Date: 4/10/25
Time: 12:00 PM - 2:00 PM EST
CPE Credit: 2 hours

Course Description:
This course provides essential insights into the current landscape of AI for accountants, drawing from real-world experiences and best practices. As companies shift from theory to in-house experimentation, accountants must embrace an R&D mindset to stay competitive. This course covers proactive strategies for AI integration, addresses potential risks like cybersecurity threats, and emphasizes the importance of in-house AI development to minimize dependence on third-party vendors. 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.

1. Introduction to AI R&D in Accounting: Why internal AI research is essential for modern firms.
2. Theory to Practice: Moving quickly from speculative AI concepts to actionable strategies.
3. Managing Exponential Change: Understanding the urgency of adapting to AI’s rapid evolution.
4. Proactive AI Engagement: Conducting in-house AI benchmarks, research, and hackathons.
5. The Dual Role in AI Development: Balancing innovation with data security and ethical responsibilities.
6. Internal AI Tools Creation: Encouraging accountants to develop AI solutions tailored to their needs.
7. Data Security and Cyber Threats: Addressing AI-enabled cybercrime and protecting against internal risks.
8. Mitigating AI Misuse: Recognizing abuse patterns and implementing safe practices.
9. Challenges in AI Integration: Handling resistance, management concerns, and rapid technological shifts.
10. Continuous Learning and Adaptation: Building a resilient, R&D-focused AI culture in accounting.

1. Analyze the importance of in-house AI R&D for staying competitive in accounting.
2. Identify strategies for moving from AI concepts to practical, value-adding applications.
3. Recognize the urgency of adapting to AI’s exponential advancements.
4. Conduct proactive AI assessments, benchmarks, and explorations in your organization.
5. Evaluate the dual role accountants play in AI development as both innovators and data protectors.
6. Encourage the creation of internal AI tools to address specific accounting challenges.
7. Develop strategies to mitigate AI-related cyber threats and protect sensitive data.
8. Recognize potential misuse patterns of generative AI and implement preventive measures.
9. Address challenges in AI adoption and foster a supportive learning environment.
10. Design a sustainable, adaptive approach to AI that supports ongoing development and ethical integration.