Gamma experts share their thoughts on how AI will influence CX going forward.
Artificial intelligence has become the catalyst forcing organisations to rethink operations. Customer journeys are being redesigned, and teams are rethinking on how best they can work together. In terms of customer experience (CX), it isn’t simply just another layer of technology added on.
AI within CX has become a key topic for debate. Exciting in potential, yet daunting in practice. With customer expectations rising, operational pressures intensifying and legacy systems showing their age, AI has transitioned from a ‘nice‑to‑have’ to an unavoidable part of modern CX strategy.
In our recent CX series, AI was a common topic of discussion among Gamma’s CX experts. Their views and insights reflect the reality of where AI is delivering value and where organisations are struggling with implementation. Above all, they’ll unveil what it genuinely takes to move forward with confidence.
The convergence of AI and CX
AI usage is already widespread. 78% of organisations now utilise AI in at least one of their business functions. Simultaneously, by the end of 2026, 37% of customer interactions could be AI-driven . Automation is slowly becoming more deeply imbedded in service environments.
‘It’s a new world’, as Gamma’s Director of CX Solutions Richard Hall says. Nobody’s sure what the development of AI within CX will look like, and only a third of companies have scaled out AI projects beyond the pilot stage. Only through practical use cases can businesses fully understand what’s possible.
The real danger comes from simply layering technology over ‘broken processes.’ Candy Iverach, Business Development Manager for CX Practice, reflects on how programmes that haven’t met expectations have damaged confidence. Adding on new shiny technology only delays the impact ‘broken and brittle’ processes can have on an organisation.
We all understand just how important CX and AI is. However, some businesses ‘don’t necessarily know the right place to start’. Cassian Bramham-Law, Strategic Partner Director for CX Practice, thinks organisations should take a more ‘holistic approach’ to this CX transformation. Think beyond the contact centre or digital channels – CX is everywhere.
AI reveals CX problems
For many organisations, AI shines a light on issues that were already there. 71% of service leaders believe their systems can’t support modern journeys, reinforcing just how widespread legacy constraints remain.
Broken process, as Richard says, is just ‘one of the banes of any CX journey.’
Data quality is another major barrier. AI is only as effective as the data feeding it, and many organisations struggle with outdated datasets. If poor quality data is being supplied, then the outcomes will be underwhelming.
AI’s role isn’t to fix these issues automatically, but its introduction forces organisations to confront them. Candy touches on ‘the fear’ about AI exposing the CX problems that were previously hidden. Robust testing plans and model offices can mitigate those fears and show just how AI-driven CX can look in practice.
Taking a particular challenge and defining the scope can help show customers ‘what good look like’ when it comes to AI in CX. Terry Gray, Public Sector Director for CX Practice, highlights how a model office process ‘exposes the staff to the benefits [and realities] of working with AI.’ A deeper, more practical understanding will help businesses comprehend how decisive AI’s role in CX can be.
Terry mentions how, despite everyone talking about AI, it’s difficult for organisations to decide ‘what a good use for it is.’ That’s why model offices and creating initial projects allows businesses to uncover proof-of-value. Controlled, real‑world experiments generate evidence for stakeholders, and reduce internal resistance, around how AI can be best deployed.
Perceived vs actual risk
Fear of AI is often emotional, rather than operational. Yet we’re now at a stage where AI is transitioning from experimentation to implementation. While only 12% of CEOs see both cost and revenue benefits from AI, we’re still in the early iterations of mass AI adoption that generates long-term success.
In CX, where journeys affect trust, it’s understandable that leaders tread carefully. Candy highlights that, because CX ‘touches everything the customer touches’, there’s little margin for error. Considering AI is nondeterministic, leaders have a right to be concerned about deploying AI within CX environments.
But inaction carries consequences of its own. Some businesses believe it’s ‘big bang or nothing’, and failing to look past the perceived risks will harm the customer’s experience. The actual risk ‘is doing nothing’, meaning the hidden risks of agent burnout and an increase in missed calls start to surface.
This rise in AI deployment comes with a closer focus on governance and guardrails. Safeguards ‘don’t happen by accident’, as Richard says; they’re built into the design from the outset. Human review loops, safety nets and clarity over accountability all help to ensure a more well-structured AI solution.
Considering governance and guardrails are ‘core to the buying criteria’ within businesses, they’re never an afterthought. It’s the best way to clear any doubts around perceived risk.
Changing what ‘good’ looks like in CX
Customers today don’t follow linear journeys. Before making a purchase, customers are expected to engage with approximately 8 meaningful touchpoints. Traditional metrics, such as handle time or abandonment rate, were built for a different era, and the idea of what ‘good’ looks like has changed completely.
‘Even the idea of success has changed’, as Richard identifies, and organisations must redefine what success looks like to them specifically. The introduction of AI into CX changed the context significantly; a change that ‘happened overnight.’
AI’s main differentiator is speed, in the sense of automation and rapid learning. Workflows are being redesigned, allowing businesses to enable continuous improvements as opposed to long, inflexible development cycles.
Automation also provides real‑time visibility, including sentiment detection, friction alerts, anomaly spotting and quality monitoring. This lets CX teams act faster and adjust journeys more accurately, all while reducing operational pressure.
That extra speed, coupled with in-depth analytics, comes at a time when 90% of buyers rank an immediate response as critically important. Response speed is still a metric to assess what ‘good’ looks like, but the ‘speed at which [businesses] can iterate and change’ will influence long-term success.
The road to a frictionless journey
Customers no longer experience channels; now, they experience moments. 44% of customers will use self-service as their first touch point, and the number of channels available continues to grow. Voice, WhatsApp, email, SMS – each one an avenue for customers and organisations to connect.
Richard remarks on how ‘the linear way of thinking’ about a customer journey changes in the digital world. You start on voice, change to video, and in some cases, responses don’t come back for another 12 hours or so. If consumers think of this journey in an asynchronous way, then such circumstances are never a bad thing.
AI can build this fluidity by stitching together interactions without losing context. Good CX, for Cassian, ‘should be invisible’, working in the background to reduce churn and strengthen satisfaction.
AI as the enabler, not the strategy
It’s easy for organisations to always be focused on the ‘quick wins’ in CX. They offer momentum, but in the long-term, they aren’t the ‘end goal’ or the replacement for long-term CX strategy. Building value and creating trust is what generates value within the CX journey.
The same can be applied to AI within CX. It can, for Candy, be implemented at speed, but it can ‘also accelerate bad experiences.’ That’s why integrating technology should be done in a ‘structured, controlled way… that [guides] people to successful outcomes.’
This methodology is the value Gamma brings to organisations looking to transform their CX. At its core, CX is about removing friction and making life easier for both customers and employees. If the AI foundations are set up correctly, then businesses won’t expose themselves to any further risk.
As Terry says, ‘it’s not about quick wins or long-term progress. It’s both.’
