How AI Is Reshaping Content Marketing Beyond Automation

Generative AI, or AI that creates text and images through simple prompts, is arguably the most popular use case in content marketing. But is it the only one?

Data suggests otherwise.

Beyond creating content, marketers are betting on AI to segment customers, do predictive analysis, track campaign data, optimize ad spend, and so much as deliver live autonomous agentic support!

At the heart of all these content marketing activities — and the newer ones arriving every year — is AI's different avatar, churning out petabytes of data in minutes, and spitting out outputs that would otherwise take human teams dozens of hours to complete.

Learn how AI is transforming every stage of content marketing, how different AI applications work, where they fit into the workflow, and how your team can unlock its full potential.

What is AI in content marketing, and how does it work?

AI in content marketing refers to the use of AI technologies across various stages of your marketing strategy.

Since marketing is inherently multidisciplinary, there is no single, universally accepted definition of AI in marketing.

You can use AI to achieve unique goals within the marketing umbrella: AI for SEO vs. AI for personalization vs. AI for image generation.

Irrespective of your use of AI in content marketing, at the core, there are two foundational technologies: machine learning (ML) and deep learning (DL).

These two AI technologies power core applications such as:

• Natural language processing (NLP), which helps machines understand, interpret, and generate human language
• Computer vision, which processes and analyzes visual content, is valuable for image tagging, video analysis, and more
• Voice and speech recognition which uses deep learning-based acoustic models to transcribe, understand, and respond to spoken language

SaaS businesses bundle these applications into end-user solutions in content marketing, social media management, customer experience, and service platforms.

Some of the most popular AI solutions in content marketing are:

• Generative AI (such as large language models) that can produce human-like content, assist with ideation, and personalize communication
• Predictive analytics, built on top of ML/DL, analyze existing customer data and predict future outcomes such as who’ll churn, who’ll convert and recommends personalized content
• Sentiment analysis and social listening use NLP to analyze text, such as from Tweets, and classify them into negative, positive, neutral sentiments, and extract themes and topics automatically
• Chatbots and conversational AI that uses NLP to understand queries, interact with humans in their language, and provide helpful resources

You can choose AI solutions for your unique requirements based on your content marketing discipline.

Nevertheless, the ultimate impact and purpose of using AI in content marketing boil down to:

✅ Faster research and brainstorming process

✅ Accelerated content creation

✅ Improved personalization

✅ Better segmentation and targeting

✅ Deeper and more insightful data analytics

✅ Cost efficiency and resource optimization

Unlike marketing automation which speeds up manual tasks, AI adds context to how you plan, create, deliver, and optimize content.

Here is a glimpse into how AI works at various stages of the broader content marketing process, the outcomes it generates, and tools that you can use:

👉 Read more: How AI is changing marketing: Must know for leaders

4 Uses of AI for content marketers in 2025

AI in content marketing is about working smarter, not just faster.

Here are four uses illustrating AI’s impact, with use case and tool examples:

1. AI-driven topic discovery

According to Content Marketing Institute, 47% of enterprise marketers report struggling to create content that stands out in the crowd.

Every brand sifts through SEO tools and keyword discovery platforms to find content topics and build a pipeline. At most, some brands may tap into their user-generated content or on Reddit.

While SEO is important, if you solely rely on it for content topics, you are missing out on the ginormous amounts of customer signals that are there outside search engines.

AI helps capture customer data from multiple sources all at once, which you can use to create more resonant yet unique content.

One such technology is social listening which uses AI to understand what customers say about your brand/product online, what they want, and how you can deliver better value through content.

A 2024 Sprinklr research suggests that one in two marketers plan to invest in social listening tools in the next six months.

AI taps into billions of real-time conversations on unstructured sources — social media platforms, forums, blogs, public review sites, etc. — and fishes out trends, themes, affinities, sentiments, and even specific talking points that would matter to you.

To get started, you need to zero in on Listening Topics for query-based listening on platforms like Sprinklr Insights.

Topics are usually keywords or phrases related to your brand that you want to track.

If your platforms support it, AI can help during this stage of finding the most accurate topics to listen to.

Instead of manually listing every keyword, Sprinklr’s AI+ generates and refines Boolean queries for broad coverage of synonyms, slang, and emerging terms around your topic.

