A few years ago, “AI in marketing” meant a chatbot on your website and recommendation algorithms gently suggesting other items you might buy. The conversation in marketing departments sounds much different in 2026, when you walk into the weekly strategy meeting. It is not about whether to use AI for this or that campaign. It is now about which elements of the project should not be automated and handled by humans.

• The Rise of AI

Artificial intelligence has long been embedded in marketing software, providing slightly better targeting, segmentation, and automation. At the same time, marketing leaders are now beginning to treat it more as an assistant, briefing it with instructions similar to those used when assigning work to a junior colleague. The AI is tasked with developing marketing strategies, with humans acting as supervisors.

This shift in the relationship is sometimes referred to as “agentic” marketing. It is less a matter of entirely new technologies and more a matter of adopting new approaches in which artificial intelligence actively participates in planning and decision-making. For example, instead of a human marketer making adjustments to a Facebook campaign every couple of days, an AI agent can constantly analyze its performance, reallocating the budget from underperforming channels to the most efficient ones.

• The End of Search Dominance

Another significant development in the field is the growing impact of artificial intelligence on search. If users begin asking questions that only make sense within the context of an entire conversation or turn to voice assistants to get answers, the way search engine optimization works will need to change. Instead of appearing on page one of Google search results, marketers may need to convince AI systems that their content represents the most accurate answer to a query.

Some companies have already begun experimenting with this emerging paradigm, referred to as Generative Engine Optimization (GEO). They are adapting their content in such a way that allows AI systems to extract and use it as a response to specific questions. From a writer’s perspective, it means creating content not for human readers but for machines that can later present it to humans in their own words. If companies fail to adapt, their online presence may gradually disappear from search results.

• New Approaches to Personalization

Artificial intelligence has opened up new opportunities for personalization, but this has also had downsides in terms of privacy. Users today are much more aware of being monitored and have reduced trust in brands that use third-party cookies to track their behavior across websites. Instead of attempting to collect as much information as possible about individual customers, many companies are now focusing on providing a better experience while being transparent about how their data is used. Thus, instead of simply targeting consumers based on their browsing history, organizations can use first-party data and AI to anticipate what they may want to buy based on existing preferences.

Effective personalization still requires striking a delicate balance between convenience and privacy. A good example is a recommendation system that learns a user’s favorite products and suggests them in subsequent purchases. On the other hand, a similar approach may seem intrusive if the company has no prior relationship with the consumer or has not explicitly requested it.

• The Future of Marketers’ Work

There is a common misconception that artificial intelligence will eventually replace human marketers. In practice, however, most companies are not looking to automate decision-making processes entirely. AI takes over some routine and time-consuming tasks, such as creating campaign variations, summarizing reports, publishing content, and testing messages at scale. At the same time, human input is required to ensure that the results make sense and align with the brand’s voice and values. In many ways, it is an extension of people’s natural ability to perform simple actions much faster than humans while leaving complex judgments to humans.

It is worth noting that AI lacks the common sense and social intelligence to understand the nuances of marketing messages. Thus, in practice, marketers still need to review what the system is proposing before making it public. It could be much less efficient to rely solely on automation, especially since there have been examples of companies’ AI systems failing to recognize critical cultural differences when developing campaigns. There have been cases where a marketing campaign had to be canceled because an AI algorithm did not know about a certain holiday and therefore decided to send a cheerful message to consumers on the day of a national tragedy. Humans would have been able to plan for such a possibility and ensure that the campaign was canceled or adjusted to avoid potentially offensive content.