AI Quotient (AIQ) in contact centers: What it is and how to raise it

Your contact center’s AI tools won’t deliver the success you’re looking for if your team doesn’t know how to use them. Given the money customer experience leaders are investing in AI, a failure to fully consider the human element could be costly. Just last year, a TELUS Digital survey found that 36% planned to allocate over $4 million to generative AI (GenAI), and there is no indication that investment has cooled.

Comparatively little is spent preparing for how humans will interact with AI technology. Forrester’s Budget Planning Guide 2026: Customer Experience revealed that only 32% of CX teams have the data literacy needed to use AI responsibly, while a survey of executives conducted by Information Services Group identified talent availability as the top barrier to implementing data and AI initiatives.

This results in a costly “deploy first, train later” pattern that risks tool abandonment, frustrated employees, wasted investment and a lack of discernment that could negatively affect customers.

To avoid this pattern, customer experience leaders must understand and raise their contact center’s AI Quotient (AIQ).

This article explains how AIQ impacts contact center AI success, how to assess and raise your team’s AIQ, and how partnering with high-AIQ teams can help you get the results you’re looking for more quickly.

Contact center AIQ influences whether agents use AI or abandon it

Research from MIT, Sun Yat-sen University, Guangdong University, and Tsinghua University defines AIQ as “a person’s ability to use AI to perform a wide variety of tasks.” Whereas IQ attempts to measure general cognitive abilities like reasoning and problem-solving, AIQ focuses on abilities relevant to artificial intelligence like crafting effective prompts and recognizing AI limitations. The researchers found that AIQ is distinct from IQ and technical skills, and, critically, can be improved through training.

To measure AIQ, the researchers had participants play chess with the assistance of AI tools against AI opponents of varying skill levels. This framework allowed them to isolate how effectively people could leverage AI support to improve their performance, a dynamic that mirrors how contact center agents are expected to work alongside AI tools to deliver better customer outcomes.

The chess tournaments revealed that amateur players using AI defeated grandmasters with more advanced AI — not because of better technology, but because of higher AIQ. World chess champion Garry Kasparov (who is very much a living, breathing human) observed that “weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.”

This goes to show that the AI tools you have access to won’t determine success. Your ability to use them does.

High-AIQ agents leverage AI to deliver better customer outcomes

To understand how the behavior of a high-AIQ agent differs from a low-AIQ agent, consider the following examples.

High-AIQ agent: A customer contacts support frustrated about a delayed shipment. The agent uses an AI copilot to quickly pull the customer’s order history, previous interactions and current shipping status. Next, they craft a prompt: “Generate a personalized apology email acknowledging the delay for a loyal customer with three years of purchase history, offering expedited shipping on their next order.” The AI generates a response, but the agent refines it — adding a specific reference to the customer’s favorite product category and adjusting the tone to match the customer’s communication style from previous chats. The interaction takes mere minutes, the customer responds positively to the personal touch and the risk of churn is mitigated.

Low-AIQ agent: A similar customer contacts support with a similar issue. The agent opens the AI tool, but isn’t sure how to phrase the prompt. They type in: “Write a sincere email about a shipping delay.” The sparse prompt garners a generic response from the agent-facing bot. It doesn’t mention the customer’s history or offer any sort of specific compensation. The agent sends it anyway because they didn’t spot any typos or outright errors. Subsequently, the customer replies asking why they weren’t offered a solution after being a loyal customer for several years. The agent is now faced with a decision, try again with AI or craft a response from scratch — either way, the support interaction is longer than it had to be.

“Deploy first, train later” can undermine AI ROI

Too often, organizations implement AI tools with fanfare, employees try them unsuccessfully two or three times and disinterest sets in. Facing pressure to provide customers with quick, correct and comprehensive responses, agents can’t afford to spend time tinkering with tools they haven’t been properly trained to leverage. According to a study from The Upwork Research Institute, 77% of employees said that AI tools have had an adverse effect on their workload and 47% of those who use AI report that they did “not know how to achieve the expected productivity gains.”

In contact centers, this abandonment pattern has measurable consequences. AI-powered knowledge bases go unused, forcing agents back to manual searches that increase handle time. Sentiment analysis tools get ignored, causing agents to miss escalation signals. AI-generated response suggestions sit idle while agents type from scratch, eliminating productivity gains. Beyond these abandonment costs, there’s the risk of AI errors going unchecked by low-AIQ agents. Before long, the business case that justified the AI investment disappears altogether.

Simultaneously, the stakes are only rising for CX leaders. As brands increasingly invest in CX AI, they are able to successfully deflect routine inquiries, which means agents can focus on emotionally charged complaints, technical escalations and high-value retention scenarios. These are exactly the situations where AI-assisted agents with high AIQ deliver the most value. Complex interactions require agents who know how best to leverage the AI tools at their disposal and when to add the human judgment that AI can’t provide.

Building high AIQ requires assessment and ongoing training systems

Raising your contact center’s AIQ requires a systematic approach that starts with understanding your current baseline.

Measure your team’s AIQ to identify training gaps

Before you can raise your contact center’s AIQ, you need to understand where your team stands today. Without baseline measurement, where and how to focus training is guesswork.

