{"id":5715,"date":"2026-09-17T12:44:48","date_gmt":"2026-09-17T10:44:48","guid":{"rendered":"https:\/\/adagri.com\/?p=5715"},"modified":"2026-09-17T15:48:04","modified_gmt":"2026-09-17T13:48:04","slug":"how-ai-in-agricultural-marketing-is-changing-the-way-farmers-make-decisions","status":"publish","type":"post","link":"https:\/\/adagri.com\/en\/blog\/jak-ai-w-marketingu-rolniczym-zmienia-sposob-podejmowania-decyzji-przez-rolnikow\/","title":{"rendered":"AI in agricultural marketing. How are farmers' decisions changing?"},"content":{"rendered":"

Today, a 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 matches their actual production needs.<\/span><\/p>\n

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.<\/span><\/p>\n

These channels still serve their purpose. However, what is changing is <\/span>information retrieval and selection process architecture<\/b>. Added to the existing ecosystem <\/span>generative artificial intelligence<\/b><\/a>. Thus, AI in agricultural marketing is becoming part of a broader shift in how audiences acquire, compare, and verify information before making a decision.<\/span><\/p>\n

Today, a farmer can send a query to an AI tool and, instead of a classic list of results, receive <\/span>a concise response, a comparison of solutions, a set of pros and cons, or a recommendation for the next step<\/b>. At the same time, the algorithms of search engines and social media platforms are exerting an increasingly strong influence on which content is exposed, in what order, and in what context.<\/span><\/p>\n

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

For agricultural marketing<\/a> this means much more than just adding ChatGPT, Perplexity, or Gemini to the list of communication channels. It is changing <\/span>brand presence model in the information process<\/b>: from classical visibility in a specific channel to presence in responses, recommendations, and contexts generated by AI systems.<\/span><\/p>\n

From multiple information sources to the purchasing decision\u00a0<\/b><\/h2>\n

Classic model <\/span>marketing funnel<\/b> is a convenient simplification: we build awareness, generate interest, support the consideration stage, and then drive conversion.<\/span><\/p>\n

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

A farmer may first watch a video on Facebook, then verify the opinion in a direct conversation with a neighbor, and next 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 later visit the manufacturer's website.<\/span><\/p>\n

For larger investments, this kind of <\/span>customer journey<\/b> can span multiple touchpoints and stretch over weeks or months. Individual interactions do not form a single, predictable sequence. They can serve an informational, verification, or comparison function, or directly support the purchasing decision.<\/span><\/p>\n

Today, additionally enters between these contact points <\/span>AI layer<\/b>.<\/span><\/p>\n

The user can ask:<\/span><\/p>\n