Here’s how AI suggests keywords related to a topic of your choice 👇

Once you’ve set the Listening Topic, you can use Smart Theme Explorer where Sprinklr’s NLP engine:

1. Filters out noise and irrelevant chatter
2. Removes stop‑words and stem phrases
3. Clusters messages into themes up to five levels deep, correlating subjects and attributes (e.g., “pandemic,” “healthcare,” “safety recall”)

From the theme list, you can select specific topics and drill into associated conversations, sentiment trends, and geographic hotspots.

Finally, you can use the information to inform your calendar with various forms of content such as infographics, blogs, help docs, FAQs, videos, refining existing landing pages, etc.

Microsoft used social listening to capture conversations about hybrid work on the heels of the COVID-19 pandemic.

The tech giant wanted to build and shape the momentum around the new style of working through products and content that would enable its users to work better remotely.

Read this case study to find out how Microsoft discovered that "hybrid work" became synonymous with "flexible work" and was the dominant term for the ideal flexible work state users wanted. This insight guided their thought leadership content.

2. Creating content faster and better with generative AI

B2B content marketers report spending an average of 33hours per week (about 82% of their work hours) creating content — social posts, blogs, newsletters, videos, and you name it.

AI is dramatically expediting content creation, by at least landing the first drafts, if not publish-ready content!

According to Sprinklr research conducted in 2024, 75% of social marketers plan to implement generative AI tools to offer better customer experiences on social media.

Generative AI helps create personalized, contextual, and accurate first drafts in minutes, saving hours of human effort.

Your human team can instead use the time perfecting the AI output into a final draft with unique angles, owned data, more context, examples, and opinions.

SaaS marketing tools you use such as social media management suits, CRMs, CDPs, CMS, etc., may already bundle these AI capabilities. Do check out for recent updates.

For example, you can use Sprinklr AI+ to create content for Facebook, Instagram, X, TikTok, LinkedIn, email, SMS, blog, website, and press releases when publishing through Sprinklr’s content marketing platform.

It’s like having ChatGPT at every stage of the content creation process.

Not just any content. AI will help you create context and platform-relevant content during different stages of the workflow. All you must do is give simple inputs as you’d on any other gen-AI tools.

Here is an example of Sprinklr AI+ creating a topic description on “breast cancer awareness” in an “empathetic” tone of voice targeted to “men and women aged 30-40 years” 👇

For more general content use cases, platforms such as ChatGPT, Claude, Perplexity, and Gemini are popular. These platform-agnostic tools can create any form of textual, code-, and image-based content.

Here’s an example of an AI output for blog ideas on a topic targeted at enterprises 👇

Some AI platforms like Grammarly can help with a flurry of quality assurance workflows for already created pieces.

Here is an example of a Grammarly dashboard and its sidebar containing prompts to fix grammar errors, summarize, change the tone of voice, improve the information, etc.👇

At the time of writing this post, there are more than 12,000 AI tools in the market, according to data from the AI tools directory Seekme.ai.

So, think of any workflow in content marketing, and there's a high chance you will find an AI for it.

3. Personalization at scale

Today’s buyers expect content that feels made just for them. AI makes that possible, even for audiences of millions.

AI in your customer intelligence or content marketing platforms segments users based on channel, behavior, location, lifecycle stage, interests, and past interactions.

For example, a feature like SmartAudienceEngine on Sprinklr builds target customer profiles from behavioral and transactional customer data ingested from your websites, mobile apps, email platforms, and e‑commerce engines, CRMs, etc.

You can use this granular data to categorize active, at-risk, dormant, and prospect audience segments.

With this information, you can personalize the message based on behavior, demographics, and churn risk so that it reaches the right customers at the right time.

This is just one example of AI that you can use to personalize content.

Have you noticed how your Netflix homepage doesn’t look the same? It’s not by fluke.

Content aggregation platforms like Netflix and Spotify use AI to deliver personalized audio-visual content on a massive scale.

Source

The streaming giant uses AI to recommend titles based on users’ unique interests, which explains why each user’s Netflix homepage and even the thumbnails look different!

AI (ML) picks the single image (thumbnail) for each show or movie that users are most likely to click on, based on their past viewing habits.

This AI-driven thumbnail personalization reportedly boosts click‑through rates for Netflix by about 30%, helping them keep viewers engaged longer and saving roughly $1billion a year by reducing subscription churn.

4. AI-led content distribution across channels

Publishing and disseminating content are the most overlooked and complex steps of content marketing.

