Transportation Spend intelligence: The AI-powered Transformation

Despite decades of digital investment, supply chains remain plagued by fragmented, inconsistent, and reactive data environments.

Now, with the rise of Large Language Models (LLMs) and generative AI, leaders stand at a pivotal inflection point. These technologies offer unprecedented capabilities—but unlocking their potential requires more than simply layering AI on top of broken systems. It demands addressing the root cause: bad data

The missing foundation

Much of today’s investment is aimed at the future—demand sensing, forecasting, and planning. But forecasts are only as good as the data feeding them. If the underlying cost center data is fragmented, outdated, or inaccurate, even the most advanced models will lead organizations astray.

Transportation spend is a prime example. It’s one of the largest and least understood cost centers—riddled with manual processes, opaque billing, and inconsistent data formats. Millions flow through this black box unmanaged and unverified, leading to flawed assumptions and missed savings.