Fortunately, there are frameworks to help you establish such a baseline. Forrester’s AIQ Assessment, for example, evaluates four competencies: understanding of AI capabilities and limitations, soft skills like willingness to work with AI, hard skills like prompt engineering, and ethics and risk awareness. The assessment surveys both leaders and their employees, which can reveal significant disconnects between the two groups. In Forrester's research, 14% of leaders believed they’d provided AI training while their employees reported receiving none.

Organizations can also measure AIQ through performance-based evaluation — comparing how employees complete tasks with AI versus without — or through organizational indicators like data literacy levels, training infrastructure and adoption rates.

Build ongoing support systems to equip your CX talent

Raising AIQ requires treating AI adoption as organizational change, not just technology deployment. The most successful organizations build continuous learning environments where contact center agents develop AI skills through practice, peer support and real-world application.

A paper from Columbia University titled Beyond AI Training: How Social and Experiential Learning Shape AI Adoption in the Workplace suggests that social learning is an important component of AI training. The researchers found that 60% of professionals relied on social and peer learning as their primary method for learning AI tools, while formal training was no one’s preferred approach. In practice, this means short videos of agents solving actual customer problems, weekly tips highlighting team successes and communities of practice where techniques are shared. When agents see their peers using AI effectively to resolve complex issues or improve handle time, adoption can spread naturally. To facilitate this, create accessible support channels that provide real-time help, as catching agents at the moment they need assistance prevents the frustration that can lead to tool abandonment. Champions programs, where high-AIQ agents mentor others, can also be used to disseminate expertise across teams while reinforcing best practices.

Beyond training methods, successful AIQ development requires employee participation in the change process. On an episode of the TELUS Digital podcast,Questions for now, about the relationship between employee-facing technology and customer experience, Thomas Hollmann, clinical associate professor, department of marketing and executive director, Center for Services Leadership at Arizona State University, emphasized the importance of agent buy-in. “Always bring the employees on board. Have them participate in the change. Have it [be] something that happens with them and not to them.” This means communicating the goals and benefits of AI adoption clearly, celebrating early wins and continuously gathering feedback. Track usage metrics and your overall employee experience, as high engagement paired with positive sentiment indicates genuine AIQ development rather than mere compliance.

You’ll also want to think about the knowledge infrastructure that can sustain AIQ development. This includes clear guidance on when to use AI versus human judgment, easily accessible resources and regular reassessment to track progress and identify new training needs as AI capabilities evolve.

Hire for adaptability, not just experience

When hiring contact center agents, assess for traits that indicate high AIQ potential such as comfort with ambiguity, willingness to scrutinize information and demonstrated learning agility with other technologies. During interviews, present candidates with scenarios where AI provides a recommendation and ask how they’d evaluate it — high-AIQ candidates instinctively think about what the AI might have missed or how the response could be improved.

The challenge is that these candidates are scarce. As we’ve alluded to, many companies struggle to find AI-ready talent. And even when you find strong candidates, ramping them to full productivity on your specific AI tools, workflows and customer base takes time.

The AI skills scarcity is driving many organizations toward a third option: partnering with outsourcing providers who have high-AIQ teams at scale.

Access high-AIQ CX talent through TELUS Digital

TELUS Digital has already built what most organizations are struggling to create — contact center teams with high AIQ.

Our advantage is built on:

• Platform-agnostic expertise: Our contact center teams excel at using our proprietary tools, client-provided AI platforms and partner technologies. We train for AIQ fundamentals that will transfer across any system.
• Proven scale and results: Fuel iX™ is our award-winning generative AI engine that enables contact center teams to build copilots, automate workflows and enhance customer interactions. Teams across our global operations leverage its capabilities to deliver measurable results for our clients. By providing our team with a safe, governed sandbox to innovate, we have managed privacy risks while putting cutting-edge AI technology directly into our team members’ hands.
• Effective training crafted by top talent: Our AI researchers and engineers build the platforms and training methodologies that develop high-AIQ contact center teams. This expertise in building AI systems informs how we teach agents to use them effectively. In addition, our training programs incorporate gamification, contests, hackathons and peer sharing, ensuring agents develop practical AIQ skills.
• Humanity-in-the-loop principles: Our human-centered approach to AI ensures technology augments decision-making rather than replacing it. Teams are trained to remain accountable for outcomes, with clear protocols for when to trust, question or override AI recommendations.

Maximize your AI ROI with high-AIQ teams

The difference between AI success and AI abandonment might just come down to your team’s ability to use it effectively. Technology alone doesn’t drive results — human capability does.

Many organizations overlook the challenge of ensuring their contact center teams are equipped to leverage AI to its full potential. This creates a costly pattern where tools get deployed, tried unsuccessfully a few times and quietly abandoned.

Building high-AIQ contact center teams internally is possible, but it requires assessment infrastructure, continuous training systems and competing for talent in a market where qualified candidates are hard to come by. For organizations that need results quickly and sustainably, partnering with a provider who has already made these investments offers a logical alternative.

TELUS Digital combines deep AI expertise with contact center operations at scale, substantiated by awards in both domains. Our teams are trained to work effectively across multiple AI platforms, from our proprietary tools to your existing systems. Contact us to learn how high-AIQ teams can turn your AI investments into measurable results.