AI in CX: The Practicalities of Implementation

The AI curtain has been raised.

In the initial 18 months following its emergence in late 2022, much of the discourse around this technology centred on unearthing and poring over its potential.

That discourse has moved on significantly as 2024 has unfolded and we’re beginning to see brands pushing past proof of concept and showcasing the tangible business value it can deliver. It’s possible now to draw connections between AI and customer experience ROI as organisations scale their investment and their use cases. AI tools are maturing quickly, crossing that nice-to-have threshold into must-have territory: Indeed, enough success stories are coming to light that boardrooms harbour heightened expectations around their fiscal impact and the clock is ticking on CX leaders to implement them and utilise them to activate enterprise-level strategies.

This pressure – this impatience – from the top is creating a raft of challenges. Big ones. On several fronts.

Many businesses are not fully equipped to roll with AI yet. It has only been one to two years since a significant number of these AI solutions came to life and the complexities of bringing nascent technology to market are multifold. Particularly technology so unprecedented in its disruption as this. There are holistic business considerations. There are technical considerations. There are data considerations. There are workforce considerations. The landscape is so dynamic and fast-moving that it is difficult to keep pace and establish the strong, robust, and resilient digital frameworks that are required to ready an organisation for an AI-based transformation.

On top of that, the very nature of AI – especially generative AI – is such that there can be no halfmeasures around implementation. It needs to be a case of considered and deliberate AI deployment from the get-go. Brands must incorporate a comprehensive risk analysis into their AI journey; one that involves legal teams and technology teams to ensure the models and the algorithms adhere to regulatory principles and social and cultural conventions. The perils associated with adopting this technology without rigorous protections in place have been welldocumented – brand reputation is on the line, and in an age of waning consumer loyalty, such a thing can be difficult to re-establish.

The prospect of working with AI is nigh-on overwhelming then. But looking the other way is not a feasible option either given how integral digital innovation is for businesses today. AI looks primed to play a decisive role in the future of customer management and all the various domains that fall within that. So, just how are brands getting started?

Where are they investing in AI technology? What impact have existing investments already made? How prepared are their respective workforces? What are their biggest concerns around AI integration?

This report offers some answers.

Based on insights gathered from a survey of more than 100 customer management executives from the CCW Europe community, it provides a broad picture of a perpetually changing, highly nuanced space.

Key findings include

• A massive 73% of respondents report that investing in CX-focused AI technology is high on the agenda of their C-suite, with more than one-fifth (21%) saying it is “very high”.
• 30% plan to deploy a new AI tool within the next six months; 24% plan to do so within 12 months; and 28% plan to do so within two years.
• 9% report they are all in on “transformative AI” - the type of AI that solves problems and anticipates customer needs before they are even articulated.
• Implementation and management costs, a lack of internal skills, and data security risks are among the top AI-related concerns for CX leaders.

How AI is Redefining Customer Management Strategies

It’s plain to see: AI is spurring a revolution in customer management.

No longer is it a topic of conversation solely for business analysts, data scientists, IT teams, and the like; Now it’s consuming boardroom meetings as senior executives come to recognise it as an immediate competitive imperative. A massive 73% of respondents report that investing in CX-focused AI technology is high on the agenda of their C-suite, with more than one-fifth (21%) saying it is “very high”. Only 15% report that it represents a “low” priority for their leaders and a mere 1% declare it is “very low”.

These findings are stark.

They reveal just how fast this technology train is moving. Rewinding just one year, conversations around AI at the top table were still inherently primitive – it was nothing more than a point of reflection for the future. Most business leaders were content to sit on the metaphorical sidelines and watch how the landscape developed. They wanted to distinguish reality from all the sensationalism: They wanted substantiation around whether it could enhance customer interactions and subsequently drive greater customer experience. Now, there is a real fear of missing out as they peer over the fence of those few forward-thinking early movers who didn’t sit on the sidelines and glimpse what’s possible when the technology is leveraged effectively. AI has captured attention comprehensively.

Certainly, many of those who did adopt the cautious, hesitant approach have since become fast-followers. Just over half of all respondents (54%) have already invested in CX-focused AI technology and many others are well on their way – 30% plan to deploy a new AI tool within the next six months; 24% plan to do so within 12 months; and 28% plan to do so within two years. Just 5% have no plans to invest at all. In short, there is an AI cascade. More and more organisations are putting AI into production and getting their pilots off the ground, and that means more learnings are on the horizon. AI-related best practices are still somewhat few and far between and so everybody is actively – keenly – looking for guidance on how to extract value from AI functionalities.

