This Location Watch was prepared with insights from Lee Cahalane of SupportNinja and Dr. Louis Siebrits of Resolv Global alongside broader industry research and market data on Colombia’s BPO and CX landscape. These perspectives highlight why Colombia is increasingly recognised as a leading destination for North American and European markets, and how its outsourcing ecosystem continues to evolve in both scale and sophistication.

Colombia CX and BPO Outlook – 2026

Colombia has firmly established itself as a high-performing outsourcing destination, combining bilingual talent, cultural alignment, and a rapidly maturing CX ecosystem. Once viewed primarily as a cost-saving alternative, Colombia is now recognised as a strategic delivery hub offering both scale and sophistication. The country has also remained relatively insulated from broader regional geopolitical tensions and is steadily overcoming outdated perceptions of political and social instability.

The country’s growth is underpinned by strong export performance, a large and skilled workforce, and increasing global confidence in its outsourcing sector. With BPO contributing significantly to employment and economic output, Colombia continues to attract investment while expanding into higher-value services.

Talent, Language and Service Culture

One of Colombia’s most distinctive advantages is its bilingual workforce, particularly in English, Spanish, and Portuguese. Beyond fluency, Colombian Spanish is widely regarded as neutral and clear, making it ideal for pan-regional support across the US Hispanic market and Latin America.

Agents are often trained in global communication standards, enabling more natural and empathetic interactions that go beyond scripted responses. This service-first mindset is a key differentiator, especially as organisations seek to balance automation with human experience.

However, competition for highly proficient English speakers is increasing, making talent retention and development an important consideration for employers.

Strategic Location and Market Alignment

Colombia’s geographic position offers strong alignment with North American operations, with overlapping time zones enabling real-time collaboration and support. This removes many of the operational challenges associated with traditional offshore models.

For European organisations, Colombia also plays a valuable role as an extension of service coverage. It enables high-quality English and Spanish support into afternoon and evening hours, effectively supporting follow-the-sun models while maintaining operational control and service consistency.

Infrastructure, Scalability and Delivery Capability

Major cities such as Bogotá, Medellín, and Barranquilla provide modern infrastructure, strong connectivity, and secure operating environments aligned with international standards. These urban centres are supported by a broader network of emerging tier-two cities, helping providers scale efficiently while managing costs.

Local governments in these regions are also actively supporting the growth of the BPO sector through initiatives such as “English for Work” programmes and targeted tax incentives.

Colombia’s large population — the third largest in Latin America — further supports workforce scalability. This enables organisations to expand operations or adjust capacity in line with demand, an increasingly important requirement in today’s dynamic CX landscape.

Cost Efficiency and Operational Stability

Colombia remains cost-competitive compared to North America while offering greater operational stability than some traditional offshore markets. Lower wage structures are balanced by relatively healthy retention rates, supporting continuity and service quality.

This combination of cost efficiency and workforce stability makes Colombia particularly attractive for long-term CX programmes rather than short-term labour arbitrage.

Technology and Evolving Service Models

The Colombian BPO sector is actively embracing advanced technologies, including AI-assisted workflows, CRM platforms, and omnichannel support capabilities. Providers are increasingly equipped to manage voice, chat, email, and social interactions within integrated delivery models.

At the same time, the market is evolving beyond traditional BPO into Knowledge Process Outsourcing (KPO). Services now extend into areas such as technical support, digital marketing, finance, legal process outsourcing, software development, and R&D — reflecting a broader shift toward higher-value, knowledge-driven work.

Sector Coverage and Investment Momentum

Colombia supports a wide range of industries, including fintech, healthcare, retail, and technology. Its combination of sector expertise and scalable delivery models makes it suitable for both specialised and high-volume operations.

Global brands have increasingly chosen Colombia as a delivery hub. For example, Amazon and HubSpot operate significant technology and e-commerce teams in Bogotá, while retail brands such as Starbucks, Victoria’s Secret, Gap, Forever 21, Lacoste, and Versace utilise the country for customer support operations. Hospitality provider Marriott International and financial institutions including Bank of America and J.P. Morgan also maintain local operations supporting both back-office and technical functions.

In addition, tech and digital-first companies including AngelList, Modern Health, and Hired are leveraging Colombia for nearshore engineering and product teams. This trend highlights the country’s transition from a cost-focused BPO destination to a strategic hub for premium bilingual talent, particularly in Bogotá and Medellín.

