Artificial Intelligence Alone Cannot Fix Broken CX
Many organisations are investing heavily in artificial intelligence to improve customer experience, but fragmented data, siloed systems and outdated infrastructure are preventing AI from delivering truly connected omnichannel CX.
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Artificial intelligence is changing everything, fast. For marketing and CX professionals, the race is on to keep ahead of the ever-changing technological landscape, or risk losing pace, and your customers forever.
But while many companies are spending big on a shiny new AI tool and layering it on top of existing systems, they could be missing the point. They’re often ignoring underlying problems with their data and legacy IT systems, which adding AI products simply can’t fix.
Adding new elements to your tech stack is one thing, but fixing fundamental infrastructure issues is much harder. It’s easy to think AI adoption is done because you are automating one process, but what if you’re really just papering over the cracks and making life harder further down the line?
Despite it being a buzzword for years, just 10% of firms believe they have achieved omnichannel CX maturity, according to recent data from the Path to Omnichannel Customer Engagement report, which drew on insights from over 100 senior customer experience professionals.
The report, which was published ahead of the CCW UK Summit, shows that while many organisations want to deliver an omnichannel experience, nearly half (49%) say they still only offer a basic cross-channel experience.
And the customer experience is lagging too – only 4% respondents say they preserve full customer history across interactions, and one in six (17%) still require customers to start over with inputting their data on every channel they use.
These were exactly the kind of issues AI promised to make easier for us, both behind the scenes as marketing and UX professionals, and when we are interacting with brands as consumers. So why is it still failing to join the dots?
Investment and intention don’t seem to be the issue. 59% of CX leaders are now investing in chatbots and virtual agents, and 19% say conversational AI and automation are among their top two omnichannel priorities for investment over the next 12 months.
But how did we get here in 2026, with customers hitting the same friction points as they did 15 years ago?
Simply put, we cannot expect technology to make impossible leaps. Without the right customer infrastructure behind the scenes, AI is just an expensive layer on top of a broken system. AI can only make connections and automations between the data sets it has access to. If data is siloed, inconsistent or missing to start with, the experience will never be fully connected.
Organisations frequently invest in new technology and tools but often ignore underlying problems with their data and legacy IT systems. And, despite trying to free customers from channelled silos in the experience, many organisations are still operating in silos themselves.
Without this missing layer, we find ourselves in a paradox with automation rapidly scaling, while the user journey remains largely unchanged. This is fueling organisations being stuck at the mid-stages of omnichannel transformation.
Despite having the ambition for change, funding and many elements of strategy in place, without a full view of data, identity and systems, it’s impossible for organisations to achieve omnichannel maturity.
In fact, layering AI tools on top of fragmented systems might ironically make the experience more complicated. Most organisations are confined to upgrading and modernising isolated touchpoints, but each new channel or attempt to digitise interactions introduces more data – and that complexity can cause overwhelm.
Counterintuitively, many of the organisations that are achieving omnichannel CX are often slowing down and taking a step back. Accelerating out of the mid-stage stall requires strategic reorchestration to redesign the end-to-end customer journey across the whole organisation.
These organisations ensure there is a full and clear view of the customer, the channel experience and the data underpinning them both. Only then can they consider how to integrate these elements before adding AI and automation tools as a final step.
This comes with challenges as changing legacy systems can be disruptive, and data ownership often sits in organisational silos. It might involve opening cans of worms because historic systems are not fully aligned with other ones.
There might be more work and heavy lifting in the short term. It might mean saying no to alluring tools which promise to improve processes. But in taking a holistic view, you can ensure the end user experience is holistic too.
These organisations are not turning a blind eye to data cul-de-sacs or hoping for a miracle by switching on an AI tool. They are being honest and realistic about their data, and understanding the roles that both technology and talented people play here.
It’s clear that technology is not slowing down. Nor would we want it to. But by understanding where tech fits, and focusing on unifying the experience, we can use things like AI as it is intended – a tool to improve, not complicate, the experience.
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