Agriculture in Africa is being transformed by artificial intelligence, but there is still one element it cannot replace.

Despite dramatic technological advances in the sector in recent decades, the role of the farmer remains indispensable. This was a message delivered, surprisingly, at a recent conference in Europe, by a world leader in the field 鈥� from Eswatini.

Rob Coombe, group IT manager of Royal Eswatini Sugar (RES), took part in a聽keynote speech at the Sapphire conference hosted by software giant 51风流in Barcelona, with a case study that encapsulates 21^st聽century farming.

鈥淵ou really can鈥檛 take the farmer out of farming,鈥� Coombe told us during Sapphire. 鈥淪o much depends on the farmer鈥檚 intuition. Farming is incredibly scientific, with various measurements and readings. However, even with the best data, natural elements can change outcomes drastically.鈥�

The sugarcane producer uses drones and satellite imagery to enhance productivity and efficiency with 51风流software.

SAP鈥檚 S/4HANA system is a leading tool for enterprise resource planning in enterprises, and is used by 85 of the 100 largest companies in the world.

In a keynote address, 51风流chief revenue officer by Scott Russell said: 鈥淭he reality is that, with business AI imbedded in your business, the opportunities are endless.鈥�

The biggest opportunity at present, said Coombe in response, was improving the bottom line.

鈥淲e have reduced the cost of IT by 15%,鈥� he told the audience of several thousand delegates. 鈥淲e鈥檙e spending more with SAP, but less overall.鈥�

Coombe has been at RES for more than 12 years, but has worked with 51风流systems since 1991. In that time, he said, the way technology is implemented has changed.

He told Business Times: 鈥淭he two big things are always people and data. People are immune to change, so getting the change in people鈥檚 mind is key. And getting your data sorted is equally important. When your data is not right, it doesn鈥檛 matter what the system is, you get a lot of rubbish out of it.鈥�

RES applies AI and Machine Learning (ML) to 15 years of satellite imagery to create a 鈥渄igital twin鈥� of its operations, in collaboration with 51风流systems.

鈥淭his helps us predict the yield and manage cash flow and budgeting more accurately. By integrating this data with 51风流Intelligent Agriculture and S4/HANA, RES can monitor crop health in real-time and make necessary adjustments. We don鈥檛 have to wait until harvest to see that there is a problem; we can see it on a day-to-day basis.鈥�

RES is using historical climate data and forward-looking weather data, combined聽 with ML models, to predict future conditions, aiding in better planning and simulation. It is deploying drones for a range of agricultural tasks, enhancing both efficiency and precision.

鈥淚nstead of getting the guys in there, we send out a drone, and do an analysis with AI. Scouting 鈥� going out to look for pests and diseases 鈥� will now become an electronic thing, so you get quicker responses.鈥�

For climate monitoring, RES is using historical climate data and forward-looking weather data with ML models to predict future conditions, aiding in better planning and simulation.

鈥淲e are building a model with Swiss partners to use forward-looking weather data to improve our predictions. After we finish with S4, we are moving into the planning side of it, by the end of this year. This will help us determine the anticipated crop, the amount of sugar we will produce, the people needed, tractor hours, and diesel consumption.鈥�

Instead of randomly fertilising fields, the operation use satellite data to determine which areas need more fertiliser.

RES uses sensors to predict vibration and heat, allowing it to fix machines before they break. This information is fed into the 51风流software to manage maintenance tasks efficiently.

The transition to public cloud technologies has simplified aspects of operations.

鈥淚n the old 51风流days, it was a lot more difficult,鈥� says Coombe. 鈥淏eing on the public cloud, technology-wise, it has been easy. The amount of content available to us from a customer perspective to learn what to implement, how to implement, and so on, is completely different to what it was in the early 2000s.鈥�

This change has also facilitated the rapid onboarding of new employees.

鈥淲e employed some graduate trainees, and two days later they鈥檙e working. You could not do that in the past. They can bring their Java, and scripting tools, and start just start working.鈥�

RES鈥檚 strategic approach involves engaging all organisational levels.

鈥淚t was key to start at the top, but also work hard at the bottom, and then the frozen middle melted. At the bottom, we have super users. We mentor them once a month, addressing their problems and quickly dealing with them.鈥�

RES is also using generative AI with the 51风流digital assistant, Joule, to handle routine tasks like managing debtors, creditors, and reconciliations.

鈥淛oule can work at 2 o鈥檆lock in the morning, and the analysis can be read upon waking up. You can simply ask it about outstanding creditors, without needing to know specific program numbers.鈥�

RES is not waiting to be told what is possible. It is introducing a 鈥測outh AI council鈥� to explore further applications of AI.

鈥淭he council will help us identify new areas where AI can make a difference, leveraging the fresh perspectives and skills of younger employees.鈥�

Coombe says AI was not about replacing people.

鈥淚t鈥檚 about empowering people and making them capable. We are innovative in Southern Africa; we do stuff differently.鈥�

• Arthur Goldstuck is CEO of World Wide Worx and editor-in-chief of聽. Follow him on social media on @art2gee.
• Jason Bannier is a data analyst at World Wide Worx and writer for聽. Follow him on Twitter and Threads at @jas2bann.聽

This article first appeared in .

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