From Assistive AI to Agentic CRM: The Real Shift
AI agents in marketing automation are software entities embedded inside CRM and content platforms that independently plan, coordinate, and execute campaigns and workflows based on live customer data and operational signals, shrinking the gap between insight and action while reducing the number of manual steps marketers must manage themselves. The important story is not more AI features; it is the rise of agentic CRM platforms that treat campaigns, service interactions, and content operations as tasks machines can own end‑to‑end. Instead of humans hopping between analytics, creative tools, and automation builders, agents now assemble audiences, draft messages, sequence journeys, and adjust flows based on performance signals. That changes marketing execution from a craft project to a continuously running system where humans design rules and guardrails, and the platform does most of the operational work.
Klaviyo’s Composer and Customer Agent: Shared Context, Shared Execution
Klaviyo has released its Composer AI marketing agent into public beta and broadened its Customer Agent into a more extensible agent platform spanning marketing and service workflows. Both agents work from the same real‑time customer profile, designed to connect marketing, service, and revenue activity inside a single CRM platform. When Customer Agent resolves a service interaction, it writes preferences and intent signals back to the customer record; Composer then uses those signals to build more targeted cross‑channel campaigns. This is agentic CRM in practice: service signals automatically shape marketing actions, and campaign engagement flows back into how service is personalized next time. According to Klaviyo’s CMO Jamie Domenici, “Businesses aren’t struggling because they lack AI tools—they’re struggling because most AI can’t act on the context that matters.” The company said the agent draws on 14 years of customer context and patterns from nearly 200,000 brands.
Composer is positioned as an AI marketing agent that can build a complete campaign from a plain‑language brief, including audience selection, email and SMS copy drafts, and send timing, with campaigns staged for approval instead of going live automatically. On the service side, Customer Agent is shifting from a prebuilt bot into a platform, with a Conversational Agent Builder, connectors, and open APIs so the agent can take actions in downstream systems instead of only answering questions. Klaviyo has cited performance signals such as 65% of questions resolved automatically and individual brands reaching high autonomous resolution rates within 90 days, showing that these agents already handle meaningful volumes of work. Composer public beta is available now, while additional Customer Agent functionality is scheduled to roll out throughout 2026, signaling that this shared‑context model will keep expanding across workflows.
Manago AI: Rebranding Around Insight-to-Execution Speed
Manago AI, formerly SALESmanago, is leaning hard into the agentic narrative, rebranding while adding AI agents and conversational workflows aimed at helping ecommerce marketing teams move from analysis to campaign execution faster. Where older marketing automation tools stop at dashboards and recommendations, Manago AI wants its agents to own the tedious middle: building audiences, drafting assets, and wiring journeys based on prompts and behavior data. The release centers on prompt‑based audience building, campaign creation, and automated actions, plus omnichannel engagement across email, SMS, WhatsApp, and web with real‑time product recommendations. This aligns with broader trends in AI marketing automation and workflow automation, where vendors are trying to compress campaign cycle time. With more than 2,000 brands and over €30 million in ARR, Manago AI is not an experimental side project; it is betting that agentic workflows will define competitiveness in a crowded marketing automation space.
The near‑term impact for ordinary users is less about replacing strategy and more about removing operational bottlenecks. Instead of analysts exporting segments, marketers briefing creative, and operations teams building flows, a single conversational interface can now span audience definition, asset generation, and automated next actions from customer behavior analysis. That translates into fewer handoffs between analytics, creative, and lifecycle execution and less manual work turning insights into live experiments. “Agentic” in this context is about moving beyond suggestions to execution: assembling segments, generating assets, launching flows, and optimizing based on performance signals at scale. For teams, the promise is faster iteration and more campaigns tested, without needing a large dedicated marketing operations function to wire everything together.
Kontent.ai’s Aiko: Agentic AI Jumps the App Fence
While CRM vendors focus on customer journeys, Kontent.ai is pushing agentic AI into content operations. On July 7 it introduced AI Connectors, linking its AI agent Aiko to enterprise systems including Asana, Atlassian, Notion and Peec AI. The zero‑code connectors let Aiko retrieve operational context, execute actions, and coordinate workflows from within the company’s Agentic CMS. Instead of content teams bouncing between project tools, issue trackers, and documentation, Aiko can pull tasks and priorities from connected apps, update statuses, notify reviewers, and advance tasks, all while users stay inside the CMS. The aim is clear: reduce context switching, eliminate manual coordination, and accelerate execution without adding new tools. More than 60 organizations already use these Agentic CMS capabilities, and AI Connectors are live in the product now, supported by an AI management system certification.
For everyday content leaders, that means less time herding stakeholders and more time deciding what should be published. Workflow automation here is not just triggers and rules; it is an AI agent that understands cross‑system context and can act on it. According to company officials, the vision is to help organizations operate content more effectively, not only create content faster, by enabling Aiko to understand context and coordinate work across systems so teams can scale content operations without scaling complexity. Agentic AI is pushing enterprise content operations past static automation toward systems that reason, adapt and act independently across platforms without constant human oversight. This year, the company accelerated its product cadence and underwent a leadership transition, a sign it is reorganizing around this agent‑first direction.
What Marketers Should Do Next: Govern the Agents, Not the Dashboards
Across Klaviyo, Manago AI, and Kontent.ai, a pattern is obvious: AI agents marketing automation is no longer about clever suggestions but about systems that act, across channels and tools, with limited human intervention. In CRM, the agent framing is a claim that the platform can take on execution tasks that used to require specialists—assembling creative variants, coordinating timing, and handling high‑volume service interactions—off a unified customer profile. In content operations, agents now reach into Asana, Atlassian, Notion and similar tools to coordinate workflows via zero‑code connectors. Marketing workflow automation is shifting from many point tools to integrated platforms where service, marketing, analytics, and content share the same underlying profile and context. Vendors are clearly trying to compress campaign cycle time, and that pressure will only grow.
The upside is obvious: fewer manual workflow steps, less context switching, and autonomous decision‑making driven by customer data rather than gut feel. The risk is equally clear: if data is messy or governance is weak, agents will turn weak signals into bad experiences and growth risk. The practical move for marketing leaders is to stop treating these platforms as tools and start treating them as semi‑autonomous team members that need clear roles, rules, and success metrics. Clean data, well‑defined guardrails, review processes, and accountability for agent‑launched campaigns are now strategic requirements, not operational hygiene. Those who get their governance in order will enjoy agentic CRM platforms that quietly run large parts of the customer journey. Those who do not will spend their time cleaning up after agents that did exactly what they were told—on imperfect data.
