Breaking New Ground: Could Generative AI Transform Procurement Activities for Buyers and Vendors?

2303 Blog Banner Image Generative Ai In Procurement — Breaking New Ground: Could Generative Ai Transform Procurement Activities For Buyers And Vendors? 2

Introduction

The world of procurement is changing rapidly, and companies that want to stay ahead of the curve need to embrace new technologies and innovations.

One such technology is generative AI, which has the potential to transform procurement activities.

By enabling more efficient processing of routine tasks, expediting supplier matching, automating contract and proposal analysis as well as assisting in risk management, generative AI could be a game-changer for companies looking to optimize their procurement operations.

What is generative AI?

The development of AI has continually made remarkable progress through several iterations, with generative AI being the latest generation.

The first generation consists of early AIs that relied heavily on pattern recognition using knowledge bases maintained by human experts. These AIs had to be tailored to specific problems and had a low capacity for abstraction. Examples of these AIs include early chatbots.

The second generation refers to statistical learning AIs, which utilized machine learning to analyze large amounts of data to generate their own models. This generation of AI is gaining maturity, and is found in many common applications such as speech recognition and voice assistants such as Siri and Google Assistant. However, they lack the ability to generate novel content, such as song lyrics and art.

The latest and third generation of AI is generative AI. This type of AI can create new outputs based on the data it has been trained on. While the term generative AI is often associated with ChatGPT, this umbrella term encompasses any AI technology that can create something on its own, such as writing articles and generating art. It also includes learning algorithms that can help make predictions.

What can generative AI do for procurement?

1. Streamline Routine Processes

A study by McKinsey found that out of the hundreds of individual tasks in the source-to-pay process, almost 60% can potentially be fully or largely automated using second and third generation AI. Crucially, these automation capabilities can extend beyond just transactional activities, such as order and invoice processing, but also strategic decision making, such as vendor selection and management.

This is already available via technologies such as Microsoft Viva Sales which uses generative AI to ‘read’ incoming email and draft automatic email responses. When linked to CRM systems and other sources of data, the AI can even pull up relevant information such as pricing, promotions or deadlines. This allows both buyers and vendors to save time choosing their words or digging for data and documents.

Forbes suggests that even more advanced AI tools can enable ‘touchless’ P2P processing. For example, AI can validate purchase requisitions, ensure proper approval and coding, review requirements, and match price quotes and statements of work with relevant contracts. This would allow most requisitions to be processed automatically, requiring a human touch only to manage exceptions from the norm.

2. Accelerate Supplier Matching

Traditionally, supplier search involves manually sifting through supplier databases to find the best supplier for a given requirement.

Second generation AI allows buyers to automate this process by training a machine learning system to analyze a wide range of data points, including supplier performance metrics, financial data, and industry trends. This can be applied to discover wastages, predict supplier performance, estimate supplier risk, and even approximate a supplier’s ESG score.

Generative AI takes this a step further by making the experience more human-friendly, thus reducing the skill gap for everyday users. This increases the accessibility of the technology even to technical novices.
Buyers can describe the desired product in plain language, and the AI algorithm can comb through vast databases of supplier information, including both structured and unstructured data. This can help buyers cast a wider net to identify the most suitable suppliers for their needs. At the same time, vendors benefit from the increased discoverability by a wider network of buyers.

McKinsey shares how this has already been done, such as during the early days of the Covid-19 crisis. Using AI, the procurement team of a regional government identified over 30 high-potential suppliers around the world for Covid-19 testing supplies, some of whom didn’t even currently produce the exact items needed. Within a month, the organization successfully obtained sufficient material to double its testing capacity.

3. Automated Contract and Proposal Analysis

Contract management is a complex process, involving numerous stakeholders and legal requirements. Understanding legalese is also a difficult hurdle that many buyers and vendors struggle with.

2^nd generation AI such as Microsoft Syntex paved the way for basic contract automation. Users can easily train their own unstructured document processing models to identify contract files and extract data automatically.
With generative AI, contract analysis can be further automated, enabling a wider variety of use cases. Crucially, technical and legal jargon can be translated into plain language that is more easily understood by all parties in a contract negotiation.

