In Part One, we argued that the market's indiscriminate repricing of software companies fails to distinguish between increasingly commoditised and competitively durable companies. WiseTech Global (ASX:WTC) is, in our view, among the clear examples of the latter.

The prevailing fear is that AI coding tools could enable a well-funded startup or ambitious competitor to replicate CargoWise's functionality. This fear is understandable. It is also a fundamental misunderstanding of what makes CargoWise’s competitive advantage a tough moat to bridge.

The Software is the Easy Part

Any capable team armed with modern AI coding tools could build a freight forwarding TMS: a booking engine, a user interface, shipment workflows. The code itself is not the constraint. What that team cannot build is everything beneath and around the code — the accumulated operational intelligence that has compounded over three decades of live deployment across the world's most complex regulatory environments.

Consider the regulatory integration layer alone. CargoWise maintains live, certified electronic connections to customs authorities and government systems across dozens of countries: ATLAS in Germany, HMRC and CDS in the UK, ACE in the US, ICS in Australia, DIAN in Colombia, Brazil's single window system, and many others.

Each connection is a bespoke integration requiring government certification as an approved technology provider. Each must be continuously maintained as regulations change. WiseTech processes approximately 74 million compliance updates annually and maintains 5.6 million product classification records. This capability requires not just code, but institutional knowledge, government relationships, and domain expertise accumulated since the 1990s¹.

A startup could build one of these country connections. Building and maintaining thirty or more simultaneously, in real-time, as governments change their systems, tariff schedules, bilateral trade agreements, and local IT infrastructure — that is a multi-year, very expensive effort that requires customer scale to fund and validate.

Architecture as Moat

There is a critical architectural distinction that separates CargoWise from virtually every competitor. Most competing platforms — including Descartes and the former BluJay — are stitched-together products from multiple acquisitions running on separate databases with integration layers between them. CargoWise runs freight forwarding, customs brokerage, warehousing, accounting, billing, compliance, and rate management on a single database².

The implications of this are profound and practical. A customs declaration auto-populates from the freight booking. An invoice generates from the actual declaration data. Compliance screening happens inline, in real-time, within the workflow — not as a bolt-on check after the fact. There is no synchronisation delay between modules, no ETL between systems, no reconciliation overhead.

This architecture was a choice made decades ago, and it is extraordinarily difficult for peers to retrofit, even with new AI-based coding tools. Incumbent competitors would likely cause significant customer disruption trying to highgrade existing systems to unify fragmented platforms.

Meanwhile, a startup could theoretically design this way from scratch but each module needs to be enterprise-grade on its own while deeply integrated with every other module, and all need to be production-ready simultaneously. No freight forwarder will adopt half a system for mission-critical operations.

Data Density as a Compounding Advantage

WiseTech's customs platform now covers approximately 80% of the world's international manufactured trade flows, with a stated goal of reaching 90%³. With the e2open acquisition adding approximately 500,000 connected enterprises and around 18.5% of global export container bookings, its data density is approaching a scale that no competitor can match through engineering effort alone.

This data feeds a flywheel: more transactions generate better compliance intelligence, better tariff classification accuracy, and increasingly powerful predictive capabilities. It is operational intelligence that can only be gathered by being the system of record for a dominant share of global trade. A new entrant, regardless of how sophisticated its codebase, starts cold — without the decades of structured, production-environment data that trains and improves the platform with every transaction processed.

The moat is not the code. It is the regulatory depth, the data density, the ecosystem lock-in, and the cumulative operational intelligence that compounds with every shipment, every customs declaration, and every compliance check processed through the system.

As Competitors Try to Catch Up, Software Leaders Will Move the Goalposts

Much of the market's anxiety focuses on whether peers or startups might close the gap. This framing misses a critical asymmetry: WiseTech is not standing still. The same AI tools that theoretically lower barriers to entry are accelerating its own development velocity, and the company is deploying that capacity against problems orders of magnitude harder than anything a new entrant would attempt.

At its December 2025 Investor Day, the company articulated development plans of agentic AI embedded directly into CargoWise workflows. The AI Classification Assistant — tackling import customs classification, widely regarded as one of the more complex processes in the supply chain — was announced in August and deployed to customers by December. These are narrow, specialised agents trained against its compliance data and constrained by guardrails that prevent hallucination, an approach only viable for a platform with the underlying data to train and validate against.

Another example is ComplianceWise, a virtual compliance officer. These are AI agents specialising by jurisdiction that assess export control risks on dual-use goods with human-level nuance. For example, a system that can flag tungsten metal bars shipped to a Chinese industrial tool manufacturer as a dual-use risk, cross-referencing consignee profiles with destination sensitivity. These sorts of developments require domain expertise, both regulatory and trade in nature.

There are numerous compelling innovation examples in the pipeline for WiseTech. The company believes AI agents deployed through CargoWise workflows can reduce required labour for logistics service providers by approximately 50% over the next three years. This is a bold claim, with material value-capture implications if the company can execute.

For investors focused on the threat of AI to WiseTech's software, the more important question may be: what happens when the company with the deepest data, the broadest regulatory coverage, and the most entrenched customer base is also the one deploying AI most effectively? The answer, in our view, is that the gap widens.

¹ FY25 Annual Report

² 2025 Investor Day

³ FY25 Annual Report

The article has been prepared by ECP Asset Management Pty Ltd (ECP). ECP is a funds management firm based in Sydney, Australia. For further information, visit www.ecpam.com. This material has been prepared for informational purposes only and is not intended to provide and should not be relied on for financial advice. ABN 26 158 827 582, AFSL 421704, CAR 44198.