What Clients Should Consider

While Colombia offers a compelling value proposition, there are several factors organisations should evaluate:

• Language quality can vary between providers, making thorough vetting essential
• Long-term success depends on strong operational alignment and governance
• Pricing models are evolving, with increasing adoption of outcome-based structures and AI-enabled efficiencies
• Talent competition, particularly for bilingual roles, may influence future hiring strategies

Bottom Line

Colombia has evolved into a powerhouse for CX and BPO. Its combination of linguistic strength, cultural alignment, scalable talent, and growing technical capability positions it as far more than a cost-saving option.

For organisations seeking resilient, high-quality, and scalable customer experience delivery, Colombia offers a well-balanced and future-ready solution. As global CX strategies continue to prioritise responsiveness, continuity, and value, Colombia’s role within outsourcing portfolios is set to expand further.

AI has amplified all of this. What was already a complex technology landscape is now louder, faster, more confident in its promises and far less easy to rationally assess. 

The result is a familiar pattern. Reams of content. Lots of conversations. Plenty of demos. Very few decisions. 

“The problem isn’t a lack of technology. It’s a lack of confidence about where to start.”

Too much choice, not enough direction

Most contact centre leaders are exposed to hundreds of tools, platforms and propositions. CCaaS, Automation, AI, Analytics, Workforce optimisation, Knowledge, Quality, Speech, Sentiment, and/or Real-time coaching. 

Each promises transformation, yet few explain sequencing or iterative value. 

Technology discussions often jump straight to an end state. Fully automated journeys. AI-first contact centres. Single platforms doing everything. The reality is that most organisations are not starting from a clean slate. They are operating with legacy systems, ingrained processes and teams who are already stretched. 

When leaders are presented with change at scale, hesitation is a rational response. 

“Indecision is rarely caused by resistance to change. It’s caused by unclear risk.”

One ecosystem, many perspectives 

One of the most common mistakes we see is treating contact centre technology as a single audience decision. In reality, it is experienced very differently depending on where you sit. 

Customers experience outcomes – Resolution, speed, effort. 

Agents experience tools – Screens, prompts, workflows, knowledge. 

Team Leaders experience data – Performance metrics, quality scores, coaching demands. 

Executives experience cost, compliance, risk and return. 

Technology fails when these perspectives are treated in isolation. A tool that improves reporting but makes life harder for agents will not deliver sustainable value. Automation that reduces contacts, but damages trust will quickly be rolled back. 

“Technology only works when data flows through the organisation, not when it stops at functional boundaries.” 

Why replacing everything may not always work

There is a temptation to believe that the answer is replacement. New platform. New vendor. Clean start. 

Sometimes that is necessary. Often it is not. Make sure you have clarity as to what you need to achieve and the capability of the solution you are looking at as large-scale CCaaS or platform replacement is expensive, disruptive and can be slow. It introduces delivery risk at exactly the moment many organisations are under pressure to stabilise performance. It also assumes that the underlying processes are already fit for automation, which is rarely the case. 

Some organisations have truly exhausted their tech ecosystem’s capabilities and potential.  

But many organisations do not need everything at once, they need progress. 

That is why we increasingly see value created through targeted, point-solution adoption. Technology that does one job well and (crucially) integrates into the existing environment.

“Momentum is more valuable than perfection.” 

Starting where impact is visible 

One of the most effective starting points we see for technology change is quality management. 

Historically, quality assurance has been constrained by sampling. A handful of interactions reviewed each month, representing a fraction of actual customer conversations. Coaching is based on partial insight. Risk is often identified after the event. 

Automation changes that dynamic. Moving from fractional sampling to full visibility unlocks far more than compliance. It enables better coaching, faster identification of issues, clearer insight into customer sentiment and more consistent experiences. 

Importantly, this type of AI does not remove people from the process. It supports them. 

• Agents receive clearer feedback. 

• Team leaders focus on coaching rather than administration. 

• Leaders gain confidence in what is happening across the operation

“AI delivers value fastest when it helps people do their jobs better, not when it tries to replace them.” 

What good looks like now 

The most effective contact centre leaders we work with are not chasing the biggest transformation story.

They are making deliberate choices.
They prioritise problems before platforms.
They sequence change rather than attempting to do everything at once.
They invest in technology that supports people and process, not just cost reduction.
They accept that doing nothing is still a decision, and often the riskiest one. 

Technology will continue to evolve. AI will become more capable. Customer expectations will continue to rise. The organisations that succeed will be those that move with intent rather than waiting for certainty. 

“The most effective contact centres are not the most automated. They are the most deliberate.”

The second half of 2025 saw a sharp acceleration in conversations about AI. While AI dominated the conversation at our roundtable, one theme cut through consistently: a growing disconnect between business ambition, technological momentum and the real needs of customers. 

