What a difference a year makes! We last wrote about artificial intelligence (AI) in early 2024. Since then, AI has become increasingly integrated into almost every marketing strategy, opening up new possibilities and reshaping the industry. According to a recent survey, 88% of marketers rely on AI in their current roles, utilizing it for all kinds of tasks, including creating and optimizing content, automating repetitive tasks, and analyzing data.
At Phase 3, we're still watching the AI evolution closely; and monitoring the trends, tools, and challenges shaping how marketing leaders use AI in marketing and where it's headed.
Key AI Trends in Marketing
It's clear that AI is transforming how marketers connect with customers. Here are a few of the most interesting trends in AI for marketing.
Personalization at Scale
AI is transforming personalization. Traditional segmentation groups customers by broad categories like age, gender, or location. In contrast, AI-driven personalization delivers content to individuals based on real-time behaviors, preferences, and engagement patterns. Platforms like Dynamic Yield and Adobe Target help you customize landing pages, emails, and product recommendations to better reflect each customer's current interests and intent. Even direct mail campaigns are becoming more personalized through AI. We discussed the power of personalization in print marketing in this recent blog.
Voice and Visual AI
Voice AI powers search tools like Siri, Google Assistant, and Alexa. These platforms interpret spoken queries and deliver relevant results. For marketers, this means optimizing your digital content for conversational search terms and local relevance, not only industry keywords. Read more about the emerging use of voice-activated devices in B2B marketing here.
Visual AI, like Google Lens, allows users to search and shop using images. Tools like Google Cloud Vision AI enable retailers to offer barcode scanning, virtual try-ons, and visually similar product searches. These intuitive features make the customer experience more seamless and interactive.
Predictive Analytics
AI-informed predictive analytics uses real-time and historical data to help you anticipate customer behavior. Platforms like Salesforce Einstein and HubSpot Predictive Lead Scoring analyze website visits, past purchases, and email engagement. They identify leads, predict churn, and guide campaign timing. Because they use real-time data and machine learning, these platforms continuously learn and refine their outputs, giving you a clearer view of emerging trends and customer needs.
Creative AI Evolution
Generative AI tools like DALL-E and Adobe Firefly can enable you to quickly produce all kinds of visual content, from logo variations to social media graphics. These tools are handy for creating large volumes of content and saving time on repetitive design tasks.
But while these tools are improving, they’re not perfect. AI-generated images sometimes look strange or unrealistic. Used wisely, creative AI tools can support design workflows, but human oversight is still necessary to maintain quality and brand integrity.
AI and Data Privacy
As personalization increases, so does the importance of data privacy. Emerging regulations, including recent updates to existing privacy laws and the introduction of new AI-specific laws, require you to be especially careful in how you collect, store, and use customer data.
One of the most significant changes affecting digital marketing is the phasing out third-party cookies. Growing concerns around consumer privacy have led major browsers and search engines to restrict or eliminate their use. Marketers must now rely on first-party data to personalize marketing.
AI can help you analyze your consented data to guide campaigns, but you should build in compliance measures. Tools like OneTrust and Ketch can assist with managing privacy preferences and regulatory compliance while integrating into AI-powered workflows. Learn more about our cookie-less future here.
Cross-Channel Integration
Modern digital marketing often spans email, social media, search, mobile apps, and websites with different formats and timing. AI-powered tools make it easier to keep your marketing consistent across channels. These tools track how your campaigns perform on each platform and can automatically adjust content, timing, or messaging to stay aligned.
For example, if an email campaign generates traffic to a landing page, AI can quickly update connected ads on social media to reflect the same message and timing. Tools like Adobe Experience Platform and Salesforce Marketing Cloud help automate this kind of coordination.
This saves you time and creates a better experience for your audience. No matter where someone sees your brand, the message and tone feel familiar and intentional.
Challenges and Limitations of AI
In our 2024 article, we discussed some of the challenges and limitations in using AI. Let’s review how those challenges and limitations have evolved since then.
