Ever since procurement was officially recognized as a management function in the 1960s, teams have always had more administrative work than they’ve been able to handle. Today, however, those high backlogs are intensified by complexity from highly volatile macroeconomic, geopolitical and environmental risks. When building a supplier shortlist, for instance, teams need to ascertain which are subject to tariff volatility, whether trade routes could potentially be disrupted, what new compliance rules are coming, and countless other variables. Despite this, many teams still soldier on using manual processes, office applications and email even though agentic AI has matured to the point where it not only streamlines volume, but the complexity of sourcing workflows.
There are many reasons companies hesitate to start transformation initiatives amidst so much firefighting and uncertainty. However, two procurement leaders, for instance, from global giants in the highly regulated pharmaceutical and finance industries insisted the time to change will never be perfect so it’s best to just get started. Perhaps surprisingly, that includes not waiting for your data to be perfect, or “it will never happen.”
One way to shift the mindset here is to not call it "transformation," but "rewiring" -- not to layer new tech over broken processes. True rewiring means stripping things back to basics to design for an agentic AI world, rather than just digitizing manual steps. As with rewiring electrics, the end game is to be able to handle more traffic and diversity with increased efficiency and less risk.
What does this “rewiring” actually entail? Let’s examine the key success factors.
Manual processes can leapfrog to agentic AI
In both cases the “burning platform” that drove the urgency and consensus to change was simple: friction. Procurement processes had slowed down so much they were hindering business growth and agility. Legacy technology wasn’t the issue. One investment manager’s process had become so hidebound, the procurement team had to wade through 12,000 emails a year. One CEO generated a purchase order that took longer than having a baby!
The picture for both started to change when new chief procurement officer leaders were brought on board with clear mandates to modernize procurement into strategic business services. Both leaders immediately saw AI as a “force multiplier” to help their teams get more out of limited resources.
It may seem like a huge leap to go from manual processes, office apps and email to modern, agentic AI. But the good news is that teams in that situation have a hidden advantage: less "technical debt" to unwind. They can leapfrog the heavy, rigid digitalization phase of the last decade without having to do the heavy lifting of systems migration. This is the procurement equivalent of developing nations skipping the construction of expensive landline infrastructure to go straight to mobile networks.
The power of prioritizing UX
One of the most important success factors in both rewiring initiatives was prioritizing the user experience (UX). This wasn't about aesthetics for their own sake but delivering meaningful operational advantages.
The first advantage was adoption; a perennial challenge with any change initiative. By prioritizing a consumer-grade interface, one organization reported achieving unprecedented adoption rates with almost no formal training. This stands in stark contrast to typical enterprise systems that often require extensive workshops and change management just to get users to log on.
Secondly, focusing on UX democratized technical skills and directly led to that force multiplier mentioned above. Legacy sourcing required “PhD-level training,” similar to mastering complex photo-editing software. The new AI interface is comparable to using a generative chatbot: a generalist can now execute forensic, high-stakes sourcing events that previously required a “super-analyst,” simply by using natural language prompts.
To ensure the UX would actually stick, one team abandoned the traditional RFP process for selecting their AI tool. Instead, they conducted a “design-thinking immersion,” inviting stakeholders from legal and business units to test the technology hands-on. This revealed what potential users – not just in procurement, but across the company – really needed and valued.
First fruits of AI success
None of this matters if we’re not solving that friction problem. Here, the KPIs speak for themselves. In one case autonomous sourcing allowed the team to insource its source-to-contract activities with half the people at half of the cost while delivering 70% faster than their previous outsourced procurement provider (think 27 days, not 6-9 months).
The company is also working with 10 times the number of RFPs, which translates to not the original target of $100 million of AI-supported company spend but $1 billion, and in just 10 months.
One leader suggested the ripple effect could be enormous, explaining that, as we’re creating efficiencies and implementing AI, leaders should ask, how do we rewire our processes as well?
Just get started
Any initiative that ends up with widespread elimination of routine, manual tasks, like weeks spent wrangling hand-coded Excel and email-based tendering back and forth, and so free up expert humans for higher-level work has to be a good endpoint, no matter what label we put on the tech that fueled the transformation.