Boards are often pushing for rapid returns or exercising extreme caution. Technology vendors are promising transformation. Yet CX metrics still struggle to reward loyalty and long-term value, leaving CX leaders to reconcile competing pressures with limited levers. 

Against this backdrop of uneven readiness for next-generation CX, we also heard clear examples of organisations making progress. Those succeeding are addressing these tensions through stronger governance, better-aligned metrics and more collaborative partner models. 

This paper draws directly on those discussions to surface the CX challenges that matter most in 2026 and beyond, and to share practical experience on how to address them. 

When AI holds up a mirror to CX

AI is revealing the true state of customer experience. Where journeys are well designed, data is connected and governance is clear, automation delivers value. Where those foundations are weak, AI simply scales existing problems faster. 

Leaders shared examples of blanket automation strategies being rolled back, CX teams managing downstream fallout from decisions they did not own, and metrics that reward efficiency while quietly destroying long-term value. At the same time, we also heard from organisations getting it right, moving quickly but thoughtfully through clear ownership, outcome-based metrics and strong change management. 

Why alignment now matters more than ever

As CX becomes increasingly hybrid, with human and AI blended across journeys, legacy thinking starts to break down. Traditional operational metrics struggle to explain value. Governance models lag behind technology. Cyber and data risks grow quietly in the background. And CX leaders are often held accountable without the authority to influence decisions upstream. 

The organisations that will win in the next phase of CX are those that: 

• Put strategy and use cases before technology 

• Treat CX as a value multiplier, not just a cost centre 

• Align boards, technology, CX and partners around shared outcomes 

• Build solid data and security foundations before scaling AI 

• Measure what truly matters to customers and the business 

From fast adoption to sustainable advantage

This whitepaper explores the real decision gaps holding organisations back and offers practical guidance on how to close them. Drawing directly from practitioner insight, it covers governance, metrics, partner models, change management and cyber security, alongside seven practical steps CX leaders can take now. 

Transformation is not optional. But speed alone is not success. The real inflection point is whether organisations can align people, metrics and leadership quickly enough to make AI work for customers and commercial outcomes alike. 

The whitepaper is free to download and available below. 

We would love to continue the conversation. Follow us on LinkedIn and share your experiences.

Much of the conversation about the future of customer contact is dominated by technology.
AI. Automation. Analytics. Bots. Faster. Cheaper. Smarter.

Yet when we step back and look honestly at where organisations are struggling, the challenge is rarely technology-first. It is people-first.

Most businesses already know what needs to change. The harder truth is that knowing does not reliably translate into doing. Strategy decks are written, tools are procured, pilots are launched – and still the outcomes lag behind ambition.

That execution gap sits squarely in the people layer.

The Gap Between Knowing and Doing

Across sectors, the pattern is remarkably consistent. Leaders understand that customer expectations are rising, that work is becoming more complex, and that traditional operating models are under strain. Teams on the ground feel it every day.

And yet progress often stalls.

This is not because organisations lack capability or intent. It is because many are still trying to solve today’s problems with yesterday’s assumptions. Training models remain largely ‘one and done’. Roles have evolved faster than the support structures around them. Managers are asked to lead a more complex, emotionally demanding workforce while being measured on metrics designed for a simpler world.

Holding the line on those legacy measures creates lagging outcomes – first for employees, and then inevitably for customers.

Future Fit organisations recognise that execution failure is rarely a technology issue. It is a people issue, reinforced by culture, incentives, and leadership capability.

The Agent Role Has Already Changed

The frontline role in customer contact is no longer primarily transactional.

Routine interactions are increasingly handled through automation, self-service, or deflection. What remains with humans is more demanding:

• Edge cases that fall outside standard rules
• Emotionally charged conversations
• Complex judgement calls
• Moments where reassurance, interpretation and empathy matter most

Yet many organisations are still hiring, training and measuring agents as if the job has not fundamentally changed.

Future Fit thinking starts with a simple acknowledgement:
the agents we need now – and in the future – are different.

They need stronger judgement, emotional intelligence, and confidence navigating ambiguity. They also carry a higher emotional load, often in remote or hybrid environments where informal support and loyalty are harder to build.

If we do not redesign roles, support, and leadership around this reality, burnout becomes structural rather than incidental.

AI’s Role: Reducing Friction, Not Replacing Humans

In a Future Fit model, AI is not the solution. It give the power to unlock it.

Used well, AI should make work more human, not less. That means:

• Removing friction from the agent day
• Reducing cognitive load
• Surfacing the right knowledge at the right moment
• Guiding decisions without dictating them
• Supporting judgement rather than automating it away

This requires intentional design. Clear purpose for each use case. Strong guardrails around how data and insight are used. Ongoing development rather than ‘set and forget’.

