Recent months’ intense focus on tariffs—covering which countries, goods, and amounts—has disrupted supply chains and unsettled markets. CEOs are establishing "war rooms" to manage the turmoil, while employees prepare for potential recession-driven layoffs impacting businesses. Companies making products from washing machines to children’s toys now critically need to understand their entire supply chain, including tier two, three, and four suppliers. The challenge lies in gathering detailed information about these deeper supplier layers. Artificial intelligence (AI) is enhancing this visibility, although even advanced technology cannot fully anticipate the unpredictable start-stop nature of President Trump’s tariffs. Evan Smith, CEO and co-founder of global supply chain firm Altana, notes that AI provides companies with insights historically difficult to obtain. Speaking to CNBC’s Technology Executive Council, Smith emphasized that tariffs have become a central topic in his dealings with CEOs, CFOs, and boards, highlighting “geopolitics front and center” through trade wars and tariff volatility. Before AI adoption, companies relied on auditors or supplier surveys to map their supply chains, but these methods were flawed—global audits could take two years, and surveys had only about an 8% response rate. Furthermore, evolving vendor relationships made maintaining current supply chain data nearly impossible. AI is transforming this landscape. At its inception, Altana built what Smith calls “the largest organized body of supply chain data on earth. ” Recognizing that public internet data is limited, Altana gathered private data from logistics firms, insurers, retailers, banks, and others.

AI analyzes this data to create a dynamic, comprehensive global supply chain map. Partners contribute data securely and retain privacy, benefiting from a shared, evolving knowledge base. For companies facing tariff complexity, AI offers insights beyond immediate suppliers. Smith illustrates with a washing machine example: a manufacturer supplies Altana with its bill of materials and direct suppliers. AI then reveals the entire multi-tier network, including hidden suppliers, enabling companies to understand tariff exposure, simulate supply chain changes, explore production shifts globally, or evaluate reshoring impacts on costs. Smith observes that mapping large enterprises’ product networks once took six months using early machine learning tools, but now can be completed within a day. Audit committees increasingly ask critical questions about China exposure, tariff scenarios, and single-source dependencies—all of which require comprehensive multi-tier supply chain knowledge. Smith concludes, “Companies have to have visibility, and it has to be dynamic to respond to the next thing. We exist in a network, and you have to know the network. The era of blind outsourcing is over. ”