Generative AI isn’t just transforming marketing — it’s already embedded in how marketing teams work. From researchers using AI to analyze customer sentiment to designers automating routine tasks, marketing professionals across functions are finding practical, immediate applications for AI tools. 

Unlike traditional martech implementations, this transformation is happening from the ground up as individual marketers adopt AI assistants for their daily work. Technology providers are rapidly developing AI agents for various jobs to be done and are now selling them to businesses and customers alike. 

Mapping AI’s impact on marketing teams

The primary workplace applications of genAI tools involve understanding information and generating text, followed by image, video and code generation, according to Forrester. These capabilities directly impact core marketing activities, reshaping how work will be done.

Since job titles and responsibilities vary across organizations, I’ve identified four key “jobs to be done” categories — understand, create, enable and execute — along with the roles that benefit most from the transformation driven by genAI and automation.

Understand

Understanding is the foundation of all marketing activities. Knowing how customers relate to a product, identifying key pain points and crafting messaging that resonates with the target audience all stem from “understanding” roles.

Market researchers use AI and automation to collect and analyze large datasets from various sources, including third-party and custom-built solutions. AI quickly interprets customer sentiment from open-text survey responses, social media posts and call-center transcripts. Additionally, synthetic personas help test and validate product value and messaging. With these advancements, researchers can generate insights faster, saving time and money before launching marketing campaigns.

Product marketers rely on AI to predict market trends, review competitor products and assess customer engagement in product categories, refining their launch strategies. In collaboration with business planning teams, AI assists in evaluating pricing across different regions, bundling offerings and comparing special deals against competitors. Automation also streamlines product launch logistics, managing handoffs and approvals between teams. Even with open-source genAI models, product marketers gain deeper insights into how their products will be received.

Data analysts use AI for advanced analytics, including predictive modeling and next-best-action recommendations, transforming data into actionable insights. Automation enhances routine data processing, report distribution and visualizations, improving the communication of campaign findings. Teams are now building AI agents to help marketers query and interpret insights for broader reach and understanding.

Dig deeper: The AI-powered path to smarter marketing

Create 

Creation roles are seeing the most immediate benefits from genAI, as the technology rapidly generates various outputs, including text, images and videos — individually or in combination. While genAI can assist with everyday tasks like drafting emails, summarizing text and generating first drafts of written content, it has a powerful impact on these four marketing-specific roles.

Communications and public relations experts use genAI to produce content for press releases, interviews and executive briefings, but its capabilities go further. AI can transcribe and translate interview recordings, improving efficiency and accuracy. Additionally, AI tools monitor consumer sentiment on social media and can respond with predefined replies to mitigate negative feedback.

Content strategists have long used genAI for idea generation, drafting text and optimizing content for SEO and SEM. Now, with proprietary models connected to historical data and company style guides, they can produce more personalized and differentiated content by segment, significantly reducing turnaround time.

Social media managers have benefited from AI through dynamic creative optimization (DCO) partners, which distribute timely and relevant ads to consumers. With genAI, teams can take more control of the ad creation process by generating copy variations, videos, images and translations using various tools.

Designers may have mixed feelings about genAI, but most will benefit from its ability to automate tedious tasks like image resizing and layout updates. It also assists with concept ideation, video editing and localization of assets. Even if design teams choose to maintain control over core graphic creation, AI can streamline supporting tasks — boosting efficiency, reducing reliance on agencies and saving time and money.

Dig deeper: A co-pilot approach to genAI (with prompt examples)

Enable

The foundational platform teams are often left out of the marketing transformation story. However, data and technology enable all marketing execution, driving customer interactions. As genAI proliferates over the next several years, these teams will see significant changes in their responsibilities.

Data engineers use AI to optimize data pipelines, automate processing tasks and detect anomalies to ensure data reliability. As companies develop custom models for proprietary outputs, data engineers must manage data contextualization, access controls and the increasing volume of new data generated by AI. Unlike other teams that simply use genAI, data engineers are responsible for enabling the proprietary models on which genAI is built.

Marketing technologists may not be the end users of genAI, but they are essential in implementing AI solutions at scale. As martech providers introduce new AI capabilities, technologists must design scalable architectures, select the best tools and data components and ensure they meet business needs. This transformation requires careful evaluation of product capabilities, licensing costs and implementation timelines.

Dig deeper: Don’t have the time to implement time-saving AI tools? Here’s what to do.

Execute

Teams responsible for executing marketing campaigns will experience significant changes in their roles with genAI.

Marketing operations (MOps) uses AI to automate repetitive tasks and workflows, such as template generation, campaign configurations and distribution. In the coming years, AI-driven workflow changes will eliminate entire steps and processes, reducing time to market and lowering costs.

Field marketers leverage AI to personalize and localize centrally produced content, making it more relevant and impactful. AI tools also help analyze and predict event success, identify potential leads and prioritize them based on conversion likelihood.

Dig deeper: Implementing AI into MOps, from campaign launch to refinement and optimization

The time for change is here. GenAI is now embedded in everyday tools, from smartphones to office productivity software. Those who embrace it will stay ahead of the curve and gain more time to focus on soft skills — building relationships, expanding networks and, most importantly, thinking strategically. Let genAI handle the routine tasks so you can concentrate on what truly sets you apart.