The Best AI Marketing Trends & Strategies in 2025

In 2025, artificial intelligence is no longer a competitive advantage, it’s a baseline requirement. Gen AI is transforming every layer of the marketing funnel, from hyper-personalized content creation to predictive customer segmentation and AI-powered campaign automation.

According to a recent PwC Pulse Survey, 78% of CMOs are actively integrating Gen AI into their marketing ecosystems. With the global AI marketing industry projected to surpass $107 billion by 2028 at a CAGR of 36.6% , these AI trends are accelerating faster than many businesses can adapt.

If you're planning your digital marketing strategy, now is the time to evaluate your enterprise AI stack and automation infrastructure. In this article, we’ll unpack the top AI marketing trends, GenAI use cases, and scalable strategies to stay ahead in a fast-evolving digital economy.

What is AI in marketing?

AI in marketing refers to the use of artificial intelligence technologies such as machine learning (ML), natural language processing (NLP), computer vision, and generative AI to automate, optimize, and scale marketing activities across the customer journey.

These technologies analyze vast volumes of structured and unstructured data to surface actionable insights, personalize engagement, and accelerate decision-making.

Here’s how AI is being used across the marketing funnel:

• Awareness stage: AI helps automate content creation, deliver targeted advertising, and enhance search engine visibility through intelligent SEO optimization.
• Consideration phase: AI enables predictive lead scoring by analyzing behavioral signals, while also supporting hyper-personalization across channels to increase engagement.
• Decision stage: AI is used to deliver contextually relevant product recommendations, optimize pricing strategies based on demand and customer behavior analysis, and improve conversion rates through real-time adjustments.
• Retention phase: AI plays a critical role in identifying churn risks, tailoring re-engagement campaigns, and powering responsive customer support through chatbots and intelligent service systems.

The benefits of AI for marketers include:

• Real-time Insights: AI tools analyze data and generate an immediate understanding of customer sentiment and campaign effectiveness.
• Improved ROI: AI helps in optimizing ad spend, targeting the right audiences and automating tasks. Companies investing in AI report a revenue boost of 3%-15% and a sales ROI increase of 10%-20%.

Consider the “Nutella Unica” campaign in Italy. Ferrero used AI to generate millions of colorful, one-of-a-kind label designs for Nutella jars. This turned a mass-produced item into a personalized, collectible experience. Within a month, all 7 million jars were sold out. The campaign also drove a wave of social media sharing and user-generated content, turning buyers into brand advocates.

• Enhanced Decision-Making: 83% of marketers acknowledge that AI allows them to concentrate on the more strategic or creative aspects of their roles.
• Improved customer experience: A recent survey found that 41% of companies see improved customer experience as the main benefit of adopting responsible AI practices.

Must Watch: Generative AI & the C-Suite: How Marketing Can Educate, Inspire and Activate | On-Demand Webinar

How is AI transforming marketing strategies?

AI isn’t just supporting marketers; it’s actively transforming how core marketing functions operate across the funnel. From content creation to advertising and automation, AI is enabling greater speed, personalization, and strategic impact. Below are key functions where AI is driving measurable enterprise value.

1. Faster content creation

AI tools can generate highly engaging and personalized blog posts, social media updates, email copy and even videos or images in minutes, tailoring tone and style to brand guidelines. Around 85% of advertisers surveyed in the US reported that AI helped them produce targeted and personalized content faster, freeing them for more strategic, high-level thinking.

Unilever, a global FMCG brand, deployed GenAI to create pixel-perfect digital twins of its brands; these images are subsequently spread across numerous channels, including TV, digital commerce and beyond at unmatched speeds.

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This increased efficiency allowed their teams to concentrate on the creative human aspects while minimizing the expenses and resources tied to extended technical production workflows.

Enterprise marketing teams often face rising content demands without the systems to manage them efficiently. Sprinklr’s Content Marketing Platform solves this by bringing campaign planning, production, publishing, and performance into one unified space. With a shared editorial calendar, AI-powered insights, and automated workflows, teams cut production costs by up to 50% and accelerate campaign delivery—without compromising quality.

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Named a Leader in the 2025 Gartner® Magic Quadrant™ for Content Marketing Platforms, Sprinklr gives global teams full visibility, creative control, and the ability to scale what works.

