AI in Marketing: Trends, Platforms, and How to Train Teams

What is AI in marketing?

Artificial intelligence (AI) continues to redefine how organizations reach audiences, making it easier for marketers to automate tasks, gain insight into customers at scale, and offer engaging personalized experiences. 

According to the Marketing AI Institute’s 2023 State of Marketing AI Report, most surveyed respondents said that AI is “very” or “critically important” to their marketing efforts, particularly for reducing time spent on repetitive tasks. At the same time, companies are “lagging behind” in providing AI education and guidance [1]. Similarly, Influencer Marketing Hub’s 2023 Artificial Intelligence Benchmark report suggests that the main reason for not adopting AI technology in marketing is a “lack of understanding” [2]. 

Leaders in marketing, technology, human resources, or learning and development, have an opportunity to create a competitive advantage. A robust marketing strategy and team training using the latest AI technologies can transform how your organization markets to consumers. 

Real-world AI in marketing examples

The uses of AI in marketing are diverse. Here are some examples you may have encountered in your day-to-day experiences:

AI-powered dynamic pricing: when algorithms change prices in real time based on demand, competitor pricing, and other factors, such as with Uber’s ride-sharing app or airline ticketing

Personalized recommendations: when algorithms personalize product or content recommendations based on user behavior, such as with Spotify or Netflix’s media streaming services

Customer support chatbots: when AI bots powered by natural language processing interact with customers to answer questions and meet their needs 

Benefits of AI in marketing

AI in digital marketing, such as social media, email, search engine optimization, mobile apps, and display advertising, can enhance consumers’ interactions with your organization online. In addition, adopting AI marketing practices can help your organization remain competitive as the business world evolves. Let’s look at some of the other ways AI can benefit marketing teams and organizations overall. 

Automate repetitive tasks.

With AI technology, marketers can automate tasks like scheduling social media posts or email blasts in advance, generating web traffic reports, and delivering recurring webinars to registrants. With automations in place, marketers can focus on more strategic and creative aspects of marketing, such as building relationships with customers and exploring new marketing channels. 

Segment customers effectively. 

AI processes diverse customer data and uses algorithms to segment customers according to factors like purchase history, behavior, and interactions. 

Create more personalized marketing campaigns.

AI can predict future behavior based on patterns and trends in customer data, enabling marketers to anticipate and meet customers’ needs.

Generate better content faster. 

With generative AI programs like ChatGPT, you can explore topic ideas, conduct research, and see examples of marketing content you want to create in seconds. You can even prompt these programs to generate content that reflects the latest marketing trends. 

Read more: How To Write ChatGPT Prompts: Your 2024 Guide

Improve customer experience.

AI can help marketers provide more effective customer support, relevant product recommendations, and streamlined journeys across multiple channels. Having these systems in place can make it easier for customers to make purchases and may even encourage customer loyalty. 

Read more: What Is Omnichannel Marketing? Definition, Examples, and Strategy

Challenges of AI in marketing 

Along with the benefits, AI in marketing presents some challenges, particularly around data, that marketing teams should keep in mind as this technology evolves.

Transparency

How should content marketers disclose when content, such as an industry report or blog article, has been generated (partly or totally) by AI? What regulations are in place to determine how businesses should inform customers about data usage? 

Intellectual property

AI in content marketing poses challenges when AI systems use the intellectual property of a third party to generate new content without attribution. There may be disputes about ownership: Is it the user, the prompt engineer, the creators of the original data the system is trained on, or the AI system itself?

Legal and ethical concerns 

With AI systems often handling vast amounts of data, it’s important to consider how customers’ personal data is stored and used to avoid security breaches. In addition, marketers should be mindful of liability in instances of AI marketing errors. 

Read more: AI Ethics: What It Is and Why It Matters

Data quality concerns

Some AI systems are trained on historical data, which might present biases or inaccuracies in outputs. 

What is the future of artificial intelligence in marketing?

