> ## Content Index > Fetch the complete content index at: https://www.ai-360.online/llms.txt > Use this file to discover other available public pages before exploring further. # NVIDIA's Richardson Discusses Multi-Agent AI Automation Systems - URL: https://www.ai-360.online/nvidias-richardson-discusses-multi-agent-ai-automation-systems/ - Published: 2025-05-30T12:49:00.000Z - Updated: 2026-11-04T11:37:19.000Z - Description: NVIDIA engineering director Bartley Richardson explains on the NVIDIA AI Podcast how enterprises can deploy multi-agent AI for the next level of automation. - Author: AI-360 - Tags: 1. Enterprise AI, Enterprise AI, NVIDIA, News, AI Agent [NVIDIA](https://www.ai-360.online/nvidia/) senior director of engineering and AI infrastructure Bartley Richardson [outlined enterprise strategies](https://blogs.nvidia.com/blog/ai-agents-next-level-automation/?ref=ai-360.online) for deploying agentic AI systems during an appearance on the NVIDIA AI Podcast. Richardson described agentic AI as "that next level of automation" for organisations seeking to implement advanced automated workflows across business operations. Richardson emphasised the critical role of AI reasoning models in agentic systems, explaining that these models have been "trained and tuned in a very specific way to think — almost like thinking out loud." He compared the reasoning process to "brainstorming with your colleagues or family," highlighting how reasoning capabilities enable better planning within automated systems. NVIDIA's Llama Nemotron models provide distinctive functionality by allowing users to toggle reasoning capabilities on or off within the same model, optimising performance for specific tasks. Richardson noted that enterprise IT leaders must prepare for multi-vendor environments where "you're going to have all these agents working together, and the trick is discovering how to let them all mesh together in a somewhat seamless way for your employees." ## Sign up for AI-360 AI from all perspectives: Where business & innovation meets application & regulation. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. To address integration challenges, NVIDIA developed the AI-Q Blueprint for building advanced agentic AI systems. The blueprint enables teams to create AI agents that automate complex tasks, break down operational silos, and drive efficiency across industries. The system utilises the open-source NVIDIA Agent Intelligence toolkit to evaluate and profile agent workflows, facilitating optimisation and ensuring interoperability among agents, tools, and data sources. Richardson reported significant performance improvements from the AI-Q implementation, stating "we have customers that optimise their tool-calling chains and get 15x speedups through their pipeline using AI-Q." He emphasised realistic expectations for agentic system deployment, noting that "agentic systems will make mistakes" but "if it gets you 60%, 70%, 80% of the way there, that's amazing." The AI-Q Blueprint addresses enterprise requirements for seamless agent integration across multi-vendor environments while providing tools for workflow optimisation and performance monitoring. Organisations can implement automated systems that break down operational silos and drive cross-industry efficiency improvements. NVIDIA's agentic AI approach positions the company to support enterprise automation initiatives requiring coordination between multiple AI systems from different vendors. The 15x performance improvements demonstrated through AI-Q optimisation provide compelling value propositions for organisations seeking to implement next-level automation capabilities while managing realistic performance expectations. --- [To read more articles like this, and be notified of new content published each week, Sign Up to our FREE newsletter](#/portal/signup/free)