In the ever-evolving world of marketing, artificial intelligence (AI) is emerging as a game-changer. But what does this mean for the marketers who use it?
The Jasper report titled The State of AI in Marketing 2025 details how AI platforms are designed to enhance human creativity by taking on time-consuming tasks like content generation and data analysis. This frees up marketers to focus on strategy, storytelling, and building meaningful connections with their audiences.
The author, Jasper’s Head of Communications and Content, Esther Chung, details in our interview how AI platforms view their role in the marketing ecosystem, the impact it has on scaling campaigns and personalizing content, as well as AI becoming an indispensable tool for teams of all sizes.
Demand Gen Report (DGR): The report states that 63% of marketers are currently using generative AI. What is the primary benefit they are seeing from this early adoption? And how can a marketing team move beyond “ad hoc” AI applications to integrate AI into existing tech stacks and workflows for a more scalable impact?
Esther Chung: Given how quickly adoption has accelerated since we launched the survey, the real percentage of marketers using genAI is likely higher than 63%. Early wins are clear: teams report increased productivity, stronger ROI, and faster content production. Perhaps most telling, 78% of marketers say AI has improved their job satisfaction, a sign that AI is taking repetitive work off their plates and freeing them up for higher-value tasks.
But adoption alone doesn’t guarantee impact. Many teams stall in pilot mode, using AI only for isolated tasks like a blog draft or social caption, often in silos. The leaders breaking through are formalizing AI programs with defined use cases, governance, and training; embedding tools directly into marketing workflows and systems; and selecting platforms purpose-built for marketing and scale. With those foundations in place, AI shifts from being a productivity booster for individuals to becoming an engine for marketing transformation, delivering consistent, brand-safe impact across channels, teams, formats.
DGR: In what ways can AI help human marketers with ideation and content creation without replacing their jobs?
Chung: AI is best understood as a partner, not a replacement. For marketers, it lightens the load of repetitive, manual tasks so they can focus on higher-order work like strategy, storytelling, and innovation. In our report, more than half of marketers already use AI to spark new ideas (55%) and create content (57%), but its true impact comes from how it amplifies human strengths.
With clear objectives and a sharp strategy in place, AI enables scale that was previously out of reach. It accelerates ideation, generates variations for different markets, languages, or formats, and enables content pipelines all while staying grounded in brand and audience context. In this way, AI becomes a multiplier: helping marketers move faster and deliver more impactful campaigns without displacing the uniquely human skills of intuition, empathy, and imagination. The result isn’t job loss; it’s stronger brands, more resilient teams, and greater human creativity at scale.
DGR: The report highlights a gap between AI adopters and those truly embedding it into their workflows. What are the key elements of a formalized AI program that can help close this gap?
Chung: We call this the AI Impact Gap: while 63% of marketers are adopting AI, more than half still can’t measure ROI. Closing this gap requires blending operational, technological, and cultural elements. Key components include documented use cases, a culture of continuous experimentation, and visible leadership buy-in to drive adoption from the top down.
In the report, we also see that “more advanced” teams also embed AI directly into daily workflows (51%), track the ROI of AI investments (96%), establish strong governance with training, councils, and clear policies, invest in domain-specific AI tools over generic ones.
DGR: How does the adoption of AI differ between larger marketing teams (over 1,000 employees) and smaller ones?
Chung: Larger teams are more likely to use domain-specific AI tools, with 57% favoring them over general-purpose tools. That’s because bigger organizations face more complexity: multiple markets, channels, and audiences where brand governance and output quality are critical. In fact, for enterprises with more than $1B in revenue, output quality (31%) and brand governance (33%) are the top priorities.
Smaller teams tend to focus on budget constraints, leadership buy-in, and data privacy as their biggest hurdles. These organizations often adopt AI in more tactical or individual ways, which can limit their ability to scale. Measurement is another dividing line: 62% of large teams track ROI on their AI investments compared to just 38% of small teams.
DGR: What did you find were the obstacles to scaling AI adoption?
Chung: The top barriers to scaling include data privacy (21%) and output quality (19%), followed by lack of expertise, leadership buy-in, and budget constraints. In practice, this shows up as inconsistent outputs, tools disconnected from business processes, and AI delivered through chat interfaces that can’t support scaled content pipelines. Without integration into core workflows and systems, AI cannot deliver enterprise-level transformation or measurable business outcomes.
The inability to measure ROI also remains a persistent challenge, hindering broader buy-in and resource allocation.
DGR: On that subject, the report indicates that 22% of marketers plan to start tracking AI ROI in 2025. What is driving this increased prioritization of measurement? How much more likely are companies using marketing-specific AI tools to measure ROI compared to those using general-purpose tools?
Chung: Teams that measure ROI are better able to align AI investments with revenue growth objectives, prove efficiency gains, and secure leadership buy-in for further adoption. In fact, companies that track ROI are 47% more likely to expand AI usage compared to those that don’t.
The ability to measure ROI drops significantly with general-purpose AI. Companies using marketing-specific AI tools are 37% more likely to track ROI than those relying on generic solutions.
DGR: How does the perception of AI maturity differ between CMOs and their teams, and what is the impact of this disconnect?
Chung: While 44% of CMOs rate their AI maturity as “advanced” or “very advanced,” only 27% of managers agree. Similarly, 65% of CMOs view leadership as “very committed” to AI, but that confidence drops sharply among VPs, directors, and managers. This gap creates misaligned expectations: leaders may assume their teams are further along than they are, while practitioners may lack the structure, training, or support to meet those expectations. The result is stalled implementation, inconsistent adoption, and a widening AI Impact Gap, where strategic ambitions outpace operational reality.
DGR: Recently, there have been concerns raised about “quiet AI layoffs.” What skills should marketers be focusing on to thrive in an AI-forward company?
Chung: The report points to a more optimistic reality: 78% of marketers report higher job satisfaction as AI takes repetitive tasks off their plates and allows them to focus on more strategic, rewarding work. Nearly half (48%) also expect AI to significantly evolve team roles, especially in organizations investing at scale, signaling transformation, not reduction.
The real risk isn’t job loss, but failing to evolve the right skills. Marketers who thrive in an AI-forward company will excel at context-setting, decision-making, and orchestrating complex campaigns, while strengthening soft skills like curiosity, strategic thinking, leadership, and relationship building. At the same time, new roles are emerging—such as Content Engineers and Workflow Architects—that blend marketing expertise with technical fluency. Building capabilities in AI strategy, data analysis, and workflow automation will be critical to turning AI from a productivity tool into a growth engine. Far from diminishing marketing’s impact, AI paired with these fundamentals positions the function to reclaim its seat as a true revenue driver.
DGR: Beyond content creation, what are some of the higher-value use cases for AI that remain untapped by most marketers?
Chung: Most marketers have yet to fully leverage AI in higher-value areas like brand governance, workflow automation, hyper-personalization, predictive optimization, and agentic use cases. These use cases move AI from assisting with tasks to autonomously improving consistency, scale, and performance across channels. The report shows that fewer than a third of marketers are using AI in these ways, but teams with “very advanced” maturity are nearly twice as likely to embed AI into these strategic areas compared to their peers.