For some organisations, the benefits of AI investment are emerging surprisingly quickly.

One in nine (11%) say that AI tools have (up to this point) had a “significant positive impact” on revenue generation, while 25% say it has had a “moderate positive impact” and 28% say it has had a “minimal positive impact”. Not one CX leader reports any negative effects. Of course, it is to be expected that only a limited number of organisations are reaping the truly needle-moving returns at this time, given how new this technology is. Even those early movers are still in the preliminary stages of their AI journey and exploring its possibilities. What’s expected, though, is that as these organisations continue to refine their AI strategies, scale them across different functions, break new ground, and deepen their integrations, the prospects of transformative growth will increase.

Adoption of AI is spiking, then. But just where are brands spending their dedicated AI budgets?

Most are currently focused on using it to solve reasonably simple tasks or workflows. A fraction more than one-quarter (26%) convey they are concentrating on “basic AI” operations that enhance simple interactions and transactions and remove friction for their teams and customers. Two in five brands (39%) are going a little deeper than that – utilising more “everyday AI” technologies that work to improve simple customer journeys throughout the funnel. And that is the most common active use case right now.

Beyond that, 15% express they are investing in “advanced AI” for complex customer journeys where automation plays a greater role and the goal is to proactively address customer problems (rather than react to them), and 9% report they are all in on “transformative AI”. This is the type of AI that solves problems and anticipates customer needs before they are even articulated – it is next-level AI-powered support that can ultimately transform core business capabilities and create entirely new best practices in customer service. Naturally, AI on this scale comes with greater costs and greater organisational overhaul, but the potential for it to deliver real competitive advantage is evidently enticing enough for the bravest CX leaders to take the plunge.

The industry will have watchful eyes on how those transformations play out.

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Discover cutting-edge strategies and practical implementations for AI in customer experience. Learn from 100+ world-class speakers and join the CX-focused Hackathon to drive meaningful change. Join us at the CCW Europe Summit, October 6th to 8th, 2025, in Amsterdam, The Netherlands.

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How to Ensure AI Success with Strategy, Skills, and Structure

As organisations look to capture and take advantage of AI-driven opportunities, significant roadblocks lie in wait.

Whether indeed the goal is to embed that “basic AI” to improve the most straightforward transactions or employ more revolutionary processes that will reform the way a business is run, it is mission-critical to align and characterise all the elements that buttress an AI transformation.
That begins with holistic business readiness.

For AI adoption to be valuable (and viable) in the longterm, organisations would be wise to craft an AI vision statement; they need to clearly define the principles fueling their AI journey. Is the desire to pursue customer-facing AI? Is the intention to use it to better equip internal teams? Is the goal to use it to drive productivity gains or drive savings? Is the emphasis on agile implementation or robust implementation?

Those are the types of questions that AI leaders need to be formulating and answering. This will help put AI guardrails in place and ensure that everyone across the organisation is on the same page – from the C-suite, to middle management, to the agents in the contact centre with their hands on the technology.

Only 12% of CX leaders report that the principles governing AI adoption in their enterprise are highly developed with 44% and 32% saying they are “moderately” and “slightly” developed respectively. Twelve percent convey they are not ready at all. So, there’s work to do across the board.

One best practice organisations can adhere to around establishing their AI principles is to ensure the conversations around what they look like are consolidated centrally. The actions and decisions required to first implement, and thereafter scale, AI must be grounded in transparent collaboration across disconnected and disparate teams – legal needs to be involved from a compliance and monitoring perspective; HR needs to be involved from an employee management perspective; technology and data teams need to be involved from an integration perspective; finance teams need to be involved from a budgeting perspective. If all those functions are engaged in the AI discussion from the outset and throughout the entire process, then introducing AI will be just that bit easier.

The numbers also tell a similar story around technical readiness. Twelve percent of respondents say their organisation is “highly” mature in terms of their ability to implement AI technology. Fortytwo percent are “moderately” mature and 37% are “slightly” mature.

Since AI hit the mainstream, new AI-based tools have been exploding on to the customer management scene with remarkable regularity. At the same time, many of the established technology software providers have been busy incorporating their own proprietary AI-powered models into their existing technology stack. This has created a huge playground for brands looking to make their first foray into AI. And that in itself raises an issue – navigating such a rich and complex ecosystem can be an all-consuming process. To do so effectively, brands must embrace a clear, consistent, and informed approach.