Crucially, it also requires honesty with employees. When AI is positioned as something being done to people, resistance is inevitable. When it is designed and communicated as something done for them, adoption follows. Ideally, it should be co-created with employees – let them see their fingerprints all over the final solution.

Future Fit organisations understand that AI does not remove responsibility from leaders. It increases it.

Metrics will set the mindset of employees – they send the message about what matters most. And these mindsets shape behaviour.

Culture Follows Metrics

One of the most common failure points in transformation is misalignment.

Technology changes. Roles change. Customer expectations change.
But metrics stay the same and still the investment in people lags.

Future Fit organisations are ruthless about asking:

• Do our measures reflect the work we actually want people to do?
• Are managers incentivised to enable value, or simply control volume?
• Are we measuring activity, or outcomes?

As technology takes care of the repeatable, human value becomes the differentiator. That demands new definitions of productivity, stronger coaching capability, and leadership that understands how to create space for quality, not just speed.

Culture does not shift through slogans. It shifts through what is rewarded, tolerated, and prioritised.

From Transformation Programmes to Continuous Evolution

There is no finish line.

Future Fit organisations do not treat change as a programme with an end date.

They treat it as ongoing evolution:

• Continuous improvement rather than big-bang transformation
• Listening deeply to employees as well as customers
• Taking analytics upstream to fix root causes, not mask symptoms
• Investing in leadership capability alongside platforms and tooling

They also recognise a hard truth: AI can paper over cracks — or expose them. The difference lies in whether organisations are willing to look honestly at how work is really done.

The Question That Really Matters

Future Fit is not about asking, “What technology should we buy?”

It is about asking:

• Why do customers come to us?
• Why do they stay?
• What do our people need to deliver on that promise – today and tomorrow?

Get the people element right, and process and technology fall into place.

Get it wrong, and no amount of AI will save you.

This Location Watch report draws on insights from Ryan Strategic Advisory’s May 2025 CX Technology and Global Services Survey (Peter Ryan, 2025) and ArvatoConnect’s Onshore-Offshore: Why the CX Value Equation is Changing (James Towner, 2025). As well as CCP’s relationship with scores of UK outsourcing decision makers and over 240 global BPOs.

The Rise of Offshoring

Since the 1990s, offshoring has become a dominant trend in business process outsourcing. Companies initially turned to India for its low labour costs, English proficiency, and large talent pool. In the 2000s, India was joined by the Philippines as another low-cost hub, particularly suitable for customer service and voice-based operations, leveraging its Western (especially US) cultural alignment. More recently, South Africa has gained attention for its quality, favourable time zones, and relatively lower cost base compared with Europe, providing a viable alternative for UK and European clients.

Yet, despite the global rise of offshore destinations, the UK has maintained its position as a key outsourcing market, valued not for cost alone but for quality, governance, and operational reliability. Its mature infrastructure, strong compliance standards, and professional capability continue to make the UK a premium outsourcing environment, where strategic partnerships prioritise service excellence and trust over purely economic considerations.

Value-Driven Outsourcing Partnerships

In 2025, UK enterprises show a clear preference for value-driven outsourcing partnerships that combine advanced technology capabilities with proven operational excellence. Ryan Strategic Advisory’s May 2025 CX Technology and Global Services survey found that AI proficiency, know-the-customer analytics, and competitive pricing are now the top three competitive differentiators for BPO providers. UK buyers emphasised the importance of strong client references and sector-specific expertise, underscoring the country’s preference for relationship-based, high-governance engagements.

Budget Stagnation and Operational Challenges

A notable trend emerging in the UK market is budgetary stagnation. Over 60% of UK CX leaders indicated that their 2025 budgets will remain flat or decline. This is accompanied by concerns over agent attrition and declining service levels, particularly in voice and digital delivery channels. As a result, many UK enterprises are reassessing delivery models, prioritising investment in AI, automation, and analytics to improve productivity without sacrificing quality. The consequence is a heightened focus on “cost-neutral transformation”, shifting spend from headcount to enabling technologies without increasing overall CX budgets.

Research also highlights that poor AI rollouts can alienate agents: 26% of UK contact centre staff are considering leaving due to unclear AI integration strategies, emphasising the need for transparent change management and training (ArvatoConnect, 2025, Impact of AI on Agents).

Onshoring and Reshoring Trends

While offshoring continues to feature in many delivery strategies, particularly to India, the Philippines, South Africa and Egypt, the latest research indicates that some UK buyers are developing a renewed focus on onshore delivery. ArvatoConnect’s 2025 findings report that:
• 73% of UK brands would choose to onshore CX if cost were not a factor
• 34% are actively planning to reshore services that were previously relocated overseas within the next year.

