Shifting trade policies and unpredictable supply chains are making cost control more difficult than ever for metal stampers. As global pressures intensify, many manufacturers are turning to digital tools and AI to better understand their exposure, model scenarios and respond before margins are squeezed. Understandably, many could use a helping hand navigating this evolving landscape, and fortunately, there are quite a few folks in that space willing to step in.
Tom Nall is one of those people. Since the mid-1990s when he began working at IBM, he has worked with companies to modernize their operations; make smarter, data-driven decisions; and develop and execute technology strategies. Now as the manufacturing industry director at Avanade, a Microsoft solutions provider, he is a go-to expert on how adopting AI can improve manufacturing operations, especially amid labor shifts and rising tariffs.
Nall recently published an article about the importance of data readiness in navigating tariffs. He has also worked closely on Avanade’s tariff navigator tool that helps give manufacturers greater clarity.
AI-driven solutions
A good chunk of metal stamping shops still use manual spreadsheets or legacy ERP systems, which often means that adopting new digital tools comes with considerable anxiety. That is why companies like Avanade are keen to develop their products with that learning curve in mind.
While these types of products are designed to be easy to use, there are steps stamping companies can take to make the adoption of AI-driven management software more approachable, even if they lack the mature data infrastructure.
“While the transition away from manual processes or legacy ERP systems may seem daunting,” Nall says, “the reality is much more manageable when done thoughtfully. Making sure the learning curve isn’t too steep is about approaching adoption incrementally. Often, and not exclusively in stamping, we see an interest in AI translating to initiatives that are trying to run before starting to crawl.”
He says the first step in an incremental process is establishing data visibility, which he likens to the “crawl phase.” Using this approach, there is no pressure to deploy advanced AI on day one. Instead, a shop can prioritize consolidating tariff exposure data, supplier inputs and material cost information. This initial step creates the foundation needed to unlock early insights in the process.
“Because solutions like Tariff Navigator are designed to layer on top of existing environments, once a solid data foundation exists, shops can begin introducing predictive and prescriptive capabilities,” he says. “This means ingesting available trade, sourcing and cost data, which can then translate to automated monitoring and scenario modeling. Sequencing is essential, and the first step here is to modernize the data environment. From there, AI functionality can be built out and scaled.”
Gaps in labor, trust
Nall says labor and skills shortages are by no means new to stamping operations and can be especially challenging for planning, procurement and cost analysis functions that rely heavily on institutional knowledge. The benefit of AI tools like Tariff Navigator is that they allow organizations to extend the capacity of lean teams.
Instead of using valuable staff time to track continually evolving tariff updates, supplier changes and landed cost implications, AI augments available labor. By continuously scanning policy shifts, flagging exposure risks and quantifying impact, tasks that would otherwise consume hours of manual effort are done automatically. In turn, the team is afforded more time to negotiate, strategize and optimize sourcing decisions rather than simply gathering information.
Beyond labor, another common barrier to AI adoption is trust. And as stamping companies deal with shifting tariffs, a profitable contract can turn into a deficit very quickly, which is why trust is essential. Nall says the path to trusting AI begins with quality data.
“If the inputs can’t be trusted,” he says, “why should the outputs be?”
To improve reliability, stamping companies must standardize and govern supplier records, material specifications and cost structures.
“Beyond a strong data foundation,” Nall says, “transparency is also a key element to building trust. AI tools should be able to provide explainable outputs, demonstrating how tariff changes or sourcing decisions influence modeled outcomes. This level of traceability means operators and executives can validate and explain insights with confidence.”
As organizations work to adopt AI in ways that strengthen trust, taking incremental steps can quickly build confidence. Beginning with focused applications, checking results and fine-tuning models help demonstrate the practical value of reliable AI.
“Beyond the technology itself,” Nall says, “it’s worth noting that trust is also built through governance, visibility, and continuous refinement of both data and AI processes.”
Tariff instability
Tariffs were already apt to change, causing stamping operations to resource materials or reprice jobs. And now, the Supreme Court’s February ruling adds another layer of uncertainty. As these issues compound, stamping companies wonder if AI can simulate “what-if” tariff scenarios to help them facilitate better decision-making. Nall says not only can AI help, but it can make decision-making proactive instead of reactive.
“Instead of waiting until costs rise,” he says, “leaders can prepare alternate sourcing strategies and pricing adjustments ahead of time.”
An example of this includes companies that import steel, for which changing tariffs would require them to evaluate affected costs, supplier viability and customer pricing.
“With AI tools like Tariff Navigator,” Nall says, “stamping organizations can model alternate sourcing regions, assess quality implications and forecast margin impact across product lines. Beyond forecasting a single input, AI enables multi-variable modeling. Companies can simultaneously analyze tariff changes, transportation costs and demand shifts.”
He adds that creating a holistic view provides executives with a clearer risk profile, which leads to a more confident decision framework even amid volatile trade conditions.
Easy implementation
Adopting new technology can come with the fear of implementation challenges, such as having to rebuild a technology environment from scratch. Fortunately, this is not the case with Tariff Navigator. Nall says the foundational digital layer includes ERP integration, supplier and sourcing data, and structured cost inputs.
“Once tariff intelligence is operationalized,” he says, “many organizations expand into adjacent AI-enabled capabilities. These often include predictive demand planning, automated supplier risk scoring, AI-assisted procurement optimization, yield and yield optimization, reducing unplanned downtime, and AI-assisted knowledge capture and worker assistance.”
As a whole, these capabilities boost throughput, Nall says, by stabilizing input costs, reducing sourcing disruptions, and enabling more accurate production planning and execution. Furthermore, over time, the digital foundation that supports tariff modeling becomes a broader competitive platform across operations.
Tracking KPIs
Return on investment will remain a core metric for stamping companies because it anchors every major equipment, tooling and process decision in measurable financial performance, and this will also be the case with companies implementing AI solutions.
“In practice,” Nall says, “the most effective and immediate way to approach ROI is by tying tariff intelligence initiatives back to operational and financial metrics already being tracked by the team.”
More than perhaps anything else, time savings is one of the biggest ways organizations find value. After all, tariff monitoring and trade analysis eat up a lot of time. Automating those tasks reduces the manual hours that procurement and finance teams spend gathering and interpreting policy updates.
“Companies also see improvements in decision speed,” Nall adds. “Cost modeling that once took days can be completed in hours, allowing shops to adjust quotes, pricing or sourcing strategies more quickly.”
Saving time is critical, but proactive margin protection is another value that AI brings to the table.
“By anticipating tariff exposure and shifting suppliers or materials proactively,” Nall says, “manufacturers can avoid sudden cost shocks that damage profitability. ROI should be evaluated over weeks and months rather than years. Early visibility into tariff exposure often produces immediate operational and financial benefits, which helps to justify broader AI investment down the road.”
Software is growing more important than ever for manufacturers looking to gain efficiencies. Go to our stamping archives and see the options available today.
