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.
The post 4 marketing ‘jobs to be done’ being transformed by genAI appeared first on MarTech.
# How GenAI Is Transforming 4 Key Marketing Jobs to Be Done
Generative AI (GenAI) is revolutionizing the marketing landscape by automating tasks, enhancing creativity, and enabling hyper-personalization at scale. As businesses strive to stay competitive, GenAI is reshaping how marketers approach their core responsibilities. This article explores four key marketing jobs to be done (JTBD) and how GenAI is transforming them.
## 1. **Content Creation and Optimization**
### **Traditional Challenges:**
Marketers often struggle with producing high-quality, engaging content at scale. Content creation is time-consuming, and ensuring consistency across multiple platforms can be challenging.
### **How GenAI Is Transforming It:**
GenAI-powered tools like ChatGPT, Jasper, and Copy.ai are revolutionizing content creation by:
– **Generating high-quality content** in seconds, including blog posts, social media updates, email copy, and product descriptions.
– **Optimizing content for SEO** by suggesting keywords, meta descriptions, and readability improvements.
– **Enhancing personalization** by tailoring content to different audience segments based on behavioral data.
**Example:** A fashion retailer can use GenAI to generate personalized product descriptions and blog posts tailored to different customer personas, improving engagement and conversions.
## 2. **Customer Insights and Market Research**
### **Traditional Challenges:**
Gathering and analyzing customer insights requires extensive data collection, surveys, and manual analysis. This process is often slow and resource-intensive.
### **How GenAI Is Transforming It:**
GenAI accelerates market research and customer insights by:
– **Analyzing vast amounts of customer data** from social media, reviews, and surveys to identify trends and sentiment.
– **Generating predictive insights** to anticipate customer needs and preferences.
– **Automating competitor analysis** by summarizing key trends and strategies from industry reports and online sources.
**Example:** A SaaS company can use GenAI to analyze customer feedback from support tickets and social media, identifying pain points and opportunities for product improvement.
## 3. **Ad Campaign Development and Optimization**
### **Traditional Challenges:**
Creating and optimizing ad campaigns requires extensive A/B testing, audience segmentation, and creative iteration, which can be time-consuming and costly.
### **How GenAI Is Transforming It:**
GenAI enhances ad campaign performance by:
– **Generating ad copy and visuals** tailored to different audience segments.
– **Optimizing ad performance** by analyzing historical data and suggesting improvements in real time.
– **Automating A/B testing** by quickly generating and testing multiple ad variations.
**Example:** An e-commerce brand can use GenAI to create multiple versions of Facebook and Google ads, automatically testing which performs best and adjusting in real time.
## 4. **Personalized Customer Engagement**
### **Traditional Challenges:**
Delivering personalized experiences at scale is difficult, requiring extensive data analysis and manual content customization.
### **How GenAI Is Transforming It:**
GenAI enables hyper-personalized customer engagement by:
– **Creating dynamic email campaigns** that adjust content based on user behavior.
– **Powering AI-driven chatbots** that provide real-time, personalized customer support.
– **Customizing website experiences** by dynamically adjusting content based on visitor preferences.
**Example:** A travel company can use GenAI to send personalized trip recommendations based on a customer’s browsing history and past bookings.
## **Conclusion**
GenAI is transforming marketing by automating tedious tasks, enhancing creativity, and enabling data-driven decision-making. As businesses embrace AI-powered tools, marketers can focus on strategy, innovation, and building deeper customer relationships. Those who leverage GenAI effectively will gain a competitive edge in the evolving digital landscape.
### **Key Takeaway:**
Marketers who integrate GenAI into their workflows can enhance efficiency, creativity, and personalization—ultimately driving better results and customer experiences.
Would you like insights on specific GenAI tools for marketing? Let us know! 🚀
Recent Comments