This course provides accountants with the leading AI insights and strategies drawn from real-world experience, empirical studies, countless CPA case studies, and social media commentary. It goes beyond theory, offering practical lessons learned from the front lines of AI implementation in the business world and accounting industry. Participants will gain actionable knowledge on bridging the theory-application gap, navigating exponential technological changes, and creating secure, adaptive AI policies. By the end of the session, accountants will be equipped to leverage AI responsibly and innovatively in their roles. This event may be a rebroadcast of a live event and the instructor will be available to answer your questions during the event.
Learning Objectives
After attending this presentation, you will be able to...
- Analyze the importance of in-house AI R&D for staying competitive in accounting.
Identify strategies for moving from AI concepts to practical, value-adding applications.
Recognize the urgency of adapting to AI’s exponential advancements.
Conduct proactive AI assessments, benchmarks, and explorations in your organization.
Evaluate the dual role accountants play in AI development as both innovators and data protectors.
Encourage the creation of internal AI tools to address specific accounting challenges.
Develop strategies to mitigate AI-related cyber threats and protect sensitive data.
Recognize potential misuse patterns of generative AI and implement preventive measures.
Address challenges in AI adoption and foster a supportive learning environment.
Design a sustainable, adaptive approach to AI that supports ongoing development and ethical integration.
Major Topics
The major topics that will be covered in this course include:
- Introduction to AI R&D in Accounting: Why internal AI research is essential for modern firms.
- Theory to Practice: Moving quickly from speculative AI concepts to actionable strategies.
- Managing Exponential Change: Understanding the urgency of adapting to AI’s rapid evolution.
- Proactive AI Engagement: Conducting in-house AI benchmarks, research, and hackathons.
- The Dual Role in AI Development: Balancing innovation with data security and ethical responsibilities.
- Internal AI Tools Creation: Encouraging accountants to develop AI solutions tailored to their needs.
- Data Security and Cyber Threats: Addressing AI-enabled cybercrime and protecting against internal risks.
- Mitigating AI Misuse: Recognizing abuse patterns and implementing safe practices.
- Challenges in AI Integration: Handling resistance, management concerns, and rapid technological shifts.
- Continuous Learning and Adaptation: Building a resilient, R&D-focused AI culture in accounting.