Content distribution is often more than scheduling posts for different platforms. It takes a team of pros to curate content for customer segments who tend to flock to specific channels.

AI helps multi-channel execution much easier.

AI in your content marketing platform automates scheduling, formatting, and publishing content across channels such as email, social, web, and paid.

If you use content marketing software like Sprinklr Marketing, you can use a host of AI-led capabilities for various stages of content distribution, all aimed at improving compliance, time to publish, and accuracy of the process.

Compliance issues before distribution often plague large enterprises, and they can lead to unnecessary delays, content pullouts, and awkward public errors.

Smart Approvals, for example, use AI to assist your campaign managers approve content before distribution which reduces last-moment scrambles and non-compliance. 

It can flag compliance issues and automate approval workflows during the creation stage which helps with faster, smoother, and error-free content distribution.

In this example, the Smart Approval is flagging content for offensive language, bad image quality, and improper tone 👇

Social media algorithms are changing quicker than we can keep track of them. Knowing the best time and format for distributing content becomes a never-ending guessing game.

Smart Scheduling, another AI-led content marketing capability on Sprinklr, suggests the best times of the day to schedule posts for the maximum chance of engagement per post.

AI automatically considers your historical and existing campaign data to suggest a unique time for each social account varying by the time of day you are scheduling.

Here’s an example of AI suggesting the best times to post on Facebook 👇

Facebook Automated App Ads is another example that uses AI (machine learning) to automate your campaigns across creatives, audience, optimization, and deliver high-value conversions with less effort.

AI does the heavy lifting of targeting the right keywords and auto-testing creative combinations for the highest-performing ads.

Global marketing teams need to coordinate across time zones, languages, and channels.

AI removes the friction of publishing content across various channels, as you saw how Sprinklr’s AI works while retaining quality control and governance.

The result is every piece of content lands where and when it should, without endless spreadsheets or back-and-forth emails.

👉 Also read: AI for content marketing: 3 biggest advantages and 11 key tools

Real-world examples of AI in content marketing

Leading brands are integrating AI in content marketing across industries to solve business problems and enhance marketing performance:

1. Corning’s Smart Bidding for paid ads

Corning’s Optical Communications team used AI‑driven Smart Bidding and Automated Pacing on Sprinklr to optimize LinkedIn ad campaigns.

Smart bidding is an AI-driven algorithm trained on a company’s data, in this case, Corning’s. It predicts the best bid value for the user’s ad sets.

This vertically tailored AI helps optimize LinkedIn campaigns by reducing costs and achieving more consistent pacing to improve results.

In a two‑week pilot, these capabilities delivered a 124% surge in website visits and a 55% reduction in cost‑per‑acquisition for Corning, freeing the team to focus on strategic work rather than manual bid management.

🔥Increase paid ads ROAS with vertically tailored AI

Replace static or manual bids. Smart Bidding uses AI to continuously learn from your campaign performance data to forecast the bid needed to achieve your specified optimization goal.

BOOK SMART BIDDING DEMO

2. Washington Post’s AI-generated news briefs

Back in the 2016 U.S. election cycle, The Washington Post deployed Heliograf, its proprietary natural language generation (NLG) system, to automatically generate brief data-driven news updates on nearly 500 electoral races in real-time.

Source

In its first year, Heliograf published around 850 articles and generated more than 500,000 clicks on election coverage that the newsroom otherwise would not have staffed.

The AI-led content also freed the journalists to focus on in-depth reporting while ensuring continuous live coverage across local and national events.

Today’s AI is far more accessible for similar and more advanced use cases, such as creating long-form blog outlines, press releases, video scripts, whitepapers, etc.

According to Ahrefs, more than 70% of new web pages live today have AI content, and they rank in SERPs just as human content if it is high quality!

3. Trivago’s AI-powered content localization

As part of a global rebranding in 2023, Trivago launched a new visual identity and logo using a multi-national campaign.

The innovation was the use of AI to tailor messaging for hyperlocal audiences.

The company used AI to localize the same Trivago ad in 10+ languages, featuring the newly launched “Trivago Guy” but with “uniquely tailored voice-overs” relevant to the local culture and market.

Trivago continues to invest in AI-powered content localization in 2025.

Their latest ad, starring German football executive Jürgen Klopp, was originally shot in English but was translated into several other languages for 20 markets, using AI.

4. Starbucks’ AI coffee personalization engine

In 2022, Starbucks launched an AI‑driven personalization engine called Deep Brew integrated into its mobile app and rewards program.

