How to use AI in your marketing strategies

Many marketers spend countless hours wrangling data, reporting on multiple channels, and responding to fast-changing trends. Artificial Intelligence (AI) lightens that load by automating repetitive tasks and sifting through data at scale, freeing you to focus on the strategic, creative work that moves the needle.

Experts believe the global AI market will grow by 33% yearly, reflecting its rapid integration across industries. A significant 69.1% of marketers have already incorporated AI into their strategies, leveraging its capabilities to analyze consumer behavior, automate tasks, and deliver tailored content.

Still, many questions remain on how best to integrate AI, keep data reliable, and ensure these insights align with your organization’s goals.

In this guide, you’ll learn what AI can—and can’t—do for marketers, along with straightforward ways to incorporate AI effectively so you can spend less time on routine tasks and more time innovating..

AI tools for marketing

The right AI tools can enhance efficiency, improve decision-making, and optimize marketing efforts across multiple channels. However, choosing the right tool depends on your business needs and objectives.

Some AI tools specialize in content creation, while others focus on SEO, social media management, ad campaigns, or analytics. Here are the AI marketing essentials at a glance:

• Tools for content creation: Generate text, visuals, and videos more easily.
• SEO tools: Find the right keywords, analyze backlinks, and create the perfect content strategy for your website.
• Tools for ad campaign management: Boost campaign automation and improve your targeting strategies.
• Email marketing tools: Optimize email send times, create powerful subject lines, and enhance audience segmentation.
• Tools for marketing analytics: Turn data into meaningful insights.

Looking at this list, you might be tempted to use as many tools as possible. That’s not always the best strategy, though. Try to avoid using too many disconnected AI tools, as it can lead to data fragmentation, with tools generating insights that aren’t aligned.

Instead, focus on a select few that integrate well into their workflows to maximize efficiency and maintain data accuracy. Let’s take a closer look at each category and see how they can help and what the best tools are for your needs.

AI tools for content creation - covering video, writing, and design

Creating high-quality, engaging content consistently is one of the biggest challenges in digital marketing. AI tools can help streamline content production by helping you write blog posts, video scripts, and social media captions, and create visual assets. While AI can’t replace human creativity, it can be a powerful assistant that speeds up brainstorming and content generation.

• ChatGPT & Claude: AI-powered writing assistants that help with blog posts, product descriptions, social media captions, and ad copy. These tools use NLP (Natural Language Processing) to generate human-like text, making content creation faster and more scalable.
• Grammarly & Hemingway: AI-enhanced proofreading and editing tools that ensure clarity, grammar correctness, and readability.
• Synthesia & Runway ML: AI-driven video content creation tools allow marketers to create professional-looking videos without needing a production team. These tools can generate lifelike AI avatars, edit videos using AI automation, and enhance video quality.
• Canva & Adobe Sensei: AI-assisted design platforms that automate graphic creation, making it easier to produce branded social media visuals, marketing collateral, and presentations. Canva’s AI-powered features help non-designers create compelling visuals, while Adobe Sensei enhances workflows for professional designers.

AI is great for research and content generation, but you must always verify accuracy and refine AI-generated material. AI should complement human creativity, not replace it.

AI tools for social media management

Social media marketing requires consistent posting, audience engagement, and trend analysis. AI-powered tools optimize scheduling, monitor audience sentiment, and help repurpose content efficiently.

• Hootsuite & Buffer: AI-powered scheduling platforms that automate content publishing across multiple social channels. These tools analyze audience behavior to suggest the best times to post, increasing engagement.
• Sprout Social: An AI-driven social listening and sentiment analysis tool that monitors brand mentions and audience sentiment. Marketers can track audiences' reactions to campaigns, identify emerging trends, and adjust messaging accordingly.
• Lately: An AI-powered tool that takes long-form content such as blog posts, interviews, or podcasts and automatically repurposes it into bite-sized social media posts. This is ideal for maximizing content lifespan and engagement.

Use AI in social media for trend analysis and automation, not the complete automation of engagement. Marketers should still handle responses and interactions to maintain an authentic brand presence.