With the rapid adoption of AI, it’s important to stay up-to-date on AI marketing trends, including how AI will affect the job market. According to the Influencer Marketing Hub’s 2023 Artificial Intelligence Benchmark Report, some surveyed marketers believe that while AI will take over many marketing operations tasks and replace job titles, humans will still carry out high-level strategy and decision-making [2]. 

Read more: 5 In-Demand Jobs Requiring AI Skills

How to use AI in marketing

With a strong AI marketing strategy, you can help your organization achieve its goals in a rapidly changing business landscape. Follow these steps to get more out of AI technology for your team:

1. Conduct a marketing team brainstorming session. 

The purpose of this session is to get a clear picture of the marketing team’s initiatives, projects, and challenges. For example, the marketing team might be building brand awareness or promoting a new line of products. Their current technology stack may lack key features or team members might be spending too much time on repetitive tasks. 

Gathering this information can help you identify the best aligned AI marketing tools and tactics for the team. 

Tip: Include leaders from other teams within the organization in the brainstorm session to align marketing efforts and the use of AI technology with the organization’s business goals.  

2. Research AI marketing tools and platforms.

With a clear list of goals and challenges to overcome, have the team research various AI marketing tools that may help them market more effectively. Be sure to investigate tools across different areas of marketing, such as long-form content creation, branding, and social listening.  

Here’s a short list of tools beyond ChatGPT to get you started: 

• Sprout Social: Enables sentiment analysis, reputation management, social media scheduling, automated workflows, and customer service chatbots

• DALL-E: Creates customizable, brand-specific images 

• Keyword Insights: Enables content research, writing, and search engine optimization 

• Zapier: Enables automation of tasks and custom chatbots 

• Optimove: Enables data-powered multichannel marketing and personalization 

Once the team has a list of potential AI marketing tools, begin testing them and trying out their features to determine which will be the most effective. Consider factors such as price, ease of use, support documentation, customization, and reviews. Be sure to collect feedback from team members along the way to understand each tool's different advantages and disadvantages.  

According to Statista, the global AI software market is expected to reach around $126 billion by 2025 [3]. 

3. Create an AI training and upskilling program. 

Once you’ve finalized the AI marketing technology stack, a comprehensive training program can help your team integrate the individual tools and processes into their workflow smoothly. When designing the training program, consider the following: 

• Tutorials to teach the team how to utilize the tools’ functions 

• Survey forms to gather team members’ feedback on their experience

• Periodic follow-up training sessions to keep the team's AI marketing skills up-to-date and brainstorm new marketing initiatives

4. Implement an AI marketing strategy.

Start by updating the marketing strategy to reflect the team’s evolving skill sets and capabilities. The marketing strategy should be firmly rooted in the marketing and business goals and outline the specific tactics the team will implement to achieve these goals using AI marketing tools. Here are some goal-driven examples: 

• Increase email subscriber conversion rates using a customer relationship management system (CRM) that segments customers, personalizes email messages, and automates product recommendations based on customer data.

• Optimize long-form content for internet searches using an SEO tool that shows trending topics and keywords, click-worthy headlines and subject lines, and relevant research. 

• Create a customer loyalty program using an AI system that analyzes customers’ purchase history, behavior, and preferences to offer personalized rewards. 

Read more: Marketing Strategy: What It Is and How to Create One

5. Evaluate the results and look for ways to improve. 

Once the team implements an AI marketing strategy, set aside time periodically to evaluate its effectiveness. How much time do team members save by using AI marketing tools? How do the results of various campaigns compare to those of prior campaigns? What’s the return on investment (ROI) for these tools?

Tip: Consider setting up an A/B test to compare AI-powered marketing campaigns against regular marketing campaigns. Which campaigns perform better? 

Keep exploring generative AI

GenAI skills are becoming increasingly relevant to a wide range of professions and job roles. Learn more about this developing technology and how to use it with courses on Coursera.

• For a quick overview of GenAI, try Google Cloud’s one-hour course, Introduction to Generative AI.

• To learn what GenAI can do, check out DeepLearning.AI’s Generative AI for Everyone.

• To improve your prompting skills, explore Vanderbilt University’s Prompt Engineering Specialization.