2. Targeted advertising

AI helps companies use their advertising budgets more efficiently. It analyzes consumer behavior and adjusts campaigns in real time. This improves targeting, messaging, and bidding to maximize return on ad spend (ROAS) and reduce cost per acquisition (CPA).

A global entertainment company used Sprinklr Marketing to improve performance on Snapchat. They A/B tested two ad setups to compare conversion windows: one focused on recent activity (7-day click, same-day view), and the other used a longer window (28-day click, 1-day view). Using Sprinklr’s tools to run and monitor the test, the company saw a 29% drop in cost per signup and a 19% drop in cost per purchase within four weeks.

This showed how AI-backed testing and real-time insights can help large brands lower costs and improve results.

3. Higher customer engagement

AI improves customer engagement by analyzing real-time behavior, customer sentiment, and context across all customer touchpoints. Using machine learning, it can classify interactions by intent, emotional tone, and stage in the customer journey. This allows companies to deliver more timely and relevant responses that improve retention and increase conversions.

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Must Read: AI Customer Experience: Top 7 Ways to Elevate CX

4. Tasks automation

Routine automation of tasks like email scheduling and social media posting has become the norm. AI-powered chatbots handle customer inquiries 24/7, providing instant support and gathering valuable data. Sprinklr leverages advanced AI capabilities to automate and optimize enterprise marketing workflows at scale. From AI-powered customer segmentation and lead scoring to dynamic email personalization and social media scheduling, Sprinklr enables marketing teams to reduce manual effort and boost campaign performance.

For example, Nike leverages AI to dynamically segment customers based on buying behavior, enabling highly targeted campaigns that increase engagement and drive revenue growth.

By adopting Sprinklr, enterprises can streamline campaign review cycles, ensure brand consistency across multiple channels, and scale their marketing operations seamlessly delivering measurable business impact.

Must Read: How to use AI in marketing automation

The biggest AI trends shaping marketing in 2025

Here are the five most impactful AI marketing trends for 2025 that forward-thinking enterprises must leverage for competitive advantage:

1. Boost conversion rates with hyper-personalized customer journeys

As customers move between channels and devices, they expect more than just recognition — they expect relevance. Enterprises are responding by using AI to personalize experiences at the individual level, not just by name, but by behavior, context, and intent.

AI systems unify customer data from sources like CRM tools, websites, purchase history, and social media. This creates a living profile of each user and allows marketing teams to segment audiences in real time. With predictive modeling, these profiles also help anticipate future behavior, enabling proactive engagement rather than reactive messaging.

Here’s how enterprises hyper-personalize the customer experience

• Map and Optimize Customer Journeys AI tracks how customers move across touchpoints, identifying drop-off points and patterns. With journey analytics, teams can pinpoint where friction occurs and adapt messaging or content to guide users more efficiently toward conversion.
• Personalize Interactions in Real Time AI-powered chatbots and dynamic website content respond instantly to user behavior. Whether it's suggesting a product, answering a question, or adjusting navigation based on past activity, these tools turn passive browsing into tailored interaction.
• Test and Adapt Creative Based on Performance AI helps marketers run continuous A/B and multivariate tests on design elements like CTAs, layouts, and visuals. Results feed directly into optimization cycles, helping teams refine what resonates with specific segments and drive better outcomes faster.

Netflix uses A/B testing by randomly assigning users to different groups. It then compares key metrics like user engagement or content discovery, helping it to identify small yet impactful changes. This further enables Netflix to tweak the UI or improve content discovery enhancing the overall user experience.

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2. Scale content creation with enterprise-ready generative AI

Enterprise marketing teams are using generative AI to scale content production while improving speed and performance. From social posts to product descriptions and email campaigns, AI tools help marketers meet increasing content demands without sacrificing quality or consistency.

A recent survey found that 58% of marketers using generative AI report better content performance as the top benefit. This shows AI is not just saving time—it’s improving outcomes.

Core use cases for AI in content creation:

• Idea generation: AI helps brainstorm new topics, formats, and content angles.
• First-draft creation: Marketers use AI to draft outlines or full content, then refine with brand voice.
• Content updates: AI suggests improvements for existing blogs, landing pages, or product copy.
• Visual content support: AI tools generate images, layouts, and infographics to improve storytelling.
• Campaign personalization: AI tailors messages to audience segments by analyzing CRM and behavior data.

Check top AI social media content creation tools.