Key drivers behind this transition include:
• Improved staff retention (31%) and access to local talent and cultural familiarity (26%)
• Customer preference for localised support (26%) and better service quality (21%)
• Simpler management structures, regulatory confidence, and access to advanced technologies (25%)

Correctly planned and executed, onshoring is increasingly seen as a future-proof strategy rather than nostalgia. Proximity improves employee engagement, cultural alignment, customer trust, and ensures tighter compliance control, especially for highly regulated industries.

AI, Automation, and Cost Parity

This rebalancing reflects a shift from a cost-driven model to one focused on resilience, agility, and customer intimacy. AI and automation are now reducing the cost of UK-based service delivery by up to 30%, narrowing the traditional economic advantage of offshore operations:
• AI-powered digital agents in the UK: £16 per hour
• Offshore human agents: £15–£17 per hour (depending on which location)
This near-parity redefines the value equation for outsourcing decisions.

Strategic Insights from ArvatoConnect

As ArvatoConnect’s Chief Growth Officer, James Towner, notes:
“Offshoring’s economic promise is fading. Today’s smartest brands are strategically resetting and planning to reshore customer experience for cultural alignment, talent retention, customer preference, and tech-driven agility.”

The emerging model blends 70% digital/AI interactions with 30% human advisors, focusing human talent on empathy, compliance, and complex issue resolution.

Hybrid and Onshore Investments

Ryan Strategic Advisory’s global survey observed limited enthusiasm for expanding offshore capacity among UK enterprises. Instead, organisations are investing in hybrid and onshore models, leveraging automation and analytics to enhance efficiency.

• BPOs are re-emphasising UK delivery centres in cities such as Manchester, Glasgow, and Newcastle
• Investments are going into next-generation CX hubs integrating AI, cloud contact platforms, and multilingual service delivery

And as ArvatoConnects research suggests, providers are piloting AI-enabled ‘micro-hubs’ that balance cost efficiency with high-quality onshore delivery, while maintaining compliance and engaging the local workforce. Of course, the most innovative offshore BPOs are just as focused on automation and AI-driven investment as their UK peers, but technology may be serving to ‘level the playing field’”

Conclusion: The UK’s Resilient Outsourcing Ecosystem

The UK’s BPO and onshoring landscape combines technological sophistication, regulatory stability, and deep sectoral expertise, creating a solid foundation for high-value service delivery.

As brands continue to prioritise data protection, cultural coherence, and high-quality service, the UK’s position as both an outsourcing and reshoring leader is set to strengthen through 2026 and beyond. In the mid-term, the integration of automation, AI support for agents, and reductions in volumes and handling times will provide an opportunity to bring more operations closer to home. This positions the UK not just as a premium delivery location, but as a cost-efficient, technology-enabled alternative to traditional offshore destinations.

We’re caught between high expectations and uneven delivery. AI has the potential to transform contact centres, but only if implemented in a transparent, human-centred, and context-aware way. This article explores how consumer sentiment, operational strategy, and evolving AI technologies converge to reveal what works and what needs further improvement.

In our February 2025 whitepaper, Customer Contact Panel highlighted that this would be a ‘year of difficult conversations’ in which speed, automation, and empathy must be reconciled. AI can increase efficiency, but risks creating a sense of detachment if it isn’t matched with emotional intelligence. Interestingly, complementary research suggests people are more honest with AI when judgment is removed, particularly in sensitive domains such as mental health, financial support, or legal services. However, as the MaxContact report confirms, the majority of consumers still turn to voice when the stakes are high.

What Consumers Are Saying (And Why It Matters)

Voice AI by the Numbers — summarising adoption, customer preferences, and industry usage stats from the Synthflow whitepaper.

 

What does all this mean for CX leaders?

MaxContact’s survey found that 55% of people abandon calls due to long wait times, while 35% cite the agent’s lack of understanding. Complex account issues, payment negotiations, or emotional complaints are scenarios where empathy matters (and where automation often fails). The data reinforces what many CX leaders already sense: customers will accept AI for triage or routine tasks, but demand a human for anything nuanced.

Only 36% of respondents believe AI has improved their contact centre experience, and nearly 32% say it has made it worse. There’s a clear generational divide: 65% of 25-34 year-olds are comfortable with AI, but only 27% of over-55s feel the same. This generational lens is essential when planning AI and omnichannel strategies.