AI tools for SEO

SEO is a field where staying ahead of trends is crucial. AI-powered SEO tools help marketers analyze keyword trends, optimize content, and improve search rankings.

• Surfer SEO & Clearscope: AI-powered SEO tools that analyze top-performing content for specific keywords and provide content optimization suggestions to improve rankings. They help you improve blog post structure for SEO success.
• Frase & MarketMuse: AI-driven research and content strategy tools that analyze competing content and identify content gaps. They generate detailed content briefs to help you create high-ranking articles.
• SEMrush & Ahrefs: AI-enhanced SEO platforms that provide competitor analysis, keyword research, and backlink monitoring. These tools help businesses identify search opportunities and track their website’s search performance over time.

AI can be a powerful SEO ally, but you should avoid over-reliance on AI-generated recommendations. These tools may suggest keyword stuffing or irrelevant optimizations, harming content quality and user experience.

AI tools for ad campaign management

AI is changing how we approach digital advertising by automating bid adjustments, audience targeting, and ad personalization. Using real-time data, AI ad platforms refine ad spending to achieve the highest possible return on investment.

• Google Performance Max: AI-driven advertising campaign automation that optimizes ad placements across Google’s platforms. It helps you adjust targeting and budget allocation dynamically.
• Meta Advantage+: AI-powered Facebook and Instagram ad platform that automates targeting, creative variations, and bidding to improve ad efficiency. This tool is useful for e-commerce and direct-response campaigns.
• Adzooma & Albert.ai: AI-based ad optimization tools that analyze ad performance across multiple platforms and suggest real-time budget and targeting adjustments.

AI-powered ad tools are excellent for automating repetitive tasks, but you should still oversee campaign performance to prevent AI from making inaccurate budget decisions based on incomplete data.

AI tools for email marketing

Email remains one of the highest ROI marketing channels, and AI enhances email performance through optimized subject lines, audience segmentation, and personalized content.

• Seventh Sense: AI-driven email send-time optimization tool that determines the best time to send emails to each recipient, improving open rates and engagement.
• Persado & Phrasee: AI-powered copywriting tools that generate high-converting email subject lines and copy based on consumer psychology and previous campaign performance.
• HubSpot & Mailchimp AI Features: These email marketing platforms use AI for audience segmentation, automated email journeys, and predictive analytics to improve engagement.

AI is valuable for A/B testing and performance optimization, but you should avoid making email campaigns overly robotic. Emails should still feel personal and human-centered.

AI tools for marketing analytics

AI-powered analytics tools turn raw marketing data into actionable insights, allowing marketers to measure performance, predict trends, and make data-driven decisions.

• Supermetrics: An AI-powered data integration platform that pulls marketing data from multiple sources, such as Google Ads, Facebook Ads, HubSpot, etc., into Google Sheets, BigQuery, or Tableau for comprehensive analysis.
• Google Analytics 4 (GA4): Uses machine learning to predict user behavior, offering insights into website traffic, engagement, and conversion probability.
• Tableau & Power BI: AI-enhanced data visualization platforms that transform raw marketing data into interactive dashboards, making it easier to analyze trends and performance.

Data-driven decision-making is only as good as the data itself. Marketers may have inaccurate insights and poor decision-making if AI tools pull in low-quality or incomplete data.

How to use AI for reporting

Why use AI for reporting?

Many marketers spend countless hours pulling data and creating the same reports week after week. As we discussed in our How to Use AI in Reporting webinar, AI can step in to automate these routine tasks—freeing you up to focus on more strategic, high-impact work.

Instead of combing through spreadsheets or building slide decks from scratch, AI can automatically gather data, highlight key trends, and even draft performance narratives. With the right setup, you’ll spend less time on manual reporting and more time on analysis and decision-making.

Preparing your data for AI

Before AI can deliver real value, your data needs to be organized and accessible.

Start by consolidating your sources. Connect platforms like Google Ads, Meta Ads, and your CRM into a single, unified destination—whether that’s a data warehouse like BigQuery or an automated spreadsheet tool. Consistency and real-time updates are key.

Once your data is centralized, enhance it to give the AI more context. For example, image analysis can help AI categorize your creative assets (e.g., distinguishing between ads featuring people, products, or landscapes), while text enrichment can tag user comments by sentiment or topic.

