This article was updated in July 2026 to reflect the growing role of AI in commodity trading, and the wider adoption of cloud CTRM in recent years.
The cloud offers businesses many benefits compared to traditional, on-premise IT solutions, including scalability, business continuity and more flexible access. In commodities, most organisations are already using the power of the cloud for at least some activities. For example, accessing emails and reports across different laptops and phones. And are there any companies who don’t use Microsoft Teams at this point?
Cloud technology has taken on new significance in 2026, because it's the foundation that determines how well AI can work within your trading systems. Practically all commodity trading firms are adding AI tools to their technology stack, and many are looking to incorporate AI with their existing CTRM. But AI answers are only as good as the data provided, and AI agents need secure, controlled access to real operational systems. A fully integrated, agentic AI, built into a cloud-native CTRM, can act directly on live data across the whole business, whereas even the best AI system adds no value if it is being fed stale or incomplete data from a legacy system.
What is cloud technology?
Cloud technology means computing power, storage, and software delivered over the internet from remote data centres, rather than run on servers you own and maintain yourself. Because thousands of organisations share the same underlying infrastructure, cloud providers can invest in far more computing power, security, and reliability than any single business could justify building alone.
What is a cloud CTRM?
A cloud CTRM is a commodity trading and risk management system that runs in the cloud instead of on your own on-premise servers, giving trading teams secure, real-time access to trading data from anywhere. In practice, a cloud CTRM can automate the entire trade lifecycle while giving everyone on your team a live view of the business, wherever they are in the world.
As well as the benefits of a cloud solution, a cloud-based CTRM often means you're benefiting from a more modern system. And upgrades are also managed centrally, so new features reach all clients much faster, letting your system grow alongside your business.
What are the advantages of a cloud CTRM?
A cloud CTRM gives commodity trading firms secure, real-time access to trading data, while also providing the live data foundation modern AI tools need to work well. The key benefits include:
- Mobile and global. A cloud CTRM can be accessed from anywhere, and fast.
- Lower-cost. When you pay for cloud hosting, you don't need to worry about backup, storage, or expertise costs, and don't need to invest in costly servers or infrastructure.
- Secure. Less risk of lost data, and access to more security resources than an on-premise solution.
- Collaborative. Some commodity management technology, like Gen10's, creates collaboration between teams as everyone is working from the same live data, and the best systems can integrate your wider business systems like a general ledger or vessel tracker, too.
- Resilient. Cloud systems use load balancing, so your system can draw on another server if one becomes slow.
- Scalable. Upgrades and new releases are pushed out via the cloud so all clients have access to the latest version. This also means more time spent on developing new features and less time implementing them.
- Less stress. You don't need to update or maintain anything, beyond your internet connection.
- AI-ready. A modern, cloud-native foundation means new AI capabilities can be added and improved without disruptive upgrades to your core system.
How do I know if a CTRM is cloud-native?
There are more cloud CTRM options available than there were a few years ago, but not all “cloud” CTRMs are equal. A cloud-native CTRM is built specifically for the cloud, allowing you to take full advantage of the speed and flexibility it offers.
Some providers, by contrast, have retrofitted cloud capability, and more recently AI, onto architecture that wasn't originally built for it. That gap shows up both in clients' real-world results and in how well AI performs once it's added, since legacy technology makes it much harder to layer AI on top in any meaningful way.
Some “cloud” solutions also aren't hosted on a true cloud at all. If a provider hosts your software on their own servers and calls it a cloud solution, you may not get the same flexibility, scalability, speed, or reliability, and you might be paying more for it too.
A few ways to check whether a CTRM is genuinely cloud-native:
- Ask the provider where they host their system. Gen10 solutions, for example, are hosted on AWS, chosen for its reliability, security, and performance.
- Check whether the system can be accessed securely from mobile devices, an indicator of cloud-native design.
- Ask whether AI features are agentic, and can take actions, or are just for answering questions and presenting data. Legacy systems are more likely to rely on data lakes and similar integrations, which typically limit AI to querying and visualising data. Cloud-native architecture, by contrast, can allow AI systems to interact with the actual operational systems, governed by the user’s controls and permission settings.
- Ask for a live demo of the vendor's AI capabilities, rather than relying on marketing claims.
- Look at what the system integrates with. The ability to share real-time information with other systems, such as general ledgers or vessel-tracking platforms, is a good sign the underlying technology is built for genuine cloud collaboration.
- Check how implementation works: does the team need to be on-site for the initial rollout and future upgrades, or can it be done remotely, with an on-site visit only if the client wants one?
Is cloud technology secure?
One of the benefits of using a large cloud provider like AWS or Azure is their investment in data security. These providers rely on the absolute security of their networks and invest heavily in the people, technology, and processes needed to stay ahead of the latest cyber security threats, from physical security to patching and round-the-clock monitoring. The scale of these operations means cloud providers can invest more heavily in security than any individual client could.
Cloud technology also means that when things do go wrong, the impact on business continuity is far smaller. If you're storing files locally and a laptop is lost or a server is damaged, that data is gone. A cloud solution spreads data across many servers and data centres, so one damaged location doesn't cause the same disruption and your data is still available.
This matters just as much for AI as it does for day-to-day operations. Keeping trading data centralised in one secure, well-governed cloud environment makes it far easier to maintain consistent AI governance, access controls, and audit trails. When data is scattered across spreadsheets, local drives, or several disconnected legacy systems, that oversight has to be pieced together manually, introducing all kinds of new risks.
Why does cloud technology matter specifically for AI?
Most AI models run in the cloud, but they can run locally too. Running locally means they work without Internet access, but are limited by your device’s processing power and often have less capacity than the cloud models.
What really matters for commodity trading firms is whether your CTRM, the system feeding that AI its data, can deliver it fast enough and securely enough to be useful.
This is where cloud-native CTRM makes the difference:
- Real-time, unified data. Legacy or retrofitted CTRM systems often store data in siloed modules or process it in overnight batches. AI features running on top of a system like that either work with stale information, or require costly custom integration just to get access to current data. A cloud-native CTRM, by contrast, gives AI features live access to unified data across the whole trade lifecycle.
- Faster innovation. Because upgrades in a cloud-native CTRM are managed centrally, new AI features can be developed and rolled out faster, which matters given how quickly the AI landscape is changing.
- Governance and oversight. As above, centralised, secure cloud data makes it easier to maintain consistent AI governance and audit trails, rather than piecing oversight together across fragmented systems.
Put simply: the same cloud properties that made CTRM better back when this article was first written (unified data, real-time access, scalability) are exactly what make AI useful within a CTRM today.
Cloud technology remains the foundation of a modern CTRM, and now of a CTRM that can put AI to genuine use. The infographic below summarises the key advantages of a genuinely cloud-native platform, from cost and scalability to security, collaboration, and AI-readiness, so you can see them at a glance.
