As the digital market space rapidly evolves, customers are seeking authenticity and human connection from brands like never before. To meet this rising demand, your marketing team needs to be agile, think out of the box and keep up with deadlines—all while operating within limited budgets and constrained team bandwidths.

Luckily, innovative technologies like artificial intelligence (AI) offer long-term solutions to meet these challenges. They are revolutionizing marketing, with an increasing number of marketers reporting that AI capabilities have helped them boost creativity and workflow efficiency. More and more teams are using AI marketing to channel their energy toward developing compelling content while efficiently managing arduous tasks like data analysis, reporting and message management.

In this article, we explore AI use cases in marketing that are top priorities for teams as they tighten their seatbelts for 2024. Keep reading for actionable insights that will help you meet your revenue goals and marketing objectives, head-on.

Table of contents:

The marketing disciplines where AI had a positive impact

According to The 2023 Sprout Social Index™, 81% of the 900 marketers surveyed say AI has already had a positive impact on their work. Seventy-eight percent feel AI has benefited them in creative areas like content ideation, and another 73% report a positive impact on productivity.

Data visualization highlighting stats from The Sprout Social Index 2023 saying 81% of marketers have already had a positive impact on their work.

AI is also helping social teams understand and respond to audiences better. It’s providing them with critical brand insights from social listening to inspire engaging content, personalize customer care and dig deeper into performance metrics.

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Further, AI-driven marketing automation is assisting marketers in increasing speed and efficiency. It’s enabling them to offload time-consuming tasks such as managing digital ads, email campaigns and social post scheduling so they have more time for strategy-building.

Not surprisingly, according to a Q2 2023 Sprout Pulse Survey of 255 social marketers, 71% are already integrating AI and automation tools into their workflow, and 82% of them report positive results.

Data visualization that reads 71% of marketers have begun to integrate AI and ML tools into their workflow.

The top 7 AI + social marketing use cases for 2024

Given these encouraging results, more companies plan to leverage AI in 2024 to strengthen their marketing teams and prime their overall business strategy. Here are the most prominent AI use cases in marketing for social media managers as they prepare for the coming year.

An image showcasing the areas marketers have already seen AI’s positive impact on and the prominent AI use cases marketers anticipate using in 2024. The top 3 are analyzing social media data, content creation and social advertising.

1. Analyzing social media data

Social media data is a treasure trove of brand and customer insights that AI tools effortlessly dig into to surface critical information. The State of Social Media Report found 95% of leaders look at social data to inform business decisions such as lead generation, product development and competitor analysis. Thus, social media data analysis is empowering not only marketing teams but also cross-functional ones.

Competitor monitoring is another AI use case in marketing, important for 92% of business leaders in 2024 per the report, to improve brand positioning.

AI tools extract competitor insights by using powerful semantic search and other AI algorithms from social listening data. For example, Sprout analyzes social data using named entity recognition (NER) to identify and analyze competing brands and their content to provide you with actionable insights to improve your brand performance.

The capability digs into competitor content engagements, post frequency, hashtag usage and other key performance areas by using keywords and @mentions you determine. Thus, cutting through the noise of thousands of social conversations in seconds to give you data that matters to your brand.

A screeshot of the Sprout Social competitor report showing an audience growth chart and a summary of the key metrics of user profiles compared to the competitor average. These metrics include Fans average, Public engagement average and Public engagement per post.

Another key area is influencer marketing. AI models monitor posts, interactions and audience demographics of potential influencers so marketers can map their suitability for brand partnerships. Sprout’s recent acquisition of Tagger further cements how social data analysis and AI capabilities are converging to manage intelligence, reporting and workflows for influencer marketing.

2. Content creation

The 2023 Index found that content creation still remains one of the most time-consuming tasks for marketers. It’s not just the creative ideation that takes up time and mind space but also the stress of ensuring the content is timely, relevant, engaging and differentiated enough to stop audiences from scrolling past.

An image that mentions a key finding from The Sprout Social Index 2023 that content creation remains the most time-consuming tasks for marketers.

Thankfully, social media managers and teams can rely on dedicated AI-enabled social management tools for content creation and ideation without the pitfalls of generic AI tools.

For example, Sprout’s Suggestions by AI Assist feature helps you create engaging, brand-tailored posts in seconds by giving you three outgoing copy options. Sprout understands nuances in social chatter by using natural language processing (NLP) and provides relevant content recommendations based on the data, leading to compelling content that translates into better leads and improved conversions.

This way, by tying sentiment analysis to marketing teams’ initiatives, they can increase the impact of their social strategy and get back time to concentrate on developing winning campaigns.

3. Social media advertising and campaign targeting

Social media advertising and campaign reporting are key AI use cases in marketing. Marketers are using AI to optimize social media advertising and make ads more attractive to audiences by analyzing engagement behavior and audience preferences. For example, this Coca-Cola campaign combines a compelling storytelling technique with generative AI to create an intriguing ad video.

Machine learning (ML) algorithms now automatically conduct A/B tests on different ad variations to continuously optimize ad campaigns by learning which elements perform best for different customer segments. This leads to more targeted, personalized ads. AI-powered insights, coupled with predictive analytics, automatically suggest relevant products and services based on past user interactions to increase campaign targeting and performance.

All these advantages enable marketers to maximize paid advertising and improve targeting results in a fraction of the time it would take to analyze and customize them manually.

