Enterprise technology is evolving at an unprecedented speed, and AI is the rocket fuel.
Yet, customer support teams have little experience with AI beyond previous-generation chatbots, ChatGPT experiments, and what’s embedded natively into their everyday systems.
As such, keeping up with the innovation and learning curves may seem too tricky.
Thankfully, CX Today’s All-Stars have kept their fingers on the pulse, sharing top takes on the future of AI in customer support to help bring their fellow practitioners up to speed.
Here are seven of the most striking predictions.
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CX Teams Will Start to Leverage Large Behavior Models (LBMs)
Contact center providers have developed natural language processing (NLP) models to detect customer sentiment for years.
Now, LLMs are helping this capability progress, enabling live and virtual agents to detect specific moods, adjust their tone, and deliver experiences that feel human-centered and empathetic.
Large behavior models (LBMs) are the next frontier for these use cases, and – according to Michael Fauscette, Founder, CEO & Chief Analyst at Arion Research – they’ll begin to underpin emotional CX.
“LBMs, unlike the more widely used LLMs (and variants like small and medium models and industry-specific models), are trained on human behaviors instead of text,” he noted.
“This creates the ability for the model to recognize human behavioral cues and accurately predict the best actions to take based on those cues and predicted behaviors.”
As such, conversational AI vendors may leverage this technology to power smarter, multimodal virtual agents – or perhaps even avatars.
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Predictive Metrics Come to the Fore
The death of NPS surveys is a perpetual prediction that comes back every year.
There are plenty of reasons why they should bite the dust. Low response rates, customer fatigue, and twisted calculations… take your pick.
Yet, NPS surveys are still here. There are two key reasons for this:
- Some business leaders have become NPS obsessed, chasing the score.
- A more compelling alternative hasn’t come along.
Thankfully, predictive metrics are bubbling to the surface to overcome the issues above.
As Luke Jamieson, a CX Evangelist, observed: “Surveys will become predictive, based on language, subject, tone, and effectiveness of interactions.”
Indeed, solutions that predict NPS scores – powered by generative AI – are already on the CX market. They evaluate each customer support interaction to decipher a customer’s score, should they have completed a survey.
That brings several possible benefits, as outlined in the article: Predictive Metrics Will Help Shape the Future Contact Center. Here’s How.
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Transactional Interactions Become Part of Something Much Bigger
The biggest shift in the future of CX is the transition from transactional experiences to relational ecosystems. That’s according to Justin Robbins, Founder & Principal Analyst at Metric Sherpa.
“Customer interactions won’t be standalone events; they’ll be part of a continuous, interconnected journey powered by AI, data, and human ingenuity,” he added.
To start that journey, many businesses pool their customer support, sales, and marketing data into a customer data platform, like Salesforce Data Cloud or Twilio Segment.
From there, brands create a more rounded view of the customer, funnel new data into AI models, and give customer-facing employees more of that all-important context.
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AI Enables More Proactive & Predictive Customer Support
“AI and automation are going to help us make the biggest leap in predictive customer care and personalization that we’ve seen yet,” believes Andrew Morawski, EVP & GM at Oracle Communications.
“These technologies are already helping us at Oracle streamline and simplify concept-to-cash-to-care and unlock new revenue opportunities for our customers.”
One massive trend to note here is how CPaaS and CCaaS are converging, enabling much better proactive and predictive customer support.
After all, contact centers can now orchestrate new experiences – around particular customer intents – that blend AI, channels, and sometimes humans.
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A More Composable Tech Stack Allows AI to Shine
With more tech providers playing nicely together and delivering out-of-the-box integrations, the option to blend best-of-breed solutions from multiple technology partners is more tangible.
As such, brands can adopt a more composable mindset when selecting the most suitable solutions from a diverse ecosystem. In doing so, they can also create a consistent approach for data and AI.
After making this point, Dennis Parker, Customer Experience Partner Leader at AWS EMEA, noted: “This trend is driven by the need for agility, flexibility, and the ability to deliver personalized, seamless experiences tailored to unique business needs.
“Traditional CX platforms are giving way to a more modular, composable approach, where organizations can mix and match various components and services to create a customized technology stack.”
“This enables organizations to deliver truly differentiated and tailored customer experiences, addressing their unique business challenges and customer needs; this model allows innovation and adaptability.”
Ultimately, with a composable CX stack, brands can more easily swap out or add new elements without disrupting their everyday workflows.
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AI Becomes Emotionally Intelligent
As AI begins to dominate the operational side of CX, the human element becomes more critical. Tracking customer emotions will help contact centers monitor this crucial service component.
Noting this, Aymen Ismail, Head of Customer Engagement Solutions at smart Europe, said: “The companies that win will be those that combine tech-driven efficiency with human-led empathy.
“CX teams will need to evolve into strategic architects of customer trust and loyalty, crafting experiences that aren’t just seamless but also meaningful.”
In doing so, they’ll spot new opportunities for human contact to create moments that customers will remember and forever value.
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Broad AI Implementations Will Face Backlash
“There will be a tangible backlash against organizations who implement broad AI programs and eliminate human interaction options,” predicted David Avrin, President of The Customer Experience Advantage.
“There will be a new “reverse disruption” with the reintroduction of customer preferred options that others have eliminated.”
Avrin’s point here is a reminder to go beyond AI metrics like containment and deflection, thinking about what’s best for the customer in each instance.
Instead, brands should focus on outcome-driven statistics to ensure that automation is to the customer’s benefit, not detriment.
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