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The Practical Path to AI in Procurement

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Estimated reading time: 7 minutes

(Source: Santy Hong/stock.adobe.com; generated with AI)

Published July 30, 2025

Today’s procurement professionals manage more moving parts than ever before. They handle global supplier networks, deal with fluctuating part availability, and navigate tight budgets while being expected to do more with less.

According to a 2018 analysis by The Hackett Group, organizations that introduce automation into procurement processes experience 21 percent lower labor costs and see 10.7 times return on investment (ROI)—more than double that of their peers.[1]

Making that type of impact does not always require a complete systems overhaul. Plenty of software tools provide value by targeting one manual process at a time. Automation—especially artificial intelligence (AI)-based automation—helps procurement teams reduce delays and errors so they can focus on more strategic decisions.

This article examines AI automation tools and how they are used to help procurement teams take the first steps toward more efficient workflows.

AI Software Categories and Use Cases

Incorporating AI into existing procurement platforms can ease everyday bottlenecks. But implementation is not just about automating tasks; it gives procurement professionals better data, and delivers it faster, so they can make informed decisions in real time. This section investigates five leading categories of AI tools being used across industries today.

Predictive Analytics

Predictive analytics help procurement professionals plan by analyzing past spending, supplier lead times, and market trends. With those insights, buyers can estimate what parts they will need and when, reducing the chances of overordering and ensuring resilience amidst unexpected shortages. Tools like SAP Integrated Business Planning (IBP) and Kinaxis Maestro (formerly known as RapidResponse) incorporate external data (e.g., economic trends, weather, supplier performance) to help adjust forecasts in real time.

Robotic Process Automation

Robotic process automation (RPA) handles routine procurement transactions. When combined with AI, it goes beyond its ordinary use case by reading documents, identifying errors, and initiating workflows. For example, RPA can find pricing mismatches in invoices or autofill purchase orders based on patterns. Companies use platforms such as UiPath and Automation Anywhere to reduce time spent on purchase requisitions, contract approvals, and payment reconciliation.

Intelligent Content Extraction

Content extraction tools pull structured data from unstructured documents. Procurement professionals often work with contracts, supplier quotes, and bills of materials (BOMs) in PDF or scanned formats. AI-powered content extraction tools use natural language processing (NLP) and machine vision to extract relevant data like part numbers, quantities, and terms, and then convert them into usable formats. Tools like ABBYY FlexiCapture and Tungsten Automation (formerly Kofax) digitize and organize records without manual entry.

Supplier Risk Intelligence

Risk intelligence tools help identify supplier or geopolitical hazards. Combining AI and real-time data helps evaluate a supplier’s financial health, delivery history, and vulnerability to global disruptions like natural disasters. Tools from companies like Resilinc and Dun & Bradstreet are used to maintain supplier scorecards and alert teams when risk thresholds are crossed.

BOM Analysis

BOM analysis tools help manage lifecycle risks and part availability by inspecting BOMs to identify obsolete or soon-to-be-obsolete components, source bottlenecks, and address compliance concerns. These tools can also suggest alternative parts based on function, footprint, and availability.

As with any technology, difficulty and cost vary. However, these AI-powered tools are designed to help procurement professionals spend less time on low-value tasks and more time making educated sourcing decisions.

Common Barriers to AI Adoption

If AI benefits are becoming clearer, why aren’t more organizations incorporating it into their procurement workflows and systems? This is largely because digital transformation, which includes AI integration, requires more than just software. Adopting AI is a concerted effort that involves aligning systems, teams, and priorities.

Although these tools are becoming more widely available, many procurement teams don’t make it past the exploration phase. Some teams launch pilot programs but encounter obstacles that derail progress before they can experience the full value. Often, this is not because the technology doesn’t work but because teams are introducing the technology into an unsuitable or unprepared environment.

