Only 35% Contact Centre Leadership Report Clear Long-term AI Strategy

On paper, readiness looks strong. Around 85% of CX leaders say their organisation is prepared to implement AI. That confidence narrows when measured against execution: only 34% feel fully prepared, while a significant share remains in testing or early-stage deployment.

Contact centres are entering a phase where ambition is no longer the challenge; execution is. Artificial intelligence (AI) has moved well beyond experimentation, and customer expectations continue to rise across every channel. Across Europe, organisations are investing heavily in AI, but the transition from pilots to scaled operations remains uneven.

The State of Contact Centres 2026 report from Puzzle is based on insights from 1,505 CX leaders across the United Kingdom, the Nordics, and the Netherlands, capturing an industry that is moving forward with intent but at uneven speeds. Organisations are investing, deploying, and testing AI, but the foundations required to scale it consistently are still evolving.

AI Readiness Is Widespread, But Maturity Varies

On paper, readiness looks strong. 85% of CX leaders say their organisation is prepared to implement AI. That confidence narrows when measured against execution. Only 34% feel fully prepared, while a significant share remains in testing or early-stage deployment.

Just 35% report having a clear long-term AI strategy, while another 32% remain in active testing, highlighting the gap between ambition and operational maturity.

The gap reflects operational readiness rather than resistance. Leaders consistently point to limited internal expertise, data privacy concerns, budget constraints, and the complexity of integrating AI into existing systems.

AI is moving into production environments, with 83% of leaders reporting that AI-powered self-service channels are now effective at resolving issues without agent involvement.

Many organisations understand the direction of travel, but fewer have the structure required to execute at scale. The focus is moving from experimentation toward more disciplined deployment and cross-functional alignment.

Tech Stack Complexity iIs Holding Progress Back

AI adoption is unfolding within increasingly complex technology environments. Most contact centres still rely on multiple providers, and only a small minority operate on a unified platform.

Contact centres now rely on an average of nearly four technology vendors, while only 3% operate on a single unified platform.

This fragmentation is extending beyond infrastructure into day-to-day operations.

Half of CX leaders (50%) report that multiple vendors increase maintenance costs, while 47% struggle with training teams across multiple tools.

Leaders report higher maintenance costs, inconsistent data, and the ongoing challenge of training teams across multiple tools. In many cases, it also slows workflows and limits visibility across operations.

This helps explain why 94% of CX leaders view consolidation as essential. As AI capabilities expand from analytics to real-time agent support, fragmented systems risk constraining impact rather than enabling it.

AI Is Starting to Deliver, But Expectations are Rising

Even with these challenges, progress is becoming visible.

Nearly half of CX leaders (49%) say enabling 24/7 support is a top AI priority, followed by improving customer experience (45%) and faster resolution times (39%).

“”I see conversational analytics as a key capability, because every customer interaction is a learning opportunity… we gain the ability to grasp how customers feel, not just what they say,”” says Søren Kristian Steffensen, Analytics Manager at DSB. 

Many organisations report that AI-powered self-service is already resolving customer queries without agent involvement, while others are seeing improvements in resolution time, productivity, and customer satisfaction.

Around 39% report faster resolution times, while 30% report improvements in productivity, cost per contact, and customer satisfaction.

What is changing is how AI is being positioned. It is no longer viewed only as an efficiency tool. Increasingly, it is being used to create consistency, support agents, and scale service delivery more effectively.

The shift extends beyond resolution toward understanding intent and sentiment within interactions.

Conversation Data is Becoming Central

Customer conversations are becoming one of the most valuable sources of operational insight.

With 78% of contact centres now using AI to analyse interactions, organisations are moving beyond static reporting towards a more dynamic, real-time understanding.

More advanced conversational intelligence tools are now used by 37% of organisations, enabling real-time analysis of sentiment and intent. Teams are using these insights to improve coaching, refine quality assurance, and make better decisions.

Instead of treating conversations as isolated transactions, they are being viewed as continuous feedback loops that shape how service is delivered.

Adoption, however, remains uneven. A significant share of organisations still lack this capability, creating a clear divide between those leveraging conversation intelligence and those still relying on traditional reporting.

Supporting Agents Is Becoming a Priority

While technology continues to evolve, the pressure on agents remains high.

Nearly half of CX leaders (46%) cite workload pressure as the biggest challenge facing agents, followed by emotional stress (34%) and repetitive tasks (31%). Increasingly complex interactions, rising expectations, and sustained workloads are redefining the role of the modern contact centre agent.

In response, AI is increasingly being positioned as a support layer rather than a replacement. Nearly nine in ten leaders (89%) believe AI will shorten training times and support ongoing development, while 91% say AI copilots and agent-assist tools will become essential within the next two years.