Did you miss Ardent Partners’ recent webinar, State of Procurement 2025: Reinventing Procurement for the Autonomous Age? The event featured a dynamic conversation between Andrew Bartolini, founder and chief research officer of Ardent Partners, and Erin McFarlane, vice president, operations for Fairmarkit, on the current state of procurement, key performance benchmarks from the just-released CPO Rising 2025 report, and the forward-looking strategies that Best-in-Class teams are using to unlock agility, resilience, and value.
In the final part of this four-part series, we feature articles based on the webcast discussion as well as this link to the full event.
AI Strategies for Practical Implementation and Long-Term Success
Artificial intelligence (AI) is no longer a distant concept or future-facing trend — it’s fast becoming an integral part of the procurement technology landscape. Yet for many procurement teams, the challenge isn’t recognizing AI’s potential but knowing how to begin applying it effectively. According to recent Ardent Partners findings, optimism about AI remains high, with approximately 75% of procurement leaders expecting it to significantly impact their teams in the next 12 to 24 months. Still, putting AI into action can feel daunting. Executing a successful strategy requires a careful balance of vision, planning, and realistic execution.
AI Is About Integration
First and foremost, it’s important to dispel the myth that AI is a standalone tool to purchase and install. Unlike traditional software, AI is usually embedded within existing platforms or accessed through new solutions that support smarter, more dynamic workflows. In other words, AI is not something you buy separately — it’s something you integrate. As such, the starting point for AI in procurement often lies in assessing your current tools and solution providers. Which platforms already offer AI capabilities? Where do your biggest pain points exist? Identifying areas of opportunity, such as contract analysis, supplier risk monitoring, or spend classification, can help pinpoint use cases that are both relevant and achievable.
Clean data is critical. A foundational step in any AI journey is getting your data house in order. AI thrives on data, but not just any data. It requires clean, structured, and accessible data to generate meaningful insights. Procurement teams must partner closely with IT and data governance leaders to understand how their data is organized, what data standards are in place, and how information can be shared safely and compliantly. This step is essential not only for functionality but also for building trust — both in the technology and the outcomes it delivers.
Establish a cross-functional governance team. Because of AI’s complexity and evolving regulatory considerations, it’s also essential to establish a governance framework. For larger enterprises, this often means joining or collaborating with an internal AI Council — a cross-functional team typically led by IT or innovation groups. These councils can help define policies around data usage, model transparency, security, and proprietary information. Procurement doesn’t need to go it alone; it should leverage these internal experts to navigate questions around ethical AI use, third-party data, and algorithmic accountability.
Education of AI is key. Another critical piece of successful implementation is internal education. AI can be intimidating to staff — particularly when there’s a lack of clarity around how it works or what it might replace. That’s why basic “AI 101” training is so valuable. Procurement professionals don’t need to become data scientists, but they do need to understand what AI is (and what it isn’t), how it functions, and how it will support (not replace) their work. Transparency and communication are key to building trust and ensuring adoption.
Deploy AI Incrementally
In terms of deployment, the best approach is to start small and scale. Identify a few manageable, high-impact use cases where AI can provide a clear benefit—such as automating invoice matching, enriching supplier profiles, or surfacing savings opportunities from past spend. These early wins help build momentum and provide proof of concept, demonstrating tangible ROI and increasing organizational comfort with AI.
Lastly, as with any transformation initiative, define your goals and success metrics from the beginning. What are you hoping to achieve with AI? Is it increased efficiency? Reduced cycle times? Greater compliance? Establish baseline metrics and put mechanisms in place to measure progress. This not only ensures accountability but also helps demonstrate the value of AI to executive stakeholders.
Ultimately, the key to integrating AI into procurement isn’t about finding the most advanced tools — it’s about aligning strategy, data, people, and process. AI won’t solve every problem overnight, but when deployed thoughtfully, it can help procurement teams become more intelligent, agile, and impactful in the years ahead.
