Sprinklr adds industry-tuned AI agents and copilots to connect marketing and service

Sprinklr adds AI agents for marketing, service, and customer feedback

Sprinklr rolled out new agentic AI tools built to automate and connect marketing, customer service, and feedback loops. The focus: faster execution, less swivel-chair work, and shared context across teams.

What's available now

• Sprinklr AI Agents: a low-code builder to create task-focused agents for marketing and service workflows.
• Sprinklr Copilot: live agent assist for customer service with contextual guidance during calls and succinct summaries after.
• AI Customer Feedback Management: analysis for solicited surveys plus unsolicited inputs from channels like social, all in one place.

What's launching next

• CCaaS telephony: planned for November. The company says the platform is already supporting customers in 100+ countries and handling 2M+ calls per day, with broader rollout ahead. Learn more
• Workforce management (January): orchestration to coordinate handoffs between human agents and AI agents.
• Industry customizations: agent templates scoped for 18 verticals (banking, retail, telco, and more). Five arrive this week; the rest ship through January. Sprinklr's no-code design environment supports these out of the box.

Why service teams are ahead on AI

Customer service moved first because the foundations were already there, said Abhishek Priyam, vice president of product management at Sprinklr. Early bot deployments, strong performance metrics, and clear workflows made the shift straightforward.

"A lot of agentic workflows were built very early just by replacing NLP with generative AI; that acted as a foundation for speeding up customer support adoption," Priyam said. "That particular business function was already ahead - and people started to double down on AI."

Bridging marketing and service

Marketing and service often run blind to each other. Data sits in silos. Processes aren't digitized end to end. That creates misses: insights trapped in the contact center that never inform campaigns, or promotions launched without warning service teams.

Justin Robbins, founder of Metric Sherpa, has lived the fallout: "We had one [in a story] on the front page of USA Today that we didn't find out about until we picked up the paper in the break room and the phone started ringing."

Robbins sees potential if companies prepare. With defined processes and accessible data, AI agents can push proactive communications, reduce surprise spikes, and improve outcomes. The catch: "Think about it from the standpoint of a car, where most people struggle to just back out of the driveway. Now we've put them in a supercharged vehicle that can go zero to 200 in three seconds. It's just too much."

Context: Sprinklr's path into CX

Launched in 2009 as a social media management platform, Sprinklr has grown into broader CX with marketing workflows, email support, live chat, conversational commerce, and CCaaS. After releasing CCaaS in 2022, it landed a 40,000-agent deal with Deutsche Telekom, followed by leadership changes and a product overhaul.

How to put these tools to work

• Start with one high-value workflow: e.g., campaign content variants, post-call summaries, or survey analysis. Define success and a rollback plan.
• Connect your data: give agents access to product, order, CRM, campaign calendars, and knowledge bases. Map permissions and PII handling.
• Close the marketing-service loop: set alerts so promotions auto-notify the contact center with FAQs, expected volume, and response scripts.
• Operationalize feedback: route insights from surveys and social to campaign briefs, journey fixes, and product teams with owners and SLAs.
• Human + AI orchestration: define when AI handles, assists, or escalates; use the upcoming WFM tools to enforce rules.
• Train your people: short playbooks for prompts, verification, and exception handling. Track adoption and quality.

Metrics that matter

• Service: first contact resolution, average handle time, QA accuracy, deflection/containment, escalation rate, and cost per contact.
• Marketing: time to produce assets, test velocity, conversion lift, and attribution to agent-triggered outreach.
• Voice of customer: CSAT, NPS, sentiment by topic, issue detection-to-fix cycle time, and impact on churn or repeat purchase.

Risk checklist

• Hallucinations: ground responses in approved knowledge; log and audit outputs.
• Compliance and consent: respect opt-ins, sensitive data rules, and regional regulations.
• Bias and tone: review prompts and outputs for fairness and brand consistency.
• Over-automation: keep a clear human override and escalation path.

Timeline and event

Sprinklr previewed and released these features at its CXUnifiers user event in Nashville, Sept. 29-Oct. 1. Telephony is planned for November and workforce management in January, with industry agents rolling out between now and then.

Upskill your team

If you're building AI skills for marketing or support, consider structured training to speed adoption and reduce errors. See the AI Certification for Marketing Specialists for a practical path from pilot to scale.