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AI Trends Under the Radar for 2025: 5 Ways AI Will Improve Customer Experience

Vova Gerneshii
GMS

Technology leaders will invest in AI-driven customer experience (CX) strategies in the year ahead as they build more dynamic, relevant and meaningful connections with their target audiences. Today's more sophisticated end-users expect more from brands including seamless services with limited downtime, more emotionally sensitive customer support and personalized, contextualized communications that address their specific needs.

As AI shifts the CX paradigm from reactive to proactive, tech leaders and their teams will embrace these five AI-driven strategies that will improve customer support and cybersecurity while providing smoother, more reliable service offerings.

Test Customer Experience Strategies with Digital Twin AI

Digital twin AI will create virtual "copies" of customers and simulate their journey with a brand. Businesses can test different strategies on these digital twins, such as new features or engagement approaches, before rolling them out to real customers, thus allowing them to refine the experience safely without impacting customer trust. This is important because many brands have launched costly AI-driven CX approaches that have failed miserably because they did not meet customer expectations or they felt disjointed, disruptive, or unfamiliar. Advance testing gives brands the ability to uncover what works versus what does not work well in advance of new CX rollouts.

To effectively drive Digital Twin AI testing, IT teams should work with detailed behavioral models and predictive analytics to mimic real customer actions accurately. Large-scale data infrastructure will be necessary, alongside continuous feedback systems, to keep refining these digital twins based on real-world data.

Leverage Emotionally Intelligent AI To Provide High-Touch Customer Support

Emotionally intelligent AI goes beyond recognizing basic emotions, like positive or negative sentiment, to pick up on subtle feelings like frustration or confusion with ethics. It can then adjust its responses to de-escalate tense interactions or address concerns more sensitively, making the experience feel more human. This is important because brands that deliver exceptional service boast higher rates of customer loyalty and satisfaction. In fact, 83% of customers feel more loyal to brands that respond and resolve their complaints in a more efficient and personalized manner, according to a new Khoros study.

This year, IT teams will build emotionally intelligent AI by investing in complex natural language processing (NLP) models that detect emotion, tone, and cultural nuances. They will also process data from multiple sources, like text and voice, in real time to adapt language and responses during live interactions.

Improve Situational Awareness in Conversational AI

Situational awareness will enable conversational AI to adapt based on the specific context of an interaction, like a customer's location, urgency, or history with the brand. This way, AI can give responses that make sense in that particular moment and address the customer's current needs. Today's consumers expect very personalized, proactive and high-touch engagement with brands as well as contextualized responses that are appropriate and relevant to the situation at hand. Companies that fail to deliver this will lose market share, especially with younger digital natives that have higher expectations for brand engagement.

IT teams can achieve this by re-jiggering their AI systems to combine real-time context data, such as location and urgency, with conversational context. Investing in advanced NLP with event-driven architecture will ensure responses are not only context-sensitive but also processed without delay.

Deploy Real-Time Fraud-Behavior Simulation to Boost Security

Today's consumers are increasingly worried about hackers stealing their information and assets particularly when engaging with brands online. Therefore, companies must invest more in AI-driven security to better protect them from hackers with more sophisticated fraud tactics — or else they risk losing them for good.

In the coming year, IT teams will use AI to simulate fraud-like actions in real time to find weaknesses in messaging systems. This "friendly hacking" approach helps identify gaps that conventional anomaly detection might miss, allowing companies to strengthen security against evolving threats.

To achieve this, IT teams will deploy generative adversarial networks (GANs) to create fraud-like behavior patterns and add them to real-time monitoring systems. They will integrate these dynamic simulations with their security platforms, automatically adjusting defenses as new behaviors are detected.

Use "Backstage AI" to Deliver Smoother, Reliable Services

In 2025, tech leaders will rely on Backstage AI, which operates behind the scenes to keep services running smoothly without the customer noticing any interruptions. It helps manage system traffic, balance loads, and optimize resources to prevent service slowdowns or downtime, providing a consistent experience for users. This comes at a time when users insist on minimal or zero downtime. Too frequent disruptions will cause them to abandon vendors that fail to provide highly reliable services, especially in this era of hybrid and remote work.

IT teams can deliver Backstage AI by leveraging real-time monitoring and traffic management, with low-latency data transfer across the system. Distributed machine learning, auto-scaling algorithms, and intelligent load balancing are crucial to make this "invisible" AI operate seamlessly.

IT teams are in a strong position to help their organizations invest in proactive AI CX strategies that deliver both immediate and long-lasting positive outcomes. We believe 2025 will be about the pursuit of short-term, bottom-line gains while shoring up customer loyalty and digital-first business buyers. Looking ahead, savvy IT leaders will invest more in core AI foundations by buttressing infrastructure and upskilling employees. As they operationalize the AI-driven CX lessons learned from 2024's experimentation, they can deliver key short-term wins and eventually succeed with GenAI, Conversational AI and other emerging technologies over the long haul.

Vova Gerneshii is Growth Product Director at GMS, ext.

