For decades, the procurement function within large organizations has been tasked with saving companies significant amounts of money — even while being treated as a short-staffed, "back-office” solution. 

That approach has left few people motivated to seek careers in procurement, and those that are find themselves hamstrung by mountains of work and regimented processes. This manual workload consumes an overwhelming amount of a procurement manager's time.

The situation has led to a lucrative class of consultants who charge significant fees to serve as extensions of the procurement team, sometimes drawing as much in costs as they provide in savings. 

Clearly this is an inefficient setup. Now, however, artificial intelligence is poised to transform how procurement works and improve its reputation, so that more companies will see it as the force multiplier it was always meant to be. 

As a former consultant, I took part in thousands of these projects, which often required poring through contracts or Excel sheets to look for needles in haystacks. True, we’d often find opportunities to save our clients money, but it came as the result of long, expensive hours. A tremendous amount of time was spent manually reading contracts, often comprising hundreds of pages, to identify potential negotiation levers.

Since procurement teams and their consultants review contracts manually in spreadsheets or PDFs, it’s difficult to base decisions on deeper subject-matter intelligence or benchmarking data to determine if they secured a good deal. 

Lacking a strong data-based case for cost cuts or concessions, the supplier must find other justifications. Thus, negotiations conducted by consultants can take on the air of generalized haggling.  Consultants might even be forced to look at prices and try to "estimate it" to justify an argument, which suppliers can easily counter by claiming specific knowledge of their individual supply chains. 

The new era of AI-driven contract intelligence, by contrast, revolutionizes procurement. PDFs can now be uploaded for machine-learning models to produce instantaneous outputs and insights. Instead of relying on the gut decision of a consultant or an overworked procurement official, AI can determine scientifically whether a deal is good or not.

Equipped with AI, companies can understand a line-by-line plan on how to improve the contract, detailing the current state, optimal "asks" and supporting arguments, backed by benchmarked data. For large deals, potential savings on the table can be quantified down to specific leverage points.

Beyond individual contract analysis, the platform democratizes critical supplier intelligence. Procurement teams can uncover financial information about a supplier, its competitors, and which emerging technologies may replace the need for a supplier in the first place. AI eliminates the need for manual supplier research and removes human error, ensuring that procurement teams are armed with necessary and correct data. While publicly available large language models can be used to conduct research, they can still hallucinate, and might be trained on irrelevant information that can obfuscate the results. It's much better to use AI technologies custom built for this environment.

Contract scoring and quantified data allow for more intelligent internal conversations with business units and leadership. Procurement professionals can strategically justify their decisions using objective data.

While most contracts have plenty of fat to cut, a high score can let you know that the contract is relatively fair, and you might not be able to extract significant reductions in price or additions to service agreements. With literal scores, organizations can begin to see their contracts as existing on a spectrum that can be improved with the right data point and leverage. In the process, procurement becomes a strategic driver of savings and risk reduction.

AI tools enable teams to overcome the information gap, creating more airtight negotiation strategies that can lead to significant cost savings — as much as 25% of overall supplier spend. 

By absorbing insights from external benchmarks and analyzing vendor behaviors through an AI lens, organizations can extend savings based on marketing dynamics. No longer must they depend on costly consultants, and they can focus on working with service providers to build stronger relationships.

AI change is coming regardless, and companies must adapt by equipping employees with the tools to be more productive and achieve better outcomes. An AI co-pilot, trained on relevant financial information and other procurement data, is the key to keeping costs down and producing more value.

Nithin Mummaneni is chief executive officer of Infinity Loop.