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Most companies are using AI. Almost none of them are doing it right.
88% of organizations are using AI in at least one business function. Only 1% describe their AI strategy as mature.
That gap isn't a technology problem. It's an execution problem. And in logistics, where margins are tight and the cost of getting it wrong shows up on the same day it happens, the right logistics visibility software isn't a nice-to-have. It's the difference between reacting to problems and preventing them.
Shipwell has spent the last two years on the right side of that gap — using AI to build faster, automate the work that shouldn't require a human, and give operators the visibility and decision support that used to take a team twice the size to produce.
How AI in Logistics Is Actually Getting Built
Shipwell uses AI to ship more software, faster. The human review behind every line of code is the part that makes it work. AI-generated output has advanced more in the last eight months than most people realize. The standard hasn't moved. The speed has.
Why the Best Ideas Come From Operators, Not Boardrooms
The best product decisions don't start inside Shipwell. They start with operators willing to say exactly where the process breaks down — and how that feedback shapes what gets built next.
What a Real Carrier Management Platform Does With AI
The Track & Trace AI Worker handles load monitoring that used to pull dispatchers off higher-value work. The In-App Assistant lets anyone on the team ask for what they need in plain language, without a technical background. The MCP Server connects Shipwell's data to the tools and workflows your team already uses. These aren't roadmap items. They're in production.
The median enterprise is already seeing 2.4x ROI on AI investments. Top performers are hitting more than 5x. The difference is execution.
The window is open.
Source: McKinsey State of AI, 2025