Finding the right vendor is crucial to AI success. And CX leaders are undoubtedly living in a land of opportunity. Supply is most definitely meeting demand, and with a partner invested in their vision, they have a means to reimagine their business. Closely intertwined with technical readiness is the imperative for CX leaders to grapple with data readiness as well.

Indeed, establishing absolute data security is a major constraint on extracting value with AI – particularly generative AI. The age-old aphorism that garbage in equals garbage out when it comes to data has never rung truer than with this technology.

Less than one in 10 CX leaders (8%) feel their data frameworks are “highly” robust and solid enough to serve and support their AI use cases, while 49% are a step behind, reporting they have “moderately” robust infrastructure in place. That leaves 43% still a long way off the pace facing considerable challenges. And this is not an area to be left wanting, given the implications affiliated with supplying AI algorithms with data that is nothing other than ethically sourced, clean, fresh, and accurate – think: inadequate outcomes for customers, flawed recommendations, security breaches, confidentiality breaches, and intellectual property infringements, to name just a handful. None of which are a good look.

Needless to say, AI is no ordinary technology and therefore the approaches to maintaining high quality data must not be ordinary either. Businesses should look to expand their datasets to safeguard against bias and ensure everything is thoroughly labelled and clearly indexed to enable optimal prompt engineering. It’s a process that demands constant review and iteration.

On the flip side to all those business deliberations is the human element. The workforce. The people. Understanding the scale of AI-based change, and the level of impact it will have on employees, is a key point for business executives to address. Indeed, even if every technical and data consideration was taken care of, a lack of skilled personnel could seriously hinder the effective deployment and management of AI systems aimed at improving the customer experience.

Interestingly, this is the area in which brands are seemingly least prepared: only 6% convey their teams are “highly” equipped to handle this technology. Reskilling, upskilling, and professional development programmes have long been a central part of business culture and talent management strategies, but they take on new meaning and new emphasis with AI. This technology requires a fundamental rethinking of what such initiatives look like – AI is more than just a tool to be used; it’s more akin to a colleague and collaborator that needs to be steered in the right direction. The general sentiment across the customer management industry is that AI won’t intrinsically replace humans, but humans well-versed in AI will more than likely replace humans who are not. It’s important, then, that businesses are forward-thinking and proactive with AI training and continually evaluate (and upgrade) the support they provide employees.

A big part of that is building a culture of psychological safety into the enterprise.

Any form of AI transformation will create organisational and operational disruption, and with disruption comes deep uncertainty. That deep uncertainty will naturally lead to a feeling of unease amongst employees and consequently they may be less inclined to take big risks, ask the hard questions, and admit to making mistakes. In short, they tend to focus on selfpreservation rather than pursuing innovation due to a perceived lack of security. This is the opposite of what business leaders need during times of transition – they need their people to push boundaries and share their learnings, good or bad. That’s what drives growth.

Psychological safety facilitates that.

And this all ties back to that AI vision statement. If the workforce has an AI north star, every member of the organisation will feel empowered to make decisions that feed into that without fear of repercussion.

Balancing Innovation with Operational Challenges

Modern consumers are an unforgiving proposition.

Dynamic shifts in their shopping behaviour and in the way they interact and engage with brands today have turned the customer management function into a foremost key business differentiator; one that harbours the capacity to power loyalty and enhance brand equity. In a perfect world, consumers would never contact customer support, but when they do now, such are their demands and expectations, that brands better be ready to meet them with tactics and strategies that minimise friction and ultimately leave consumers feeling heard and, crucially, valued (and with their issue resolved).

AI is undoubtedly central to those efforts – in various guises, in various places.

Indeed, when it comes to spending on CX-focused AI technology, there are many avenues of interest for CX leaders at this moment. The primary source of investment is improving the customer service function – a whopping 84% of CX leaders reporting as such. Behind that, driving business efficiencies emerged as a top priority as well as boosting agent productivity and taking better advantage of data. Respondents are also leaning on AI to increase revenue and augment their personalisation strategies, while some smaller segments are using the technology to reduce employee attrition and stay on top of competitive pressures.

In terms of specific AI focus areas, respondents again indicate they’re looking into a wide range of use cases. Chatbots and virtual agents come in as the most common application, with self-service automation and automated workflow management tying for second. There is also a significant number of brands tapping into AI to generate sales and marketing content and deliver better experiences via video chat.

Altogether, these responses indicate a strong desire among many companies to unleash AI across multiple domains of their contact ecosystems. By doing so, they aim to usher in a new era of productivity, transforming how they operate and connect with customers on a large scale.