The core problem is bad AI, not AI itself. As noted in our earlier whitepaper, many AI deployments fail not due to technical limitations, but due to design and governance flaws. When AI is introduced without clear escalation paths, brand tone calibration, or decision traceability, customer confidence suffers. Mature solutions in the market now take a more human-aligned approach, creating AI agents that behave like brand-trained teammates, capable of recognising tone, understanding escalation logic, and respecting compliance frameworks.

Every decision should be traceable. Every transfer should carry context. These principles distinguish AI that scales from AI that stalls.

Omnichannel vs. Human-Centric: Getting the Balance Right

Consumers prefer voice support for immediate, emotionally resonant assistance. MaxContact’s research shows 60% view phone calls as the fastest route to resolution, far surpassing digital channels. Automation should manage repetitive tasks and noise, freeing up humans for high-value, high-empathy interactions. Smart triage, seamless handoffs, and transparent automation logic are crucial for omnichannel success.

Trust, Tone, and Transparency: Designing AI That Works

To address the most cited customer frustrations: poor escalation, limited response options, robotic tone – solutions must be designed with:

• Cultural and tone calibration
• Customisable escalation protocols
• Transparent audit trails
• Privacy-by-design aligned to GDPR and beyond

These aren’t technical ‘extras’, they are fundamental requirements in sectors where mistakes can harm trust, reputations, or wellbeing. In regulated or high-stakes categories such as healthcare, dating, or finance, the operational risk of misjudged automation is simply too high.

AI has advanced quickly, but trust remains fragile. Customers want efficiency, but not at the cost of clarity or empathy. The future of contact is digitally respectful, not just digital. The best AI solutions will pause, listen, and escalate when needed, not just answer fastest.

For contact centres navigating this balance in 2025, the opportunity lies in creating experiences that feel both seamless and human where AI takes the pressure off, but never takes over.

In our earlier whitepaper, we explored how AI adoption is reshaping customer contact – an area in which great risk and reward intersect. Six months on, the case for agentic AI has grown stronger, particularly in sensitive customer interactions where honesty and trust are essential.

Drawing on academic research and industry data, we now understand that AI can do more than just automate processes. It can unlock “more honest” conversations, especially in situations where fear of judgment by others or shame might inhibit disclosure.

This isn’t just a theory! Research from Stanford, MIT CSAIL, and NUS Business School reveals a striking trend: people are more open with AI than with human agents in contexts like mental health, financial distress, addiction, and relationship issues.

Why?

Because AI doesn’t judge.

Stanford calls this the social desirability bias, where people moderate their speech based on perceived perceptions. Removing this perception leads to greater honesty.

The ‘confession booth effect’, a term coined by NUS, also demonstrates this. In anonymised AI conversations, people admitted behaviours they hid from humans, like not reading terms and conditions or sharing passwords. In an insurance use case, initial disclosure accuracy rose by 40% when AI agents led the conversation.

MIT CSAIL found that people expend less mental energy managing impressions when talking to AI. This frees cognitive bandwidth for self-reflection and better problem-solving.

Now taking this approach, judgment-free AI agents can be implemented in high-trust, high-friction industries, such as mental health screening, legal triage, financial support, and trust & safety work. These artificial agents are more scalable and effective than humans.

The paradoxical truth is that people often feel more ‘heard’ by AI than by humans, because they don’t feel the need to pretend.

Yet traditional AI platforms struggle with emotional nuance, privacy, and secure escalation. It is essential to overcome these hurdles with strict compliance (GDPR+), contextual accuracy, and human-aligned escalation protocols.

The case for AI grows when combined with market data

Perhaps considered in the context of the long forecast demise of voice as a channel, recent research from the Synthflow white paper brings together a number of key usage stats which when considered with the findings of the academic research support the notion that AI voice will be here to stay?

 

What does all this mean for CX leaders?

• Trust is key. Sensitive topics require the psychological safety of customers to be part your AI solution.
• Design your AI agent around customer fears, not just FAQs.
• Measure resolution accuracy and emotional sentiment, not just AHT.
• Voice AI, when built correctly, can be the most honest channel for customers.
• Integrated agentic AI ensures a consistent experience across platforms.

Customers don’t need AI to sound human. They need AI to “feel safe”. The leading approach to agentic AI will redefine what honest, efficient, and compliant customer interactions can be – especially in a world in which truth drives trust, and trust drives revenue.

Organisations that have adopted AI in their contact centres have often seen significant improvements, such as halved response times, 40–70% operational cost reductions, and increased contact handling capacity. However, as some partners have noted in their recent engagements with members of the the CCP team, these gains can be followed by a flattening curve and then a performance dip, if not implemented correctly.

