Shaz Khan is the CEO and co-founder of procurement platform Vroozi. All opinions are the author’s own.
As a child, I loved reading the Encyclopedia Brown series. What made the books so engaging is that they challenge the reader to choose a path, and then based on those options, Encyclopedia Brown either faced a dead end or solved the case. While it was fun to play out these scenarios in fiction, the networked business and global economy requires the capability to sift through hundreds of thousands of clues to provide reliable answers and simulate scenarios accurately and quickly.
Artificial intelligence is on the cusp of removing many of the mysteries from procurement decision-making entirely. If we are able to feed reliable and clean data into an AI engine, we can produce confidence scores with a greater degree of accuracy. Moreover, AI has the ability to deliver these results faster than humans can, regardless of combined expertise. With AI, solutions that would potentially take months or years to figure out can happen with the flick of a finger.
AI will reshape the procurement landscape by empowering procurement professionals to do their jobs more efficiently, completely revolutionizing their company’s ROI. Supply chain insights with price predictions, category management and supplier identification, and working capital optimization are just a few of the possibilities to create financial and productivity results.
As we embrace and integrate this technology into the industry, here are some key considerations to maximize benefits while minimizing risks.
Reshaping the procurement landscape
Using AI in procurement practices comes from the cumulative power of cross-department and stakeholder participation. Procurement professionals and organizations can reap multiple benefits from price points, product quality, lead time, supplier identification and relationship building across finance, sales and suppliers.
For example, AI can identify suppliers within any given spend category to match competitive pricing, optimizing cost efficiency and supplier performance. However, AI segments suppliers not just based on cost, but by rating a supplier’s risk profile in real time, discovering their sustainability practices, outlining their capacity to deliver and capturing the supplier’s historical performance.
The use of large language models can make sense of large volumes of unstructured data by extracting the relevant information, significantly enhancing the decision-making process. Data about the latest market trends, technological advancements and regulatory changes that could impact sourcing strategies. Assessing which suppliers meet the company’s criteria in terms of reliability, quality, cost-effectiveness and ethical practices, further facilitates a more informed selection process.
AI also has the ability to automate workflows within the procurement cycle. The technology can analyze historical purchasing data, usage rates and inventory levels to automatically generate requisition orders — allowing procurement leaders to easily keep track of inventory. Further, AI tools can process invoices and payments. Automating the process can reduce processing times, avoid late payment penalties and take advantage of early payment discounts.
Although the advent of AI is still relatively new in the procurement cycle, we have already realized many capabilities for AI to populate data for a given transaction within seconds.
Ethical considerations of AI in procurement
Accurate and current data is a major concern when it comes to the ethical use of AI in procurement. Effective supplier management relies on comprehensive and current data about supplier performance, reliability and risk factors. Incomplete or outdated data can lead to incorrect assessments of suppliers, potentially impacting partnerships and relationships.
The effectiveness of predictive analytics also depends on the accuracy and currency of the data fed into the system. Populating AI with dirty data can spur poor predictions, leading to overstocking, stockouts and missed opportunities for cost savings. The financial health of a business is tightly linked to its procurement strategy and failing to identify these opportunities can impact a company’s financial performance and cause it to lose a competitive advantage.
The ultimate area of consequence in AI will relate to privacy, particularly for the buyer-supplier collaboration. Large data sets can potentially include sensitive information, which can be at risk for data breaches. We are still in the first inning of realizing the potential dangers of AI. However, by strengthening consent mechanisms, enhancing cybersecurity measures and establishing privacy laws around data minimization, we can lay the foundation to effectively address these emerging threats.
The future of AI in procurement
Maximizing AI’s potential will require companies to invest in internal training programs early and often. That could require micro-certifications in specific niche skills, such as machine learning algorithms and programming, or lengthy courses on AI and ethics at universities.
Education is the foundation, but the application of these skills is what will lead to results. The companies that employ these systems effectively and recruit the right talent that understands AI from a conceptual framework will come out ahead in the long run.
AI has the potential to empower all procurement professionals to be Encyclopedia Brown, as long as they know how to use it to extract the information they need to make a difference.
