For much of the last decade, customer experience investment was driven by a relatively simple argument.
Better experiences create better outcomes.
Today, that argument is no longer enough.
Customer Contact Panel sponsored research by Ryan Strategic Advisory through the 2026 CX Technology and Global Services Survey to explore a challenge we encounter regularly: what gives organisations the confidence to approve investment in customer operations transformation?
We asked 815 enterprise executives what forms of external support would help them make faster and more confident decisions regarding contact centre technology, outsourcing and operational change.
The answer was remarkably clear.
Proof.
Business case and ROI modelling ranked as the single most important factor.
Independent views on technology options, trade-offs and proven outcomes ranked immediately behind.
Delivery model design also emerged as a major consideration.
Taken together, the findings reveal a significant shift in how organisations evaluate CX investments.
Decision makers are no longer looking for promises.
They are looking for evidence.
This reflects the environment many organisations now operate within.
Budgets remain under pressure.
Technology options continue to multiply.
AI vendors are making increasingly ambitious claims.
Outsourcing models are evolving.
The number of potential solutions available to contact centre leaders has never been greater.
Ironically, more choice has made decision making harder.
The challenge facing many organisations is not a shortage of opportunities.
It is a shortage of confidence.
Can the supplier deliver?
Will the technology work?
How long will implementation take?
What risks need to be managed?
Most importantly, what return will the organisation receive in exchange for its investment?
The survey suggests that organisations increasingly want independent validation before committing to major decisions.
This explains why advisory support, benchmarking, decision validation and technology assessment all scored strongly among respondents.
Executives are seeking reassurance that the choices they make are grounded in proven outcomes rather than marketing claims.
This has important implications for suppliers and internal transformation teams alike.
Features are no longer enough.
Capabilities are no longer enough.
Even successful case studies may not be enough.
Organisations want to understand how a proposed solution will perform in their environment, against their objectives and within their commercial constraints.
That requires a different conversation.
One focused less on products and more on outcomes.
Less on innovation and more on implementation.
Less on possibility and more on proof.
Perhaps the most significant finding from the survey is that decision making itself is becoming a competitive advantage.
The organisations moving fastest are not necessarily those with the largest budgets or the newest technology.
They are the organisations that can build confidence, align stakeholders and create a credible business case for change.
In a market full of options, confidence may be the most valuable asset of all.
And confidence starts with proving the ROI.
Catch up on the series by reading Why CFOs Hold the Key to CX Transformation here, followed by Who Really Drives CX Change? here.
Most customer experience transformation programmes begin with an assumption.
If the business wants to improve customer outcomes, the people responsible for customer experience will naturally drive change.
The reality appears more complicated.
As part of the 2026 CX Technology and Global Services Survey by Ryan Strategic Advisory, Customer Contact Panel sponsored research into a question we regularly encounter when supporting customer operations transformation programmes: who actually drives change inside large organisations? The results highlight a clear distinction between the executives who champion transformation and those who are more likely to support it once a direction has already been agreed.
When asked which board-level stakeholders are most likely to drive customer operations transformation, respondents consistently pointed towards CEOs, Managing Directors, Chief Operating Officers and Chief Customer Officers.
In fact, nearly seven in ten respondents identified CEOs as either enablers or strong enablers of change.
The Chief Customer Officer and Chief Marketing Officer scored even higher when it came to strong enabling influence.
These findings reinforce an important truth.
Successful CX transformation is rarely a technology initiative. It is usually a business initiative.
The strongest advocates for change tend to be leaders who are accountable for growth, competitiveness, customer retention or operational performance.
However, some of the survey’s most interesting findings relate to the roles that were notably absent from the list of major change drivers.
Chief People Officers and HR leaders were among the least likely to be identified as strong enablers.
Transformation Directors and Solutions Leaders performed better, but not as strongly as many might expect given that transformation is often their primary responsibility.
Even Chief Technology Officers were more likely to be viewed as enablers than strong enablers.
Why does this matter?
Because many organisations continue to position transformation projects around technology implementation rather than business outcomes.
Technology teams help make change possible.
Transformation teams help coordinate delivery.
But the survey suggests that the initial momentum often comes from commercial and operational leadership.
The leaders driving change are those closest to customer outcomes, growth targets and operational performance metrics.
For CX leaders seeking support for a new initiative, there is an important lesson.
The first challenge is not selecting the right solution.
The first challenge is building the right coalition.
