The AI Revolution is Coming: How Procurement Pros Can Prepare

Why AI is Critical for the Future of Procurement

The age of artificial intelligence is upon us. AI and automation are transforming industries across the board, and procurement is no exception. In fact, AI has the potential to revolutionize procurement in game-changing ways.

According to our recent survey, 78% of procurement leaders believe AI will disrupt the profession within just 3-5 years. For procurement teams, implementing AI is not a matter of if, but when. The organizations that embrace AI early will gain a real competitive advantage. They’ll be able to reduce costs, risks and cycle times while freeing up budget for more strategic initiatives.

The message is clear: to remain relevant in the coming years, procurement must prepare now for the AI era. The transformation has already begun. This article explores the coming impact of AI on procurement and provides advice for preparing your team to harness the power of intelligence automation. The future starts today.

Current State of AI in Procurement

Artificial intelligence is transforming businesses across industries, and procurement is no exception. The most common applications include analysis of spend data, contract lifecycle management, supply chain risk assessment, and supplier discovery.  

While AI adoption in procurement is still in an early stage, its growth has accelerated rapidly in recent years. The IBM survey found AI adoption in procurement jumped from 20% in 2018 to over 50% in 2021. This trend will likely continue as organizations realize the significant cost savings and process efficiencies enabled by AI. For procurement teams, AI promises to automate repetitive tasks, find hidden insights in data, and improve strategic decision making.

Benefits of AI in Procurement

AI and automation can provide significant benefits for procurement teams. Some of the key ways AI can improve procurement include:

Leveraged procurement intelligence

• AI tools can quickly analyze large volumes of spend data and identify patterns, risks, and opportunities that may be difficult to uncover manually. This provides procurement with greater visibility into spending.
• Natural language processing allows AI systems to read contract details, invoices, and other documents to extract key insights. This automates the data collection process.
• Machine learning algorithms can categorize spend, detect anomalies, and highlight areas to target for savings such as maverick spend.

Procurement Intelligence: Leveraging data for smarter sourcing decisions

Enhanced contract management

• AI can speed up contracting by automatically reviewing agreements for errors, risks, and compliance issues. This reduces the manual review burden.
• Systems can match contracts to purchase orders and invoices to ensure proper execution. They can also provide alerts around key deadlines like renewals.
• Automating routine tasks like extracting terms and conditions allows procurement teams to focus their efforts on high-value strategic activities.

Transforming Supplier Contract Management: The Power of Digital Technologies

Improved supplier development

• AI tools use advanced market intelligence to identify potential new suppliers that meet sourcing needs, widening the pool beyond existing partners.
• These systems score suppliers on parameters like quality, pricing, delivery reliability and financial health to assess fit, enabling the ability to make more informed decisions.
• Automating supplier onboarding and conducting due diligence processes are faster and reduce administrative tasks for buyers.

Supplier Development – Practical Guide to Leveraging Technology

AI automation enhances productivity in key areas of the source-to-contract process, enabling procurement to operate more efficiently.

Use Cases

AI is transforming key procurement processes in the following ways:

Spend Analysis

AI can extract data from contracts, invoices, and other documents to map out spending patterns across the organization. Advanced analytics identify opportunities to consolidate purchases, reduce maverick spending, and leverage economies of scale.

Invoice Processing

AI automation tools can extract key data from invoices and cross-check against contracts and purchase orders. This reduces processing costs and ensures compliance with negotiated terms.

Market Intelligence

AI-powered market intelligence tools continuously scan multiple data sources to identify changes in supply markets. This allows procurement teams to spot issues and opportunities early.

Challenges

Implementing AI in procurement can come with some key challenges that organizations need to be prepared for:

Data Quality

AI systems are only as good as the data they are trained on. Low quality, inconsistent, or insufficient data will result in poor AI performance. Organizations need to invest in improving data infrastructure, collection, and cleaning to ensure high quality input data for AI systems.

Change Management

Transitioning to AI-driven processes requires change management to get buy-in across the organization. There may be cultural resistance, lack of understanding of AI, and concerns about job security that need to be proactively addressed through training, communication, and leadership.

Skills Gap

The specialized skills needed to develop, implement, and manage AI systems are in short supply. Organizations will need to reskill existing procurement teams or acquire new talent with experience in areas like data science, machine learning operations, and AI ethics; building multidisciplinary teams is key.

