Agentic AI has moved from experimental territory into mainstream CX operations, with organisations across sectors deploying autonomous agents to handle customer interactions at scale. The shift reflects a fundamental change in how support teams architect their workflows: rather than using AI as a supplementary tool within existing ticketing systems, teams are now building agent-first architectures where autonomous systems handle routing, resolution, and escalation decisions independently. This represents a departure from the traditional Zendesk or Freshdesk model where humans remain the primary decision-makers and AI assists at the margins. The implications are substantial—teams must now decide whether to retrofit agentic capabilities into legacy platforms or migrate to purpose-built solutions like ChatSpark's AI Operator or Salesforce Agentforce, each of which treats agent autonomy as a foundational design principle rather than an afterthought.
The business case has solidified considerably. Research shows 96% of organisations report that agentic AI deployments met or exceeded ROI expectations in 2026, signalling that the technology has moved beyond proof-of-concept phase into predictable value delivery. For CX leaders, this creates an urgent strategic question: what does this mean for teams already running Agentforce or similar platforms, and are they positioned to compete with purpose-built agentic layers, or will integration become the default path? The answer likely depends on vendor roadmaps and integration depth. Simultaneously, Salesforce's $3.6B acquisition strategy in this space signals that consolidation is underway—larger platforms are absorbing agentic capabilities rather than building them organically, which suggests smaller vendors and point solutions will either integrate or face margin pressure.
For support teams operationally, the transition demands clarity on governance and control. Agentic systems require different oversight models than traditional AI—teams need visibility into agent decision-making, clear escalation thresholds, and audit trails that satisfy compliance requirements. The question becomes not whether to deploy agentic AI, but how to govern it responsibly whilst maintaining the speed advantage that makes these systems valuable in the first place. Organisations that treat agentic deployment as a simple tool swap rather than an operational redesign will likely underperform those that rebuild their processes around autonomous decision-making from the ground up.
Transforming Customer Engagement With Agentic AI FTI Consulting
Transforming Customer Engagement With Agentic AI fticonsulting.com