Understanding who naturally supports change, who remains neutral and who may resist investment can dramatically improve the chances of success.
Many transformation programmes fail before they begin because they focus on technology selection before stakeholder alignment.
The data suggests the reverse approach may be more effective.
Get the right people around the table first.
Then decide what to do next.
If you missed the first article, Why CFOs Hold the Key to CX Transformation , you can read it here. Then continue to the third article, Show Me the ROI: What CX Leaders Need to Prove, here.
For years, the customer experience industry has focused on technology.
CRM, AI, automation, analytics, cloud migration and workforce optimisation have dominated conference agendas and boardroom discussions. Yet despite the growing number of available solutions, many organisations still struggle to move forward with meaningful change.
New research from the 2026 CX Technology and Global Services Survey suggests the problem may not be technology at all.
Customer Contact Panel sponsored a series of questions within the survey by Ryan Strategic Advisory, gathering the views of 815 enterprise executives responsible for strategic contact centre decisions across North America, Europe and Asia-Pacific. The findings reveal a striking pattern.
When respondents were asked which board-level stakeholders are most likely to drive or block change in contact centre operations, one role stood out above all others.
The CFO.
Forty percent of respondents identified the CFO or Finance Director as either a blocker or extreme blocker to customer experience investment decisions. No other executive role attracted a higher level of resistance. Meanwhile, only 36% viewed finance leaders as enablers or strong enablers.
That creates a significant challenge for anyone attempting to introduce new technology, redesign an operating model, or secure investment in customer service transformation.
The findings are not necessarily a criticism of finance leaders. In many organisations, the CFO is fulfilling exactly the role they are expected to play.
Their responsibility is not to champion innovation. Their responsibility is to protect capital allocation and ensure investments generate measurable returns.
The issue is that many CX initiatives are still presented in terms that finance teams struggle to validate.
Better experiences.
Improved customer journeys.
Reduced effort.
Greater engagement.
All worthwhile objectives, but often difficult to translate into financial outcomes.
The survey’s second question helps explain why this matters.
Respondents were asked what external support would help them make faster, more confident decisions around contact centre investment. The clear winner was business case and ROI modelling.
More than four out of five respondents rated ROI modelling as having either high or critical impact on decision making.
The message is straightforward.
Most CX leaders spend time trying to convince stakeholders that change is necessary. The data suggests they should spend more time proving that change is financially justified.
The organisations making progress are not necessarily those with the best technology.
They are the organisations that can clearly demonstrate the commercial impact of change.
If finance is holding the purse strings, then finance needs evidence.
The future of CX transformation may depend less on the quality of the solution and more on the quality of the business case behind it.
Continue the series by reading Who Really Drives CX Change? here, followed by Show Me the ROI: What CX Leaders Need to Prove here.
Guardrails amidst the chaos
The world of AI – perhaps especially in the contact centre and customer experience space – is clouded with exaggerated claims, disputed evidence and unqualified ‘experts’. Everyone talks about guardrails, but there’s no settled agreement as to what is and isn’t reasonable or acceptable. So legal regulations and requirements would presumably be helpful in defining some foundational guardrails? But at a federal level the US government is active opposed to any AI-specific regulation and in the UK, while the government points to its ‘sector led’ approach, there are no plans for an overarching AI law.
However, it’s very different in the EU where the AI Act has been law since 2024 and will be fully implemented from this August. The Act is often described as “the world’s first comprehensive AI legislation”.
In which case, if you’re based in the UK, North America, Africa or Asia you may well be thinking “why should I care? That doesn’t affect me”.
If so, you’d be wrong; very wrong.
Why the EU AI act matters to you
No EU presence? It doesn’t matter. If you have EU customers you will need to comply with the Act’s requirements. And even if you don’t your EU suppliers will. And even if you don’t have EU suppliers or partners, it’s quite likely that in the global regulatory vacuum the EU AI Act will become a default standard, similarly to the way GDPR did for data protection.
While the odds of your organisation being prosecuted under the Act are low, bear in mind that fines are at GDPR levels. So, for the gravest transgressions you’d be looking at €35 million or 7% of global annual turnover.
What does the Act say?
Unsurprisingly, the Act’s quite lengthy, but there are some key highlights to get your head around:
The definition of AI:
”a machine-based system designed to operate with varying levels of autonomy, capable of adapting after deployment, and generating outputs such as predictions, recommendations, content, or decisions that can influence physical or virtual environments”
What’s ok and what’s not:
- Unacceptable Risk AI: Banned totally
- Social scoring, manipulative AI, and biometric categorisation based on sensitive traits are prohibited
⚠ Watch Out
Use of black-box AI for things like fraud prevention or dynamic pricing could put you at risk.