We have revisited our February 2025 whitepaper, ’2025: A Year of Difficult Conversations’, in which we explored how AI, automation, and digital transformation would drive new operational and ethical challenges in customer contact. We previously highlighted the tension between cost optimisation, customer experience, and why thoughtful project governance will be required.

We thought it would be good to consider what may have changed and what lessons should be revisited.

Six months of continued observation and implementation across the market have revealed risks that automation without the appropriate planning and controls can have on your future operating model are more nuanced. While short-term AI gains are impressive, traditional approaches may erode long-term value through burnout, agent attrition, and customer dissatisfaction. This is the ‘AI Paradox’: the risk that productivity gains today may fuel tomorrow’s operational decline.

Beneath the surface, a gradual yet detrimental erosion of the human layer is occurring. Collaborating with AI often leads to front-line staff experiencing reduced recovery time, increased complexity in remaining ‘manual’ queries, and escalating customer expectations. Without adjustments to team structure, support, or metrics, burnout becomes a growing threat.

This productivity half-life, a period where efficiency peaks and subsequently declines due to human strain, is no longer merely a theoretical risk. Businesses are starting to witness this AI-driven degradation in tangible figures: within 18 months of implementing traditional AI, attrition rates rise by 65%, customer satisfaction scores decline by 20-30%, and agent engagement scores fall concurrently as the technology matures.

Agentic AI presents a more sustainable alternative. Instead of perceiving AI as a replacement for human input, CCP’s partners are illustrating how task-completing AI agents can alleviate the burden on agents, facilitate judgment-free conversations, and ensure capacity for the most significant human interactions when needed. Consequently, it not only yields improved outcomes for customers but also contributes to enhanced retention, reduced training expenses, and a more resilient workforce.

Mitigating the AI Burnout Trap: Lessons from the Last Six Months

• Implement phased AI rollouts with human impact measures.
• Adopt agentic AI that empowers humans, preserving judgment for complex cases.
• Shift success metrics from AHT to FCR, CSAT, and agent engagement.
• Involve agents in AI workflow design and iteration.
• Regularly audit the AI-human balance: check whether tech amplifies or exhausts people?
• Track attrition, training costs, and productivity when calculating your ROI.
• Lead with transparency and ethics when deploying conversational automation.

Make certain you are on the right course

In short: if your AI roadmap doesn’t include agent wellbeing, then you’re building in risk. Efficiency must be sustainable, not just measurable.

Six months on, the market is beginning to learn this the hard way. The good news? There’s still time to course-correct. The AI paradox isn’t inevitable it’s just the result of decisions made without the full picture.

If you’d like to discuss in more detail how you can leverage the experience of our team and our partners, then feel free to contact us.

Of all the contact centre use cases for AI, Pure Voice AI is the most disruptive – and potentially the most transformative. Unlike Agent Assist or auto-wrap that augment human performance, Pure Voice AI replaces the agent entirely for certain interactions.

What is the AI doing in Pure Voice AI?

Pure Voice AI uses fully autonomous AI agents capable of holding spoken conversations with customers—with no human agent in the conversation. For an inbound call, the AI could triage the call, and if it can deal with the interaction itself, it doesn’t need to trouble a human agent. If the enquiry does need a human agent, it can monitor who’s available and route the call to the next best available agent.

Ultimately, the idea is that these AI agents can answer questions, resolve issues, and even handle sensitive interactions such as payment disputes or appointment scheduling.

It’s far more sophisticated than IVR (interactive voice response) trees or chatbots. Pure Voice AI uses advanced natural language understanding, real-time decisioning, and speech synthesis to hold dynamic, human-like conversations.

Key benefits: 24/7 service

The benefits case here is far less about cost reductions, agent productivity gains and optimisations, as use cases 1-6 have already delivered well here.

It is far more about providing round the clock service and enhancing brand experience. Because we all have lives, and work, that mean calling between set hours can sometimes be difficult. But the reason many contact centres are not 24/7 with human agents is because the business case of the cost and overheads – from staff costs to heating and lighting – doesn’t stack up.

Smoothing demand

Not only is calling at set times difficult, it creates spikes in demand, for example around lunch time or just after work. What’s more, pro-active outbound calls can also be scheduled for more customer friendly times of day.

Multi-lingual cover

Where a contact centre needs to serve multiple languages, there is typically a primary language that most human agents speak, with a handful of specialists available for secondary languages. Which means that those secondary languages are a scarce resource, both in terms of availability and recruitment. With Pure Voice AI in the mix, it can detect the language being spoken and switch seamlessly into it.

Implementation considerations

While everyone is trying to rush to this use case, without computer use, proper integrations, optimised and redesigned processes, there is no real opportunity to leap-frog to full voice AI. Because the foundations are simply not in place to support it.

