Autonomous sourcing platforms, driven by artificial intelligence, are achieving significant returns on investment, according to a new report by research firm HFS.
Chief procurement officers report lower costs, higher productivity and greater visibility from AI-enhanced spend management. Procurement teams are better able to conduct RFx’s — “requests for anything” —while adhering to established procurement guidelines.
RFx is the best way to evaluate suppliers, create negotiating leverage, and ensure a fair market value for spending. Yet dissatisfaction frequently stems from the prolonged timelines associated with the procedure.
Simultaneously, the push by chief financial officers for cost savings is expanding procurement’s influence across spending categories. CPOs are being prompted to explore potential savings in previously overlooked areas, resulting in a notable increase in incremental sourcing activity.
As a result, procurement leaders are considering alternatives to hiring, such as staff augmentation and the adoption of innovative technologies that make sourcing more efficient and sometimes enable self-service. One solution is autonomous sourcing, which draws on proprietary AI and GenAI to transform the procurement discipline.
AI-driven sourcing platforms enable procurement leaders to engage in interactive discussions with system users, and review both internal and supplier-sourced documents. Additionally, they can produce requests for proposals by incorporating defined requirements, company policies and category-specific standards. GenAI, meanwhile, analyzes unstructured supplier proposals to generate evaluation matrices. It can also draft contractual documents stemming from the RFx process.
According to the HFS research, Global 2000 companies using autonomous sourcing can go to market in just 23 minutes on average, with more than 64% of projects created in less than a day.
Autonomous sourcing platforms combine supplier discovery algorithms with company preferences and strategies to identify the most suitable suppliers.
Following are three case studies on the use of autonomous sourcing cited in the HFS Research report.
In the financial services sector, Fidelity Investments reported that implementing autonomous sourcing reduced contract negotiation time by approximately 50%, while achieving an overall average cost reduction of 20%, thanks to the use of a more transparent bidding process.
By identifying instances of contract “padding,” Fidelity was able to adjust payments to more accurate and realistic levels. Suppliers, for their part, appreciated the platform’s capability to connect them with relevant RFPs they might have otherwise missed. They can now quickly evaluate their chances of winning or losing a bid. Fidelity also integrated ChatGPT-style interfaces with back-end finance and procurement systems to simplify and streamline supplier engagement.
Another financial services company, T. Rowe Price, found that AI-powered procurement greatly reduced “friction” in spend-management workflows, making these processes much smoother to navigate. CPO Harold Wu said the rapid ROI resulted in substantial cost savings and improvements in sourcing operations.
T. Rowe Price expects even greater AI-driven improvements to procurement in the future, particularly in how it obtains things like professional services from third parties.
In the life sciences sector, AI has played a crucial role in the digital transformation of procurement at UCB. The €5bn Belgian-based pharma company was motivated by the need to streamline its buying model to reduce the involvement of the procurement team in routine tasks. By adopting autonomous sourcing, it achieved a significant reduction in contract cycle times, and saw notable improvements in user satisfaction.
AI-driven autonomous sourcing is the key to helping businesses transform into what HFS Research defines as the “generative enterprises of tomorrow.”
Keith Hausmann is chief customer officer at Globality.