In this exclusive three-part series for PASA, Antonia Macrides, chief growth officer at FinTech, explores how AI automates and optimises procurement, from improving control and reducing errors to managing expenses, streamlining workflows and handling contracts, leading to both time savings and long-term value.
The series begins by delving into Generative AI (GenAI).
In Part 2, Antonia pivots to Machine Learning and Predictive Analytics, showcasing their invaluable contributions to supplier management and decision-making.
Finally, in Part 3, she explores the emerging realm of negotiation bots, addressing the ethical considerations of AI in Procurement and reflecting on its broader socioeconomic impacts.
Procurement is radically transforming with the introduction of Artificial Intelligence (AI). The potential is huge. Is that an enormous overstatement? Amara said that society tends to overstate the short-term effects of technology while underestimating its long-term implications.
With each passing moment, AI is refining its ability to sift through and systematise sprawling datasets. It grows more efficient and sophisticated with time.
Today, AI excels at marshalling large volumes of data — some readily available, some previously siloed — and synthesising this information to forge connections and insights that traditional processes could not achieve.
The shift from rule-based systems to AI marks a change in what kind of data can be used and how data is used.
Because it’s hot right now, let’s start with GenAI!
GenAI is an evolutionary leap in AI that took the world by storm in 2023 with the proliferation of tools like Chat GPT, Gemini (xBard), Claude, HuggingChat, etc.
According to McKinsey (2023), GenAI is poised to significantly impact operations, particularly in document creation and analysis tasks.
What exactly is GenAI?
GenAI produces novel information (somewhat) by reflecting on the patterns found in its training data.
This branch of AI, illustrated by models such as Generative Adversarial Networks (GAN), involves a collaborative effort between a Generator, which crafts new data, and a Discriminator, which evaluates its quality, thus ensuring the creation of refined and contextually relevant outputs.
ChatGPT and other Large Language Models (LLMs) exemplify GenAI’s utility by generating, understanding, analysing and critiquing text and providing insights. These models are transforming the landscape by automating tasks and enriching decision-making processes.
And in procurement, this is no exception.
GenAI lends itself well to market analysis, spend analysis, opportunity analysis and the creation and assessment of strategic sourcing documentation, like requests for proposals (RFPs), supplier evaluation and contract development.
Use case: spend analytics
Historically, spend analysis and classification have been managed through rule-based systems and manual processes.
This approach can often lead to inefficiencies, such as time-consuming data classification and inconsistencies due to subjective interpretations.
Procurement leaders have long faced difficulties standardising these processes, and procurement departments frequently grapple with overlapping IT systems, resulting in data inconsistency and consolidation problems.
Enter Gen AI, which offers a novel perspective by enhancing the way data is classified, moving beyond previous limitations.
The inflexibility of past AI systems often stemmed from poor data quality, leading to unreliable outputs.
GenAI, however, can interpret and process data with greater context and flexibility, making it particularly adept at understanding diverse data types and improving classification accuracy. It can potentially process line-item data with a high degree of accuracy.
This means that even if an organisation has poor data quality, GenAI could still classify it correctly to a high degree, which was previously unachievable.
Note that this may create a data privacy issue since a team member may inadvertently expose strategic information if it is not adequately secured. This is explored further in Part 3.
Here’s the real kicker: GenAI’s explainability (or XAI) — gives it the edge by offering clear explanations for its decision-making processes.
Where traditional systems often confuse us (“why was this classified as that?”), GenAI can articulate the reasoning for each categorisation. This, in turn, makes you confident in categorisation and the subsequent insights.
This feature is invaluable for Data Scientists as it navigates the delicate balance between model simplicity and accuracy.
Simple models, while more transparent, may compromise on precision, whereas highly accurate models typically sacrifice explainability.
GenAI, however, strives to deliver both.
Your colleagues are using GenAI. There, I said it.
Acknowledging the presence of GenAI in the workplace might raise eyebrows. Still, it may be integrated into daily operations more than you might realise.
From crafting detailed RFx documents to dissecting market trends and evaluating potential suppliers, GenAI is an excellent support.
As McKinsey’s research shows, these technological advancements are set to automate an impressive 60-70 percent of tasks that currently fill employee hours in knowledge-centric roles, indicating a sizeable uptick from previous estimates.
Beyond procurement tasks, it’s also quietly powering through other activities like resume writing, job applications and simulating salary negotiations, providing a competitive edge in career advancements.
Your next ‘hire’: GenAI
GenAI extends far beyond text generation, offering a broad spectrum of applications that revolutionise various applications within procurement.
It automates and improves a range of tasks, from analysing vast quantities of vendor data to generating insightful reports and simulating procurement scenarios for predictive outcomes.
Moreover, GenAI extends to enhancing ‘soft-skill’ tasks such as stakeholder engagement, crafting persuasive communications and employing nuanced negotiation tactics.
By leveraging natural language processing and sentiment analysis, GenAI can guide procurement professionals in tailoring their approaches to stakeholder influencing, ensuring that communication is practical and strategically aligned with organisational objectives.
Clearly, GenAI is not just an auxiliary tool but a fundamental driver of efficiency, innovation and strategic decision-making in procurement processes, potentially reshaping how procurement is conducted and managed.
Such a shift necessitates a re-evaluation of the roles and responsibilities within procurement teams.
Are you thinking about GenAI’s potential impact?
Have you explored the specific problems GenAI can solve for your procurement function? To spark deeper thinking and planning around this, here are some thought starters:
1. Strategic Alignment: How does GenAI complement our procurement strategy and organisational objectives? Identifying the specific challenges GenAI can address is crucial, ensuring a clear path to value creation
2. Priority Use Cases: Identifying immediate and future opportunities for GenAI applications is essential. Which procurement processes can benefit immediately, and which areas might become viable for GenAI enhancement over time?
3. Risk Management: Deploying GenAI comes with risks, including concerns around data privacy, compliance and operational integrity. Planning for risk mitigation is a must to safeguard against potential pitfalls
4. Impact on Workforce: The introduction of GenAI will inevitably reshape the roles and responsibilities within procurement teams. Proactively planning for re-skilling and up-skilling, alongside fostering a culture of innovation and adaptability, will be vital to harnessing GenAI’s full potential
5. Measurement of Success: Establishing clear metrics to evaluate the success and return on investment of GenAI initiatives is critical. Tracking the right key performance indicators will illuminate the efficiency gains, cost savings and strategic enhancements brought about by GenAI.
These questions are designed to guide you through the initial phases of integrating GenAI into your procurement operations, ensuring a thoughtful, strategic approach to harnessing this powerful technology.
As we’ve explored the transformative power of GenAI in procurement, it’s clear that the landscape of its use is evolving.
From strategic sourcing and contract management to operational purchasing, GenAI offers promising avenues for innovation in procurement.
This is just one element of AI’s journey in transforming procurement practices.
Are you fully leveraging the potential impact of AI within your procurement strategy?
In the next part of our series, we’ll delve into Machine Learning and Predictive Analytics to further enhance supplier management and decision-making processes, marking another step forward in this evolution.
About the author:
Antonia’s interest in behavioural economics has led her to blend technological expertise with psychological insights. Antonia founded Australia’s first boutique procurement recruitment firm and has since worked with organisations to map and measure procurement capability using technology with a track record in tech and AI, specifically in NLP and machine learning applications. Educated in research, psychology, theology and certified in AI, Antonia understands the human factors influencing procurement.
To learn more about GenAI, secure your place now for ProcureTECH ‘24 – the largest independent eProcurement conference in the ANZ region, which takes place online on 20-21 March.
