3 AI Trends That Will Change Your Commodities Business in 2024

It seems like there’s a single trend throughout the commodities industry: AI. Everyone is talking about it and scrambling to incorporate some aspect of it into their operations.

So, it’s no surprise that AI for commodities isn’t just one trend to look out for in 2024. Its growing popularity has spawned a variety of directional shifts in the industry all centered on how to best adapt it to get accurate, real-time data on which to base important decisions. Here are some of the big trends to look for in the commodities industry in the next year.

Trend No. 1: Intelligent Applications for Commodities

The biggest trend coming down the pike in 2024 is intelligent applications. According to Gartner, by 2026, 30% of new applications will use AI to drive personalized adaptive user interfaces. That’s up from less than 5% today.

But what is an intelligent application? Let’s defer to Jim Hare, Gartner Distinguished VP Analyst. He defines intelligent applications as:

Intelligent applications act much like a skilled, seasoned senior employee – the kind that brings you their observations and analysis, tells you what steps they’ve already put in place to make improvements, and then provides thoughtful recommendations on next steps. Even more important is that AI is embedded into the process enhancing the user’s day-to-day activities where it can deliver measurable value.

Source: Gartner. (2023, September 27). Demand Grows for Intelligent Applications Powered by AI.

Sounds great, right? So why is that adoption rate stuck at 5%?

There are a few reasons.

1. It’s new. Though some elements of machine learning and other AI have been around for over a decade, the wider push to use ChatGPT and other AI tools in offices everywhere is less than a year old. Some companies are still unsure how to best apply it.
2. Costs are a question. Because it’s so new, the costs around AI tools are nebulous. People are used to the latest technology coming with huge price tags. But when you examine the benefits — like improved efficiency, growth, and staff longevity — it’s usually more cost effective than you think.
3. ROI is unclear. As companies race to understand AI, many struggle with how to measure the ROI of this new technology. Which results can be directly tied to it, and which can’t? And let’s not forget the ongoing costs to maintain all of these models.

What’s at Stake If You Miss this Trend?

In the commodities world, legacy technology and practices can rule the day. After all, if it’s not broken, why fix it?

But while things might look fine at the 30,000 foot level, on the ground, the picture is less rosy.

Your employees are spending too much time manually processing transactions instead of analyzing the data behind them. This valuable information ends up on the cutting room floor because it isn’t relevant to the person entering it. That’s a piece of the picture you miss when it’s time to improve planning and decision making.

For your employees, that manual data entry is time consuming and tedious. It can take hours to track down and correct a single error, which leaves them too exhausted and stressed to make recommendations about what to do for the next trade, the next business opportunity. And when another job opportunity comes along, they’re ready to jump ship, leaving you to fill their position and train someone else.

Tech that can encourage collaboration and break down silos can make everyone happier at work and —most importantly — make your business more profitable as it uses the data to learn from past mistakes and correct for them moving forward.

How to Get on The Right Track with This Trend

Digitization isn’t a magic wand you can wave at your data. McKinsey research shows that while 90 percent of companies have launched some flavor of digital transformation, only a third of the expected revenue benefits, on average, have been realized. Culprits include unengaged employees, inadequate management support, a lack of cross-functional collaboration, and no accountability to ensure the projects succeed.

And a Gartner article says that by 2028, more than 50% of enterprises that have built large AI models from scratch will abandon their efforts because of costs, complexity and technical debt resulting from those deployments.

So how can you ensure your intelligent application/digitization project not only succeeds, but thrives? It’s all in the planning.

• Visualize the process. Plan ahead and look at the problems you’re trying to solve, not the technology you want to implement. What does your desired end state look like? What are the biggest impediments? Plan out your project and establish responsibilities for each part of it. A digitization partner can help you put the right processes in place and help you focus on the ROI you want to achieve.
• Recognize gaps in communication/collaboration. It’s easy for a trader to see value in a trade while other stakeholders see only risks. Understanding how the project can help get everyone on the same page before a trade will help the team see the end goal, as well as helping to quickly resolve discrepancies when they arise. And better communication throughout the process can help it achieve the results you envision.
• Look at what having the data will mean. What could you as an organization do if you had the right data? The right goal can help motivate the team to successfully complete the project.

Trend No. 2: Accessible Data for AI

You probably have a lot of data in your organization. But you can’t get to it.

It’s locked up in the silos of those legacy systems — waiting to be manually rekeyed or shared, which is why getting to it when you need to reconcile something can be a struggle.

This may explain why spending on technology can feel like a poor investment. A recent Bain & Company article reported that only 13% of executives say that they are getting the business value they expected from their spending on technology.

