AI in agricultural marketing. How are farmers' decisions changing?

Today, the farmer is involved in a multi-source decision-making process. They are looking for a tractor, a plant protection product, a corn variety, or a fertilization solution. They verify parameters, confront opinions, compare technologies, and check whether the salesperson's recommendation corresponds to their actual production needs.

Until recently, a marketer could relatively easily identify the main brand touchpoints and the most important sources of information used by farmers. These were primarily Google, industry portals, forums, manufacturer websites, YouTube, and direct contacts with an advisor, dealer, or another farmer.

These channels still serve their purpose. However, what is changing is architecture of the information search and selection process. Added to the existing ecosystem generative artificial intelligence. As a result, AI in agricultural marketing is becoming part of a broader shift in the way audiences acquire, compare, and verify information before making decisions.

Today, a farmer can submit a query to an AI tool and, instead of a classic list of results, receive a concise answer, a comparison of solutions, a set of pros and cons, or a recommendation for the next step. At the same time, the algorithms of search engines and social media platforms are exerting an increasingly powerful influence on which content is exposed, in what order, and in what context.

As a result The farmer's customer journey is becoming less linear, more fragmented, and increasingly dependent on algorithmic information selection.. The user is not only switching between consecutive channels. Increasingly, they are also using the AI layer, which aggregates, interprets, and organizes information from various sources.

For agricultural marketing this means much more than just adding ChatGPT, Perplexity, or Gemini to the list of communication channels. It is changing brand presence model in the information processfrom classic visibility in a specific channel to presence in answers, recommendations, and contexts generated by AI systems.

From multiple information sources to the purchasing decision 

Classic model marketing funnel is a convenient simplification: we build awareness, generate interest, support the consideration stage, and then drive conversion.

The problem is that the actual procurement process rarely proceeds in such an orderly fashion. The farmer's decision-making path is multi-channel, non-linear, and dependent on the purchasing context.

A farmer may first see a video on Facebook, later verify the opinion in a direct conversation with a neighbor, and then search for the product on Google. After a few days, they might talk to a sales representative, return to YouTube, analyze a discussion on a forum, and only then go to the manufacturer's website.

For larger investments, this kind of customer journey can span multiple touchpoints and last for weeks or months. At the same time, individual interactions do not form a single, predictable sequence. They can serve an informational, verification, or comparison function, or directly support a purchasing decision.

Today, additionally enters between these contact points AI layer.

The user can ask:

• which tractor will be suitable for a farm of a specific size,
• what is the difference between the two varieties,
• which herbicide will work well in specific conditions,
• what are the limitations of a given technology,
• what to look for when buying a telehandler,
• how to compare offers from several manufacturers.

In such a model, the brand does not always communicate with a potential customer directly anymore. Between the brand and the recipient appears AI interface, which searches, selects, organizes, interprets, and synthesizes information from multiple sources.

That's what changes the character brand touchpoint. Visibility is no longer determined solely by the presence of a product in a search engine, on the manufacturer's website, or in social media. What is also gaining importance is, whether the brand and its offer will be included in the response generated by the AI system and in what context they will be presented to the recipient.

And that is precisely one of the most important changes.

A brand can be a source of answers even when the user does not visit its website

„Generative AI is changing not only the way information is searched, but also the architecture of the decision-making process. The user no longer has to move from a query to a source to obtain and preliminarily organize information. The AI system aggregates data from multiple sources, selects them, and synthesizes them into an answer. For brands, this means the necessity of analyzing visibility not only in search results, but also in the layer of answers generated by AI systems.”
— Marcin Chrobot, co-founder and CEO of Martin & Jacob

For years, one of the primary goals of SEO was to guide the user from a search engine to a brand's website. The search model was based on a simple scheme: the user entered a query, received a list of results, chose a specific link, and went to the information source. In a generative model, the response can be generated directly within the AI system, based on information from multiple sources. 

Table 1. Traditional and Generative Information Retrieval Model 

Generative AI changes not only the way information is searched for, but also brand presence model in the information process. The user can receive a response containing information about a product or company without visiting its website beforehand.

For the brand, this means the need for a broader perspective on visibility. Question „Are we high on Google?” stops exhausting the topic of brand presence in the information search process.

Equally important is the question: „Are information about our brand and products available in sources from which AI systems can build answers?”

