quantum computing (emerging risks to encryption/complex modelling), providing strategic foresight rather than generative AI prompting, automation in reporting/audit, or ethical basics

• Balanced view on machine learning's realities
  • Explicit exploration of strengths (pattern recognition, efficiency) alongside practical limits (no true understanding, bias/hallucination risks, data quality dependencies), reinforcing the need for professional scepticism and human judgment—aligning closely with ICAEW warnings on over-reliance while enabling confident, verified use.

• A focused, live/discussion-oriented session delivers targeted, implementable takeaways - checklists, templates, scenarios - for those moving from experimentation to governed, day-to-day deployment without overwhelming time commitment.

• Unmatched depth in UK/EU regulatory intersection for regulated professions
  • The trainer's insider perspective (from Law Society leadership, direct advisory work with regulated sectors like accounting, and clients in finance/professional services) provides authoritative, nuanced guidance on how ICAEW ethical principles (integrity, competence, confidentiality via PCRT January 2026 AI-in-tax updates), ICO data protection/AI accountability (DPIAs, fairness in processing), and EU AI Act deployer obligations (high-risk classifications, transparency, SME sandboxes from August 2026) apply specifically to accountants' day-to-day AI use. 

• Proven expertise in governance and risk for professional firms
  • As someone who advises law and accounting practices on AI supplier due diligence, organisational guidelines, cyber/AI compliance, and avoiding pitfalls (e.g., hallucinations, bias, confidentiality breaches in client data), the course's emphasis on practical tools - due diligence checklists, AI policy essentials, DPIA triggers/contents - carries real authority. The trainers work (including publications, podcasts, and seminars on AI's "make or break" impact for firms) ensures the content addresses real-world enforcement risks and professional conduct expectations in a way that's grounded and actionable.

• A cross-technology and forward-thinking lens from a digital law specialist

 

For Whom This Course Is an Absolute Must:

In the current 2026 landscape - with ICAEW highlighting AI as a core skills focus for the year, HMRC setting transparency expectations for AI in tax software, ICO reinforcing DPIA/accountability requirements for AI processing personal data, and the EU AI Act's high-risk/deployer obligations applying from August 2026 (relevant for cross-border clients or EU outputs) - attendance is essential for:

• Accountants or firms already using or piloting generative AI/agentic tools (e.g., for drafting reports, analysing datasets, automating compliance, or client insights), where failing to conduct proper due diligence, develop guidelines, or perform DPIAs risks ethical breaches, regulatory scrutiny, or professional liability.

• Professionals in practices advising SMEs or EU-connected clients on AI adoption, as the EU AI Act (with SME support measures like simplified obligations and sandboxes) imposes deployer duties, transparency rules, and potential high-risk classifications in finance-related applications (e.g., credit assessments or automated decisions).

• Those responsible for firm-wide governance of AI—such as creating organisational guidelines, managing supplier risks, or ensuring human oversight—particularly if their practice has not yet formalized policies amid ICAEW's calls for enhanced competence and ethical safeguards.

• Tax practitioners handling AI-assisted work, given the January 2026 PCRT guidance explicitly linking AI use to fundamental principles and warnings from cases where AI outputs led to errors or criticism.

• Accountants seeking to close personal/professional skills gaps in a year where ICAEW predicts wider-scale adoption but stresses overcoming AI shortcomings (e.g., lack of true understanding) through verified, human-led application—non-attendance could leave individuals or firms lagging in compliance and competitivenes

This session is highly relevant for:

• Chartered accountants (ACA/ICAS/ACCA members) in practice, whether in small/medium firms, mid-tier practices, or larger firms, who handle day-to-day tasks involving data analysis, automation, or client deliverables where AI can enhance efficiency.

• In-house finance professionals and accountants in corporate, commercial, or advisory roles evaluating or deploying AI for internal processes (e.g., financial forecasting, compliance checks, or risk assessment).

• Tax specialists and advisors navigating AI's application in tax work, where recent PCRT guidance (updated January 2026) requires applying fundamental ethical principles to AI tools to avoid risks like inaccurate outputs or breaches of professional conduct.

• Practice leaders, partners, and compliance/responsible persons (e.g., those overseeing firm policies, risk registers, or CPD) responsible for governing AI use, supplier due diligence, and alignment with ICAEW/ICO expectations.

• Audit and assurance practitioners interested in AI's role in sampling, anomaly detection, or reporting, especially in light of FRC guidance on AI in audit and the profession's shift toward agentic AI beyond experimentation.

The content assumes basic familiarity with digital tools and focuses on actionable, UK-centric strategies amid 2026 trends: widespread experimentation moving to governed deployment, skills gaps in AI literacy, and pressure to upskill while addressing limitations like bias, hallucinations, and over-reliance.

 

This course is a concise and actionable - crafted for UK accountants and finance professionals eager to leverage artificial intelligence for enhanced productivity and client service delivery, while ensuring full compliance with ethical standards, data protection rules, and emerging regulations as of February 2026.
This practical session explores best practices for responsibly identifying, evaluating, and implementing AI systems in accounting workflows, from routine automation and data analysis to advanced advisory support. It addresses the profession's rapid shift toward governed AI adoption in 2026, as highlighted by ICAEW's focus on skills development, overcoming AI limitations (such as hallucinations and bias), and ethical integration; the January 2026 PCRT topical guidance on applying fundamental principles to AI in tax work; HMRC expectations for transparent AI in tax software; ICO guidance on AI and data protection (including fairness, accountability, and DPIA requirements for high-risk or innovative processing); and the EU AI Act's phased obligations (with high-risk deployer duties effective from August 2026, plus SME-friendly measures like simplified procedures and innovation support).

Participants will leave with clear, implementable strategies to:

• Perform effective due diligence on AI suppliers, asking the right questions about transparency, security, model reliability, and professional alignment.
• Meet regulatory requirements from ICAEW (ethical principles, competence, and PCRT application to AI in tax), ICO (data protection compliance and accountability), and the EU AI Act (risk classifications and deployer obligations relevant to accountants/SMEs).
• Develop robust organisational AI guidelines covering acceptable use, oversight, documentation, human review, and integration with firm policies.
• Determine triggers for and structure AI-specific DPIAs, including risk identification, mitigation, and ongoing monitoring per ICO expectations.
• Understand AI's synergies and interactions with technologies like blockchain (for traceability and audit enhancement) and quantum computing (future computational impacts).
• Appreciate machine learning's strengths (e.g., pattern detection, efficiency) and limits (e.g., no true comprehension, error risks), enabling accountants to use AI as a reliable "auxiliary brain" while preserving professional judgment.

Delivered interactively with real-world examples, checklists, and discussion opportunities, this course provides the regulatory certainty and risk management toolkit needed to adopt AI confidently and ethically - turning it into a competitive advantage without compromising integrity, confidentiality, or compliance in today's fast-evolving professional landscape. Ideal for those moving beyond experimentation to practical, governed deployment in practice or in-house roles.