The Creativity Gap
AI doesn’t understand culture, emotion, or narrative structure. That means it often produces uninspired or redundant ideas. It can’t anticipate cultural shifts, interpret lived experiences, or develop strategic storytelling that resonates deeply with human audiences. In short, AI doesn’t understand what truly moves people, because creativity and emotion aren’t built into algorithms.
Imagine an AI bot creating an ad for a neighborhood restaurant. It might correctly list the daily specials and operating hours. Still, it can't evoke the feeling of gathering around a table with family or the comfort of a favorite meal after a long, stressful day. A human storyteller can frame those details into a narrative that actually inspires someone to want to book a table.
Great marketing is more than delivering information; it inspires trust through creativity. And that kind of creativity still starts and ends with people.
Empathy Deficit
Marketing that connects also requires empathy. Consumers are more likely to purchase from brands that show understanding of their needs and emotions. Like creative ideas, AI struggles with emotional intelligence. This makes it challenging for AI to generate content that authentically connects with audiences on an emotional level. While it can identify patterns in behavior and engagement, it lacks the lived experience, intuition, and cultural awareness needed to express empathy in a meaningful way.
A notable example occurred when Air Canada's chatbot provided incorrect information to a grieving passenger seeking a bereavement fare. The error led to financial and emotional distress for the passenger, culminating in a court ruling that held Air Canada accountable.
Effective marketing demands empathy, authenticity, and understanding. While AI can support marketing campaigns with relevant data, the emotional connection still needs a human touch.
Bias in AI Models
AI can amplify bias if it’s trained on skewed data. This has real consequences in marketing, from exclusionary language to uneven representation.
For example, a 2024 study revealed that Meta's advertising algorithm exhibited racial bias in distributing ads featuring models with different skin tones. For every $1,000 spent on ads with light-skinned models, advertisers had to spend $1,159 to get the same engagement with darker-skinned models. When both types of images had the same budget, Meta used about 64% for ads with lighter-skinned people. In other words, Meta used biased data to train its algorithm. This caused unequal representation and engagement in its customers' marketing campaigns.
To reduce these risks, it's vital to regularly review both the data used to train AI tools and the content the tools create. Tools like IBM Watson OpenScale and Google's AI fairness toolkits can help identify and correct bias in AI-generated content.
Adapting to Market Shifts
AI is great with patterns, but not with unpredictability. When the world changes fast (think pandemics, protests, or sudden economic shifts), AI can fall behind.
During the early months of the COVID-19 pandemic, several brands faced criticism for running digital ads perceived as tone-deaf or insensitive to the global crisis. For instance, KFC suspended its long-standing "Finger Lickin' Good" campaign in the UK due to concerns that the slogan promoted behavior contrary to health guidelines. Similarly, Hershey's and Coors pulled ads that featured close personal interactions, such as hugging and handshakes, which were discouraged during the pandemic.
Human oversight is still essential for interpreting cultural signals, assessing context, and responding with appropriate tone and timing.
Dependency Risks
Relying too much on AI can lead to content that lacks originality and fails to reflect a brand's unique voice. When multiple companies use the same tools without careful customization or human oversight, the result can feel repetitive and impersonal.
This sameness weakens brand recognition and makes it harder for content to stand out. Customers may begin to tune out, disengage, or associate a brand with a lack of innovation.
Let AI handle volume, but reserve strategic storytelling and tone-setting for your team.
Cost and Expertise Barriers
AI tools are never plug-and-play solutions. While many tools promise ease of use, most require significant upfront investment in software, training, and integration. In addition, businesses need to allocate time and expertise to fully leverage AI’s potential.
A 2024 McKinsey report highlights that only 1% of companies consider themselves mature in AI use. The vast majority of businesses are still learning how to implement, train, and pay for AI tools. The report emphasizes that the primary barrier to scaling AI initiatives isn’t employee readiness but a lack of decisive leadership and strategic direction. For example, cost uncertainty makes it difficult for leaders to predict the ROI of new AI tools. Also, many employers are struggling to understand their AI staffing and training needs.