Despite all this mounting enthusiasm, though, there is still great apprehension within the CX community around adopting this technology. Which is totally understandable. It is unknown. And the risks involved are many.

The chief concern right now is implementation and management costs – nearly one in two CX leaders (45%) are worried about this piece of the AI puzzle. And this comes back to planning. AI costs can quickly soar if organisations haven’t done their due diligence and baked risk management strategies into their processes. It is critical that AI explorers pay close attention to the terms of their AI partnerships and building the fit-for-purpose organisational structures required to operate this
technology effectively.

The second most quoted concern is that of a lack of internal skills or knowledge. And this is interlinked with those cost considerations. Indeed, since this technology is still very much emerging and evolving, the necessary expertise to handle it might not be readily available within existing brand teams. This consequently creates a reliance on external vendors, or the need for significant investments in training and development.

Behind these top two obstacles, there are a bunch of other AI-related threats occupying the thoughts of CX leaders – these include everything from data security risks, integration barriers, regulatory and privacy concerns, building on a disconnected data strategy, and the inability to pivot from legacy operating systems. There are also some looking at the ethical implications of AI deployment and hallucinations. Collectively, all these concerns are meaningful and well-founded, and any slips in any of these areas can undermine trust in AI processes, both internally and externally, and ultimately set organisations back as they look to capitalise on the opportunities out there.

They are not to be underestimated.

Diving deeper into the type of AI that businesses are using, respondents reveal a burgeoning interest in generative AI.

This technology undoubtedly introduces a paradigm shift. It represents a huge leap forward from more traditional, non-generative AI technology and it marks a fundamental shift in the way humans and machines work together. In the context of employing agent facing generative AI, just 31% are totally inactive in this area while 13% are in monitoring mode. At the other end of the spectrum, 10% have already invested in this technology and are satisfied with their incumbent providers and 5% are reviewing their existing partnerships. A further 15% have use cases active and 19% are currently deploying pilots.

Fascinatingly, CX leaders appear to be more invested in customer-facing generative AI, where the risk to brand image and brand reputation is greater: Just under one in four (24%) are inactive and 14% report to be monitoring the landscape. Twelve percent and 6% are satisfied with, and reviewing, their incumbent providers respectively. And again, just under one in four (23%) are in the pilot stage.

The natural focal point of AI innovation within the customer management framework remains the contact centre. For obvious reasons. It’s the first port of call for customers when they need something.

CX leaders are utilising AI in several ways to improve the service it offers customers when they do reach out: The most prevalent solution is agent assist, with 36% of respondents declaring they have that use case active right now. Technologies pertaining to intelligent call routing (34%), self-service (32%), conversation analysis (27%), and agent productivity (22%) are also widely adopted. Thirty-one percent have no use cases currently active.

Each one of these technologies works in different ways but they are all designed with one goal in mind: To foster deeper, better, quicker, more memorable engagements. Meeting the needs of customers is getting harder and harder (and harder), particularly in their times of need. AI-led solutions are proving to be an effective counter.

The potential impact of generative AI applications is untold.

Their capacity to understand and interpret unstructured data sets and then transform them into action items or recommendations for either agents or customers is a game changer for brands. In short, it is unlocking entirely new functionalities and opening the door to massive efficiency gains. And that is an exciting prospect.

Final Words

The narrative around CX-focused AI is one of bold innovation.

Companies willing to invest in, and experiment with, AI are setting the stage for the future of customer experience – one that is more dynamic, personalised, and responsive than ever before. The landscape is being reshaped in real-time, with AI as the key differentiator. Those who lead this charge will not only redefine their customer relationships but also secure their position at the forefront of their industries.

Revolutionize CX with AI & Automation

Discover cutting-edge strategies and practical implementations for AI in customer experience. Learn from 100+ world-class speakers and join the CX-focused Hackathon to drive meaningful change. Join us at the CCW Europe Summit, October 6th to 8th, 2025, in Amsterdam, The Netherlands.

Learn More

Methodology and Demographics

To understand the role and impact of AI on the customer management landscape, CCW Europe conducted a survey of 100+ thought leaders from the CCW Europe community. All pioneers in their respective fields spanning customer care, support services, customer operations, customer insights, product management, and many more, the respondents collectively came
from a range of companies of all sizes plying their trade across all the major industries including financial services, healthcare and pharmaceuticals, hospitality and travel, retail, automotive, telecommunication, energy, and government and NGO services.