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AI Trends Under the Radar for 2025: 5 Ways AI Will Improve Customer Experience

Vova Gerneshii
GMS

Technology leaders will invest in AI-driven customer experience (CX) strategies in the year ahead as they build more dynamic, relevant and meaningful connections with their target audiences. Today's more sophisticated end-users expect more from brands including seamless services with limited downtime, more emotionally sensitive customer support and personalized, contextualized communications that address their specific needs.

As AI shifts the CX paradigm from reactive to proactive, tech leaders and their teams will embrace these five AI-driven strategies that will improve customer support and cybersecurity while providing smoother, more reliable service offerings.

Test Customer Experience Strategies with Digital Twin AI

Digital twin AI will create virtual "copies" of customers and simulate their journey with a brand. Businesses can test different strategies on these digital twins, such as new features or engagement approaches, before rolling them out to real customers, thus allowing them to refine the experience safely without impacting customer trust. This is important because many brands have launched costly AI-driven CX approaches that have failed miserably because they did not meet customer expectations or they felt disjointed, disruptive, or unfamiliar. Advance testing gives brands the ability to uncover what works versus what does not work well in advance of new CX rollouts.

To effectively drive Digital Twin AI testing, IT teams should work with detailed behavioral models and predictive analytics to mimic real customer actions accurately. Large-scale data infrastructure will be necessary, alongside continuous feedback systems, to keep refining these digital twins based on real-world data.

Leverage Emotionally Intelligent AI To Provide High-Touch Customer Support

Emotionally intelligent AI goes beyond recognizing basic emotions, like positive or negative sentiment, to pick up on subtle feelings like frustration or confusion with ethics. It can then adjust its responses to de-escalate tense interactions or address concerns more sensitively, making the experience feel more human. This is important because brands that deliver exceptional service boast higher rates of customer loyalty and satisfaction. In fact, 83% of customers feel more loyal to brands that respond and resolve their complaints in a more efficient and personalized manner, according to a new Khoros study.

This year, IT teams will build emotionally intelligent AI by investing in complex natural language processing (NLP) models that detect emotion, tone, and cultural nuances. They will also process data from multiple sources, like text and voice, in real time to adapt language and responses during live interactions.

Improve Situational Awareness in Conversational AI

Situational awareness will enable conversational AI to adapt based on the specific context of an interaction, like a customer's location, urgency, or history with the brand. This way, AI can give responses that make sense in that particular moment and address the customer's current needs. Today's consumers expect very personalized, proactive and high-touch engagement with brands as well as contextualized responses that are appropriate and relevant to the situation at hand. Companies that fail to deliver this will lose market share, especially with younger digital natives that have higher expectations for brand engagement.

IT teams can achieve this by re-jiggering their AI systems to combine real-time context data, such as location and urgency, with conversational context. Investing in advanced NLP with event-driven architecture will ensure responses are not only context-sensitive but also processed without delay.

Deploy Real-Time Fraud-Behavior Simulation to Boost Security

Today's consumers are increasingly worried about hackers stealing their information and assets particularly when engaging with brands online. Therefore, companies must invest more in AI-driven security to better protect them from hackers with more sophisticated fraud tactics — or else they risk losing them for good.

In the coming year, IT teams will use AI to simulate fraud-like actions in real time to find weaknesses in messaging systems. This "friendly hacking" approach helps identify gaps that conventional anomaly detection might miss, allowing companies to strengthen security against evolving threats.

To achieve this, IT teams will deploy generative adversarial networks (GANs) to create fraud-like behavior patterns and add them to real-time monitoring systems. They will integrate these dynamic simulations with their security platforms, automatically adjusting defenses as new behaviors are detected.

Use "Backstage AI" to Deliver Smoother, Reliable Services

In 2025, tech leaders will rely on Backstage AI, which operates behind the scenes to keep services running smoothly without the customer noticing any interruptions. It helps manage system traffic, balance loads, and optimize resources to prevent service slowdowns or downtime, providing a consistent experience for users. This comes at a time when users insist on minimal or zero downtime. Too frequent disruptions will cause them to abandon vendors that fail to provide highly reliable services, especially in this era of hybrid and remote work.

IT teams can deliver Backstage AI by leveraging real-time monitoring and traffic management, with low-latency data transfer across the system. Distributed machine learning, auto-scaling algorithms, and intelligent load balancing are crucial to make this "invisible" AI operate seamlessly.

IT teams are in a strong position to help their organizations invest in proactive AI CX strategies that deliver both immediate and long-lasting positive outcomes. We believe 2025 will be about the pursuit of short-term, bottom-line gains while shoring up customer loyalty and digital-first business buyers. Looking ahead, savvy IT leaders will invest more in core AI foundations by buttressing infrastructure and upskilling employees. As they operationalize the AI-driven CX lessons learned from 2024's experimentation, they can deliver key short-term wins and eventually succeed with GenAI, Conversational AI and other emerging technologies over the long haul.

Vova Gerneshii is Growth Product Director at GMS, ext.

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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