It’s hard to argue that 2023 will be remembered as the year that generative AI exploded into the public consciousness. Image and text generation in the form of ChatGPT and Midjourney ignited excitement, controversy, contempt, and a fervour to adopt in equal measure. The generative AI industry is predicted to be worth more than $660 billion per year by the end of the decade.
But while there’s no denying that generative AI will be a part of the economic landscape of 2024 and beyond, it’s not yet clear what that will look like. More importantly, it’s no guarantee that generative AI will, uh, generate any ways for the technology to make back the hundreds of billions already spent to develop it.
It wouldn’t be the first major trend to be backed to the hilt by big tech firms, only to dissolve into nothingness like that racoon who drops his cotton candy in a puddle. In stark contrast to 2022, this year’s tech roundups and trend predictions have put a conspicuous lack of emphasis on the metaverse. Now, to be clear, the fact that Yahoo Finance calculated that “Mark Zuckerberg’s $46.5 billion loss on the metaverse is so huge it would be a Fortune 100 company” is great news for those of us who didn’t want to spend our thirties attending meetings in a glowing virtual mallscape surrounded by cutesy, animated versions of our bosses and coworkers. Huge relief. It’s also quite funny. More relevantly to the topic of generative AI is the cautionary tale that, unless big, expensive technological developments can be monetised, they will disappear.
So, how do we monetise generative AI?
How to make generative AI useful
Technology is most valuable when it solves problems, and saves time and money, or at least improves people’s quality of life—when there’s a measurable benefit of some kind, sometimes to humanity, and usually to shareholders. That’s the stuff that sticks around.
While its applications and capabilities—especially when it comes to creative tasks or just the ability to make something actually original—are limited, generative AI may actually be a good fit for the procurement sector, potentially solving a major issue the industry is currently experiencing.
Generative AI and the Procurement Skill Shortage
The procurement sector is short on talent—with five out of six procurement leaders claiming they will lack skills, staff, and other vital human resources in the near future. This is the case for several reasons, but primarily: an ageing workforce is starting to retire faster than new hires can skill up; also, the requirements of the job are becoming more technology centric as procurement digitally transforms, leaving departments underskilled even if they’re no understaffed; and lastly, the amount of work for procurement functions is increasing overall, as it becomes more of a driver of business efficiency and innovation.
If generative AI could be used to reduce procurement teams’ workload by automating certain aspects of the job, it could be a key piece of the puzzle when it comes to solving the skill shortage.
Retail giant Walmart has been successfully running pilot projects using its AI-powered Pactum solution to automate supplier negotiations. According to Deloitte, not only did Walmart find it “helpful for landing a good bargain, three out of four suppliers prefer negotiating with AI over a human. This strongly indicates that the ecosystem is ready to embrace this disruption.” While I’m not sure if this example is an endorsement of AI or an indictment of Walmart’s procurement team, the ability for generative AI to take over routine communication, negotiation, and other interactions in the source-to-pay process could free up huge amounts of time to focus on more strategic activities.
Gen AI’s future
It’s not hard to imagine that both buyers and suppliers could input their desired results and parameters into a generative AI negotiator and outsource the relationship management entirely. Out of curiosity, this morning I set up ChatGPT in two windows and had it conduct an RFP, tender negotiation, and sale agreement for the sale of an order of self-sealing stem bolts between O’Brien Enterprises and Quarks. It was a very civil, if slightly roundabout affair, and everyone seemed to come away happy—hacky business journalists especially.
Goofy demonstrations aside, there’s real potential for significant elements of routine communication and relationship management in the procurement process to be automated, or at least assisted by generative AI. If correctly combined with data analytics on contextual information ranging from weather patterns, commodities pricing, and supplier behavioural history, a generative AI could offer useful insights to procurement professionals while its generally low threshold for usability allows less tech-savvy procurement professionals to harness more powerful digital tools.
By Harry Menear