- High-Risk AI: Strict new controls in place
- Applies to recruitment, education, healthcare, credit scoring, policing, and safety-critical infrastructure
Requirements: Detailed risk assessments, transparency, human oversight, and conformity checks before launch
⚠ Watch Out
Don’t assume you’re exempt. Even seemingly innocuous recruitment screening tools could fall within the scope of these rules.
- General-Purpose & Generative AI: New obligations
- Foundation models (like ChatGPT or image generators) must ensure transparency, appropriate labelling AI-generated content, management of systemic risks, and clarification of the use of copyrighted data
- Limited-Risk AI: Transparency required
- Chatbots and similar tools must clearly inform users they’re interacting with AI
⚠ Watch out! Many voice bot providers currently advise clients to hide the fact that customers are interacting with machines. This will need to change – even as it becomes increasingly hard for customers to tell.
- Minimal-Risk AI: Largely unaffected by the Act
- Spam filters, video game AI, and similar tools are mostly out of scope of the Act
Who carries the liability?
As you might expect, the Act differentiates between AI developers (providers) and AI users (deployers).
- Developers (providers) are liable for ensuring that AI systems comply with the Act’s requirements, including safety, transparency, traceability, and respect for fundamental rights. They are specifically liable if harm results from software defects, cybersecurity vulnerabilities, or algorithmic discrimination.
- Users (deployers) are responsible for the legal operation of AI under their control. They need to ensure proper monitoring, human oversight, and adherence to transparency obligations are in place. Users will be held liable if harm occurs due to misuse, failure to supervise, or neglecting operational safeguards.
This means there is less scope for commercial partners to attempt to contractually ‘offload’ legal obligations onto their customers or suppliers than we often see in the realm of data protection. Added to which, when so many organisation and service providers are taking the opportunities to adapt and build upon AI foundation models, they may find themselves legally regarded more as developers than users.
What’s to be done?
What’s clear is that the use of AI in customer experience and contact centres in alignment with the EU AI Act isn’t a one-team or one-time task. Organisations need to truly understand where AI is being used, to achieve what and how. This isn’t just a job for the compliance team. Tech, data, proposition, digital, risk, pricing, finance, legal and customer experience colleagues all need to be involved. And to stay involved as AI solutions innately change and develop over time.
It’s a classic cross-functional business change project, but one that is likely to spur or reflect significant changes in business rules and structures – as well as needing to become embedded into ‘business as usual’ processes.
Need Help Navigating the EU AI Act?
At Customer Contact Panel, we help organisations find and successfully implement compliant, effective AI solutions, so you can innovate with confidence and accountability.
Drop us a line and we’d be happy to have a chat.
If you’re looking for a practical breakdown of what the EU AI Act requires and how to prepare, read our detailed guide:
EU AI Act Compliance: What Every Business Needs to Know and Do
Optimising Sales in the B2C Contact Centre: Designing Better Conversations at Scale
For many consumer-facing organisations, the contact centre is one of the most commercially influential parts of the business, yet it is often optimised narrowly around volume and speed. Conversion targets and short-term performance metrics can dominate, while the quality of the customer experience becomes secondary.
The strongest B2C sales operations take a different approach. They focus less on pressure and more on creating the conditions for confident decision-making. As self-service, digital channels, and automation absorb simpler transactions, the conversations that reach agents are more complex and emotionally charged. Customers are not just buying; they are seeking reassurance. Agents need strong product knowledge, empathy, and the ability to adapt in real time. Training must therefore move beyond scripts and compliance to emphasise judgment, listening, and consultative skills.
What organisations choose to measure shapes behaviour. B2C sales environments that balance conversion and revenue metrics with quality, customer outcomes, and long-term value tend to perform more sustainably. Narrow KPIs drive narrow behaviours, while balanced measures support richer, more productive conversations.
CRM platforms, analytics, and automation should provide agents with context, customer history, and next-best actions quickly and intuitively. When systems reduce friction, agents can focus on the customer rather than navigating tools. Not every contact represents the same opportunity, so aligning propositions to customer intent improves conversion while protecting the customer experience. Regular call listening, targeted feedback, and incentives that reward quality outcomes help teams improve consistently without increasing burnout.
