ISG's 2026 Contact Centers Buyers Guide, combined with live deployments from Telstra and workforce analysis from Cresta, reveals that contact center AI evaluation has fundamentally shifted from feature adoption to operational proof. ISG assessed 27 vendors across an 80/20 split favouring product experience—measuring not just AI and automation capability but also governance, integration, adaptability, and lifecycle ROI—signalling that buyers now demand evidence of platform readiness beyond demonstration rooms. Telstra's Agentforce deployment across 1,000+ agents handling refunds, eligibility validation, compliance, and record updates demonstrates this shift in practice: AI is moving into workflows that affect money, regulatory obligations, and customer records, where controlled action and accountability matter more than conversational speed. The question for enterprise teams already running Agentforce or similar agentic platforms is whether their governance and integration infrastructure can actually support this level of operational responsibility at scale, or whether they risk deploying AI into workflows without the oversight mechanisms ISG's framework now demands.
Cresta's 2026 CX Workforce Report complicates the automation narrative further. Only nine percent of customer conversations are fully AI-handled; 76% involve humans and AI working together, with 93% of leaders reporting that agent conversations are becoming more complex. Yet 81% of contact centers cite integration complexity as a barrier to AI adoption, and only seven percent report easily accessible conversation data across the business. This creates a paradox: AI is supposed to elevate human work and enable redeployment, but the infrastructure to support hybrid workflows remains fragmented. ScorebuddyCX's QA data sharpens the problem. Whilst nine in ten contact centers now use AI for quality evaluation, only 14% consistently review those scores, and trust gaps persist between managers (76% trust) and agents (57% trust). Critically, just 18% of coaching conversations are triggered by AI insight, and 15% of centres generate no coaching from AI analysis at all. The operating model risk is stark: automated insight without review discipline, coaching conversion, or accountability becomes noise rather than improvement.
For CX leaders, the implication is unambiguous. Adoption metrics no longer prove progress. The vendors and platforms that will win are those that can demonstrate integration depth, data accessibility, governance rigour, and measurable operating change—not just feature breadth. Teams should audit whether their current platform stack supports the full chain from AI action through human review, coaching, and behaviour change. The contact center AI test is no longer about what the technology can do in isolation; it is about whether the organisation can operationalise it safely, govern it responsibly, and convert insight into sustained performance improvement.
IT Now Calls the Contact Center AI Buying Shots: So What? CX Today
ISG, Telstra, Cresta, and ScorebuddyCX Expose AI’s Contact Center Test CX Today