AI-based recommendation systems are now being applied in broader ways for businesses, like finding, assessing, and selecting suppliers. -BY Donna Benjamin

Not long ago, people were awed by the ability of Artificial Intelligence (AI) to manage chatbots because it meant the technology could understand natural human language. Since then, AI has advanced in leaps and bounds, with algorithms now capable of generating new images independently, predicting 3-D protein structures, and advising financial clients, to mention a few. AI recommendation systems also generate suggestions for products and services customers are most likely interested in, meaning they do not have to search online. Given all these abilities, applying AI-based recommendation systems to the supply chain makes sense. Such a system can analyze relevant data to efficiently find, assess, and select suppliers.

Recommending Suppliers Based on the Facts

An AI recommendation system is a machine learning system that analyzes data to provide personalized recommendations. These systems analyze user behavior, preferences, and historical data to provide recommendations on products, services, or content that a user is likely interested in buying or trying.

Regarding supplier selection, AI recommendation systems analyze data on supplier performance, pricing, and other relevant criteria to provide recommendations for the most suitable suppliers for an organization's needs. The supplier recommendation systems can also consider unique and specific criteria, such as quality control, certifications, and compliance requirements. These systems can automate and streamline the supplier selection process, making it faster and more efficient while ensuring that the best suppliers are chosen. Using machine learning algorithms to analyze this data, AI-powered recommendation systems can quickly identify the suppliers most likely to meet an organization's needs and provide the best value. This can save organizations significant time and resources that would otherwise be spent manually evaluating suppliers. Another clear benefit of using the AI recommendation system for supplier selection is that it can better identify all qualified suppliers and all suppliers with potential or adaptive capabilities without necessarily falling into historical bias patterns. This will support supplier diversity and environmental and social efforts.

Scouting for Suppliers

A study published in the International Journal of Physical Distribution & Logistics Management addressed using artificial intelligence for supplier scouting. The researchers studied 12 cases of technology providers offering AI-based scouting solutions. They noted information processing needs are high when searching for suppliers, and AI can be a valuable supplement to human capabilities, especially in times of crisis. As an example, they mentioned the chip shortage and scarcity of raw materials during the COVID-19 pandemic, which drove businesses to aggressively search for alternative suppliers. Business environment volatility has continued after the pandemic, so the ability to continuously identify new suppliers has become crucial.

AI is beginning to play a role in supplier scouting, though it is still considered a developing use of the technology. If successful, the researchers believe, AI will replace much of the manual effort it can take for many procurement professionals to find new suppliers. AI can be more efficient at time-consuming tasks, like exploring databases that may be outdated, searching websites, and collecting supplier information on platforms. This recent study explored how AI can meet information processing needs in supplier scouting and address the need for more formalization. AI can handle extremely complex specificities linked to organizational supplier requirements and the detailed supplier information needed about raw materials, production processes, certifications, and national and local regulations. However, AI systems still need procurement personnel with technology skills to understand and utilize an AI recommendation system for finding and selecting recruiters. Without these human overseers, the AI recommendation system cannot deliver its maximum value. Thus, the researchers concluded that AI-based solutions could reduce the uncertainties that exist in the current procurement practices if they are properly partnered with human support.

Wanted: Good Data Supporting Business Needs

Making AI recommendation systems for supplier scouting and selection requires good data. In this case, “good” data means data that is not biased or toxic. Otherwise, diverse suppliers may once again be excluded from consideration.

One suggestion is to use a smaller customized AI system based on the organization’s data with bias rooted out. No matter how sophisticated technology gets, humans should always be involved at various points to ensure an unbiased outcome. Does the AI recommendation system only find non-diverse suppliers or exclude women-owned businesses because it was trained on historically biased data? Do the final supplier recommendations ever include any diverse businesses? If AI recommendations do not support the progress of supplier diversity leaders, it is not a sound system. This is where the importance of feeding AI the correct data concerning business needs, in addition to the external data AI will draw upon, cannot be overstated.

Recent features in Inbound Logistics give several examples of how AI recommendation systems can support sourcing from different angles. The LevaData AI-powered supply management platform helps companies make data-based decisions concerning direct materials sourcing. It provides manufacturers with accurate lead times and identifies alternate suppliers to ensure supply continuity. The AI-driven e-procurement platform Procureship recommends suppliers for buyers of marine equipment, solutions, and services. The algorithm accesses the marketplace of service providers. AI recommendation systems can also support environmental sustainability in various ways. BlueNode, for example, can analyze emissions data from ports, rail and maritime carriers, terminal operators, and shippers. This data can become another set of inputs to the AI recommendation system to guide the selection of the most environmentally friendly logistics suppliers.

AI Land of Opportunities

AI is a growing influence in sourcing and procurement. Five years ago, people were wondering how it could be applied. It is advancing at record speed, and its business utilization is growing. Many new tech companies are emerging, developing AI-driven supply chain management platforms that include finding and selecting suppliers. Using AI is an opportunity for businesses to advance supplier diversity and environmental sustainability through informed supplier selection, and also an opportunity for diverse tech suppliers in the AI field to grow their businesses.