6 Procurement Tasks You Can Confidently Hand Over to AI

While AI is fast making inroads into all facets of procurement, there are some procurement tasks which can be handed over to AI immediately given the level of maturity the algorithms have reached. AI can help automate various high-volume repetitive tasks that burden procurement teams today. This provides quick productivity wins and allows reallocation of staff to more strategic initiatives.

Some of these prime opportunities include:

Spend Analysis:

Spend analysis used to require extensive manual parsing and categorization of purchase data. Advanced AI/LM techniques can rapidly process millions of transactional records from disparate systems to categorize, cleanse and enrich spend data. The enriched dataset reveals spend patterns, quantifies purchasing efficiencies, identifies savings opportunities, and enables strategic category management.

Supplier Discovery:

Finding new qualified suppliers has typically depended on manual outreach and inefficient web searches. AI automation leverages vast supplier databases, pairs them with public data on certifications and capabilities, and rapidly matches requirements with qualified suppliers globally. This expands procurement’s reach and provides more negotiation leverage.

Contract Lifecycle Management:

AI capabilities like optical character recognition extract key data contained in contracts in seconds. This data populates contract repositories to provide end-to-end visibility. AI tracks milestones such as contract renewals, identifies opportunities to improve terms upon renewal, and monitors partner adherence. This optimization and oversight mitigates many procurement compliance risks.

Invoice Processing:

Processing invoices is labor intensive, as accounts payable teams must validate agreement with POs, confirm delivery, check accuracy, and handle approvals. AI tools, on the other hand, ingests invoice data instantly via OCR, cross-check with contracts and purchase records, flag any discrepancies, and route valid invoices for touchless processing and payment. This creates massive efficiency gains.

Demand Forecasting:

By synthesizing datasets like historical consumption, market conditions, promotions, and upstream supply forecasts, AI demand forecasting generates very accurate projections. This facilitates procurement optimization of inventory buffers and safety stock to avoid shortages. AI provides the supply chain visibility needed to respond quickly to changes.

Conclusion

Applied AI techniques such as machine learning, natural language processing, and intelligent process automation can automate many of the procurement tasks. This amplified productivity, cost savings, and insights free procurement leaders to pivot from task doers to value creators across the organization.

Here’s how GEP is using AI to transform enterprise procurement processes.