Evisort describes how generative AI can help with various tasks such as auto-reading contracts, highlighting areas for review, comparing contracts against company policies, generating clauses when given a prompt, and even drafting intelligent business revisions in real time.

This can even be extended to proposal or bid analysis. Vendors can take advantage of generative AI to assist in drafting or polishing their proposals, while Buyers can employ the technology to summarize, mark up and compare proposals for faster decision making.

AI technology is rapidly maturing and could soon become a mainstay in the future of procurement, helping to save time, reduce errors, and manage contract risks.

4. Risk Management

Procurement activities involve a degree of risk, not just for buyers, but also for vendors. Managing these risks is vital to ensure successful outcomes for the organization.

For Buyers, AI can assist with due diligence and risk analyses by combing through various sources such as supplier rating systems, news feeds, market trends, regulatory changes and more. At the same time, vendors can leverage the same technology to assess the background of potential buyers.

And when paired with a robust Business Intelligence (BI) system, internal transactional data can also be analyzed to flag anomalies and worrisome patterns. Together, these learning models can be a valuable early warning system to alert both buyers and vendors before anything even begins to go wrong.

This applies not just to structured supply chain data, which can be easily analyzed, but also unstructured ‘dark data’. According to IBM, dark data makes up around 80% of supply chain data which requires the help of AI that can learn in a human-like manner in order to analyze it. With the global push for increased transparency, platforms like the Open Contracting Partnership provide an exponentially growing pool of public data that is impossible to fully capitalize on without AI.

And while much of this is already possible with second generation machine learning, generative AI improves on the user experience with its ability to parse natural language prompts and respond in the same manner. This class of AI also includes explainable AI, which can provide human-understandable explanations for how they arrived at a particular conclusion, allowing for greater trust and transparency in risk analyses.

Challenges for generative AI in procurement

Nevertheless, the implementation of AI in procurement is still in its early stages and faces several challenges. Some of these hurdles identified by the World Economic Forum include data governance, leadership and ethics.

Data governance – This refers to the process of managing and leveraging data in a way that is both secure and efficient. Different organizations have varying levels of data maturity, and this can make it difficult to successfully implement AI in procurement without compromising data security.

Leadership – The adoption of AI requires a multidisciplinary team, technical expertise, and partnership between buyers and vendors. The skills gap in AI procurement is potentially much bigger than conventional procurement, which means that it may take longer to get up to speed. Mindset shifts and a greater appetite for risk are also needed to address this challenge.

Ethics – Transparency, interpretability, and auditability are important considerations when using AI in procurement. Ensuring that AI solutions adhere to ethical guidelines is critical to building trust between the buyers and vendors. This is particularly of concern as lawsuits have already been filed against generative AI that was trained on art without the artists’ permission.

Conclusion: The future of procurement with generative AI

The transformative potential of generative AI for procurement is clear. By streamlining routine procurement processes, supplier matching, contract analysis and risk management, generative AI has the power to revolutionize procurement operations and bring significant benefits to buyers.

However, as with any emerging technology, there are challenges to overcome. The implementation of AI in procurement is still in its early stages and requires careful consideration of issues such as data governance, leadership and ethics.

Despite these challenges, the future of generative AI in procurement looks bright. As a Microsoft Partner, our WeManage team is looking forward to further developments in the field, especially as Microsoft is actively partnering with OpenAI. Already, generative AI like ChatGPT is being made available through Microsoft’s Azure OpenAI Service. As the technology matures, we look forward to exploring new tools to help improve our users’ experience.

*Cover Image by Freepik.

Breaking New Ground: Could Generative AI Transform Procurement Activities for Buyers and Vendors?

Introduction

What is generative AI?

What can generative AI do for procurement?

Challenges for generative AI in procurement

Conclusion: The future of procurement with generative AI

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Introduction

What is generative AI?

What can generative AI do for procurement?

Challenges for generative AI in procurement

Conclusion: The future of procurement with generative AI

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