Even widely available tools like ChatGPT or Canva require users to understand prompt engineering, content validation, and brand alignment. Without the right people to manage these processes, AI outputs can become inconsistent, off-brand, or even risky.
To get the most value from AI, budget for the software and for ongoing training, support, and oversight so your team can use it responsibly and effectively.
The Critical Role of Brand
At Phase 3, we've found that AI works best when guided by a clear, consistent brand. A strong brand foundation, including well-defined messaging, tone, values, and visual identity, is crucial to leveraging any AI tool successfully. If you can't clearly articulate who you are and what your brand stands for, AI won't be able to either.
Think of it this way: AI doesn’t understand your business. It understands patterns. Without specific inputs, it’ll default to generic outputs. That’s why training AI tools with your brand guidelines is so important. Brand guidelines help AI generate content that reflects your brand personality and voice, supports your market positioning, and speaks directly to your customers.
Well-trained AI can generate branded copy and visuals faster and more consistently. But the strategy, story, and final polish still come from your people.
Practical Strategies for Using AI
To summarize this article so far, here are the actionable strategies we suggest our clients take to incorporate AI into their marketing campaigns.
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Train AI with Brand Guidelines: Upload your personality, customer personas, visual assets, tone of voice, taglines, design rules, and content examples.
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Use AI for Volume, Not Vision: Automate repetitive tasks, like resizing assets or generating variations.
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Monitor and Adjust: Audit your AI outputs regularly to ensure brand alignment and catch bias.
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Respect Privacy: Pair AI with strong consent practices and compliance tools.
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Target Smarter: Use AI to refine audience segments and time your campaigns.
When used thoughtfully and trained correctly, AI can amplify your brand message by helping you create more consistent, efficient content at scale.
AI-Driven Marketing Innovations We're Watching
The world of AI is constantly evolving. There are exciting innovations on the horizon. Here are just a few to keep an eye on.
Intuitive Generative AI Tools
Platforms like Canva's AI-enhanced tools allow marketers to create and batch branded social media graphics using already designed brand assets loaded into the tool. It's as simple as writing a short description of the desired design. For instance, typing "Create an Instagram post about Earth Day using shades of green and blue with eco-friendly icons" generates a ready-to-use design.
AI in AR/VR Experiences
AI can create immersive experiences, such as virtual try-ons or interactive product demonstrations, enhancing customer engagement. For example, a cosmetics brand leverages artificial or virtual reality tools that enable customers to "try on" makeup in a virtual mirror using their smartphones. AI customizes the recommendations based on skin tone, lighting, and preferences gathered from user interactions.
Emergence of "AI Creativity Coaches"
Tools like Adobe's AI Creativity Coach assist teams in campaign planning by offering suggestions based on market trends and past performance. For example, a SaaS company uses Jasper or ChatGPT to analyze competitors' marketing campaigns and provide unique angles for differentiation.
The Path-Forward: Balancing AI with Human Expertise
At Phase 3, we've been watching the evolution of AI closely and experimenting with how it can support our work. While we don't consider ourselves AI experts, we've found value in using it to streamline repetitive, non-creative tasks, like generating variations of social copy, resizing graphics, or organizing data. These efficiencies allow our team more time to focus on work that requires a human touch, including strategy, messaging, design direction, and emotional storytelling. As AI tools evolve, we'll keep testing, learning, and staying informed. Our goal is to use technology to enhance our work, not replace what makes it meaningful.
Wrapping Up the AI Discussion
AI in marketing is evolving fast. And it's here to stay. Used thoughtfully, it can make your marketing team more efficient, your campaigns more personalized, and your decisions more data-driven. However, the best results come when a strong brand strategy guides AI and creative professionals manage it.
The future of marketing belongs to teams that know how to use AI responsibly while holding onto what makes brands human. Phase 3 helps businesses build the brand clarity and systems needed for innovation. Contact us to learn more about building a marketing strategy that blends creativity, technology, and trust.