Similarly, AI tools can create dynamic ads that automatically update product information and prices based on user behavior and choice. This maximizes your return on investment (ROI) while saving your marketing team the cumbersome task of monitoring and adjusting ad copy manually.

Check out Sprout’s social ad reporting capabilities to boost ROI from the paid content you’re scheduling.

4. Social media scheduling and posting

Social media teams juggle multiple priorities, from responding to timely customer issues and queries to making sure they don’t miss scheduling content and post deadlines. That’s why social marketers seek to manage posts and schedules much in advance so they can prioritize campaigns and manage team workflows better.

AI marketing tools automate these functions seamlessly, and with precision, saving teams time and effort. For example, Sprout’s AI capabilities automate social media scheduling and posting by determining the best times to post for maximum audience engagement and impressions. Machine learning algorithms analyze engagement metrics over periods of time to provide several scheduling options in the form of Optimal Send Times and hashtag recommendations to ensure optimal post engagement.

This enables marketers to plan, organize and schedule social posts across networks including Facebook, Instagram and LinkedIn with data-driven accuracy.

A screenshot of the Sprout Social Optimal Send Times feature that rates the best times to post so your content has the maximum impact.

5. Building chatbots

Chatbots are a compelling AI use case in marketing. And 54% of marketers plan to use them at scale in 2024 for social customer care, along with other resources like FAQs and customer forums, per the 2023 Index.

Chatbots enable brands to deliver real-time, personalized interactions with customers for round-the-clock responses to inquiries. This goes a long way to enhance customer satisfaction and build strong brand relationships, given that 16% of customers expect brands to respond immediately, and 23% within two hours.

Chatbots enabled by ML and neural networks become smarter as they process more information and gather valuable data on user behavior. These virtual agents, however, need to be trained, adapted to your tech stack and monitored. Makeup brand Sephora uses AI chatbot Kik to connect with its customers and for live influencer interaction to drive engagement.

Rules-based chatbots, on the other hand, are simpler. They can easily be set up in a matter of minutes and enable brands to offer 24/7 availability to their customers.

Whether you use an AI-enabled chatbot or a rules-based one like Sprout’s, you can boost efficiency multifold by answering product queries, providing recommendations and guiding users through the sales funnel even when your marketing team is unavailable. What can be better for customer support than that?

6. Social media measurement

Social performance analytics have become a critical part of a brand’s overall strategy. A whopping 60% of marketers plan to measure and quantify the value of social engagements in terms of revenue impact to meet their 2024 business goals.

And given the rise in leadership teams’ involvement in a brand’s social engine, 32% of marketers say they now share social metrics with their executive leadership on a weekly basis.

Data visualization highlighting stats from Social Social Index 2023 reporting 32% of marketers share social metrics with their executive leadership on a weekly basis.

ML models like Sprout automatically and accurately measure quantitative and qualitative social metrics within minutes, sparing you hours of manual engagement and performance analysis. This bodes well for marketers who want to enhance their social media ROI while navigating social media’s ever-changing landscape.

7. Sentiment analysis

Marketers are turning to sentiment analysis to assess the tone and sentiment expressed in comments, posts and conversations around their brand to determine whether they are positive, negative or neutral. This is a critical AI capability considering 44% of marketers, per The State of Social Media Report, use sentiment mining to understand customer feedback and improve how they respond to issues.

Analyzing sentiment in social chatter also helps brands spot early indications of negative sentiment and take proactive measures before a situation escalates.

For example, in Sprout, you can detect unusual spikes in brand mentions and monitor whether they are negative or positive. This enables you to actively monitor your reputation to ensure brand health. Similarly, sentiment analysis algorithms also tag incoming messages as positive and negative so your social customer care teams can prioritize them based on how critical they are.

Screenshot of Sprout's sentiment analysis feature that tracks the sentiment in your social listening data to track customer sentiment and emerging trends.

How to adopt AI in a mindful way

Creating connections and building community requires a lot of time and effort, both of which are limited for already strapped social marketing teams. AI can address this challenge by automating functions, simplifying workflows and increasing team transparency. However, there is apprehension from both social marketers as well as customers. While social teams worry about job displacement, 42% of consumers, per the 2023 Social Index, are apprehensive about brands using AI in social media interactions fearing reduced human interaction.

Leadership teams can help manage these concerns by paving the way for implementing org-wide AI use cases in marketing in a thoughtful manner. This includes working closely with the IT and legal team to choose the right AI tools for use by different departments. Plus, initiating and developing an effective AI use policy for employees so there is a concrete framework they can work around to benefit from AI software.

This is important because intentionally incorporating AI tools into your tech stack can offload manual and cumbersome tasks such as posting, scheduling and performance analytics, so marketing teams can focus on work that truly depends on their expertise. This includes AI analytics, audience research, creating compelling content, driving audience engagement and more importantly, personalized customer care.

Stay tuned in as AI use cases in marketing evolve

Navigating social media’s meandering terrain is no easy feat. Marketing leaders today need to keep a close ear to the ground to capitalize on changing market trends to outsmart competitors and win customer loyalty. These social insights will empower your marketing teams and provide them with the direction they need to build on every opportunity to be agile and elevate your brand.

Stay tuned on the latest social trends to forge real business impact into your marketing strategy. Download the Sprout Social Index™ today.