Back to Search
AI, Technology & Innovation
AI & Ethics for Accountants: Becoming an Ethical Guardian (Live Webinar)
DELIVERY FORMAT
Online Virtual
SEMINAR TYPE
PD Seminar
NEW SEMINAR
Overview
Artificial intelligence is transforming accounting; automating reconciliations, flagging anomalies, generating forecasts, and processing returns at unprecedented speed; however, this efficiency comes with profound ethical responsibilities that many practitioners don't yet understand.
“AI & Ethics for Accountants: Becoming an Ethical Guardian in an Automated World” equips accountants with practical frameworks for responsible AI use and actionable guardrails for everyday decisions. Professionals will learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, privacy), recognize and mitigate algorithmic bias, protect client confidentiality in an era of data-hungry tools, and maintain professional accountability even when AI does the heavy lifting.
“AI & Ethics for Accountants: Becoming an Ethical Guardian in an Automated World” equips accountants with practical frameworks for responsible AI use and actionable guardrails for everyday decisions. Professionals will learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, privacy), recognize and mitigate algorithmic bias, protect client confidentiality in an era of data-hungry tools, and maintain professional accountability even when AI does the heavy lifting.
Course Description
AI adoption in accounting is accelerating faster than the ethical guardrails needed to use it responsibly.
Organizations and professionals are deploying AI tools without fully understanding the risks to client confidentiality, professional accountability, or regulatory compliance, whether AI arrives through a brand-new tool a firm deliberately adopts, or quietly, as AI features get built into the software and service providers they've already relied on for years.
This exposes firms to reputational, regulatory, and liability risk, plus a competitive risk that cuts both ways: firms that avoid AI altogether risk losing efficiency to competitors who adopt it, while firms that adopt it carelessly risk losing client trust.
This session closes that gap with actionable guidance, helping participants learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, and privacy) and Human in the Loop verification to recognize and mitigate algorithmic bias, protect client confidentiality, and maintain professional accountability even when AI is doing the heavy lifting.
These skills apply directly to daily practice, protecting client interests and using AI to enhance professional judgment so that participants leave with confidence and apply what they learnt to work immediately.
The teaching approach is practical and deliberately low-hype: complex technical concepts are translated into plain language, delivered through case studies and simple analogies, with the session built around what participants can implement quickly.
AI creates both opportunities and risks, and this course treats it accordingly: empowering accountants to engage with it thoughtfully rather than a fear-based approach as their careers evolve, with a vendor-neutral, ethics-first perspective focused on maintaining professional integrity with any AI tool.
Organizations and professionals are deploying AI tools without fully understanding the risks to client confidentiality, professional accountability, or regulatory compliance, whether AI arrives through a brand-new tool a firm deliberately adopts, or quietly, as AI features get built into the software and service providers they've already relied on for years.
This exposes firms to reputational, regulatory, and liability risk, plus a competitive risk that cuts both ways: firms that avoid AI altogether risk losing efficiency to competitors who adopt it, while firms that adopt it carelessly risk losing client trust.
This session closes that gap with actionable guidance, helping participants learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, and privacy) and Human in the Loop verification to recognize and mitigate algorithmic bias, protect client confidentiality, and maintain professional accountability even when AI is doing the heavy lifting.
These skills apply directly to daily practice, protecting client interests and using AI to enhance professional judgment so that participants leave with confidence and apply what they learnt to work immediately.
The teaching approach is practical and deliberately low-hype: complex technical concepts are translated into plain language, delivered through case studies and simple analogies, with the session built around what participants can implement quickly.
AI creates both opportunities and risks, and this course treats it accordingly: empowering accountants to engage with it thoughtfully rather than a fear-based approach as their careers evolve, with a vendor-neutral, ethics-first perspective focused on maintaining professional integrity with any AI tool.
Applicable for
Firm owners and partners, CFOs and finance executives, compliance officers, controllers, senior accountants, operations managers, and risk managers, IT professionals supporting accounting systems and any accounting professional who uses or oversees AI tools.
No technical background required.
No technical background required.
Learning Objectives
- Distinguish AI from generative AI & LLMs and apply the "garbage in, garbage out" principle to evaluate AI-generated outputs.
- Evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, privacy).
