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Shaz Khan is CEO and co-founder of procurement platform Vroozi. All opinions expressed are the author's own.
As a kid, I loved reading the Encyclopedia Brown series. What made these books so compelling was that they forced the reader to make career choices that would either stall Encyclopedia Brown or solve the case. While it's fun to act out these scenarios in fiction, networked businesses and global economies require the ability to accurately and quickly simulate scenarios, sifting through hundreds of thousands of clues to come up with reliable answers.
Artificial intelligence is on the verge of completely removing much of the mystery in procurement decision-making. With reliable, clean data fed into an AI engine, it can generate more accurate trust scores. What's more, AI has the ability to deliver these results faster than humans, regardless of their mix of expertise. With AI, solutions that could take months or years to resolve can now be achieved with the flick of a finger.
AI is reinventing the procurement landscape by empowering procurement professionals to operate more efficiently, revolutionizing enterprise ROI. Supply chain insights through price forecasting, category management and supplier identification, and working capital optimization are just some of the possibilities that drive financial and productivity outcomes.
As you adopt and integrate this technology into your industry, here are some key considerations to maximize the benefits while minimizing the risks.
Restructuring the Procurement Environment
The use of AI in procurement operations comes from the cumulative power of cross-functional and stakeholder participation. Procurement professionals and organizations can gain multiple benefits from pricing, product quality, lead times, supplier identification, finance, sales, and supplier relationship building.
For example, AI can identify suppliers within specific spend categories and match competitive pricing to optimize cost efficiency and supplier performance.However, AI goes beyond categorizing suppliers based on cost to also assess supplier risk profiles in real time, uncover sustainability practices, outline delivery capabilities, and understand a supplier's historical performance.
Large-scale language models can be used to extract relevant information to understand large volumes of unstructured data, significantly enhancing the decision-making process. Data on the latest market trends, technological advancements and regulatory changes that may impact your sourcing strategy. Evaluating which suppliers meet your 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, utilization, and inventory levels to automatically generate purchase orders, making it easier for procurement leaders to track inventory. Additionally, AI tools can also handle invoices and payments. Automating the process can help reduce processing times, avoid late payment penalties, and take advantage of early payment discounts.
While the emergence of AI in the procurement cycle is still relatively new, many of its capabilities are already in place, allowing data to be input for a given deal within seconds.
Ethical Considerations for AI in Procurement
Accurate and up-to-date data is a major concern when it comes to the ethical use of AI in procurement. Effective supplier management relies on comprehensive, up-to-date data on supplier performance, reliability, and risk factors. Incomplete or outdated data can lead to incorrect evaluation of suppliers, impacting partnerships and relationships.
The effectiveness of predictive analytics also depends on the accuracy and currency of the data fed into the system. Inaccurate data fed into AI can lead to poor prediction accuracy, which can lead to excess inventory, out-of-stocks, and missed cost-saving opportunities. A company's financial health is closely linked to its procurement strategy, and missing these opportunities can impact a company's financial performance and cause a loss of competitive advantage.
A final area of impact for AI concerns privacy, especially in buyer-supplier collaboration. Large data sets can contain sensitive information and pose the risk of data leakage. We are only just beginning to realize the potential dangers of AI. However, strengthening consent mechanisms, strengthening cybersecurity measures, and establishing privacy laws around data minimization can lay the foundation for effectively addressing these emerging threats.
The Future of AI in Procurement
To realize the full potential of AI, companies will need to invest early and often in in-house training programs, which could involve micro-certifications in specific niche skills like machine learning algorithms or programming, as well as longer university courses on AI and ethics.
Education is the foundation, but it's the application of these skills that drives results. Companies that effectively adopt these systems and hire the right talent who understand AI from a conceptual perspective will have an advantage in the long run.
AI has the potential to turn every procurement professional into an encyclopedic intellectual, if only they knew how to extract the information they need to make a difference.
