Measuring What Matters: Communicating the ROI of AI and Tech Tools in Global Trade

Written by Thariq Kara, CEO and Co-founder of BITE Data

The ROI Blind Spot in Trade Technology

Global trade is at a digital crossroads. Artificial intelligence and advanced analytical tools are rapidly transforming how organizations manage compliance, logistics, and supply chain visibility. Yet, amid this wave of innovation, one challenge persists: picking the right technology for your company and figuring out the true return on investment (ROI) of these technologies, so that procurement teams and the C-suite can understand why a tool might be critical to global trade operations.

Trade leaders understand the operational potential of AI:  automated document classification, predictive logistics analytics, or risk scoring models for example, can provide huge value to the efficiency of a global trade team. Over the last couple of years, I have witnessed a migration from weariness and fear, to resigned interest and now almost a fear of missing out if some level of automation and AI is not integrated into global trade team operations.  However there needs to be a balance between speed of uptake, identifying the right tools for your company (don’t just pick the bright shiny object that everyone’s talking about!), and evaluating the return on investment. Critically, the ROI must include an evaluation of whether the tool(s) is even improving operations or not.

This article provides high level guidance on potential frameworks and methodologies that could be used for identifying the right tools, calculating their ROI, and communicating the results in language that resonates across the organization.

1. Picking the Right Tools: Building an Evaluation Framework

Before calculating ROI, companies must first ensure they’re evaluating the right technologies. The best AI tools should align not only with current pain points but also with long-term business goals and operational readiness.

Here are some examples that define this alignment:

1. Business Need Mapping – Begin with the problem, not the product. AI should directly address measurable pain points such as customs declaration errors, duty drawback issues, or forecasting bottlenecks in cross-border product movement. How critical is it to your organization to improve a particular pain point? Determine what value the overall business would see if there was a 10% improvement.
2. Process Integration Readiness – Determine to what level your organization needs to integrate the tools you are looking into. Does it absolutely need to integrate with your ERP? Or can you use it to improve a manual process outside of your ERP or TMS? Does your company have budget for IT integration?
3. Data Maturity – AI performance depends on clean, accessible, and structured data. Conduct a data audit before any major AI investment. Is your underlying data ready for better tools?
4. Vendor Stability: There are a lot of new companies and technology platforms out there. What is important to your organization from a service support perspective and can the company you are engaging with meet those needs?

Set up a scoring system for each of the tools you’re evaluating and a set of features that are a must-have to your organization, with a weighting based on what is more important to your organization or company- every organization is different. For example, some Global trade teams may not have budget to integrate tools with their ERP, in which case that parameter would either be weighted very low or may not exist at all in an evaluation.

Additional recommendation: don’t look for one tool to fix all your problems. Monolithic systems are hard to maintain and are costly over time.

2. Determining ROI: Moving Beyond “Time Saved”

Procurement and executive leaders rarely approve tools based solely on efficiency claims. Instead, they prioritize how technology affects business outcomes.

Below are examples of effective ROI paramters for trade technology:

• Operational Efficiency – 30% reduction in manual data entry → Reduced FTE hours and cost per transaction.
• Compliance Risk Mitigation – 40% fewer classification errors → Reduced penalty exposure and rework costs.
• Revenue Enablement – Improved delivery prediction accuracy → Fewer missed SLAs and higher customer retention.
• Strategic Agility – 50% faster adaptation to tariff changes → Improved resilience and faster market response.

To calculate ROI, trade leaders can apply a Total Cost of Ownership (TCO) vs. Business Impact model:
1. TCO – Includes licensing, training, integration, and maintenance.
2. Quantifiable Benefits – Hard savings (time, error reduction) and revenue gains.
3. Qualitative Benefits – Soft metrics like compliance assurance, decision-making speed, or employee satisfaction.

For structure, consider recognized frameworks such as Gartner’s Benefits Realization Model or Forrester’s Total Economic Impact (TEI) methodology. Both translate technology benefits into boardroom language, linking automation, insight, and resilience to measurable financial outcomes.

Just like section 1, to start off with small steps, try a weighted scoring system to determine ROI – what metrics matter more to your business and how should they reflect in your decision making process.

3. Communicating Value to Procurement and the C-Suite

Even a strong ROI and tech evaluation model can fall flat if it isn’t communicated effectively.

To resonate with the C-suite, here are a few recommendations global trade leaders can take:

1. Speak in financial terms. Link AI-driven improvements to cost avoidance, reduced working capital, or revenue protection.
2. Tell a story. A “before and after” narrative, supported by real metrics, builds trust.
3. Visualize success. Dashboards showing risk score reductions or compliance improvements make ROI tangible.
4. Tie to corporate KPIs. Align AI initiatives with sustainability, resilience, or digital transformation goals.

Procurement may need a nudge  as well – here are some ideas for this group:

1. Emphasize lifecycle cost predictability, vendor reliability, and contractual flexibility – importantly, check to see that the vendor checks these boxes in the way you need them to.
2. Highlight interoperability – how the tool fits into existing supplier and trade networks could affect lifecycle cost – an import metric for procurement teams.

Closing Thought

The ability to quantify and communicate a technology evaluation process and  ROI calculation for technology enablement will soon define the leaders in global trade digitization. As compliance pressures, data volumes, and geopolitical risks intensify, AI will evolve from a cost-saving initiative to a strategic enabler of resilience and competitiveness.

The organizations that succeed will be those that don’t just adopt technology.

1. What business problem does this tool solve — and is that problem measurable?
2. How will it integrate into existing workflows and data systems?
3. What’s the total cost of ownership over three years?
4. What KPIs define success — and who owns them?
5. Can we articulate value in financial, compliance, and strategic terms? 

It’s critical to look at ROI as not just a financial metric, but also a storytelling tool. When we can clearly articulate how technology strengthens compliance, speeds trade, and safeguards supply chains, we elevate the conversation from “what does it cost?” to “how does it empower us?”