AI Agents and RPA for Accountants Key Differences and Uses
Agentic AI excels in autonomous complex tasks while RPA automates repetitive processes. Learn how accountants can leverage both technologies.
Introduction
As automation becomes integral to tax and accounting workflows, robotic process automation (RPA) and agentic AI are emerging as key technologies. The accounting profession, traditionally cautious, is increasingly adopting these tools to enhance efficiency and client service.
Key Findings
- 2025 State of Tax Professionals Report: 49% of respondents plan to use technology to boost profits, and 47% prioritize AI investments.
- Future of Professionals Report 2025: 53% of professionals already benefit from AI, with 80% expecting high or transformative impacts in five years.
Defining Agentic AI and RPA
Agentic AI
- Leverages generative AI and large language models (LLMs) for autonomous operation.
- Adapts to changing scenarios, seeks information proactively, and improves outputs without constant human intervention.
- Capabilities:
- Accesses multiple data sources and tools.
- Executes multi-step processes autonomously.
- Makes decisions within defined parameters.
RPA
- Uses bots to automate repetitive, rule-based tasks.
- Follows predefined rules without learning or adapting.
- Requires regular updates and maintenance.
Differences Between AI Agents and RPA
- Agentic AI: Best for complex problem-solving, adapts to new data, and operates autonomously.
- RPA: Ideal for repetitive tasks, lacks decision-making capabilities, and is rigid in structure.
Use Cases for Accountants
Agentic AI
- Monitors regulatory changes and flags compliance issues.
- Analyzes market trends and financial data for tax planning.
- Reviews financial records and prepares audit reports.
- Handles client communications and schedules meetings.
RPA
- Automates purchase orders and bank reconciliations.
- Scrapes websites for data like banking transactions.
- Best for tasks with no API alternatives.
Will AI Replace RPA?
Experts suggest both technologies will coexist:
- Michael Kim (Thomson Reuters): "RPA is effective for stable, rules-based processes, while agentic AI excels in cognitive tasks."
- Dustin Teribery (Thomson Reuters): "RPA and AI may complement each other in the future."
Embracing Technology
Adopting these tools can save time and improve efficiency, allowing accountants to focus on high-value services. Thomson Reuters offers resources like CoCounsel for AI integration.
Special Report
Agentic AI 101: What your business needs to know.
Related News
Microsoft Releases Open-Source AI Agent Framework
Microsoft unveils its open-source Agent Framework to streamline AI agent development with enterprise-ready tools and simplified coding.
GoDaddy Launches Trusted Identity System for AI Agents
GoDaddy introduces a trusted identity naming system for AI agents to verify legitimacy and ensure secure interactions as the AI agent landscape grows.
About the Author

David Chen
AI Startup Analyst
Senior analyst focusing on AI startup ecosystem with 11 years of venture capital and startup analysis experience. Former member of Sequoia Capital AI investment team, now independent analyst writing AI startup and investment analysis articles for Forbes, Harvard Business Review and other publications.