AI Use Cases to Supercharge Procurement

AI in procurement

Karen BonifacioArtificial Intelligence (AI) in procurement is growing in popularity due to the advancements in technology, writes Karen Bonifacio, SEO Specialist/ Content Writer at Procurement Tactics, in Utrecht, Netherlands. In this article, she answers key questions: what is AI and how does it change the procurement industry?

Artificial intelligence is integrated into every device that is available today. But what is it?

When we think of AI today, we first think of robots that are capable of doing human tasks. We even think of Siri and Alexa when we talk about AI. However, this is just a part of the large scope of AI.

AI is used in every aspect of our lives. Almost everything that we use is AI-driven and AI-based. It is the ability of a digital computer to simulate or mimic human intelligence processes.

AI systems work by learning and analysing the data for correlations and patterns to make predictions of future states. AI programming focuses on three skills, namely reasoning, learning and self-correction.

AI is intended to help enhance human capabilities and to make tasks simple and fast to process. Contrary to what many people believe, AI does not replace humans, but rather integrates into everything they use in today’s world.

Here are some examples where AI is used today:

  • Self-driving cars
  • Manufacturing robots
  • Virtual assistants
  • Chatbots
  • Natural language processing tools
  • Facial recognition
  • Navigation apps
  • Media recommendation
  • Online banking
  • Smart appliances
  • 3D photography

Now, let’s talk about AI in procurement. AI in procurement is a software solution that intends to resolve tasks in the procurement process. Because AI is software, it has a huge potential to improve and adapt any work practices, no matter the size of an organisation.

Many people misunderstand AI. In terms of procurement, AI is not a sentient being that is capable of replicating human movements as you see in movies.

AI should not be considered as a replacement for human expertise but as a facility to help the procurement process. Many AI software solutions still require the active assistance of a procurement expert.

Types of AI in Procurement

  1. Machine Learning (ML)
    Machine learning is an algorithm that detects patterns. The detected patterns are used for prediction or decision-making in the procurement process.
  2. Robotic Process Automation (RPA)
    This algorithm copies human actions to reduce repetitive simple tasks. Although RPA offers many opportunities for procurement to improve, it should not be considered as AI.
    Think of RPA as a software robot that copies human behaviour, while AI is the simulation of human intelligence.
  3. Natural Language Processing (NLP)
    Natural language processing is an algorithm that interprets, generates and transforms human language. It can also analyse and understand human languages.

The Benefits of AI in Procurement
The following are some of the benefits that are to be gained by implementing AI in procurement:

  1. Cost optimisation
    Through improved supplier selection, contract management and demand forecasting, AI enables organisations to negotiate better deals, curtail uncontrolled spending and realise significant cost savings.
  2. Scalability and adaptability
    AI systems can efficiently handle large data volumes and adapt to evolving business requirements and market dynamics, scaling to accommodate growth and delivering real-time insights for agile decision-making.
  3. Continuous enhancement
    AI systems continually learn and improve through machine learning algorithms and identifying patterns, trends and anomalies, to enable ongoing optimisation of procurement processes and outcomes.
  4. Streamlined operations
    AI’s ability to automate manual tasks boosts efficiency, accelerates processes and reduces administrative burdens, allowing your procurement team to focus on strategic activities.
  5. Improved risk management
    AI can proactively detect patterns of fraud, assess supplier financial stability and identify potential disruptions in the supply chain, allowing organisations to take preventive measures and safeguard against operational and reputational risks.

The Challenges of AI in Procurement
Although AI has a lot of benefits, many companies may also face the following challenges when implementing AI in procurement:

  1. Data challenges
    AI heavily relies on data quality and availability, and the scattered nature of procurement data can pose a challenge. To counter this, you must know how your organisation can enhance data quality and ensure its availability.
  2. Overcoming resistance
    The successful implementation of AI in procurement requires overcoming resistance to change and addressing fears of job displacement. You must learn about strategies to foster a positive mindset and gain buy-in from procurement professionals.
  3. Building AI expertise and skills
    Effective use of AI in procurement needs a skilled workforce. Thus, you must invest in upskilling and reskilling initiatives and provide training programmes that can equip procurement professionals with the necessary expertise.
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