Building an AI Strategy

As with any new technology implementation, having a solid strategy is key to successfully adopting AI in procurement. Here are some tips for building an effective AI strategy:

• Assess needs and identify use cases – Carefully evaluate your current procurement processes and pain points; look for repetitive tasks and bottlenecks that could benefit from automation. and talk with stakeholders to understand what challenges they face. Next pinpoint realistic use cases where AI could provide value, whether it’s automating invoice processing, analyzing spend, or improving supplier discovery.
• Develop a phased roadmap – Don’t try to implement AI across procurement overnight. Create a multi-year roadmap focused on rolling out AI in phases, starting with pilot projects. Quick wins can build confidence and momentum for more advanced use cases later. Prioritize high-impact areas first.
• Start with narrow AI – Broader artificial general intelligence does not exist yet. Focus your strategy on narrow AI that specializes in specific tasks. Choose vendor solutions tailored for procurement versus general-purpose AI.
• Plan for change management – Adopting AI will require changes in processes, skills, and mindsets. Develop a proactive change management plan. Train procurement staff on using new AI tools. Clearly communicate the benefits of AI to build buy-in across your organization.
• Consider risks – AI can raise valid concerns around transparency, bias, and job loss. Develop an ethical AI approach that monitors for risks and bias in algorithms. Look at AI as an aid, not a replacement for procurement specialists. Focus AI on enhancing workers rather than replacing them.

Getting Buy-In

Getting organizational buy-in and support is critical for a successful AI implementation. When presenting an AI strategy to leadership, focus on clearly communicating the benefits:

• Cost savings and process efficiencies – Highlight how AI can drive significant cost reductions through increased procurement productivity and process optimization. Show benchmarks and use cases from other organizations.
• Better spending decisions – Emphasize how AI-driven insights, predictions, and recommendations will empower procurement to make more strategic sourcing decisions. Demonstrate how AI can help identify savings opportunities.
• Enhanced supplier relationships – Explain how AI can enable a proactive, collaborative approach with suppliers through real-time visibility, risk monitoring, and joint process improvements. Stress the benefits of optimizing relationships.  
• Competitive advantage – Underscore how AI-powered procurement will establish a competitive edge through accelerated velocity, mitigated supply chain risks, and greater resilience to market changes. Connect AI capabilities with key business goals and KPIs.
• Future-proofing – Highlight that AI investments future-proof the function, equipping procurement with cutting-edge capabilities that will soon become a new norm. Proactively adopting AI ensures the function won’t get left behind.

To gain buy-in, the business case must resonate with leadership priorities. Emphasize the tangible benefits AI will deliver for savings, productivity, relationships, and competitiveness. With a compelling vision, procurement can secure the sponsorship needed to implement AI successfully.

Preparing Your Team

As you implement AI, you’ll need talent that can build, deploy, and manage AI applications. Consider hiring data scientists and machine learning engineers. They will be key in developing custom AI solutions tailored to your procurement needs.

It’s also important to train your current employees on AI. Explain how AI will impact their roles and what new skills they may need to learn. Provide resources and training to upskill employees on working alongside AI. Some areas to focus on include:

• Basics of AI, machine learning, and data science
• Tools like Python, R, SQL, and visualization software
• Statistical analysis and critical thinking
• Understanding AI model outputs and limitations
• Ethics and responsible use of AI

Your procurement team’s deep knowledge of sourcing strategies, supplier markets, and category management is invaluable. Coupling this with the ability to leverage data, run analyses, and interpret AI insights will be a key differentiator. Focus on developing these blended skill sets in your team.

Build a culture of learning; sponsor employees to take courses and certifications in AI and data science. Foster internal experts who can share knowledge. Being proactive will ensure a smoother transition when adopting AI in procurement.

Measuring Success

To measure the impact of AI in procurement and ensure continuous improvement, focus on tracking these key metrics:

• Cost savings – Track how much money is saved over time by automating tasks, getting better prices from suppliers, reducing maverick buying, etc. Set goals for cost reduction.
• Contract cycle times – Monitor how long it takes to complete each stage of the contract lifecycle with AI automation versus manually. Faster cycle times increase productivity.
• Supplier performance – Use AI to continually assess supplier quality, delivery times, responsiveness, and pricing against agreements. Quickly identify issues.
• Process efficiency – Calculate processing times for procure-to-pay, quote-to-order, and other workflows. AI should drive increased efficiency over time.
• Maverick spending – Measure the percentage of spending that happens outside of preferred vendors and contracts. AI tools can help identify and reduce maverick spending.
• Forecast accuracy – Compare actual spending to forecasts produced by AI. Continually tune forecast algorithms to improve accuracy.
• User adoption – Monitor usage rates for AI tools. Work to increase adoption across the organization through training and communications.

By regularly measuring performance across these metrics, procurement teams can prove the value of AI, fine-tune solutions, and expand deployments to maximize the benefits. Tracking metrics leads to continuous improvement on the AI-enabled journey.

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