According to Deloitte’s 2023 Global Chief Procurement Officer (CPO) Survey,[2] the top barriers to AI adoption include the following:

  • Conflicting priorities: Procurement teams often juggle urgent sourcing needs, cost control, and risk mitigation. Without providing a clear link to immediate business outcomes, AI initiatives tend to lose traction.
  • Outdated technology infrastructure: For AI tools to work well, they need clean, connected systems. Outdated enterprise resource planning (ERP) platforms or siloed data can limit effectiveness.
  • Talent constraints: Many teams lack the in-house expertise or time to manage implementation and ongoing use.
  • Lack of funding and executive buy-in: Without clear ROI data or support from leadership, AI-related investments are less likely to be adopted.
  • Data quality issues: AI can’t generate actionable insights if the available data is incomplete or inconsistent.

Incorporating AI in procurement is more than just upgrading systems. Recognizing the key roadblocks is the first step toward progress.

Practical Wins to Get Started

It’s important to recognize that procurement teams don’t have to implement AI all at once, as many successful transformations started small. Teams that focus on urgent needs and use tools that fit existing workflows can build momentum even without a large budget or complete support in the organization.

Here are a few strategies to help teams move forward:

  • Start with one process: Instead of overhauling multiple systems at once, identify one manual, time-consuming task to automate, like invoice validation, supplier onboarding, or data extraction. If this is successful, it can show value and create internal support.
  • Use your own data to build a case: Internal data will help determine the potential impact. How many hours does the team spend manually processing purchase orders each week? What's the cost of late payments due to slow approvals? Comparing internal data to industry benchmarks can show the ROI, allowing teams to make a stronger case for AI.
  • Get other teams involved: It is helpful to involve any departments that might be affected, such as IT, finance, and legal, early on. Shared ownership helps boost long-term success.
  • Work on existing data: Even the most advanced AI tools rely on quality data. Clean, consistent data improve outcomes. Supplier names should be standardized, duplicates removed, and BOM files centralized, where possible.
  • Use low-cost, minimal-lift tools: Integrating spreadsheet add-ons, browser-based summarizers, or modular approval tools creates quick gains without complexity. This may help justify broader transformation later.

AI Tools for When You Do Not Have Buy-In

Fortunately, plenty of tools work with the systems already in place, allowing teams to take things one step at a time. These tools are helpful for smaller teams or anyone trying to implement automation on a limited budget. The following lightweight solutions can help teams introduce automation without requiring a major investment.

Spreadsheet-Integrated Tools

Procurement professionals already rely on applications like Microsoft Excel and Google Sheets for tasks like bid tracking and spend analysis. AI plug-ins, such as SheetAI for Google Sheets or Power BI with Microsoft Azure Machine Learning (ML) integrations, can enhance existing tools with features like smart summarization, part comparison, or anomaly detection.

Online AI Assistants

Teams use AI chat tools like ChatGPT or Claude to simplify everyday procurement tasks, such as summarizing supplier contracts, extracting key terms from requests for quotes (RFQs), or even drafting response emails.

Spend Management and Approval Tools

Tools like Procurify or Zip automate intake, monitor spend, and generate budget alerts. These cloud-based tools require minimal IT setup.

Tools from Distributors

Certain distributors may offer digital tools such as BOM managers, part comparisons, and real-time inventory data to simplify sourcing decisions. These tools can even include intelligent recommendations or risk indicators for faster decision-making.

All the tools in this section provide a more practical, low-risk way to test automation while helping procurement teams reduce manual work and exhibit early value without full buy-in.

Conclusion

Adopting AI technology in procurement departments doesn’t always require a major systems overhaul. Often, it starts with something simple like automating a routine task or finding a faster way to get information from supplier documents. Small changes like these free up time and improve decision-making.

Regardless of team size, there are many options to help procurement move faster, reduce risk, and control costs. AI can help make the work easier and the team more effective.

 

[1]https://www.thehackettgroup.com/hackett-world-class-procurement-organizations-see-21-percent-lower-labor-costs-while-digital-transformation-continues-to-raise-the-bar-on-procurement-performance/
[2]https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-2023-global-chief-procurement-officer-survey.pdf

The article is for informational purposes. Mouser does not endorse or promote any of the products.