- Recognize how algorithmic bias and historical data inequities can produce discriminatory ("predictive injustice") outcomes in AI systems.
- Apply data privacy safeguards to everyday AI tools used in client-facing accounting work.
- Apply practical guardrails, including a quick-start checklist and human-in-the-loop verification, for responsible, professional AI use.
Content
- AI Foundations (non-technical)
- Defining AI vs. Generative AI and LLMs (Large Language Models)
- The "Garbage In, Garbage Out" Principle
- Hallucination and the "Generate and Review" verification paradigm
- Five Pillars of Trustworthy and Responsible AI
- Fairness and bias mitigation, explainability, transparency, robustness and security
- Data privacy and governance; professional codes of conduct and AI integration
- Algorithmic Bias
- Predictive injustice and the lack of diversity in AI development
- Historical inequities in training data
- Data Privacy in Everyday AI Tools
- Recognizing privacy and confidentiality risks when using AI tools in client-facing work
- Practical Guardrails
- The CRAFT prompting framework and specialized prompting for financial tasks
- Human-in-the-loop verification
- Using AI for fraud detection and strategic advisory work
- Top 5 ethical risks in accounting AI
Course Dates & Registration
Improving Your Virtual Learning Experience
Live webinars have varying levels of expected interaction, with some requiring microphone and camera capabilities to support a proper learning experience – please email pdreg@bccpa.ca if you have concerns.
In general, we encourage participants to have their cameras turned on to enhance their virtual learning experience. This practice promotes a stronger connection with the instructor and fellow participants, and fosters improved communication and collaboration.
Live Webinar FAQs can be found here.
Registration terms and conditions, including the cancellation policy can be found here. If you require further assistance, please contact the PD Department.
Course Details
Cost
$120
Members
$130
Non-Members
Eligible Hours
- 2
- CPD Hours
- 2
- Ethics Hours
- 0
- AML Hours
Passport
- 3
- Credits
Interested in similar content?
Starting April 1, 2026, a 2.1% fee will be applied to all credit card transactions. Learn more about this fee and how it relates to PD registrations.
AI, Technology & Innovation
AI & Ethics for Accountants: Becoming an Ethical Guardian (Live Webinar)
DELIVERY FORMAT
Online Virtual
SEMINAR TYPE
PD Seminar
NEW SEMINAR
Course Details
Cost
$120
Members
$130
Non-Members
Eligible Hours
- 2
- CPD Hours
- 2
- Ethics Hours
- 0
- AML Hours
Passport
- 3
- Credits
Overview
Artificial intelligence is transforming accounting; automating reconciliations, flagging anomalies, generating forecasts, and processing returns at unprecedented speed; however, this efficiency comes with profound ethical responsibilities that many practitioners don't yet understand.
“AI & Ethics for Accountants: Becoming an Ethical Guardian in an Automated World” equips accountants with practical frameworks for responsible AI use and actionable guardrails for everyday decisions. Professionals will learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, privacy), recognize and mitigate algorithmic bias, protect client confidentiality in an era of data-hungry tools, and maintain professional accountability even when AI does the heavy lifting.
“AI & Ethics for Accountants: Becoming an Ethical Guardian in an Automated World” equips accountants with practical frameworks for responsible AI use and actionable guardrails for everyday decisions. Professionals will learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, privacy), recognize and mitigate algorithmic bias, protect client confidentiality in an era of data-hungry tools, and maintain professional accountability even when AI does the heavy lifting.
Course Description
AI adoption in accounting is accelerating faster than the ethical guardrails needed to use it responsibly.
Organizations and professionals are deploying AI tools without fully understanding the risks to client confidentiality, professional accountability, or regulatory compliance, whether AI arrives through a brand-new tool a firm deliberately adopts, or quietly, as AI features get built into the software and service providers they've already relied on for years.
This exposes firms to reputational, regulatory, and liability risk, plus a competitive risk that cuts both ways: firms that avoid AI altogether risk losing efficiency to competitors who adopt it, while firms that adopt it carelessly risk losing client trust.
This session closes that gap with actionable guidance, helping participants learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, and privacy) and Human in the Loop verification to recognize and mitigate algorithmic bias, protect client confidentiality, and maintain professional accountability even when AI is doing the heavy lifting.
