How is your procurement team leveraging Gen-AI?

generative AI in procurement

Last modified on June 17th, 2024

The procurement technology landscape has undergone a transformative shift in the last decade, with most organizations now relying on robust source-to-pay solutions to streamline their daily operations. The next frontier lies in leveraging the capabilities of GenAI and automation to drive efficiency, accuracy, and data-driven decision-making throughout the procurement process. Read on to learn more!

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Automating Manual Processes with GenAI

Time-consuming and error-prone manual tasks can be effectively replaced by automated AI scripts, saving time and resources. For example, many companies still conduct purchase request (PR) reviews manually, a process that can be streamlined by implementing AI-backed tools. These tools leverage historical data, predefined rules, and machine learning algorithms to validate PRs automatically, freeing procurement professionals to focus on higher-value activities.

Enhancing Source-to-Pay Effectiveness with GenAI

GenAI holds the potential to optimize various aspects of the procure-to-pay process, including validation, classification, and market scanning. By harnessing the power of AI, procurement organizations can drive data-driven decision-making, increase operational efficiency, and gain a competitive edge in a highly competitive business landscape.

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Adopting GenAI for Long-Term Success

To successfully adopt GenAI in procurement, organizations should follow a strategic approach:

  1.  Upskill and Involve the Procurement Team: Conduct generative AI training for the procurement team and crowdsource ideas for potential use cases, fostering a bottom-up approach that aligns with operational realities.
  2. Benchmark Existing Tools: Evaluate the AI capabilities offered by current procurement software providers before investing in in-house development, leveraging existing solutions where possible.
  3. Start Small, Move Fast: Begin with specific, high-impact use cases as proof of concept while envisioning the long-term potential of GenAI for operational efficiency, risk mitigation, and competitive advantage.

Trustpair’s Machine-Learning-Driven Vendor Fraud Prevention Solution

Trustpair’s fraud prevention solution is a good example of the impact of AI and machine learning on the procure-to-pay (P2P) cycle. By replacing manual vendor controls with automated account validation, our solution significantly reduces the risk of vendor fraud while improving efficiency and data accuracy.

We integrate hundreds of external banking data sources, enabling three layers of data control: company information verification, banking information validation, and correlation analysis between the two. Our proprietary machine learning algorithm combines external data sources, anonymized client payment histories, and mutualized data to deliver real-time risk assessments and live warnings of any data changes or anomalies throughout the payment chain. Request a demo to learn more!

To conclude

As the procurement landscape evolves, embracing generative AI and automation is no longer an option but a necessity. By leveraging cutting-edge technologies, procurement teams streamline processes, enhance data accuracy, and drive strategic decision-making. Organizations that proactively adopt GenAI will not only gain a competitive edge but also position themselves as future-ready, attracting top talent and investor confidence.

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