Three Requirements for Production-Ready AI Agent Assist Technology
- Fuel iX™ is TELUS Digital's proprietary enterprise AI platform and suite of products for clients to manage, monitor and maintain generative AI across the enterprise
- Fuel iX supports measurable contact center gains, including reduced average handle time (AHT) and improved sales conversion, along with higher CSAT and NPS, reduced After-Call Work, increased speed to proficiency and reduced team member attrition
Vancouver, BC, Aug. 20, 2026 (GLOBE NEWSWIRE) -- Enterprise contact centers are no longer debating whether AI agent assist technology belongs in live customer conversations and have now moved to making it scale. As AI agent assist trends in 2026 shift from pilot curiosity to production requirement, TELUS Digital, a global technology service provider in AI-powered customer experience (CX) and future-focused digital transformation, has outlined the operational requirements contact center leaders should evaluate when selecting an AI agent assist partner.
Erin Walker, Global VP, CX AI, Business & Delivery at TELUS Digital, says, "AI agent assist technology works in production when three things are right: the platform integrates natively with the CRM and knowledge base so agents have full customer context in a single view; the latency is low enough that recommendations and next best actions land in real time before the agent moves on; and the system captures which recommendations agents accept, ignore, or modify, aggregating those insights across all agents so the deployment keeps getting sharper at scale."
KEY FACTS
- TELUS received the first Privacy by Design certification (ISO 31700-1) for its GenAI-powered customer support chatbot, built on Fuel iX
- Three requirements determine production-ready AI agent assist technology: native CRM and knowledge base integration, real-time low-latency recommendations, and a continuous feedback loop that aggregates agent signals at scale
What AI agent assist technology actually does in a contact center
AI agent assist technology is a category of enterprise software that provides real-time guidance to human contact center agents during live customer interactions. The technology listens to or reads the conversation as it unfolds across voice, chat, or email channels and surfaces relevant information directly in the agent's workspace, without requiring the agent to search for it manually.
Separating enterprise-grade AI agent assist technology from consumer-grade copilots
Three operational realities determine whether AI agent assist technology performs at enterprise scale, and all of them live in the production environment.
| # | Requirement | In production | Without it |
| 1 | Context + next best action | CRM, knowledge base, order history, and entitlements in one view, with a recommended action. Does not solely rely on data. | Agent switches screens mid-call. Friction returns. Context without guidance leaves the decision burden on the agent. |
| 2 | Real-time latency | Recommendations land before the moment passes. Benchmarked under load, across different languages and integrations in scope. | Guidance arrives late and is ignored. Agents stop trusting the tool regardless of recommendation quality. |
| 3 | Continuous improvement | The system learns from what agents accept, ignore, and modify across every interaction. The model sharpens with real usage at scale. | Quality flatlines post-launch as business context shifts. |
What it takes to keep AI agent assist technology improving after go-live
Without a mechanism to capture which recommendations agents accept or modify, a deployment cannot learn from real usage, and quality can flatline after launch. A 2025 study tracking an enterprise AI assistant serving more than 30,000 employees found that performance degraded post-deployment as business context shifted and that a structured feedback loop reversed the decline, lifting routing accuracy to 96% and cutting latency by 70% within three months.
Two organizational requirements follow. The first is agent adoption: a feedback loop only generates a useful signal when agents use the tool consistently. This requires building the conditions for that, such as recognition tied to recommendation acceptance and onboarding that frames the tool as a career accelerant rather than an oversight mechanism. The second is ongoing engineering support. Dedicated engineers must monitor recommendation quality and retrain on emerging signals, or the deployment hits a ceiling it cannot raise on its own.
How AI agent assist improves contact center productivity
Buying decisions in this category can stall on feature comparisons when the harder variable is implementation. TELUS Digital approaches agent assist technology as an implementation and orchestration partner, working with enterprises to evaluate whether to build on the Fuel iX platform directly or integrate with the technology they already run. Fuel iX provides the foundational infrastructure for that work, spanning real-time agent assist technology, model orchestration, and enterprise-grade moderation and observability, resulting in measurable impact on the metrics that matter: reduced After-Call Work, lower average handle time, higher CSAT and NPS, and improved agent retention without increases in headcount or operational complexity.
Frequently Asked Questions
Question: How does AI agent assist technology work to help human agents reduce task burden?
Answer: The technology takes on the parts of an interaction where speed and accuracy matter most, such as surfacing customer history, retrieving knowledge base content, and generating next best actions so agents can focus their energy on the judgment calls and empathy that define a great customer experience.
Question: What does real-time AI guidance during a live customer call actually look like in practice?
Answer: Effective agent assist surfaces the relevant recommendation, account context, prior interaction history, and next-best action in the same view the agent is already working in without requiring a screen switch. TELUS Digital's Fuel iX™ Agent Assist is built to deliver guidance at the moment it is relevant during the live conversation.
Question: Why does AI agent assist technology stop improving after go-live even when it worked well in the pilot?
Answer: A feedback loop only produces a useful signal when two conditions hold: agents use the tool consistently enough to generate real usage data, and dedicated engineers are monitoring that data and retraining on emerging signals. Without agent adoption, there's no signal to learn from. Without ongoing engineering support, the signal exists, but nothing acts on it.
Citations
- Aaditya Shukla et al., "Adaptive Data Flywheel: Applying MAPE Control Loops to AI Agent Improvement," arXiv:2510.27051, October 2025; also published in the EACL 2026 industry track. https://arxiv.org/abs/2510.27051 (verified live, June 10, 2026).
About TELUS Digital
TELUS Digital crafts unique and enduring experiences for customers and employees and creates future-focused digital transformations that deliver value for our clients. We are the brand behind the brands. Our global team members are both passionate ambassadors of our clients’ products and services and technology experts resolute in our pursuit to elevate their end customer journeys, solve business challenges, mitigate risks, and drive continuous innovation. Our portfolio of end-to-end, integrated capabilities include customer experience management, digital solutions, such as cloud solutions, AI-fueled automation, front-end digital design and consulting services, AI & data solutions, including computer vision, and trust, safety and security services. Fuel iXTM is TELUS Digital’s proprietary platform and suite of products for clients to manage, monitor and maintain generative AI across the enterprise, offering both standardized AI capabilities and custom application development tools for creating tailored enterprise solutions.
Powered by purpose, TELUS Digital leverages technology, human ingenuity and compassion to serve customers and create inclusive, thriving communities in the regions where we operate around the world. Guided by our Humanity-in-the-Loop principles, we take a responsible approach to the transformational technologies we develop and deploy by proactively considering and addressing the broader impacts of our work. Learn more at: telusdigital.com.