Source

Machine learning analyzes customer preferences, weather, and location data to suggest tailored product recommendations, drive‑thru suggestions, and dynamic menus across its global store network.

If reports are to be believed, the coffee giant reported a 30% increase in ROI and a 15% growth in customer engagement following Deep Brew’s rollout.

Here’s a flywheel depicting the business impact of AI.

Source

5. Booking.com banks on fast-moving social media trends with AI

Booking.com, one of the world’s leading digital travel companies, analyzed over 9,500 TikTok comments in just 60 days!

Their use of AI is centered around the brand requirement to respond to fast-changing trends, understand real-time sentiment, identify engagement drivers, and respond swiftly without relying on manual comment moderation or delayed reporting cycles, especially on dynamic platforms like TikTok.

Sprinklr’s AI tagged thousands of comments by sentiment and intent, automatically routing insights to marketing and care teams on the same unified CXM platform.

This data helped surface brand advocates, inform creative decisions, and optimize content performance — all without slowing down campaign delivery.

Booking.com saved over 17 hours of manual moderation time and unearthed rich audience insights that will directly shape future content strategies.

AI also helped achieve much faster engagement with fans and fewer missed opportunities on trending content.

🔥Build your custom AI to power entire marketing campaign lifecycles

Sprinklr AI+ assimilates the goldmine of data you already own from your existing campaigns. On top of that, it taps into billions of fresh conversations around your topics in 30+ public sources and uses the best generative AI models to offer ideation, copywriting, reviewing, translation, and other content services — in one platform. This is unparalleled AI in any content marketing platform!

BOOK SPRINKLR AI+ DEMO

Watch: How AI Transforms Content Recommendations to Elevate Online Experiences | Sprinklr

How AI is evolving content strategy (beyond automation)

By now you will probably agree that AI is more than a tool for speeding up content production.

It plays a central role in how you listen to your audiences, plan the content mix, distribute assets at scale, and adapt using real-time data analytics.

1. Real-time insights that power faster, smarter decisions

AI interprets intent, uncovers hidden patterns, and provides market clarity.

Platforms like Sprinklr Marketing integrate AI in almost every workflow you can imagine, analyzing data from multiple sources, and delivering instant feedback loops and actionable next steps.

Rather than relying on quarterly reports or lagging indicators, you can pivot campaigns based on live audience sentiment, competitor activity, or trend signals within hours, not weeks.

2. Continuous learning through AI-powered feedback loops

With AI, content strategy becomes a living system.

Every campaign, no matter how small, feeds performance data back into the system.

AI reviews the results, identifies patterns, and recommends changes, closing the loop between creation and impact.

This real-time loop allows teams to iterate faster, fix what’s underperforming, and double down on what works, without waiting for lengthy reporting cycles.

Image Address

Source

3. Predictive content that meets audience needs before they arise

AI now helps you go beyond reactive content creation.

By studying behavior patterns, search trends, and engagement signals, AI can predict what information different customer segments will need. Even before they ask for it.

In this way, you can create value earlier in the customer journey, build trust, and reduce customer churn by shifting from a reactive to predictive content strategy.

4. End-to-end alignment with compliance and governance needs

For complex organizations, content workflows must be both agile and accountable.

AI platforms bring structure to large-scale operations — ensuring everything from ideation to publication meets your brand’s standards, legal requirements, and regional regulations.

AI can route content through custom approval chains, monitor compliance risks, and flag inconsistencies across markets, which saves time and reduces errors.

For organizations looking to stay ahead, adopting AI is about agility, precision, and making content more intelligent at every step.

👉 You might like: 4 Best AI in marketing examples [+ use cases]

AI is your content marketing co-pilot! Embrace it with Sprinklr Marketing

AI is fundamentally transforming content marketing from a creative guessing game into a data-driven science.

For enterprises, the benefits are clear: smarter strategies, faster execution, hyper-personalized engagement, and measurable business impact.

From real-time insights and predictive analytics to multi-format orchestration and compliance, AI is empowering marketing leaders to deliver content experiences that drive growth and loyalty.

Now is the time to move beyond automation and embrace AI as a strategic co-pilot.

Explore Sprinklr Marketing and see how you can use future-proof content strategy, outpace competitors, and inspire audiences at scale.

Ready to see how Sprinklr’s AI can reshape your content marketing?