Another level of analysis also appears: „What image of our brand will emerge when the system compiles information from our website, industry portals, user reviews, dealer materials, forums, and other publicly available sources?”

This is of particular importance in the agricultural sector, where a purchasing decision often requires comparison technical data, economic parameters, user experiences, and practical applications of the solution. In such an environment, a brand can participate in the decision-making process even when the user does not visit its website directly.

The brand has less and less control over the context of the message. 

A brand can design a campaign very precisely. It can define the target group, prepare the creative work, select reach channels, and determine the sales arguments.

However, he does not control all of it informational context, where the recipient will encounter the product and evaluate it.

A farmer might see a manufacturer's ad, and a moment later:

• read the comments and user experiences,
• find an article comparing available solutions,
• watch the machine test,
• ask the AI system for alternative solutions,
• analyze the forum discussion,
• contact the dealer,
• consult the solution with an advisor.

Each of these touchpoints can provide new information, change the interpretation of a previous brand message, or influence the further direction of the decision-making process.

That is why it is increasingly difficult to describe marketing as sequence of planned and controlled advertising exposures. The recipient operates within a much broader information environment, where the brand message is confronted with content from many independent sources.

It therefore becomes much more accurate to think of agricultural marketing as information ecosystem, in which the brand is one of many participants, and its message is subject to continuous verification, interpretation, and contextualization.

The problem is not the lack of information, but the selection of it.

Just over a decade ago, one of the fundamental challenges was availability of information. Today, the problem increasingly looks the other way around. The recipient operates in an environment of an excess of content, sources, and messages, which is why the importance of mechanisms responsible for their is growing. selection, prioritization, and interpretation.

In practice, it is increasingly important that, who or what decides what information the recipient will see, which of them will be omitted, and which they will assign sufficient credibility to use in further decision-making.

The function of such filters is already performed today by social media algorithms, search engines, and recommendation systems. Generative AI adds another layer to this. The system can aggregate information from multiple distributed sources, select it according to the query context, and then present it to the user. one synthetic answer.

This also changes the marketing perspective. The question „How to reach a farmer?” no longer resolves the problem of effective communication.

Equally important is the question: „What will happen to our message when the farmer starts confronting it with information from other sources?”

This means moving from thinking exclusively about distribution of the message to analyze its further functioning in the information environment. The brand must take into account not only the moment of reaching the recipient, but also how its message will be verified, compared with competitive information, and used at subsequent stages of the purchasing decision.

Reach matters, but it doesn't define effectiveness 

This does not mean that traditional advertising is losing its function. Reach continues to support building brand awareness, introducing new products, increasing the recognition of the offer, and initiating interest among potential audiences.

The problem begins when reach is becoming the primary metric of campaign effectiveness.

Reaching 100,000 people still does not allow to determine:

• how many recipients actually matched the target customer profile,
• how many were at the stage where the message could have influenced their decision,
• how many showed interest in the product or solution,
• how many verified the message in other sources,
• how many included the offer in the comparison process,
• how many moved from interest to actual purchase consideration.

The importance in agricultural marketing quality of reach and audience matching is particularly important. A 20-hectare farm and an 800-hectare farm can be classified in the same „farmer” category, but their needs profile, investment potential, production structure, machinery park, decision-making process, and potential business value can vary significantly.

Therefore, reach volume alone does not allow for assessing the actual communication values of the campaign. An analysis is needed of who the message reached, what stage of the decision-making process the recipient was in, and whether the contact with the brand translated into subsequent actions.

That is precisely why during agricultural marketing conference PLUSAGRI 2026 In November, the question will arise as to why a large reach can be a wrongly defined agro campaign goal. The conference program focuses precisely on communication effectiveness, trust-building, data utilization, and changes in the way farmers acquire, select, and verify information. 

What does this change mean for agricultural brands?

The change in the way information is searched and processed necessitates a broader perspective on brand presence in the information environment. Just being present in selected channels is not enough. The brand must also take into account the places and sources from which a potential customer acquires, compares, and verifies information.

Table 2. How does the presence of the agro brand change in the information environment? 

