The next frontier in commodities trading is not replacing traders. It is removing the friction that prevents them from doing what they do best.


For an industry that has invested billions in technology over the last three decades, commodities trading still requires an astonishing amount of human effort to answer apparently simple questions.


“What is our exposure?” “What happens if this vessel is delayed?”


“ Which contracts are affected by that refinery outage?”


“Has anyone dealt with this counterparty before?”


The answers exist somewhere. Across trading platforms, ETRMs, shipping systems, market data feeds, emails, SharePoint sites, spreadsheets and operational reports, the information is there. The challenge is assembling it quickly enough to make better decisions than the competition.


In an industry where timing is measured in minutes, and sometimes seconds, that delay has a cost.


Artificial intelligence promises to change this. Not because it is capable of replacing traders or risk managers, but because it can finally tackle one of the industry’s oldest problems: information fragmentation.


PLATFORMS


OPERATIONAL REPORTS


COMMERCIAL TRUTH


SPREADSHEETS


SHAREPOINT SITES


THE LAST MILE OF DIGITAL TRANSFORMATION


Over the years, commodities organisations have successfully digitised much of the trade lifecycle.


Deals are captured electronically. Market data arrives in real time. Risk is calculated more frequently and with greater sophistication. Logistics are increasingly automated. Settlement processes are more efficient than ever before.


Yet the human workflow between those systems often remains stubbornly manual, with highly experienced professionals still spending hours searching for documents, reconciling inconsistent data, validating assumptions and coordinating information between teams before they can make a commercial decision.


The technology exists. The information exists.


What has been missing is something capable of bringing it all together.


YET THE HUMAN WORKFLOW BETWEEN THOSE SYSTEMS OFTEN REMAINS STUBBORNLY MANUAL, WITH HIGHLY EXPERIENCED PROFESSIONALS STILL SPENDING HOURS SEARCHING FOR DOCUMENTS.


This does not mean that AI can simply be placed over a fragmented technology estate and expected to make sense of it. Poor-quality data, inconsistent definitions and weak governance do not disappear when an agent is introduced. If anything, AI makes the strength of an organisation’s data foundations more important, because decisions can now be reached and acted upon at far greater speed.


MARKET DATA FEEDS


EMAILS


TRADING


(Energy Trading)


SHIPPING SYSTEMS


ETRMS


13 | ADMISI - The Ghost In The Machine | Q3 Edition 2026


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