What can we expect to see?

While not quite there yet, it is just around the corner, and there will undoubtedly be a proliferation of pure voice AI, especially for outbound. Though businesses should expect regulation to swiftly follow.

As we await the true potential of Pure Voice AI, it is a case of charting a path to how you achieve this in future, not the focus for today. Down that road lies complexity, risk and far greater likelihood of project failure. When you could be realising value right now and incrementally from use cases that build the maturity on which to develop pure voice AI. A far safer path to value on every front.

To find out more about how CCP can help you make the right technology choices, read more here or get in touch.

This series of articles is drawn from our webinar with Jimmy Hosang, CEO and co-founder at Mojo CX. We explored seven key use cases for AI in contact centres, starting from the easiest productivity gains to value generating applications. You can find a summary of all seven use cases here, or watch the webinar in full here.

Agents often juggle multiple tasks during customer interactions, from information retrieval across systems, to research perhaps through search engines, and data entry to note-taking in CRMs and/or admin systems. Not to mention holding a conversation where they are listening and responding as naturally as possible. It’s a lot to ask while also ‘being present’ with the customer. The opportunity for errors and a sub-par conversation is obvious.

AI-driven hands-free conversations are designed to remove everything other than the conversation from the agent’s to do list.

What is the AI doing in Hands-free Conversations?

This again builds on the previous use cases as a good starting point. Think right back to use case 1 – autowrap, where the AI summarises call notes, and can either simply be copied and pasted into the CRM by the agent, or automated through deep integrations.

Imagine then a world, where not only does the AI do this, but it also navigates you though CRM screens as well as other platforms and apps, retrieving customer records and auto-populating information as you go. Meanwhile use case 5 – agent assist, is popping up with useful prompts to guide the call. Science fiction? Or science fact. The reality is that this is a genuine use case of today.

Key Benefits of Hands-Free Conversations: Absolute focus on the call

A truly liberating experience, the agent is focused solely on their conversation with the customer, while being fed the information they need to support the call and without worrying about what they are capturing as the AI is listening and interpreting to do that on their behalf.

The agent can listen intently, truly process the query and be mentally available to deliver responses where they’ve had the headspace to consider its appropriateness and the style of their delivery. Placing the human interaction at the very centre of the call to the exclusion of all other noise is extremely valuable when it comes to resolving that customer’s needs.

Reduced time spent on admin

If you were to say 10-20% of an agent’s time on a call is just typing and clicking to enter information and navigate screens, while a slightly arbitrary number, it’s inevitably slowing the call and reducing its value to the customer as the agent fills to give themselves the time to type.

Reduced keying errors

As the AI takes care of data entry, there are fewer agent keying errors. Not only does this reduce time on corrections, assuming there are field validations in place, or time taken to later interpret poorly captured data, it improves data quality overall. A key requirement for better analysis, better AI, better compliance, and better future performance.

Improved accessibility

What’s more, hands-free conversations can enhance accessibility – acting as a reasonable adjustment for people with visual impairments or limited hand function.

Implementation Considerations

First, the deep integrations necessary to support hands free integrations take time and shouldn’t be underestimated. Which is in part why this is use case 6 of 7. Because there will need to be some AI maturity building already to ensure both support for and success for this use case. But assuming you have that, it’s a natural progression to freeing agents simply to support customers.

However, there is another school of thought. Where the AI simply deals with all of the legacy for you. Which means you simply live with the poor processes, old mainframe systems, disparate add-ons and Excel spreadsheets you currently have, but without having to interact with them. The savings of not dealing with those, and not having to learn complex keying procedures to get to the screen you want, would be phenomenal and free cash for investment elsewhere. Listen from around 45 minutes into the webinar for Jimmy’s slightly mind-blowing hot take.

Second, accuracy and model training is paramount, which means training and testing the models will also take time and effort. As with other use cases, you will need to develop your own views of what is acceptable

Third, while it sounds all-encompassing, you could consider running the trained model locally and therefore reduce the computational costs.

Measuring Success

The primary KPIs here sit in customer satisfaction, agent productivity/average handling time and data entry or processing error rates. Beyond those, agent job satisfaction can be measured through feedback, attrition rates, etc.

But by far the most interesting benefit is the absolute focus on the customer and the delivery of superior service that should translate through to customer lifetime value.

To find out more about how CCP can help you make the right technology choices, read more here or get in touch.

This series of articles is drawn from our webinar with Jimmy Hosang, CEO and co-founder at Mojo CX. We explored seven key use cases for AI in contact centres, starting from the easiest productivity gains to value generating applications. You can find a summary of all seven use cases here, or watch the webinar in full here.