AI in Marketing: What’s Working and What’s Not?

Where AI is getting marketers’ attention

Chatbots among top AI use cases

A survey of 300 marketers on AI usage in marketing shows that chatbots for customer interactions are currently the most widely adopted AI application, with 62% of respondents already implementing such solutions and another 29% planning to do so within the next 6–12 months [1]. The reasons behind this popularity are clear. As customers increasingly expect 24/7 service and instant responses, companies must keep pace with these demands while still controlling operating costs.

AI chatbots have therefore become a key enabler. They can automate routine inquiries while still delivering a human-like interaction experience. Global analysts are confident in the continued growth of AI chatbots. Gartner, for instance, predicts that as many as 80% of standard customer service queries will be resolved by agentic AI without any human intervention [2].

This level of automation, combined with round-the-clock availability, enables companies to operate more efficiently without maintaining large support teams. Operationally, the impact is substantial, as organizations can improve service continuity while reducing costs by as much as 30% [2].

AI chatbots are not only a win for businesses; they benefit customers as well. Trained on a massive database, they can collect and present information about services and products with a high degree of accuracy, helping customers make better-informed decisions. One example is a leading Asian financial group that partnered with FPT to implement an aggregation and comparison platform for insurance products with a built-in GenAI chatbot.

The platform offers smart search capabilities, personalized filters, and intuitive visual comparisons, making it easier for customers to browse and evaluate insurance options. The GenAI chatbot enhances this experience by delivering instant responses to inquiries and providing tailored recommendations based on individual preferences. As a result, customers can identify their preferred insurance plans more efficiently, spending 50–75% less time researching products. The platform also enables them to review a wider range of options, ultimately choosing plans that better fit their needs and saving 10–20% in premiums by securing better deals.

Content generation remains popular

Content generation remains one of the most popular AI use cases among global marketers. A survey by Coleman Parkes Research ranks it as the second most widely adopted AI application, with 45% of respondents already using it and another 41% planning to implement it within 6–12 months [1]. This finding is consistent with research by HubSpot, which identifies content generation as the top AI use case, with one in four marketers using the technology to turn text into multimodal campaigns [3].

Marketers are using AI effectively to accelerate the content production process, starting from brainstorming and ideation. AI tools can quickly generate outlines, first drafts, summaries, or idea lists, significantly reducing the time spent staring at a blank page. AI-powered search can also crawl and collect information from websites, organizing it into well-structured summaries of research and analysis, thereby saving writers considerable time.

By automating routine tasks such as grammar checking, rewriting, and repurposing, AI tools seamlessly take over repetitive work and allow writers to focus on higher-value activities like editing and strategizing. Consequently, marketers already report significant time savings from using AI tools in content generation, cutting as much as three hours per piece [4]. At a company level, these time savings translate into faster publishing, more frequent updates, and a stronger ability to respond quickly to news and emerging trends.

When AI backfires on brand performance

Overusing AI without proper human oversight can ultimately hurt brands more than any efficiency it delivers. AI-generated content is widely criticized for violating intellectual property rights, creating serious legal and reputational risks. Because these systems are trained on vast pools of public data, they can unintentionally produce outputs that mimic or include the styles, designs, and elements of copyrighted works.

Relying on such outputs not only exposes brands to potential lawsuits but also erodes brand authenticity, making customers question the values a brand claims to uphold. A clear example is LEGO, which was called out for using an AI-generated image for its Ninjago characters that featured a headband from the Japanese manga Naruto – an IP LEGO did not hold a license for [5]. Beyond unauthorized use of intellectual property, the backlash focused on how this move clashed with LEGO's own identity as a brand built on quality and creativity.

Heavy reliance on AI can also weaken a brand’s effectiveness when emotional resonance is central to how it connects customers with its values. Genuine emotional impact comes from real people, lived experiences, and authentic storytelling – elements that AI can only imitate on the surface. While the technology may reproduce artistic styles, it lacks the shared experiences, environments, and cultural understanding that underpin true emotional connections.

This limitation became apparent when Coca-Cola faced criticism for its fully AI-generated 2024 Christmas promotional video. Intended as a tribute to its iconic 1995 commercial and a celebration of reunion and joy, the campaign instead drew backlash from viewers who described it as "soulless" [6].

Over-reliance and careless deployment of AI do not just invite criticism; they actively push customers away. Survey findings show that nearly half of respondents report lower trust in brands that use AI-generated emails, citing a lack of authenticity and transparency. Many customers are willing to walk away altogether: 79% of respondents say they are very likely to switch brands if AI is the primary tool used for brand communications.

The long-term implications are equally serious. More than half of surveyed consumers express reluctance to recommend such brands to others, signaling a direct threat to future growth and brand loyalty [7].

What does it mean for businesses?

For businesses, AI in marketing is a powerful performance booster but must be deployed with strict human and legal oversight. It can significantly improve revenue and competitiveness, yet careless adoption exposes organizations to accuracy, ethical, and compliance risks that can damage both results and reputation.

Despite its drawbacks, AI applications in marketing significantly improve business performance. Companies report their largest revenue gains from AI use cases in marketing and sales [8]. As a result, leaving AI out of marketing strategies can be detrimental, potentially causing businesses to lose competitiveness in the market. However, integrating AI into marketing requires careful monitoring and should be guided by the following principles:

• Human oversight is critical: AI should serve as a tool, not a replacement for human judgment. Marketers need to review, fine-tune, and edit AI-generated outputs so they accurately reflect the brand’s unique voice and values.
• Fact-checking is non-negotiable: AI biases and hallucinations occur more often than many might expect. Verifying the claims, arguments, and evidence produced by AI is essential to maintain information accuracy and credibility.
• Legal and compliance standards must be monitored closely: Regulations on data privacy, intellectual property, and AI-generated content are tightening worldwide. Ensuring compliance with these evolving laws is vital to avoid legal risks and reputational damage.
• Choosing the right AI partner matters: An ideal AI provider should not only demonstrate strong technical capabilities but also uphold strict ethical, security, and legal standards. This includes transparency about training data, clear policies on model training, safeguards against misuse and security threats, and a firm commitment to responsible AI.

With strong AI capabilities, an extensive partner ecosystem, and a large pool of skilled talent, FPT has become a trusted AI and digital transformation partner for global enterprises. The company supports more than 1,100 businesses worldwide, including over 130 Fortune 500 companies. To drive AI-first innovation, FPT continues to invest heavily in expanding its technological capacity, including the development of two AI factories in Vietnam and Japan equipped with NVIDIA H100 and H200 GPUs and ranked among the world’s TOP500 fastest supercomputers.

FPT has also introduced FleziPT – an AI-first platform for delivering agile AI solutions with speed, precision, and quality, cutting development time by 60% and reducing rework by 50%. The company is actively advancing its AI research and development with a strategic emphasis on responsible AI, in collaboration with global partners including NVIDIA, Microsoft, Landing AI, Mila, and others.

Conclusion

AI in marketing is clearly here to stay, powering always-on chatbots, faster content creation, and measurable gains in both efficiency and revenue. Yet as the backlash against AI-generated campaigns and IP missteps shows, brands that lean too hard on automation without human judgment risk sacrificing authenticity, trust, and even legal safety. The real advantage now lies not in using more AI, but in using it more wisely—with rigorous oversight, fact-checking, and compliance woven into every output. That’s where responsible AI partners like FPT, with deep technical capacity and a strong ethical focus, become strategic differentiators rather than mere vendors. For marketers, the question is no longer whether to adopt AI, but how to build a future-ready strategy where technology amplifies, rather than replaces, the human stories that make brands worth believing in.