Agentic AI Will End Channel-Based Marketing by 2028
By 2028, 60% of brands will use agentic AI to run direct, one-to-one customer interactions, based on new insights from Gartner. This shift moves teams away from managing separate channels and toward connected systems that work across marketing, sales, and support.
"This marks the end of channel-based marketing as we know it," said Emily Weiss, senior principal researcher in the Gartner Marketing practice.
What It Means for Marketing and Support Leaders
- Unify customer data. Clean IDs, consistent consent, and shared profiles across teams. If your CDP or CRM is fragmented, fix that first.
- Map cross-touchpoint journeys. Identify where handoffs break-ad click to site visit, chat to ticket, email to rep-and close those gaps.
- Add agentic AI to your current stack. Start with narrow, high-impact flows (quote follow-ups, cart recovery, appointment scheduling, tier-1 support) and expand with clear guardrails.
- Make personalization compliant. Enforce consent, PII minimization, and audit trails. Treat model outputs like any other regulated asset.
Service Is Next: 80% of Issues Handled by AI by 2029
Gartner expects agentic AI to handle 80% of service issues by 2029. That means faster resolutions, fewer queues, and agents focused on complex or sensitive cases.
The practical move now: build blended workflows. Let AI handle intake, triage, and resolution where confidence is high, with seamless escalation to human agents when needed.
Trust Becomes the KPI in Influencer Marketing
By 2027, brands will spend half of their influencer budgets on content quality and creator authenticity-identity checks, content provenance, and safeguards against manipulated media. The goal is simple: protect customer trust as AI content floods search and social.
In a Gartner Consumer Community survey of 335 US consumers (Oct-Nov 2025), 78% said clearly labeling AI-generated content is "very important" or "the most important factor" in keeping their trust.
"Trust is now the most valuable asset in influencer marketing," Weiss said. "Brands should adopt clear labeling conventions, invest in third-party verification tools, and monitor creator engagement quality to ensure transparency and compliance as AI-generated content becomes mainstream."
90-Day Action Plan
- Audit journeys. Pick three core journeys (acquire, onboard, retain). Document steps, drop-off points, and handoffs.
- Data readiness. Standardize IDs, fix consent capture, and define what data each agent can access.
- Pilot one agentic workflow. Example: abandoned cart recovery that can answer objections, offer alternatives, and book demos-then hand off to a rep if needed.
- Define human-in-the-loop. Set confidence thresholds, escalation rules, and who approves sensitive responses.
- Set the right KPIs. Conversation ROI, time to resolution, conversion rate lift, CSAT/NPS impact, and labeled vs. unlabeled content performance.
- Label AI content. Publish a clear policy and stick to it across web, email, social, and creator work.
- Vet creators. Verify identity, require provenance signals, and monitor engagement quality over vanity metrics.
Tech and Ops You'll Need
- Connected data layer. A CDP or equivalent with events, profiles, and consent unified across marketing, sales, and support.
- Orchestration. Tools that coordinate AI agents across channels and systems without breaking compliance.
- Governance. Prompt libraries, response policies, red-teaming, and audit logs for every agent decision.
- Training and enablement. Upskill teams to design conversations, review AI outputs, and measure business impact.
Helpful Resources
- Gartner: AI insights and research
- C2PA: Content provenance standards
- Practical AI workflows for marketing teams (Certification)
Bottom Line
Channel-first playbooks are fading. Teams that move to agentic, data-connected experiences-and treat trust as a core metric-will set the pace. Start small, ship fast, and build the governance muscle now while the stakes are still manageable.
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