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Moving Past the Hype: Making the Business Case for AI in Procurement

Today’s procurement teams are facing complex challenges. High levels of economic and trade uncertainty are driving a return to savings-focused decision-making, an increased interest in risk transference and fewer internal resources. In addition to these external factors, many enterprises have yet to address ongoing internal challenges like a lack of visibility and clear ownership (and, thus, accountability) over extended workforce spend.

If this is resonating with you, know that you are not alone. This state of procurement is driving many leaders to discuss artificial intelligence (AI) in services procurement, but real progress is often held back by hesitation and uncertain value. While everyone wants to use AI in procurement, and many are in modular ways, few have done so end-to-end to deliver clear-cut results. The gap between desire and reality feels insurmountable: Where do I begin? How can I secure investment in AI? How can I drive enterprise change that lasts?

I recently co-hosted a series of workshops advising procurement leaders on how to do exactly that – get started, secure investment and drive enterprise change that makes an impact – and it all starts with building a killer business case.

Why Building a Business Case for AI Is So Important

Building a good business case is both a science and an art. Business cases need at a minimum to be both qualitative and logical, i.e., financial models, ROI, cost/benefit analysis and risk assumptions. They require data, benchmarks and past outcomes to reduce uncertainty and appeal to finance-led decision makers. Quantitative data bolsters credibility that can withstand scrutiny. It needs clear problem statements, options analysis and decision criteria to help stakeholders compare alternatives objectively.

Data is used to earn trust. Yet, data alone is rarely persuasive. Data needs to be coupled with good storytelling to drive bias towards action. That means connecting the numbers to strategic priorities, urgency and consequences. Since not all benefits are easily quantifiable, experience and insight help translate intuition, risk and timing into a persuasive narrative. A strong narrative drives conviction.

What Does Best-in-Class AI-Enabled Procurement Look Like?

Before we get to building the business case and defining the problem statement, start with setting a benchmark. Here are a few attributes that define best-in-class procurement today:

  • Mass Adoption: The biggest problem in procurement is the spend you don't touch  – either you don’t know about it at all, or you don’t know about it until an invoice arrives in your inbox. Most organisations have approximately 60% of unmanaged spend and 40% of managed spend. For best-in-class companies, those ratios flip to 60% managed and 40% unmanaged. (There will always be people who refuse to follow the rules.) 
  • High User Satisfaction: Best-in-class organisations don't underestimate the importance of user experience. A positive UX drives repeat usage, which then further increases spend under management and the ability for procurement to be a strategic advisor that drives greater competition, cost savings and compliance.   
  • Human in the Loop: With so much hype around AI, one mistake we see is taking humans completely out of the process. Keeping a human in the loop ensures compliance. 

Benefits of Best-in-Class Procurement

Organisations that have embedded agentic or generative AI effectively into their procurement processes have realized impressive benefits, upwards of 17-22% in cost savings, and sometimes taking RFP generation from months to minutes. Additional benefits include reduced manual work, greater contract consistency and procurement seen more as a business enabler rather than an obstacle.

Essential Ingredients for Your Business Case

There are several key elements you’ll need to build your business case, including risks, benefits, cost to build the solution and change management. However, at the end of the day, a business case is a story of why the change you have in mind is valuable to invest in and bringing them on a journey to that same conclusion.

Problem: What’s Broken Today & Risks of Doing Nothing

Sometimes it’s difficult to narrow down the problem. When I’ve run workshops on this topic, I encourage everyone in the room to write down their most prominent services procurement challenges on sticky notes. Then plot those problems to a solution frame, as depicted below. Lining along the axis on how complex the problem would be to solve, and the measure of impact it would have on the business if it was resolved.

Map Problems to Solution Frame - AI in Procurement Blog

Some of the most common problems I hear include lack of competitive bidding, over-long services procurement timelines, worker misclassification risks and cost over value focus. While these are all worthy and formidable problems to address, the impact of resolving those challenges varies. For example, if procurement is brought in too late, the impact if solved may be medium, as it could improve competition and thus more competitive pricing. However, resolving a problem like budget overruns could have a much higher impact if solved, as you’d experience a direct cost impact.

Solution: What Changes Are You Recommending – and at What Level

Once you’ve identified the problem statement for the business, you have to look at what level AI can help you with solving the problem. Defining your level of ambition will help you align how far you’re willing to go to solve that problem. I break this into three levels:

  • Level 1 is control focused. This could include using AI tools the organisation has already invested in to impact policy, governance and behaviours only. Examples could include intake rules, rate cards and mandates.  
  • Level 2 is enabling focused. This could include moderate investment in AI technology, like an AI-powered analytics tool, such as a VMS, that primarily impacts activity. 
  • Level 3 is outcome focused. This could include embedding advanced AI solutions into your procurement function that not only accelerates activity; it positively impacts outcomes.  
     

In practice, you should illustrate the difference in scope of impact by offering solutions at different levels. For example, a simple fix, like a policy change, may not take time or money, but it may not resolve all the issues either. A Level 2 solution may need more budget or technology investment on a modular level. Level 3 solutions may be a programmatic change where AI is making decisions on behalf of the organisation across the supply chain. Often, Level 2 solutions are well positioned to be a compelling balance of risk mitigation, cost and level of change.

For each solution offered, you should identify:

  • Benefits: What value is created or risk reduced  
  • Cost: What is the investment and effort required 
  • Change: What residual risks does change bring and what risks remain after  

 

Make the Case for Human-Led, AI-Enabled Procurement

AI in procurement doesn’t win investment because it’s exciting — it wins when you can show, in plain business terms, how it will reduce risk, lower cost and improve outcomes. The fastest path past the hype is a business case that combines quantification with a clear narrative; define what’s broken today (versus the cost of doing nothing), set an ambition level your organisation can realistically absorb, and make benefits, costs, change effort and residual risks explicit. From there, start with the use cases where you have the best data and the clearest stakeholders, keep a human in the loop to protect compliance and build momentum through measurable wins. With the right business case, AI stops being a future-state concept and becomes a pragmatic, actionable procurement advantage.

If you’re interested in exploring how AI can advance your procurement function or want to discuss where to start, let’s connect for a conversation. Reach out to learn more about practical next steps tailored to your organisation’s needs.

    Written by Jonathan Winters
    Jonathan is a subject matter expert for services procurement – also known as Statement of Work (SOW) - for AGS in EMEA. This means he consults with companies on how they manage their services procurement business to help determine if there is a better solution to their current process. He is a regular speaker on HR procurement as his views are often sought by those in his specialism.