Amplifying human talent in contact centers: How TELUS Digital scales AI adoption in CX

Customer experience (CX) management is at a turning point. Scaling AI adoption within contact centers has become essential to stay competitive in a market where CX leaders must learn from every customer interaction. According to Zendesk’s CXTrends26 report, 96% of high-maturity organizations claim that AI materially accelerates first-reply and full-resolution speed, whereas only 60% of low-maturity organizations say the same.

So, how do low-maturity enterprises take strides to become industry leaders? At a recent Tech It Out event by The WICT Network, Jamie Timm, TELUS Digital Global SVP of Service Delivery and Operations, shared proven strategies for implementing digital CX transformation at scale.

“The most successful companies aren't the ones that try and replace human intelligence with artificial intelligence,” she says. “They're the ones that enable their great people with that intelligence.”

At TELUS Digital, our goal isn’t to swap a person for a prompt; it’s to make our best talent indispensable by equipping them with the technology and knowledge to deliver exceptional experiences in the moments that matter most for your customers.

In this article, we’ll share the high-impact solutions and three-phase playbook for AI implementation in CX, highlighted at Tech It Out, that we’re using to support 80,000 contact center agents globally.

Find the truth about your customers in the contact center

There is perhaps no place more human than the contact center — the direct, real-time intersection of customer problems and team member resolutions. Customer requests can be complex and emotionally charged, and humans can interpret them with empathy in ways that AI cannot. The resulting goldmine of information — customer thoughts, frustration points and creative solutions from agents — is buried in phone calls, text interactions and agent notes, often siloed in ways that prevent enterprises from using those insights to properly train teams and make proactive interventions that can prevent churn.

While accessing all of this information and scaling this type of initiative is daunting, the opportunity is massive. TELUS Digital contact center agents and team leaders in places like Guatemala, India, Morocco and the Philippines became our source of truth for crafting a truly transformative AI adoption strategy. To drive results from this human-centric approach, we focused on three high-impact solutions:

• Fuel iX™ Agent Trainer: Enabling contact center teams with a platform extension that creates synthetic, realistic text and voice conversations for training purposes.
• Knowledge management: Addressing the common problem that poor knowledge access lengthens every call and increases agent training time and costs.
• Conversational intelligence: Ensuring agents have the customer data they need to personalize experiences.

The importance of high-value time

Implementing these human-led tools has enabled our team members to become more effective contact center agents and helped reshape how we measure success.

In our new reality, where AI chatbots resolve basic customer issues and the calls that reach human agents are the most complex, relying on average handle time as the core metric fails to capture the true value of modern human-led interactions. The objective should not be to shorten the conversation, but to optimize the time spent to drive meaningful outcomes. The focus on high-value time can lead to effective resolution, a better customer experience and new up-sell opportunities.

This strategy, which optimizes our internal service efficiency metrics alongside client-mandated KPIs, enabled us to scale with confidence using a rigorous three-phase rollout.

TELUS Digital’s three-phase playbook for AI adoption in CX

By treating our global team members as partners in the innovation process, we’ve prioritized human readiness at every step of the technological rollout.

Phase 1: Test and learn with agents

This first phase involved nearly 500 agents across three locations and helped us determine the best way to scale. We focused on two key aspects: the rollout of Agent Trainer and the development of focused AI copilots for team leads and agents.

By providing synthetic voice and text conversations that simulate real support interactions, Agent Trainer enabled our agents to build skills and confidence rehearsing difficult situations without the pressure of interacting with live customers. Ensuring agents felt supported and had access to on-demand, intelligent coaching helped address critical industry challenges of slow onboarding and high attrition rates.

Phase 2: Nurture AI influencers through change management

Expanding the rollout to 10,000 agents across six locations, we discovered that the team members who most frequently adopted AI tools were reliable core-tier performers. To bring adoption to life among our lowest and even highest performers, we implemented a strong change management program that used the ADKAR model (awareness, desire, knowledge, ability and reinforcement):

• Awareness and desire: We placed AI engineers on the contact center floor, who partnered with operations leaders for on-demand support. We identified peer “AI influencers” who created launch videos that showcased success stories and sparked interest in team use of AI.
• Knowledge and ability: We fostered a feeling of ownership and collaboration among team members by establishing regular interactions in which AI engineering teams implemented changes based on agent feedback. We found that this rapid iteration increased the likelihood of tool use.
• Reinforcement: We employed tactical strategies, including gamification, contests and rewards, to encourage the successful use of AI tools.

Phase 3: Scale human potential and embrace adaptability

We continue to gain insights from this current phase, which has extended AI enablement to our global network. While change management remains consistent, we are actively evolving solutions to reach and support all team members.

A key insight has been that creating too many niche AI solutions too quickly can be counterproductive for agents. By rethinking the architecture of these solutions and integrating engineering with CX operations, we’ve been able to accelerate the impact of AI implementation across all our contact centers, applying data from customer interactions to building new AI-powered agent tools.

Results: The human and business impact

By targeting specific operational pain points, results observed across our three-phase rollout confirm that a human-led AI approach can drive superior outcomes for employees, customers and the business itself.

Amplifying our global talent

With Agent Trainer accelerating contact center agent proficiency by up to 50%, our team members are more prepared than ever to exceed customer expectations. We have also seen AI implementation enhance team leadership bandwidth. In the case of TELUS, a leading Canadian telecom and parent company of TELUS Digital, our Agent Quality Insights tool, which uses AI to analyze interactions and identify skill gaps, improved coaching efficiency by 26%, enabling supervisors to manage more agents.

Enhancing the customer experience

For our clients' customers, these implementations have led to measurable improvements in first-call resolution, ensuring needs are met without unnecessary transfers or repeat calls. Along with a decrease in total call time, we have seen an overall improvement in the quality of interactions, contributing to higher customer satisfaction (CSAT). Our clients, outside TELUS, have benefited from AHT reductions of up to 17% without sacrificing quality, contributing to a +0.7 average CSAT uplift (e.g., 3.9 to 4.6, out of 5.0).

Driving sustainable business efficiency

With Agent Quality Insights providing 100% call and chat coverage, we have transformed contact centers into insights engines for our clients, from capturing product feedback to informing go-to-market language.

As we track cost savings from service efficiency, the business impact of this initiative is aligning with our broader enterprise AI transformation goals. Additionally, we have maintained a record of zero compliance incidents while scaling these solutions.

Recommendations for your digital CX transformation

We’ve seen for ourselves that scalable AI implementation is repeatable. To guide your approach, here are TELUS Digital’s six lessons Jamie Timm shared with the Tech It Out audience:

1. Start with human problems, not technology solutions. Don't "AI everything." Pick one area, one team or one process, and apply technology creatively to solve a business problem.
2. Go where the humans are. You cannot design impactful solutions from corporate headquarters. For us, our global delivery visits were game changers in helping us see problems and test solutions face-to-face.
3. Democratize innovation within secure boundaries. Build with security by design from the start. This allows you to scale quickly and focus on learning and adoption, giving team members the freedom to experiment without needing permission at every step.
4. Preserve human agency and decision-making. People want advice and suggestions from AI, but they must remain in control of complex decisions and relationships.
5. Balance innovation with control. Agree on principles early. This enables you to empower teams to utilize their creativity and move forward.
6. Don't wait for the perfect technology. Start with the technology that exists today and the great people who make your organization run.

Remember, the truth about your customers is already in your contact center, and as the customer experience transformation partner to the world’s most admired brands, TELUS Digital provides the technology and expertise to help your agents leverage it.

Connect with our experts to discover how we can design and deliver an end-to-end, AI-fueled experience tailored to your unique business needs.