In 2024, AI adoption surged to 90% — and following that rapid onboarding, 76% of marketers are optimistic about AI’s future. As AI completes its shift from a novel concept to an actual tool with real impact, Corbett Drummey, VP of Brand Collaboration for creative technology provider Lightricks, explained that organizations are now focused on the practicality of AI technologies.
“We’re seeing a ton of practical uses now, like AI tools that help create visual content, optimize creative campaigns and analyze data,” said Drummey. “AI offers a way to automate tasks, personalize customer experiences and gain a competitive edge.”
As companies turn to AI for greater efficiencies and process improvements, they’re tasked with boosting productivity while maintaining quality and the customer experience. Specifically, Ashley Topping, Head of U.S. Marketing for email signature management platform Exclaimer, pointed to AI’s ability to process vast amounts of data and identify actionable insights as particularly valuable, especially in a landscape where precision and relevance are key to success.
As marketers move beyond AI adoption and focus on execution, the top three use cases for AI in 2025 include:
Fueling Intent-Based Marketing With Predictive Analytics
One of the biggest opportunities to leverage AI is intent-based marketing. According to the “AI Marketing Benchmark Report 2024,” 84% of marketers use AI to align web content with search intent. This analysis of user intent within marketing strategies isn’t without merit, as Gartner research uncovered that personalization through intent data can improve campaign ROI up to 20%.
“By analyzing intent signals from website visits, downloads or third-party platforms, AI helps marketers deliver timely, relevant content to accounts showing buying intent,” said Topping. “This aligns perfectly with ABM strategies, where precision targeting is critical.”
Topping explained this is where AI-powered predictive analytics come into play. She continued that data analysis technique can help marketers forecast customer behaviors, identify high value accounts and prioritize leads most likely to convert.
“AI-driven lead scoring models analyze historical and intent data to recommend the best outreach strategies,” said Topping. “This enables sales and marketing teams to focus their efforts on high-priority opportunities.”
Generating Personalized, Relevant Content
The top uses for generative AI in content creation include ideation, content development and drafting content. Specifically, Topping pointed to AI tools such as ChatGPT and Jasper as innovators revolutionizing content creation due to their ability to generate personalized emails, social posts or ad copy at scale.
However, practitioners can’t throw content into the AI winds with no strategy, as poorly executed AI-generated content presents negative brand effects. Specifically, 52% of consumers said they’re less engaged with content they suspect is AI-generated, while another 26% perceive AI-generated content as impersonal. This means success in AI content creation requires defining the company voice and sharing those elements of communication with the technology.
“All use of AI in marketing requires maintenance and management: A robotic GPT-created email could come across as inauthentic, so the time saved isn’t worth it until marketers really fine-tune their use of AI,” said Lynn Tornabene, Chief Marketing Officer of Anteriad, a marketing and B2B data solutions provider. “Marketers need to train the AI and determine the best way to personalize content while keeping their distinctive brand voice.”
Autonomously Chatting With Customers
The value of chatbots and conversational AI is recognized by both practitioners and customers. More than half (52%) of marketers prioritize AI for its ability to enhance customer engagement, while 69% of customers prefer to use robots for immediate answers.
“AI-powered chatbots enhance lead generation and customer support by providing instant, tailored responses,” said Topping. “They also collect valuable data that can feed into broader marketing strategies, ensuring a seamless user experience.”
Still, the pitfalls seen in AI-generated content also extend to chatbots. According to Tornabene, without the proper training, conversational AI is prone to churn out clunky, generic answers that can frustrate customers..
“Fully automated buying journeys and chatbots could be a bit riskier if they frustrate customers or come across as robotic or inauthentic,” said Tornabene. “Marketers can lean into AI that doesn’t affect authenticity or even enhances it. Beyond that, they need to monitor any AI capabilities — like chatbots — that may create negative customer experiences.”
She continued that practitioners need to take great care training any autonomous AI agents, with a specific focus on supplying the tool with as many materials as possible so it can accurately engage customers. Adding to that, Topping stressed the importance of monitoring the technology closely to ensure it’s helping, not hurting, business.
“Marketers need to balance automation with human elements to maintain brand authenticity,” said Topping. “Incorporating human touchpoints ensures that marketing efforts remain genuine and relatable.”
Conclusion
As practitioners deploy AI for more customer-facing applications and increase their reliance on its data analysis capabilities, organizations must keep up with the latest changes and ensure the technology is always meeting their needs.
“AI tools and creative capabilities are only going to continue changing,” said Lightrick’s Drummey. “If organizations want to strategically and successfully implement it across their workflows and maintain a competitive edge, they need to ensure it’s addressing real needs and their teams are equipped to leverage them effectively.”
