Redefining contact centers in the age of AI: What successful AI looks like in practice

Artificial intelligence (AI) is no longer a future consideration for contact centers – it is already reshaping how organizations deliver customer service, support agents and measure performance. Yet as businesses move from experimentation to implementation, the conversation is now shifting from whether or not to adopt AI toward how to do so responsibly and effectively.

At CX Network's May 2026 event All Access: Redefining Contact Centers in the Age of AI, leaders from financial services, retail, AI technology and customer experience explored what successful AI adoption looks like in practice.

Throughout the event, we heard one consistent message: the future of the contact center depends on balancing automation with human connection, particularly as organizations move beyond isolated AI pilots toward more strategic, outcome-led implementation.

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AI adoption is becoming more strategic and outcome-focused

Speakers repeatedly emphasized that businesses are no longer investing in AI simply because the technology exists. Instead, within the contact center, organizations are focusing on using AI to achieve specific operational and customer experience outcomes, such as reducing friction, improving coaching, increasing efficiency and delivering more personalized service.

In the event's opening panel discussion, Harry Clapham from Tangerine Bank explained that focusing on desired business outcomes, rather than individual AI features, has enabled the organization to unlock multiple use cases simultaneously, including sentiment analysis, call transcription and agent coaching.

Meanwhile, Ebrahim Hyder described how, after careful deployment of agent-facing tools, the company is now looking to introduce customer-facing generative AI capabilities as AI adoption continues to expand. The company is preparing to pilot "Mia," a brand-aligned AI assistant designed to reflect the tone and experience customers expect from a luxury retailer.

Both panelists confirmed that organizations are becoming more disciplined about AI governance, stakeholder alignment and return-on-investment expectations before scaling deployments.

Catch up with their session on CX+ 

Human agents remain central to customer experience

Another key finding was that human agents will always remain essential, particularly for emotionally sensitive or high-value interactions.    

Rather than using AI to replace agents outright, many organizations are redesigning the role of the contact center employee. AI is increasingly being utilized to handle repetitive, transactional enquiries, allowing human agents to focus more fully on conversations that require empathy, judgment, and relationship-building.

This hybrid human-AI model was mentioned several times throughout the event. Again and again, speakers highlighted that customers still expect emotional intelligence and reassurance in moments of stress or complexity, especially in sectors such as banking, retail and healthcare.

It was also acknowledged that, as AI takes on more routine tasks, organizations may need to rethink workforce development. Emotional intelligence, adaptability and coaching capabilities are likely to become increasingly valuable skills for customer service teams and leaders alike.

Governance, trust, and human oversight are essential

Another major takeaway was that trust remains one of the biggest factors determining whether AI initiatives succeed. Without clear governance structures and guardrails, businesses risk creating AI systems that are inaccurate, inconsistent or non-compliant.

For this reason, speakers stressed the importance of involving legal, compliance and information security teams early in the implementation process.

In his interview, Manav Kapoor from Amazon emphasized the importance of explainability and transparency, particularly in high-impact use cases such as fraud detection and trust management.

He advocated for a gradual "crawl, walk, run" approach to AI adoption, where organizations begin with smaller, lower-risk applications before expanding into more complex workflows. This staged approach allows businesses to refine feedback loops, build employee confidence and strengthen governance over time.

The event also highlighted that maintaining human oversight remains essential, particularly in areas where AI decisions may impact customer trust or financial outcomes.

Catch up with Manav Kapoor's session on CX+

Context-aware AI is emerging as a competitive differentiator

As customer expectations evolve, the ability for AI systems to understand context and deliver seamless interactions is becoming increasingly important.

Sasha Glatt from ElevenLabs outlined several characteristics of effective AI agents, including emotional awareness, memory, contextual understanding and multimodal capabilities.
According to Glatt, successful AI interactions are those where customers feel understood, heard and remembered – not simply processed efficiently.

This reflects a wider shift in customer experience strategy. Organizations are no longer competing solely on speed and cost reduction; they are increasingly competing on the quality and personalization of AI-enabled experiences.

The discussion also demonstrated how advances in generative AI and voice technology are lowering barriers to deployment. AI systems that once required extensive technical expertise can now be configured using prompts, templates and uploaded knowledge bases, enabling faster experimentation and iteration.

Catch up with Sasha Glatt's session on CX+ and find out more about conversational AI in the CX Network report, The news rules of conversational AI

AI Is transforming quality assurance and coaching

Operationally, one of the most significant impacts of AI may be in quality assurance and performance management.

Mike Ahnemann from SuccessKPI discussed how AI-powered analytics are enabling organizations to move beyond traditional sample-based quality assurance models.
Historically, most contact centers could only review a small percentage of calls due to time and cost constraints. AI is now making it possible to analyze customer interactions at scale, identifying sentiment trends, compliance risks, coaching opportunities and sales performance issues across significantly larger datasets.

The potential commercial impact is substantial. Ahnemann shared an example in which AI-driven coaching insights helped a shipping company improve upsell performance by 20 percent, revealing significant untapped revenue opportunities.

However, the session also reinforced that AI analytics are most effective when paired with human expertise. AI can identify patterns and insights, but human leaders are still required to interpret findings, coach employees and ensure systems remain aligned with business objectives.

Catch up with Mike Ahnemann's session on CX+

AI agents are becoming more integrated into existing ecosystems

The event also demonstrated how AI is increasingly being designed to work alongside (rather than replace) existing contact center systems and human agents.

In their session, Regal showcased how voice AI agents can integrate with existing platforms such as Five9 while supporting seamless handovers between automation and live agents.
This interoperability is becoming increasingly important as organizations seek to modernize customer service operations without completely rebuilding their technology stacks.

Regal's demonstrations also highlighted another emerging trend: customers may behave differently when interacting with AI. According to the company's analysis of hundreds of millions of calls, customers often provide more detailed information to AI agents early in conversations, helping organizations gather richer contextual data and resolve issues more efficiently.

Catch up with Regal's session on CX+

Conclusion: Contact centers are entering a new operating model

CX Network's All Access: Redefining Contact Centers in the Age of AI highlighted an industry moving rapidly from experimentation toward operational transformation.

The event demonstrated that AI is already delivering measurable value across customer service operations, from intelligent routing and automated quality assurance to voice AI and real-time agent support. However, it also reinforced that technology alone will not define success.

Organizations that achieve the greatest impact are likely to be those that approach AI strategically, embed governance early and maintain a clear focus on customer trust and human connection.

The emerging contact center model is not fully automated. Instead, it is increasingly collaborative: AI handling efficiency and scale, while human agents provide empathy, judgment and complex decision-making.

As customer expectations continue to evolve, the challenge for organizations will not simply be implementing AI, but designing experiences where automation and human interaction work together seamlessly.

Quick links 

• Key insights from All Access: AI revolution in CX and contact centers 
  
• AI and customer trust: Reflections from CCW 2026 Sydney
  
• What happened at All Access: The AI Revolution in CX
  
  

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