Intuit's AI Chief on the Future of Agentic AI and Business Automation
Intuit's chief AI and data officer Ashok Srivastava discusses the company's AI agent development, challenges, and the future of AI in business automation.
By Beth Pariseau, Senior News Writer
Published: 22 Jul 2025
Ashok Srivastava, chief AI and data officer, Intuit
Ashok Srivastava, Intuit's chief AI and data officer, has been at the forefront of the company's AI initiatives since joining in 2017. Under his leadership, Intuit developed its generative AI operating system (GenOS), which includes platforms like GenStudio, GenRuntime, GenSRF, and GenUX. These tools support AI development, including the creation of AI agents for QuickBooks, such as Payments Agent, Accounting Agent, and Finance Agent.
Key Challenges in AI Agent Development
Srivastava highlighted the technical hurdles in developing AI agents, particularly in making GenRuntime work with thousands of APIs. "APIs defined for humans needed to be restructured for machines," he said. Another challenge was shifting developers' mindsets from declarative code to probabilistic programming with LLMs. Intuit addressed this through extensive training programs.
Ensuring AI Agent Reliability
To prevent AI agents from providing inaccurate information, Intuit developed GenSRF, a system that evaluates model outputs using LLMs and human oversight. "Hybrid systems combining rules and LLMs are the way to go," Srivastava emphasized.
Deterministic vs. Probabilistic Workflows
Srivastava advocates for a balanced approach: "Use rules for simple tasks and LLMs for complex reasoning." For example, Intuit's Payments Agent uses LLMs to suggest payment strategies, resulting in customers getting paid 10% faster.
The Future of AI
Srivastava predicts two major trends:
- Human-AI Collaboration: Bridging the gap between human experts and AI systems.
- Advanced Reasoning Models: Improving AI's ability to reason under uncertainty, particularly in financial decision-making.
"Creating algorithms that operate with partial information will be critical," he said, pointing to the need for research in Markov decision processes.
For more on Intuit's AI initiatives, read about GenOS and their collaboration with Google's Agent2Agent Protocol.
Contact Beth Pariseau at email or @PariseauTT.
Related News
Data Scientists Embrace AI Agents to Automate Workflows in 2025
How data scientists are leveraging AI agents to streamline A/B testing and analysis, reducing manual effort and improving efficiency.
Agentic AI vs AI Agents Key Differences and Future Trends
Explore the distinctions between Agentic AI and AI agents, their advantages, disadvantages, and the future of multi-agent systems.
About the Author

Michael Rodriguez
AI Technology Journalist
Veteran technology journalist with 12 years of focus on AI industry reporting. Former AI section editor at TechCrunch, now freelance writer contributing in-depth AI industry analysis to renowned media outlets like Wired and The Verge. Has keen insights into AI startups and emerging technology trends.