Customer experience improvement remains a primary driver for artificial intelligence adoption, and agentic AI is now becoming the core operating layer for contact centers. At this year's Customer Contact Week (CCW), major vendors including Zoom, Salesforce, Dialpad, RingCentral, Talkdesk, and 8×8 made a series of announcements that signal a shift from simple chatbots to autonomous AI agents capable of perceiving, reasoning, and executing multi-step actions across systems.

Agentic AI refers to AI systems that can act independently to achieve goals, rather than just responding to prompts. In the contact center context, these agents can handle inbound and outbound interactions, escalate to humans with full context, and orchestrate workflows across CRM, ticketing, and communication platforms. The announcements at CCW highlight how deeply agentic AI is being embedded into CX platforms, and what that means for enterprise IT leaders responsible for customer experience.

Dialpad: Real-time Customer Intelligence with Gemini

Dialpad announced an integration with Google's Gemini Enterprise for Workspace, turning conversation data—transcripts, sentiment, and commitments—into a native data source inside Gmail, Docs, and Chat. Users can ask Gemini to summarize recent interactions, surface risks, or prepare for meetings using recent calls and emails. This addresses the reality that nearly 79% of opportunity data never reaches CRM systems, making the actual interaction history the source of truth for customer context. By ingesting Dialpad conversation data directly into the Gemini environment, latency is reduced and answer quality improves. This integration exemplifies the shift toward treating unstructured interaction streams as primary data.

Zoom: Agent Architect and Performance Suite

Zoom introduced Agent Architect, a tool that turns prompts into production-ready voice and digital virtual agents by integrating intent, data sources, and workflows. This eliminates the need for teams to handcraft interaction flows. The accompanying Agent Performance Suite simulates interactions pre-launch and monitors live metrics such as containment, resolution rates, and cost per interaction. This ties AI quality management to both human and virtual agents. Zoom also unveiled an enhanced customer context layer across its CX portfolio, outcome-based pricing, and multi-location deployment, enabling enterprises to build an AI service pattern once and localize it across regions.

RingCentral: Agentic AI Inside RingCX

RingCentral expanded its AIR Pro offering to embed native agentic AI into RingCX. AI agents can now handle inbound and outbound interactions, autonomous outreach triggered by events, and intelligent handoffs that carry full customer history into live conversations. A natural-language workflow builder lets operations teams design RingCX flows without code. New analytics aim to close the gap between AI experiments and measurable customer outcomes. RingCentral positions this as part of an AI-native strategy, backed by rising AI-driven annual recurring revenue and broader investments in workforce management and analytics.

Salesforce: WEM for Agentforce Contact Center

Salesforce, a relatively recent entrant in the contact center space, announced Agentforce Workforce Engagement Management (WEM). This brings AI performance, human-agent metrics, and workforce management into a single view within the Service Command Center. Leaders can forecast demand, schedule both human and AI agents, and monitor adherence and quality from one console. Native coaching tools tie evaluations to outcomes such as CSAT and revenue. Because WEM is built directly on the Salesforce stack, it runs on the same data and workflows as CRM and digital channels, reducing integration overhead with third-party CCaaS providers. Although Salesforce has been in the contact center space for less than a year, the company is expected to close feature gaps quickly given its deep understanding of customer interactions.

Talkdesk: Agent Builder and CXA Vision

Talkdesk's Agent Builder is part of its broader Customer Experience Automation (CXA) strategy, which proposes a unified system of autonomous AI agents that orchestrate service experiences across channels and backend systems. CXA and its builder tools are positioned as a new category centered on multi-agent orchestration and low-code customization. The goal is to enable enterprises to design AI agents and automation flows that span the full CX lifecycle rather than siloed bots at the edge. This extends agentic AI into channels like email and across business workflows, making AI agents a holistic part of customer service.

8×8: AI Routing and AI Studio

8×8 released AI routing and AI Studio, adding another dimension to agentic CX. AI Studio provides a native environment where teams can describe the agents they need in natural language and deploy them across voice and digital channels on 8×8's existing infrastructure. These AI agents deliver always-on inbound coverage—handling intake, identity verification, call routing, and multi-location reception—and can also drive proactive outbound engagement, sales qualification, and internal support use cases. Under the hood, 8×8's intelligent call routing uses real-time analytics and customer profiling to match callers to the most qualified agent, improving efficiency and personalization compared with traditional rule-based routing.