These skills apply directly to daily practice, protecting client interests and using AI to enhance professional judgment so that participants leave with confidence and apply what they learnt to work immediately.
The teaching approach is practical and deliberately low-hype: complex technical concepts are translated into plain language, delivered through case studies and simple analogies, with the session built around what participants can implement quickly.
AI creates both opportunities and risks, and this course treats it accordingly: empowering accountants to engage with it thoughtfully rather than a fear-based approach as their careers evolve, with a vendor-neutral, ethics-first perspective focused on maintaining professional integrity with any AI tool.
Organizations and professionals are deploying AI tools without fully understanding the risks to client confidentiality, professional accountability, or regulatory compliance, whether AI arrives through a brand-new tool a firm deliberately adopts, or quietly, as AI features get built into the software and service providers they've already relied on for years.
This exposes firms to reputational, regulatory, and liability risk, plus a competitive risk that cuts both ways: firms that avoid AI altogether risk losing efficiency to competitors who adopt it, while firms that adopt it carelessly risk losing client trust.
This session closes that gap with actionable guidance, helping participants learn to evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, and privacy) and Human in the Loop verification to recognize and mitigate algorithmic bias, protect client confidentiality, and maintain professional accountability even when AI is doing the heavy lifting.
These skills apply directly to daily practice, protecting client interests and using AI to enhance professional judgment so that participants leave with confidence and apply what they learnt to work immediately.
The teaching approach is practical and deliberately low-hype: complex technical concepts are translated into plain language, delivered through case studies and simple analogies, with the session built around what participants can implement quickly.
AI creates both opportunities and risks, and this course treats it accordingly: empowering accountants to engage with it thoughtfully rather than a fear-based approach as their careers evolve, with a vendor-neutral, ethics-first perspective focused on maintaining professional integrity with any AI tool.
Applicable for
Firm owners and partners, CFOs and finance executives, compliance officers, controllers, senior accountants, operations managers, and risk managers, IT professionals supporting accounting systems and any accounting professional who uses or oversees AI tools.
No technical background required.
No technical background required.
Learning Objectives
- Distinguish AI from generative AI & LLMs and apply the "garbage in, garbage out" principle to evaluate AI-generated outputs.
- Evaluate AI systems against the Five Pillars of Trustworthy AI (fairness, explainability, robustness, transparency, privacy).
- Recognize how algorithmic bias and historical data inequities can produce discriminatory ("predictive injustice") outcomes in AI systems.
- Apply data privacy safeguards to everyday AI tools used in client-facing accounting work.
- Apply practical guardrails, including a quick-start checklist and human-in-the-loop verification, for responsible, professional AI use.
Content
- AI Foundations (non-technical)
- Defining AI vs. Generative AI and LLMs (Large Language Models)
- The "Garbage In, Garbage Out" Principle
- Hallucination and the "Generate and Review" verification paradigm
- Five Pillars of Trustworthy and Responsible AI
- Fairness and bias mitigation, explainability, transparency, robustness and security
- Data privacy and governance; professional codes of conduct and AI integration
- Algorithmic Bias
- Predictive injustice and the lack of diversity in AI development
- Historical inequities in training data
- Data Privacy in Everyday AI Tools
- Recognizing privacy and confidentiality risks when using AI tools in client-facing work
- Practical Guardrails
- The CRAFT prompting framework and specialized prompting for financial tasks
- Human-in-the-loop verification
- Using AI for fraud detection and strategic advisory work
- Top 5 ethical risks in accounting AI
Course Dates & Registration
Improving Your Virtual Learning Experience
Live webinars have varying levels of expected interaction, with some requiring microphone and camera capabilities to support a proper learning experience – please email pdreg@bccpa.ca if you have concerns.
In general, we encourage participants to have their cameras turned on to enhance their virtual learning experience. This practice promotes a stronger connection with the instructor and fellow participants, and fosters improved communication and collaboration.
Live Webinar FAQs can be found here.
Registration terms and conditions, including the cancellation policy can be found here. If you require further assistance, please contact the PD Department.
Interested in similar content?
Starting April 1, 2026, a 2.1% fee will be applied to all credit card transactions. Learn more about this fee and how it relates to PD registrations.