That’s soon going to change. In 2024, AI —and the modern data architecture it’s part of —will force businesses to eliminate information silos and consolidate their data into one system that’s agile, intelligent, available in real-time, and easily accessible to anyone on your team who needs it. Businesses will harness AI to capture and take full advantage of their complete data picture, giving them not just data, but the lightning-fast, deeply informed intelligence they need in today’s market.

To do that requires access to data in a format the AI can understand.

What’s at Stake if You Miss This Trend

Smashing silos and gaining effortless access to your universe of data sounds great. But that technology can be costly, time-consuming, and inconvenient to establish within your company.

So … why should you bother?

Because risks are coming at you fast and furious.

World events are threatening the already-strapped supply chain and driving prices up even further. And in the Covid era, working from home went from a luxury to a necessity. When your employees aren’t in the office, can they securely access the data they need, or will the problem have to wait for them to solve it in person? And if they can’t, what’s at stake? Can you afford to miss a delivery to a client, or scramble to get the commodities from somewhere else? Can you afford to buy and store more just in case something like this comes up? Every mistake can cost you huge sums of money, and without the right data at hand, those mistakes are inevitable. And these issues have become more costly as interest rates have risen dramatically.

“It’s costing you a lot of money to be inefficient.”

– Rick Nelson, CEO, ClearDox

How to Get on The Right Track With This Trend

Here again, look at all the work automation can free up from your human staff so they can focus on the bigger picture that AI can’t yet manage alone.

With less time spent on the inefficiencies caused by those legacy systems, can they develop stronger relationships with suppliers and customers? Be more strategic about how and where they store materials? Work on opportunities to scale and grow your business? With less grunt work on their plates, you can empower them to do work that makes a difference to them and for your company or add new business without adding costs on the back end.

Trend No. 3: Clean, Shared Commodities Data

Your decisions are only as good as the data you use to make them. If there’s a time lag to get new data on your desk or discrepancies among different sets of data, you can’t forecast for next week, never mind next year. A single source of truth, updated in real time, will give you the confidence you need to take the next steps in your business.

And sharing that data is more important than you think. If internal stakeholders, suppliers, and partners have access to the clean, verified data they need quickly, they can optimize all facets of the trade and make those big company decisions faster and with better outcomes.

AI is no different. And if it’s not fed data that is accurate or up to date, the AI tools you use won’t be as valuable to you in the long term.

More broadly than that, however, there is a movement toward industry-specific large language models, where these models use multiple datasets from business across an industry or segment – not to share sensitive information, but to grow its own analytical and data recognition expertise. From there, it’s able to analyze and make recommendations based not only on what’s going on in your business, but on the larger market picture as well.   It’s a rising tide that lifts all boats, giving commodities businesses more intelligent insights and better decision-making, while still protecting sensitive data.

What’s at Stake if You Miss This Trend

Without clean, accurate data, you’re flying blind. You might be over or under-buying on a contract because your data doesn’t account for the most recent transactions you made against it. So, it’s not just costing you the ability to forecast and scale, it’s costing you money—and your reputation—in the present tense. Will the parties you trade with continue to do business with you if you don’t fulfill the terms you both agreed on? Will you be able to make up for the additional unbudgeted costs for buying too much? Is the availability of inventory accurate and is it where the business requires it to be?

And you may wonder if sharing your data is worth it. It certainly seems to go against the conventional wisdom of locking everything up tight. And it is important to be vigilant when choosing an AI solution provider, to ensure they take data security as seriously as you do. But with the proper safeguards in place, an industry-specific AI can be an incredibly powerful team member with the big-picture insights that help you move forward.

How to Get on the Right Track

It can be tricky to balance the desire to keep your data locked up in a vault with your need to save time and increase flexibility in your day-to-day operations.

We recommend going slowly and partnering with a provider with experience in the commodities arena. They’ll help you set up the system and work with you to feed it the right information so it can start giving you the real-time data you need. They’ll also help you decide which data shouldn’t be entered, so you’ll always have confidence that your trade secrets are safe. But you should expect your vendors to be commodity experts so they can help you to optimize the impact across your processes.

2024 Is Coming: Is Your Commodities Business Ready?

Some trends come and go, but AI is no mere trend.

Already, its power is being harnessed by businesses across the globe, to help them unclog their processes and data and give them the speed and intelligence that will help them stay ahead. Commodities businesses who want to succeed in 2024 and beyond will move toward AI that intelligently applies what it knows, while training it to further excellence with clean industry data – resulting in real-time intelligence, better decisions, and optimal outcomes.

Ready to discuss AI and data digitization for your company? We’re happy to talk about solutions.