What This Means for AI in CX

Collectively, these announcements confirm that the contact center market is shifting from static chatbots to agentic systems. Zoom's Agent Architect, RingCentral's AI agents, Talkdesk's CXA, Dialpad's Gemini integration, and 8×8's AI Studio all assume AI will be a durable part of the workforce and not an add-on. The emphasis on autonomous outreach, multi-step workflows, and multi-agent orchestration reflects a move toward large action models that can drive end-to-end outcomes rather than individual tasks.

Another key shift is the treatment of AI as part of workforce management. Salesforce's WEM and Zoom's Performance Suite illustrate that AI is being managed like labor. Supervisors expect to see AI utilization, quality scores, and adherence alongside human metrics, and to forecast staffing requirements across both human and digital resources. That changes how IT and operations approach capacity planning, service-level management, and optimization—AI becomes a schedulable, coachable resource, not just infrastructure.

Dialpad's approach underscores a third shift: data gravity is moving toward interactions. By making transcripts and interaction histories queryable via Gemini and Workspace, Dialpad is shifting data gravity from static CRM records to dynamic, unstructured interaction streams. This aligns with Zoom's customer context layer and RingCentral's intelligent handoffs, both of which rely on persistent memory of past interactions to avoid start-from-scratch experiences.

These moves also deepen the platform debate. Salesforce is betting that WEM plus Agentforce Contact Center atop CRM is the right nerve center for CX. Zoom, RingCentral, Talkdesk, 8×8, and Dialpad advocate their own unified CX fabrics built around contact center and communications data. For enterprises, this raises questions about where to anchor AI governance and observability: in CRM, CCaaS, UCaaS, or a combination. The winners will likely be those who can offer clean integration patterns and shared context across these layers.

Guidance for CX-Focused IT Professionals

Treat AI agents as products, not features. Most of these announcements emphasize faster agent buildout—prompt-based creation in Zoom and 8×8 AI Studio, and low-code flows in RingCX and Talkdesk. As an IT leader, you need product-management discipline for AI agents: clear ownership, versioning, and lifecycle management. Define success metrics beyond containment; tie each agent to business KPIs such as NPS, first-contact resolution, and revenue impact, and use suites like Zoom's Performance Suite, Salesforce WEM, and 8×8's analytics to iterate.

Align AI governance with your data backbone. Dialpad's integration with Gemini Enterprise and 8×8's intelligent routing underscore that the value of AI is constrained by data access and governance. Before scaling agentic AI, clarify where your source of truth resides—CRM, ticketing, or conversation intelligence—and ensure your chosen CX platforms can ingest and act on that data under appropriate controls. This includes policies for transcript retention, PII handling, model access, and audit trails across Zoom, RingCX, Talkdesk CXA, 8×8 AI Studio, and Gemini-based workflows.

Design for a hybrid workforce by default. The future of service is a hybrid workforce of humans and AI agents. All vendors have focused on AI-to-human handoffs with shared context and common quality frameworks. Build your routing, WFM, and quality programs around that reality. That means routing policies that consider both AI and human capacity, skills, and risk thresholds; quality scorecards that evaluate interactions holistically regardless of which worker started or finished the engagement; and coaching workflows that leverage interaction data to up-level both human agents and AI policies.

Prioritize explainability and observability. Agentic AI introduces multi-step actions across systems, increasing operational risk when you cannot see what is happening. Favor platforms that offer real-time dashboards with drill-down into AI and human performance, simulation environments to test agents before they reach production, and clear logs of AI decisions for risk and compliance teams to review. Bake those requirements into RFPs and architectural standards, as black-box agents will not survive enterprise scrutiny.

Build a CX AI reference architecture. Given the breadth of innovation, CX teams need a reference architecture that defines the system of record for customer data, the system of engagement for interactions, and the system of insight/action for AI. Map which vendor plays which role, how you will integrate them, and how identity and context flow across the stack. Then resist the urge to agentify everything; identify a few high-impact journeys with clear pain points, apply these tools to design hybrid workflows, prove value, and expand from there.

Start with a few high-value journeys. Vendors offer accelerators, prompt-based agent creation, no-code builders, and low-friction integrations, but your organization still needs a disciplined rollout. Identify two or three customer journeys with clear pain points and measurable upside (e.g., returns, appointment scheduling, technical troubleshooting), then use these tools to design agents and hybrid workflows for those use cases first. Iterate, prove value, and expand from there.

Source: TechRepublic News