„In the generative AI environment, a brand must be present not only in channels that directly direct the user to its website. The quality and consistency of information available across the entire digital environment are also gaining importance. An AI system can use multiple sources, so the communication strategy should also take into account how information about the brand functions outside of its own channels.”
— Jacek Skowroński, Management Board Member, Chief Technology Officer

A broader overview of the brand's presence

The first conclusion is simple: A media plan can no longer be the brand's only roadmap for presence. The company should know not only where it is buying advertising space, but also where potential customers might look for information about its products and solutions.

This means the necessity of parallel management advertising, SEO, expert content, PR, industry portals, social media, dealer materials, customer reviews, online communities, and sources used by AI systems.

Consistency of Information as an Element of Credibility

The second change concerns consistency of the information message. If the manufacturer presents a product in one way, the dealer communicates different information, an industry article emphasizes other features, and users describe the product in yet another way, the recipient receives an inconsistent picture of the offer.

In the generative AI environment, the problem can be further highlighted. The system can aggregate information from various sources and construct a response based on it. Therefore, the consistency of data about a product, its application, parameters, and limitations becomes an element of management. brand credibility.

Content as a Knowledge Resource

The third change concerns quality and content features. The material published by the brand ceases to serve solely as a tool for acquiring traffic from Google. It becomes a resource of knowledge about the brand, the product, the technology, and the problems that the potential customer faces.

That is why agricultural brands should create materials that address real questions arising in the decision-making process:

• How does the product work?
• Who is it for?
• Under what conditions is its application justified?
• What operating costs does it incur?
• What solutions can it be compared to?
• What are its limitations?
• What does its implementation look like?

The more specific, up-to-date, and verifiable information the brand shares in its channels and external sources, the greater its ability to participate in the recipient's information process – even when the recipient does not land directly on its website.

Marketing must also begin to monitor the verification stage

So far we have devoted a lot of attention to, How customers find the brand. However, one question is becoming increasingly important: where does he go later to verify information and assess whether he can trust the brand?

This can be:

• Google,
• agricultural portal,
• Facebook group,
• conversation with a dealer,
• another farmer,
• question asked to the AI system.

This does not mean that artificial intelligence will automatically replace existing sources of information. We currently have no basis to assume such a scenario regarding Polish farmers.

That is why we need data showing how the process of information search and verification actually takes place.

Does the Polish farmer actually use AI in decision-making?

This is one of the questions it is supposed to answer PLUSAGRI COMDEX 2026 – Martin&Jacob research project.

The study is not limited to measuring artificial intelligence awareness among farmers. It analyzes, among other things,. sources of information, use of AI tools, methods for verifying answers, level of trust, and the place of new technologies in the decision-making process. The project combines CAWI and FGI research with an analysis of the behavior of the agricultural community.

This distinction matters because different levels of contact with AI can be pointed out:

• knowing what ChatGPT is, for example,
• use it for simple questions,
• use AI responses when choosing a product, technology, or solution for the farm.

Only an analysis of actual behavior will make it possible to determine, what function does AI currently play in the information and decision-making process of the Polish farmer, and is it becoming an important touchpoint with the brand.

From the question „where to advertise?” to the question „how is a decision made?”

This is one of the most important changes in the way of thinking about agricultural marketing.

For years, the fundamental question was: How to reach a farmer?

Today we need to step up to the next level and analyze the whole the process of gathering and verifying information:

• How do farmers access information?
• How does it compare the available solutions?
• Which sources does he trust?
• Where does it verify the information it receives?
• Which information actually influences his decision?

AI does not eliminate existing communication channels. I am adding another layer to the already assembled information process, in which the farmer uses multiple sources and repeatedly verifies information before making a decision.

That is why agricultural marketing today doesn’t just need a greater number of messages. It needs better understanding of the process by which information is selected, verified, and ultimately influences the purchasing decision.

A large part will be devoted precisely to this issue PLUSAGRI 2026 – Agricultural Marketing Communication Forum, which will take place on November 18 in Warsaw under the slogan „Farmer in the Age of AI”. 

November 18, 2026.
Warsaw Presidential Hotel, Warsaw
PLUSAGRI – Agricultural Marketing Communication Forum
„Farmer in the Age of AI”

Participation in the conference is free of charge and possible only on the basis of a personalized invitation.

Discover the PLUSAGRI 2026 program and register your interest in receiving an invitation → plusagri.pl 

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