Agentic AI and AI Agents Transform Procurement Efficiency
Procurement leaders can enhance efficiency and decision-making by combining agentic AI and AI agents, which complement each other in automating tasks and processes.
By Shaz Khan, CEO and co-founder of Vroozi
Image: Getty
Procurement leaders face mounting pressure to do more with fewer resources while maintaining compliance and productivity. Artificial intelligence (AI) offers a solution, but confusion persists between AI agents and agentic AI—two complementary technologies reshaping procurement.
AI Agents: Task Automation Specialists
AI agents are process-driven assistants that require human input to execute tasks. Examples include voice assistants like Siri or chatbots that streamline procurement workflows. Key use cases:
- Automating invoice processing (reducing 20-minute tasks to seconds)
- Supplier sourcing and onboarding
- Generating purchase orders
However, AI agents have limited autonomy and need manual updates for improvements.
Agentic AI: The Strategic Decision-Maker
Agentic AI operates with minimal human oversight, analyzing real-time data to make recommendations. For example, it can:
- Optimize tail spend by identifying cost-saving supplier alternatives
- Predict supply chain disruptions and suggest mitigation strategies
- Autonomously manage supplier risk profiles
Synergy in Action
Combining both technologies unlocks greater efficiency:
- An AI agent (e.g., chatbot) receives a request like "Need a laptop for new hire Sarah starting Thursday."
- Agentic AI determines Sarah’s role-based requirements and sources the best option.
Implementation Roadmap
Procurement teams should:
- Educate staff on AI frameworks
- Experiment with pilot projects
- Improve data quality—AI depends on clean, structured inputs
- Strengthen governance for autonomous processes
- Integrate AI into defined workflows
The Future of Procurement
AI won’t replace professionals but empower them to focus on strategic work. As terminology evolves, the focus will shift to practical applications—reducing costs, improving efficiency, and enabling smarter decisions.
For more insights, visit Forbes Technology Council.
Related News
Zscaler CAIO on securing AI agents and blending rule-based with generative models
Claudionor Coelho Jr, Chief AI Officer at Zscaler, discusses AI's rapid evolution, cybersecurity challenges, and combining rule-based reasoning with generative models for enterprise transformation.
Human-AI collaboration boosts customer support satisfaction
AI enhances customer support when used as a tool for human agents, acting as a sixth sense or angel on the shoulder, according to Verizon Business study.
About the Author
Dr. Emily Wang
AI Product Strategy Expert
Former Google AI Product Manager with 10 years of experience in AI product development and strategy formulation. Led multiple successful AI products from 0 to 1 development process, now provides product strategy consulting for AI startups while writing AI product analysis articles for various tech media outlets.