Artificial Intelligence, one of the Buzzwords in technology, is also getting its hold over domains like Procurement, Finance, etc. The impact, benefits, and adoption of AI in Procurement is not a quick process with instant results; but rather it is a journey towards short-term benefits, medium-term benefits, and long-term benefits. With relation to AI, let’s deal with Procurement at a greater depth!

Artificial Intelligence in Procurement

Procurement, being the most important part of a Business Process, can never fully be replaced. Imagining an AI-based Procurement without Human Intervention is next to impossible. Rather, the introduction of AI in Procurement should be taken as the entry of a new efficient member who would fasten up the workforce. Specifically, automation of time-consuming and repetitive tasks is the main problematic area, for which AI will provide direct solutions. So, what forms the basis of artificial intelligence in Procurement? Though some of the terms are common and hyped, there are still some other terms that need proper limelight and understanding when we’re talking about AI in Procurement Procedure. These terms include:

Artificial Intelligence (AI)
Machine Learning (ML)
Natural Language Processing (NLP)
Robotic Process Automation (RPA)

All the above-mentioned terms operate on algorithms. Algorithms refer to a set of instructions that are specific for a given problem. Here comes Human Intervention, which we tend to ignore when dealing with ai and procurement. Algorithms aren’t something that a machine or bot would design on its own. It is programmed and re-programmed by experts to deal with those repetitive problems.

Now what kind of problems would AI in Procurement solve?

Risk Management: Algorithms allow risk managers to respond faster to repetitive and burdensome areas of risk management.
Vendor Matching: Systematic connection of supplier data that is contained in invoices to a vendor hierarchy via ML Algorithms.
Capturing Market or Supplier Data: Use of NLP (Natural Language Processing) to search and capture data on supplier markets.
Anomaly Detection: Automatic detection and insights for unexpected changes, that are related to Procurement
Account Payable Automation: Fastening up payment procedure and fraud detection for a smooth workflow.
Strategic Sourcing: Recognition of Bid Sheets and Introduction of Bots for specific e-Sourcing like for raw materials.
Optimizing Supplier Relationships: Improving Supplier-Customer Relationship by making it more data-informed.

The Untouched but impactful areas

JIT Financing (bill factoring & discounting) already is popular among the supplier community, and there is a play for AI in prediction, suggestion, and even execution. Newer areas like personalized finance plans and payment plans, funding, credit check, and scoring would be assisted or automated through AI.

The Biggest Question

The most common question raised regarding AI and ml in Procurement is:

Will AI ever take over Procurement Process completely?

To answer this question from a wide perspective, AI is not used to “Automate Jobs”, but rather it is about “Automating Tasks”.

Supplier Transformation Assistant

The success of procurement automation heavily revolves around suppliers. Many parameters like suppliers’ communication, relationship, working model and collaboration, quality, compliance, and goodwill denote whether procurement is strategic or not!

Tasks that most people deal with including hectic paperwork, scheduling, appointing meetings, and assigning tasks could be automated with the help of AI.

Factors to Implement Effective AI Strategy in Procurement

Essential categories like Supplier Portal, Contract Management, Procure-to-Pay, and Supply Chain Financing are required to frame an automated strategy that would act as a critical enabler in the provision of the best experience. Embracing AI in Procurement is the most efficient way of enhancing the performance and outcome of the Enterprise.