These steps make your data “AI-ready,” unlocking more meaningful insights later on.

Analyzing your data with conversational AI

Traditionally, answering specific questions—like "What was our cost per conversion for Campaign X in September?"—required running manual queries or exporting spreadsheets. Conversational AI changes the game.

Using tools powered by large language models (LLMs), you can simply ask a natural language question like "Show me CTR by campaign last quarter," and get an instant, precise answer.

Even better, conversational AI handles follow-up requests without needing you to reframe your query—helping you explore your data more naturally and efficiently.

With less back-and-forth between marketing and data teams, decisions get made faster—and with more confidence.

Creating AI-driven reports and presentations

Once you’ve pulled insights, AI can also transform how you present them—saving hours of manual work while keeping your reports sharp and relevant.

Here’s how AI can streamline reporting and presentation creation:

• Auto-generate slide decks or documents: Tools like Looker Studio Pro embed AI directly into your workflow. You can select the charts you want, and the platform will automatically build slides with narrative summaries. For recurring reports, updating visuals with new data takes just a click.
• Produce customized reports for each stakeholder: Custom-built solutions connect to your data warehouse and tailor reports based on individual preferences. Whether an executive wants a revenue overview or a marketing manager needs campaign-level details, AI drafts the right report automatically on a set schedule.
• Deliver audio summaries for easy consumption: For stakeholders who prefer listening over reading, you can turn AI-generated insights into short audio clips—like mini-podcasts—offering a more accessible, flexible way to digest information.
• Personalize insights by user role: AI can tailor the depth and focus of reports depending on who’s reading them. Executives get high-level KPIs, while marketing specialists receive detailed performance metrics like CTR, CPC, and pacing data.

By combining automation with smart personalization, AI ensures that every report isn’t just faster to produce—it’s more relevant, actionable, and impactful for every user.

Understanding why you should use AI in a marketing strategy

AI doesn’t replace marketers. Instead, it enhances their efficiency and effectiveness. Here’s how:

• Automation of repetitive tasks: AI saves time by handling data collection, reporting, and campaign optimizations.
• Data-driven decision-making: It enables real-time campaign adjustments based on predictive analytics.
• Hyper-personalization: AI tailors content to individual user behavior, boosting engagement rates.
• Scalability: It allows brands to reach larger audiences without increasing workload.

Despite its benefits, AI is not a one-size-fits-all solution, and marketers must carefully navigate its limitations. While it excels at pattern recognition, predictive analytics, and automation, it lacks human intuition, creativity, and contextual understanding, which are essential in crafting compelling marketing campaigns.

The key to successful AI adoption lies in balance. AI should support marketing efforts, not dictate them.

Applications of AI in marketing

AI has become an essential component of modern marketing, helping brands make smarter decisions, create engaging content, personalize customer experiences, and analyze performance more efficiently than ever before.

To make the most of it, you must integrate it into your current marketing framework rather than use it in isolated tools without cohesion.

Marketers who adopt AI without a structured strategy risk inefficiencies and misaligned efforts. Instead of using 20 different AI tools, focus on a few core AI-powered solutions that complement each other and align with your goals.

Below, we explore four major applications of AI in marketing—strategy development, content creation, customer experience optimization, and analytics—with real-world examples that show how AI is already influencing cross-channel marketing strategies.

AI in strategy development

Strategic decision-making is one of the most powerful applications of AI in marketing. AI helps businesses identify consumer trends, optimize campaigns, and improve targeting by analyzing vast data.

With it, you can improve your market research and trend analysis strategy, audience segmentation and targeting, and optimize ad campaigns.

Still not convinced? Coca-Cola, one of the best-known brands worldwide, uses AI-powered market research to inform new product development and marketing strategies. The company leverages AI-driven sentiment analysis from social media and consumer feedback to identify emerging flavor preferences and cultural trends. This allows them to create data-driven marketing campaigns that resonate with their target audience.

AI in content generation

Creating high-quality, engaging content consistently is one of the biggest challenges in marketing. AI is now crucial in automating content production while maintaining brand consistency and audience engagement.