3. Transform decision-making with real-time predictive AI

Enterprise marketing teams are under pressure to move faster and act with greater precision. Predictive analytics helps analyze historical data to forecast market trends, anticipate customer preferences and churn, measure campaign performance, evaluate customer interactions, and assess potential lifetime value and purchasing patterns. With these insights, marketers can optimize workflows and make more informed, data-driven decisions.

With Sprinklr AI, marketers can forecast trends, identify emerging risks, and deliver content based on what customers are likely to need next—not just what worked before.

Sprinklr analyzes behavior patterns, search activity, and engagement signals across social, web, and support channels. These insights help predict which information or support each segment is likely to seek at every stage of the journey.

This shift from reactive to predictive content strategy enables enterprises to:

• Create value earlier in the customer journey
• Deliver more relevant and timely messages
• Build longer-term customer trust through proactive engagement
• Reduce churn by meeting needs before they arise

By aligning content and communication with predicted intent, Sprinklr helps marketing and CX teams deliver consistent, personalized experiences at scale.

💡Pro Tip: Implement predictive analytics with real-time tracking of key performance indicators (KPIs) to refine your strategies instantly and boost your marketing impact.

A robust and comprehensive analytics tool is all you need to get actionable insights for data-driven marketing decisions.

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4. Automate workflows and operations with AI agents and multimodal AI

Research suggests that 82% of companies plan to integrate AI agents in 1-3 years, expecting automation and enhanced efficiency. AI agents, or agentic AI, are the new quantum leap in AI technology. Think of it as a super-smart assistant that can make decisions on its own.

AI agents can scan data, segment audiences, score leads, coordinate meetings and set up email sequences, all without needing constant input. It learns from experience and suggests strategies to streamline operations and enhance customer understanding.

The result? A more efficient team focused on creating engaging, personalized experiences for clients, all thanks to this powerful AI system. Manus AI is one such agentic tool gaining traction in the industry.

Helpful Read: Why Enterprises Need to Invest in Agentic AI in 2025

5. Build trust with ethical and responsible AI practices

AI systems are only as strong as the data behind them. For marketing teams, that means ensuring data is consistent, secure, and ethically governed. Without proper governance, organizations face increased risks: poor data quality, compliance violations, and flawed decision-making that can undermine AI’s effectiveness.

Strong data governance ensures that AI models are trained on accurate, reliable inputs. It also protects sensitive customer data from breaches and restricts access to authorized users only. Most importantly, it supports compliance and reduces the risk of biased or discriminatory outcomes—building trust with customers and regulators alike.

Best practices for responsible AI governance

To ensure your AI marketing strategy is both effective and compliant, enterprises should adopt these core practices:

1. Establish a data governance framework

Create centralized policies that define how data is collected, stored, accessed, and used across teams. This reduces redundancy, prevents misuse, and improves data quality for AI models.

2. Align with global regulatory standards

Adhere to globally recognized data privacy regulations such as GDPR, CCPA. Ensure AI tools support audit trails, consent management, and data minimization requirements.

3. Enable cross-team collaboration

Ensure alignment between marketing, legal, IT, and compliance teams on how AI is implemented. Shared understanding prevents gaps in accountability and reduces the risk of non-compliance.

4. Prioritize transparency

Make it clear how AI systems arrive at decisions—especially when those decisions impact customers. Wherever possible, offer users visibility into how personalization or targeting is being applied.

5. Evaluate vendors for built-in trust capabilities

Choose AI solutions that prioritize security, privacy, and compliance by design. For example, Sprinklr’s AI-powered platform is built with enterprise-grade governance controls, including data encryption, role-based access, and rigorous compliance practices. Visit Sprinklr’s Trust Center for a full overview.

How to build an AI-driven marketing strategy

Adopting AI in marketing effectively requires a structured approach and implementation. Here’s how to use AI in marketing strategically:

Step 1: Define clear AI use cases and KPIs: Identify the marketing challenges where AI can drive the most impact, such as automating content creation, analyzing large datasets, or predicting customer churn. Set KPIs that track impact on efficiency, engagement, or revenue.

Step 2: Assess your data readiness and infrastructure: AI models depend heavily on high-quality, accessible data. Evaluate your existing data sources, quality and governance and prioritize data cleaning and management to ensure reliability. Ensure your tech stack can integrate with AI tools.