In B2C environments, optimising sales is not about doing more with less. It is about designing better conversations at scale.
Optimising Sales in the B2B Contact Centre: From Lead Handling to Revenue Enablement
In B2B organisations, contact centre sales activity is often undervalued. It is sometimes seen as tactical support rather than a strategic contributor to revenue. Yet when designed effectively, the contact centre can play a critical role in pipeline creation, opportunity progression, and account growth. Unlike B2C, B2B sales conversations are rarely about immediate conversion. They are about qualification, insight, and orchestration across longer buying cycles.
B2B agents need a clear understanding of ideal customer profiles, buying signals, and sector context. Conversations are consultative by nature, requiring confidence, commercial awareness, and the ability to progress opportunities rather than simply pass them on. Integration between the contact centre, CRM, and wider sales teams is essential. Clear ownership of stages, structured handovers, and shared visibility of the pipeline prevent leads from stalling or being lost between channels.
Success is less about call volumes and more about quality indicators such as qualification accuracy, pipeline contribution, progression to the next stage, and account value over time. When metrics reflect this reality, behaviour follows. CRM systems, data enrichment, and analytics should support agents in identifying intent, capturing insight, and triggering next steps efficiently. The goal is not speed, but relevance. Ensuring consistency of qualification and messaging across teams remains critical. Small improvements in conversation quality can have a significant downstream impact on revenue.
When aligned correctly, the contact centre becomes an extension of the B2B sales function, improving coverage, responsiveness, and commercial discipline. Optimising B2B contact centre sales is not about closing faster. It is about enabling better decisions at every stage of the buying journey.
Whether your organisation operates in B2C or B2B markets, Customer Contact Panel (CCP) can help you source the right sales specialists to strengthen your contact centre operations.
Contact us today: hello@customercontactpanel.com
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.
AI regulation is no longer just a tech or compliance issue, it’s becoming a boardroom priority.
In the US at a federal level the government seems to be actively opposed to AI regulation and in the UK, despite an interesting Private Member’s Bill, there’s no sign of any overarching AI law. But while the US and UK are still debating their approaches, the EU is ahead of the game with the world’s first comprehensive AI law: the EU AI Act. If you do business in or with Europe, this will affect you.
Why Should You Care?
No EU presence? Doesn’t matter. If you have EU customers or suppliers, you’ll likely be contractually required to meet the Act’s standards
Remember GDPR? The EU’s data privacy rules became the global benchmark. Expect the AI Act to have a similar impact
The Risk-Based Framework: What’s In, What’s Out
1. Unacceptable Risk: Banned
- Social scoring, manipulative AI, and biometric categorisation based on sensitive traits are prohibited
- Watch out: Using “black box” AI for things like fraud prevention or dynamic pricing could put you at risk
2. High-Risk AI: Strict Controls
- Applies to recruitment, education, healthcare, credit scoring, policing, and safety-critical infrastructure
- Requirements: Detailed risk assessments, transparency, human oversight, and conformity checks before launch
- Don’t assume you’re exempt: Even apparently innocuous recruitment screening tools could be caught by these rules
3. General-Purpose & Generative AI: New Obligations
- Foundation models (like ChatGPT or image generators) must ensure transparency, label AI-generated content, manage systemic risks, and clarify use of copyrighted data
4. Limited-Risk AI: Transparency Required
- Chatbots and similar tools must clearly inform users they’re interacting with AI.
- Heads up: Many bot providers still advise clients to hide from customers that they’re talking to machines —this will need to change
5. Minimal-Risk AI: Largely Unaffected
- Spam filters, video game AI, and similar tools are mostly out of scope
The Compliance Challenge
For UK and global businesses, the message is clear: even without local laws, EU standards will shape your obligations. Cross-border operations will face growing compliance pressure, just as they did with GDPR.
Balancing Innovation and Compliance
The real challenge? Staying innovative while meeting new regulatory demands. Businesses must:
- Identify which AI systems are in scope (which will include understanding exactly which parts of the business are using AI, to do what)
- Ensure transparency and risk management
- Be ready to demonstrate compliance to customers and partners
Need Help Navigating the EU AI Act?
At Customer Contact Panel, we help organisations find compliant, effective AI solutions—so you can innovate with confidence and accountability.
For a broader perspective on why the EU AI Act matters globally and how it is shaping AI governance beyond Europe, see: