Modern farming is as much about data as digging. Here are 3 emerging agricultural skills

• Emerging technologies are changing the role of farmers, agronomists and agricultural intermediaries.

• Every job in farming will require some reskilling in the coming decade.

• As the human-robot relationship is defined, data analysis skills will be particularly important.

Emerging technologies in the field such as artificial intelligence, computer vision and robotics will play a key role in the ability to improve the productivity and performance needed to feed a growing population. These new tools, technologies and devices on the field are redefining the day jobs of agronomists and food growers. Educating the agricultural workforce with the skills to manage and harness the power of these new robots and tools will be crucial to achieve mass adoption.

Managing a farm, including its workforce, is changing. On the one hand, automation of existing processes and new technologies means that some workers will need to retrain or reskill as their jobs will become obsolete. On the other hand, as a farm increases capital per worker, particularly as many of the new technologies utilize automation, it is important to assess whether its employees have the right skills to fully take advantage of new technologies. Every job in the ecosystem is being redefined, and so are the skills and capabilities that are required to succeed in these professions.

Over the past 30 years, there has been a significant consolidation of farms. This means that small traditional holdings have transitioned into larger businesses in which farmers' roles changed to that of managers. Government data shows that in the US, large farms with over $1 million in revenues account for 50% of US farm production, up from 30% in the 1990s.

Farmers are already spending more time in front of screens and less time in the field. The image we have of a farmer on his tractor is fast becoming a thing of the past. Autonomous tractors will pull or push machinery for ploughing, tilling, disking, harrowing or planting. The same goes for other human processes such as picking fruits, which are being roboticized. All these autonomous devices and new technologies require management, which the farmer will be responsible for. Identifying the right product fit as a buyer, knowing how to operate new devices, and understanding the return on investment (ROI) that technology brings as part of their existing infrastructure will be crucial.

The image of the agronomist as a “plant doctor” is rapidly changing to that of a data scientist. Of course, their experience and vast knowledge about an area is crucial, but now they will also have to combine their knowledge with many additional data sources from devices such as sensors and aerial imagery – and they will need to understand the tools to aggregate, manage, and analyze this data. Interpreting data and insights, and turning them into action will be a process, especially when there is a clash between data-driven recommendations and intuition (or existing methods) that have guided the decision-making process in the past.

Precision agronomy is becoming a career in its own right. The profession will focus on helping growers with precision agriculture practices and act as a bridge that connects technology and data-driven insights to traditional agronomic practices. In order to support farmers, and to fully understand the value and ROI of new practices and products, agronomists will need the right statistical tools and skills to understand the significance of the results.

Dealers and vendors of agricultural products and equipment also play an important role in the future of agriculture. They used to make straightforward transactions selling equipment, seeds, chemicals, etc. When the product they sell to farmers is a technology platform or a robot, leading the training and onboarding process will also become a crucial part of their role. They will need to become teachers or trainers to help customers get the most value out of these platforms or devices – besides being a salesperson, the success in their role will depend on their ability to teach farmers how to use them.

Food growers rely on an increasing tech stack of software (dashboards, analytics, programmatic alerts) and hardware (robotics, sensors, cameras, etc). Orchestrating them so they all work in sync and towards the same productivity goals will be key. The help and support of technology vendors will play a crucial role in helping farmers integrate new technologies into existing processes and systems.

In the long term (five to 10 years), many roles will involve learning to manage a fleet of robots. More and more tasks which used to be done manually are being automated. Full harvest automation will be a reality in the coming years. Just like with autonomous vehicles becoming commonplace in cities, so will autonomous tractors in the field. Weeding robotics can be incredibly accurate and reduce pesticide usage by 90% with computer vision. Drones will help food growers monitor conditions remotely, and even apply fertilizers and other treatments from above. All these will require the industry to rethink our relationship with robots, also known as human-robot interaction (HRI). Figuring out how to optimize the way in which humans work side-by-side with robots will be an industry in itself in a not-so-distant future.

In the mid-term (three to five years), until tech platforms are completely intuitive and robots fully autonomous, the emphasis when it comes to skills will be on platform orchestration and data management. Selecting, aligning and managing all the tools and platforms to increase productivity is still a complex task – which requires significant input from tech creators, vendors and farmers themselves.

Since many of the new technology tools deliver an unprecedented amount of data, the short-term challenge is to transform data into insights and therefore value. For example, over the past few years many farmers have learned how to read aerial imagery. However, in the future they should be able to receive insights based on data that has been already processed and analyzed. In the meantime, skills in data analysis to improve the level of data literacy will give food growers an edge to adopt emerging technologies.