Step 3: Choose the right AI tools and platforms: Select solutions that align with your use cases. Consider whether third-party tools or in-house development is more suitable for your needs. Third-party tools are faster to integrate and require minimal setup, while in-house development offers greater customization but requires substantial investment. Check out list of most reliable AI tools for marketing.

Step 4: Maintain human oversight: Always blend AI capabilities with human creativity, intuition and empathy. AI should support, not replace, human decision-making. Ensure that customer interactions maintain a sense of authenticity and brand personality. Striking the right balance between automation and human oversight is crucial to success.

Step 5: Start small, iterate and scale wisely: Begin with pilot projects targeting high-impact areas. Measure results, learn from them and then scale successful initiatives across the organization.

Step 6: Embed ethical AI governance and security: Establish clear guidelines for data privacy, transparency and bias mitigation. Regularly audit your AI models. Trust and data security are non-negotiable. This includes training data and website code protection.

By following this approach, marketers can maximize AI’s effectiveness, enabling informed decisions to optimize marketing strategies and ROI.

Examples of brands using AI in marketing

Let's examine how leading enterprises are leveraging AI to transform their marketing operations and deliver measurable results:

1. Planet Fitness and Sprinklr

AI use case: Planet Fitness leveraged Sprinklr AI+ along with Social Listening and AI-powered response tools to enhance agent efficiency, personalize customer interactions, and gain deeper consumer insights.

With over 2,400 locations and customer queries pouring in across platforms like X, Google Reviews, and TikTok, Planet Fitness needed to scale its social media customer support without compromising response quality. Their agents struggled to maintain brand tone, personalize replies, and extract actionable insights from customer conversations in real time.

Results:

• Increased agent efficiency: Enabled 38 social media care agents to handle high volumes of customer interactions more effectively with AI-powered response suggestions.
• Enhanced response quality: Boosted personalization by tailoring tone, length, and wording for each social channel using AI tools like Reword, Modify Tone, and Make it Shorter/Longer.
• Advanced social listening: Streamlined query-building and delivered proactive alerts for conversation spikes, enabling faster, smarter business decisions.
• Focused customer engagement: Freed agents from repetitive tasks, allowing them to deliver more thoughtful, meaningful interactions and improve overall customer satisfaction.

2. Unilever

AI use case: Unilever is brilliantly leveraging AI to supercharge its customer service experience. They're not replacing humans entirely but empowering their customer service agents with AI tools.

Unilever deployed "Alex," an AI email triage system powered by ChatGPT, to automate consumer message processing at its Consumer Engagement Center.

The tool analyzes daily emails, separating legitimate queries from spam while drafting context-aware responses for human agents to approve or refine.

Results:

Unilever's customer service agents, armed with AI, have managed to slash their response times by a whopping 90%. Imagine the ripple effect:

• Massively improved efficiency: Less time spent per query means more queries handled.
• Boosted customer satisfaction: Faster resolutions lead to happier customers. And happy customers are loyal customers.
• Freed-up human capital: When AI handles routine elements, your talented agents can focus on more complex, high-value interactions.

Actionable C-Suite Insight: “AI handles the grunt work; humans handle the heart work.”

This Unilever example isn't just about cutting seconds off a clock. It’s a powerful demonstration of AI augmenting human capability to drive core business metrics.

3. The Home Depot

AI use case: This leading home improvement retailer has deployed “Magic Apron,” an AI-powered digital concierge integrated across their website and mobile app to transform their customer experience. This tool leverages advanced large language models to mimic the in-store associate experience, answering product inquiries, summarizing product reviews and providing real-time project advice.

Result: Customers receive personalized, context-aware guidance that streamlines the shopping journey—from exploring product details to getting tailored project recommendations. The Home Depot’s success story here isn’t just about smarter search; it's about reducing friction in the customer's path to purchase and problem-solving through AI.

To know about more, check out more real-world examples of AI in marketing.

Final thoughts

AI in marketing has become critical for enterprise teams aiming to accelerate decision-making, deliver hyper-personalized experiences, and achieve measurable business outcomes at scale. From predictive analytics to automated workflows, AI is changing how organizations engage with customers, improve efficiency, and stay ahead in competitive markets. To make the most of this shift, companies must move beyond disconnected tools and adopt a strategy that integrates data privacy, automation, and real-time insights into a single, cohesive system.

Sprinklr enables enterprise marketers to apply AI across every stage of the customer journey. With built-in tools for content planning, audience targeting, performance analysis, and real-time listening. Talk to our experts to know more.