Eighty-three percent of marketers say customers expect two-way conversations. Yet 69% admit they struggle to respond quickly to inquiries. That gap may be the most critical signal in Salesforce’s latest State of Marketing report.
The AI revolution in marketing is already operational. Nearly 4,500 marketers surveyed globally confirm that expectations are rising faster than most teams can adapt. While 75% of organizations are already using at least one form of AI, execution still lags behind ambition.
This is no longer just a CMO issue. It is a frontline marketing reality.
Source: Salesforce State of Marketing report
Three out of four marketing teams are using AI in some form, according to the report. On paper, that sounds like a broad transformation. In practice, many teams are still layering AI tools on top of disconnected data and legacy workflows.
Marketers say AI can help them reclaim significant time each week. That reclaimed time goes beyond speed. It represents expanded capacity for strategy, creative thinking and customer insight. But the value only materializes when marketers develop the skills to guide, interpret and manage AI systems effectively.
Data analysis and AI fluency are quickly becoming core competencies. The marketer who cannot interpret data or orchestrate AI tools will struggle to stay relevant.
Marketers trust AI to talk to customers
Eighty-one percent of marketers now say they trust AI to respond to customer inquiries. That represents a breakthrough moment. AI agents can provide round-the-clock responsiveness at a scale that human teams alone cannot manage.
Responsiveness without relevance falls short. To deliver meaningful conversations, AI must be powered by unified, contextual customer data.
Salesforce’s findings highlight a persistent issue. Many marketing teams still lack full access to customer data across departments.
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When service, sales and commerce data remain siloed, personalization suffers. AI systems cannot accurately predict behavior or recommend next-best actions without complete visibility.
As a result, personalization efforts often fall short. Eighty-four percent of marketers admit their campaigns still feel generic. That underscores a critical point. AI by itself cannot create personalization. Connected data drives meaningful personalization.
Some progress is visible. A growing share of marketers are using predictive behavior modeling to segment audiences. But predictive capabilities require investment in data architecture, governance and cross-functional alignment.
Agentic marketing is moving to implementation
The clearest signal that agentic marketing is emerging is not conceptual. It is operational. Sixty-one percent of marketers say their organizations are either experimenting with or fully implementing AI agents. That means autonomous systems are no longer side projects. They are entering live workflows.
This shift is strategic, not tactical. Sixty-eight percent of marketers say generative AI is critical to their overall marketing strategy. That level of prioritization suggests AI is becoming infrastructure, not a campaign tool.
Autonomy, however, depends on timing and context. Sixty-four percent of marketers say real-time data activation is critical to their success. Agentic systems cannot function on delayed reporting. They require current signals to trigger next-best actions, adjust journeys and personalize responses as interactions unfold.
The data foundation also separates leaders from laggards. Fifty-seven percent of high-performing marketing teams report having a unified customer data platform in place. That unified view allows AI agents to act with awareness rather than guesswork.
Taken together, these numbers point in one direction. Marketing is moving toward systems that do more than assist humans. They operate alongside them, triggering journeys, adjusting messaging and optimizing interactions continuously.
The opportunity is not simply automation. It is coordinated autonomy powered by real-time data and unified customer context.
Source: Salesforce State of Marketing report
Marketing is aligning with revenue
Revenue accountability is no longer aspirational. It is measurable. According to Salesforce, 83% of high-performing marketers report having a clear view into their impact on the sales pipeline, compared with far lower visibility among underperforming teams.
The alignment is structural. More than half of marketers say their top KPIs now directly tie to revenue growth and pipeline contribution rather than engagement metrics alone. At the same time, 60% report that improving customer journey orchestration across marketing, sales and service is a top priority, reinforcing the need for lifecycle-wide visibility.
Data integration is emerging as the dividing line. Fifty-seven percent of high-performing teams say they have a unified customer data platform in place. That unified view enables closed-loop reporting, clearer attribution and stronger credibility with finance and executive leadership. Marketing is no longer measured by output volume. It is evaluated on growth contribution.
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Personalization remains the hardest challenge
If revenue alignment is accelerating, personalization is still catching up. Eighty-four percent of marketers admit their campaigns still feel generic, despite years of investment in segmentation and automation.
The gap is not awareness. Seventy-eight percent of marketers say they need more personalized content than they can currently produce. Meanwhile, 64% say real-time data activation is critical to success, yet many teams still lack the infrastructure to deliver on that expectation consistently.
Fragmented data remains a primary obstacle. Only 57% of high-performing teams report having unified customer data, leaving a significant portion of the market unable to personalize without full context. AI can scale content production, but without strong data governance and connected systems, automation simply accelerates generic output.
The result is a paradox. The tools for hyper-personalization are widely available, but the operational foundation to execute at scale is still uneven.