February 13, 2025 Navigating the Ripple Effects of Rising Tariffs

Companies can strengthen supply chain resilience by leveraging AI and achieve the transparency to navigate rising tariffs and global trade disruptions.

By Steve Ponting, Director at Software AG

With President Donald Trump’s administration planning to raise tariffs in 2025, concerns are rippling through global supply chains. Specific talk of imposing tariffs on major trade partners like Canada, Mexico, and China has only fueled uncertainty, leaving businesses scrambling to prepare for potential widespread disruptions.

Tariffs—taxes levied on imported goods—are designed to protect domestic industries or serve as leverage in trade disputes. While their average rate remains relatively low at 2.5 percent (down from 3.6 percent in 1993, according to McKinsey), even small adjustments can send shockwaves through industries.

For many businesses, especially those reliant on global supply chains, these plans have set off a flurry of concern. Few manufacturers operate solely within the U.S., and major retailers depend heavily on international suppliers to meet demand. In an effort to insulate themselves, some companies are turning to preemptive measures like stockpiling or accelerating imports. However, such strategies come with risks, including the potential for creating shortages, driving up prices, and exacerbating supply chain instability—issues that could impact consumers worldwide.

To weather the challenges ahead, U.S. companies must remain agile and build up their resilience. Success will hinge on two critical pillars: supply chain transparency and risk mitigation, which can be achieved by leveraging technologies like artificial intelligence (AI) to better adapt to the complexities of a changing trade landscape.

Transparency: The Foundation of Supply Chain Disruptions

In an era of increasing trade volatility, transparency is critical for building operational resilience and avoiding demand shocks. Companies equipped with real-time, accurate data are better positioned to anticipate shifts in consumer behavior and global trade, enabling them to make informed decisions on procurement, logistics and fulfilment strategies.

Transparency extends beyond merely sharing information; it involves a concerted effort to foster trust and collaboration across the entire supply chain. By maintaining open communication with suppliers, manufacturers, and distributors, businesses can ensure all parties are aligned on potential risks and opportunities, paving the way for more strategic, long-term decision-making.

Building transparency requires a dual focus on design and process. From a design perspective, companies should establish clear organizational goals, employ AI-driven scenario planning, and implement knowledge-sharing systems that deliver actionable insights in real-time. Process transparency, meanwhile, emphasizes tracking performance through tools like AI-powered process mining and root-cause analysis, which identify inefficiencies and bottlenecks in workflows.

AI-enabled process mining is especially transformative, as it uncovers hidden vulnerabilities within supply chains. By analyzing operational data, companies can pinpoint areas that require optimization, enhancing their ability to withstand disruptions. This proactive approach minimizes reactionary decision-making, ensuring businesses remain stable even during turbulent periods.

Together, these practices ensure operational clarity while strengthening collaboration and trust across supply chain partners. Transparency allows businesses to avoid reactionary decisions that could harm operations or the broader market, positioning them for long-term success.

Leveraging AI Modeling to Light the Path Forward

While transparency lays the groundwork for resilience, advanced technologies like artificial intelligence (AI) provide the tools to navigate complexities with precision. AI has emerged as a catalyst for transformation in supply chain management, empowering companies to predict disruptions, optimize workflows, and enhance collaboration—all core elements to a resilient framework.

AI-powered predictive analytics enable businesses to anticipate demand fluctuations, monitor global trade patterns, and detect vulnerabilities within their supply chains. For instance, AI can analyze vast datasets to detect emerging risks—such as port congestion or geopolitical shifts—before they escalate into disruptions. With the capability to forecast these challenges, businesses can then reroute shipments or adjust delivery timelines proactively, staying one step ahead of potential delays rather than merely reacting to them.

AI also enhances collaboration by making process insights accessible to non-experts, enabling employees across an organization to analyze workflows, identify inefficiencies, and drive improvements without requiring deep expertise in process modeling. AI-driven tools, such as process modeling assistants, allow users to visualize workflows, predict the impacts of disruptions, and identify areas where re-engineering could add value. Making process intelligence accessible helps companies proactively refine operations and develop mitigation strategies rooted in data, reducing overreliance on reactive measures like last-minute stockpiling.

AI-powered process modeling also enables organizations to conceive of entire workflows in a visual, graphical format. By mapping out key activities across departments, businesses can predict ripple effects of anticipated disruptions and design effective mitigation strategies. For example, weaknesses identified through process mining can inform re-engineering efforts, demonstrating where changes can make a material difference.

AI’s iterative capabilities also support long-term adaptability. By regularly analyzing successes and challenges, businesses can refine their strategies incrementally, staying ahead of evolving conditions. This continuous learning approach hones the operational resilience “muscle” that becomes critical during crises, ensuring organizations are prepared to handle both predictable and unforeseen disruptions.

From Potential to Practicality: Embracing AI for Long-Term Success

As the global trade environment grows increasingly unpredictable, companies must transition from viewing AI as a future possibility to embracing it as a practical necessity. The integration of AI into supply chain operations offers a path to resilience and strategic advantage, particularly when paired with human expertise.

This synergy between AI insights and human judgment is crucial for aligning predictive analytics with on-the-ground realities. For example, combining AI-driven demand forecasts with supplier input can help refine inventory strategies, minimizing disruptions while optimizing costs. Such collaboration creates actionable blueprints for change management, equipping organizations to respond effectively to dynamic trade conditions.

Beyond analytics, AI drives process transformation by harmonizing historical data with industry standards. This enables companies to identify best practices and adapt to changing trade norms, ensuring they remain agile and focused on strategic goals even amid uncertainty.

Building a Resilient Future in the Midst of Uncertainty

In these uncertain times, preparation and adaptability will separate businesses that thrive from those that falter. The path forward requires a commitment to innovation, collaboration, and strategic foresight to navigate the challenges of an evolving economic landscape. By prioritizing transparency, leveraging advanced technologies, and fostering resilience, companies can mitigate the ripple effects of rising tariffs and build supply chains that are not only robust but also future-ready.

As the global trade environment continues to evolve, businesses that embrace these principles will be well-positioned to weather disruptions and seize opportunities. In doing so, they create supply chains that are not just resilient but also future-ready—capable of thriving in the face of disruption and complexity.

About the Author:
Since joining Software AG’s UK management team in 2021, Steve Ponting, Pre-Sales and Solutions Director for EMEA North, ARIS – a global leader in Process Intelligence – has steered the region’s Pre-Sales organization. 

With over 20 years of experience in sales and go-to-market leadership, Steve is widely regarded as an expert in leveraging cutting-edge technologies including artificial intelligence (AI), machine and deep learning, computer vision, and process intelligence to drive meaningful, measurable results for customers, partners, and consultancy providers alike. 

A proven global leader, Steve excels in navigating culturally diverse environments, blending strategic foresight with emotional intelligence to cultivate trust, inspire teams, and deliver impactful results. His leadership style, grounded in empathy and a commitment to long-term value creation, has been pivotal in driving business transformation across sectors.

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