It can help boost your content creation process, whether it's copy, videos, or design. AI won’t replace a person’s creativity. It will complement it.

For instance, The Washington Post has successfully used AI-generated journalism through its proprietary AI tool, Heliograf. With it, they generated hundreds of automated news reports during the 2016 Olympics and U.S. elections, freeing up human journalists for in-depth reporting.

AI in customer experience optimization

AI is redefining customer experience by making every interaction more personalized, responsive, and efficient. From AI-powered chatbots to predictive product recommendations, it enhances engagement across every channel.

For example, AI chatbots and virtual assistants deliver instant, 24/7 support—resolving common questions without human delay. Behind the scenes, AI also analyzes past purchases, searches, and interactions to offer personalized recommendations and predict potential issues before they arise.

That said, personalization must feel authentic, not intrusive. AI-driven experiences are most effective when balanced with human insights, ensuring every interaction feels thoughtful and genuine—not automated for automation’s sake.

Netflix offers a prime example. Its recommendation engine analyzes over a billion interactions each day, serving up highly tailored content that keeps viewers engaged—and loyal.

AI in marketing analytics & performance optimization

One of AI’s most powerful applications in marketing is its ability to analyze performance data in real time and provide actionable insights. AI-driven analytics tools help marketers measure, track, and optimize campaigns more effectively.

Real-time reporting and data analysis, predictive analytics to boost campaign performance, and automated A/B testing are some of the best examples of how AI supports marketing analytics.

Remember, though, that AI-driven analytics are only as good as the data they rely on. Marketers must ensure their data is clean, unbiased, and properly structured to get the most accurate insights.

Implementing AI in your next marketing strategy

Integrating AI into your marketing strategy can significantly enhance efficiency, personalization, and decision-making, but only if implemented correctly. Many businesses struggle with where to start, aligning AI with their goals, and avoiding common pitfalls like poor data quality or over-reliance on automation.

A successful AI adoption strategy should be methodical and iterative, ensuring AI enhances processes rather than replacing critical human oversight. Here are some steps to help you get started.

• Identify marketing challenges: Determine which tasks or processes could benefit from AI-driven improvements.
• Choose AI tools wisely: Select solutions that align with your business goals rather than adopting AI simply for the sake of it. Focus on tools that integrate well with your existing marketing stack.
• Ensure data quality: AI relies on high-quality, unbiased data. If data is incomplete or inaccurate, AI-driven insights will be unreliable.
• Test and optimize: Start with small-scale AI experiments, measure performance, and refine your approach before committing to full-scale implementation.
• Train your team: AI adoption requires education. Ensure your marketing team understands AI capabilities, limitations, and ethical considerations to maximize effectiveness.

Implementing AI is not without challenges, though. Here are some solutions to common issues:

• Data privacy concerns: Use AI tools with strong security measures. Ensure compliance with GDPR, CCPA, and internal data policies to protect customer information.
• AI bias and hallucinations: Manually review AI-generated insights before implementation. AI models can sometimes generate misleading or biased content, so human oversight is essential.
• Learning curve for teams: Provide AI training workshops and encourage hands-on experimentation to build confidence in AI-driven decision-making.

One prominent mistake marketers make is setting their sights too high too soon. AI adoption should be a learning process: test, refine, and scale gradually, rather than implementing AI across all processes at once.

Get started with AI

AI is here to stay and transforms how marketers strategize, create, and engage with audiences. Staying ahead of emerging AI trends is crucial for maintaining a competitive edge.

Various key trends are already making a massive difference in marketing and will continue influencing how we approach this domain.

• Generative AI: Tools like ChatGPT and Synthesia automate content, video, and ad creation.
• Predictive analytics: AI forecasts trends and customer behavior, optimizing marketing strategies in real time.
• AI-driven personalization: AI dynamically adjusts website content, emails, and recommendations based on live user interactions.
• Privacy-First AI: AI is helping brands navigate cookie-less tracking and secure first-party data while ensuring compliance.

Most marketers already use AI in some capacity, whether in analytics, automation, or personalization. The key to success is maximizing AI’s capabilities while keeping human creativity and strategy at the core.