AI in Procurement Is a Game Changer for Government

The Role of AI in Modern Procurement

Given its powerful capabilities, “AI has a significant role to play in procurement, practically, from a staff augmentation and automation perspective,” says Sarjoo Shah, executive director at Oracle.

“We can certainly use it in vendor selection and management — analyzing historical vendor performance data, predicting the reliability and risk, maybe even conducting sophisticated market research and benchmarking,” he says.

AI offers powerful potential to support research and analysis, giving procurement professionals “a better grasp of the current market situation” says Zachary Christensen, deputy chief cooperative procurement officer at NASPO.

State and local procurement could benefit from AI’s ability “to understand the current market, what capabilities exist, and even the different suppliers that are available,” Christensen says. All this can lead to a better RFP, “and if you have a better RFP, then you’re going to get better responses.” 

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Practical Applications of AI in Procurement

The most obvious use case for AI is to use it to generate baseline language for RFPs. However, there are other areas where AI can help.

“AI can be used to streamline the scope of work, ensuring that you are putting out scopes of work that are technically sound, that limit external questions and inquiries,” says Brian Esposito, deputy secretary of procurement for the Pennsylvania Department of General Services. The idea here is that AI can help sculpt RFPs into more concise, clear documents, which can expedite responses.

“We don’t need 35-page scopes of work when maybe a five-page or three-page scope of work would do,” he says. “Utilizing AI for something like that is a pretty strong application.”

AI can also produce automated spend analyses. Procurement professionals can use AI tools “to enable comprehensive spend categorization, identify cost saving opportunities and spending patterns, and then do predictive analytics on cost modeling and budget optimization,” Shah says.

It can also support contract management. “Maybe we can redefine that term as ‘smart contract management’ — doing an automatic contract review and risk assessment, bringing in a legal AI engine to do intelligent clause extraction and comparison,” Shah says.

Integrating AI Across Procurement Systems

Given that procurement processes reach across multiple state and local systems, a thoughtful implementation plan is essential.

At the outset, “one of the best practices is really knowing what use case you have in mind that you’re trying to solve — what is the issue or challenge? — and then finding a solution that actually addresses that need,” Christensen says.

To ensure the AI can operate across multiple systems, the architecture must be application programming interface-based and then use a microservices architecture, Shah says. “Implement modular AI components, agentic AI where possible, and then create the architecture in such a way that it can scale.”

Procurement will likely start with small use cases, but success will drive further adoption, and the architecture should be scalable enough to handle that, he says.

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Risks and Security Considerations of AI in Procurement

Artificial intelligence in procurement comes with all the usual considerations that state and local government brings to the AI conversation, including questions about data security and unintended bias in outputs.

“When a tool is making a decision for that entity — if you’re using a tool to decide who gets a contract — you have to be able to show how that decision was made,” Christensen says. For state and local, transparency is key.

Government also needs to tend to data privacy and security. That means using “advanced encryption protocols at rest as well as when data is in motion, along with strict access control mechanisms,” Shah says. “We highly recommend role-based access control and regular security audits to make sure that, if a person has changed their role, they won’t have access to what they shouldn’t.”

Training is critical to mitigating risks and making effective use of AI. “You don’t want someone using it and saying, ‘I’m running with this output without cross-checking it,’” Esposito says. “That is a very real concern, and a lot of that comes down to communication and training.”

The Future of AI in Government Procurement

There are strong indications that AI will play an increasing role in state and local procurement going forward.

“According to a Deloitte study in 2024, 92% of procurement agency heads are considering AI,” Shah says. “I see a lot more predictive analytics, which is AI-fueled, as well as real-time market prediction, dynamic pricing, proactive supply chain management, automated demand forecasting and such. And I see a lot more intelligent automation with generative AI.”

In the private sector, some businesses have developed AI chatbots that answer questions about RFPs, a possibility that isn’t too far off for state and local government agencies.

Procurement professionals need to prepare themselves accordingly. “Government procurement teams need to keep up with current technology and understand how AI could help us to deliver goods and services more effectively,” Esposito says.

“Public sector procurement has always run obsolete programs with obsolete processes,” he adds. “Now we have the ability to flip the narrative on that and utilize the newest technology to modernize and streamline our entire process.”