CIO Review Europe
About UsConferencePartner With Us

The Experience Architects: When AI Thinks, Acts and Cares

CIO Review Europe | Tuesday, June 09, 2026

“How can I help you today?” That simple question, once answered by a human on the other end of a phone line, has evolved into something extraordinary. Today, it might come from a chatbot that remembers your preferences, anticipates your needs and delivers solutions faster. Never have to wait, no matter the time or place.

That’s the world AI-powered Customer Experience Management (CXM) has built for businesses aiming to win hearts in the digital age.

Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

Collecting feedback is the routine, but what about deep diving and directing the emotions behind each input? A few years back, not many companies would have believed in the possibility of understanding the real sentiment behind each feedback and acting on it efficiently.

Many organisations now use the CogniVue feature from SurveySparrow, an AI text analysis tool, to conduct root cause analysis and find hidden insights based on the sentiment score followed by the AI text analysis. It can analyse text from customer reviews, emails, social media posts and other digital touchpoints to determine the sentiment behind the words. Coupled with sentiment analysis, AI can read between the lines, gauging tone and mood to craft responses that hit just the right note. This can help businesses understand how customers feel about products or services and identify areas for improvement.

Personalisation: More Than a Buzzwor

Today, when personalisation means only using a customer’s name in an email, AI takes it to a whole new level. Take Amazon, for instance. Their AI-driven recommendation engine doesn’t just suggest random products—it curates a shopping experience uniquely tailored to you. By analysing your browsing history, past purchases and even those forgotten wish lists, Amazon creates a “just for you” vibe that keeps customers returning.

Then there’s Netflix. Its algorithms don’t just stop at “you liked that action movie, so here’s another.” They dig deeper, analysing customers’ pauses, rewinds and guilty pleasures, to suggest content so spot-on that it feels like the platform knows them better than their best friend.

Beyond recommendations, AI is now used to create immersive virtual reality (VR) and augmented reality (AR) experiences for events, concerts and fan merchandise. For example, Taylor Swift’s Eras Tour leveraged AI for ticket sales optimisation and introduced AR-enhanced merchandise that redefined fan engagement. AI’s impact on entertainment extends beyond screens to how audiences interact with brands.

A Road Toward Smart Stays

The hotel and hospitality industry has embraced AI to elevate guest experiences, creating a blend of efficiency and luxury. Take Hilton’s "Connie" Concierge, for instance. Connie interacts with guests, answering their questions about hotel amenities, nearby attractions and dining options. Its ability to learn from interactions ensures that advice for customers is increasingly relevant over time. Similarly, Marriott’s AI-powered chatbot, accessible through their app or platforms like Facebook Messenger, enables guests to make reservations, request services or conversationally check loyalty points. By using NLP, the chatbot ensures that even complex requests are handled smoothly, offering a hassle-free experience.

These AI platforms have a hidden game changer: They are powered by dynamic pricing algorithms that ensure competitive yet attractive pricing based on market demand, seasonality and guest behaviour.

Levelling Up Loyalty

By incorporating game-like elements, such as points, levels and challenges, into loyalty programs and amplified by AI, companies have taken how they interact with their customers to another level. With the help of AI, these programs have become smarter, more dynamic and deeply personalised, catering to the specific preferences and behaviours of individual customers.

Starbucks, for instance. It has long been a pioneer in loyalty programs, but its Rewards Program uses AI to analyse customer preferences and purchasing patterns. This allows the app to offer customers rewards and discounts tailored to their favourite drinks or frequently purchased items. Limited-time challenges, such as "Earn double stars on your next visit," encourage customers to return more frequently. For example, customers may be offered a challenge like, “Buy three drinks this week to unlock a free reward.” The AI dynamically adjusts these challenges to match individual habits, keeping customers engaged without overwhelming them.

Happier, Optimised Agents

When an AI chatbot encounters a query beyond its knowledge base, it seamlessly escalates the conversation to a human agent. Turing AI takes this further, autonomously creating tickets and intelligently assigning them to the right customer support agent or product manager through its Product Assist feature. A critical aspect of customer support is time efficiency. DevRev Turing AI addresses this by introducing a "/summarise" command. This command provides a quick overview of the conversation, allowing customer support agents to comprehend the issue promptly and drastically reduce customer wait and queueing times. No more sifting through endless chat logs—AI summarises, ensuring a swift resolution.

Repetitive tasks like triaging inquiries, looking up customer histories, searching knowledge bases or verifying user details can drain an agent’s time and energy—AI steps in to handle these. Moreover, when 40 percent of organisations are gearing up to reskill their agents by 2026 so they can focus on consequential customer engagements, For enterprises tackling high volumes of interactions, this reduces agent burnout, boosts team morale and ensures resources are always directed to where they have the most impact.

Where Is It Headed Next?

From the AI customer experience examples above, it’s evident that AI has moved the past text and voice recognition into the realm of emotions—emotional AI, if you will. Algorithms are being developed to advance AI comprehension and response to facial cues and voice inflexions. Customer service based on body language—how you express things versus what you actually say— elevates the stakes considerably. Empathetic AI-driven customer experience is the ultimate achievement in this conversation.

AR/VR, as it advances, will change the game, redefining the shopping experience from A to Z. Throw this together with AI neural networks/quantum computing and deep learning capabilities as they progress in leaps and bounds to analyse data more accurately and faster. Undoubtedly, it will create a more autonomous AI role in managing customer experiences by supporting human agents and acting independently from them as functional intermediaries, thus optimising the customer journey. As we step into 2025, it can be said that we are on the cusp of an extraordinary revolution in customer experience.

More in News

FREMONT, CA : The European e-commerce market has experienced remarkable growth in recent years, driven by expanding internet access and evolving consumer preferences. As online shopping becomes increasingly prevalent, consumers demand seamless and efficient delivery experiences. In response, European retailers and logistics providers are adopting advanced technologies and innovative strategies to optimise delivery processes, ushering in a new era of frictionless fulfilment. Innovations Driving Frictionless Delivery in Europe The logistics landscape in Europe is evolving rapidly, with key innovations enhancing efficiency, sustainability, and customer convenience. Autonomous delivery vehicles are transforming the industry with cutting-edge technologies. Companies are deploying autonomous robots capable of navigating sidewalks and roads to deliver small packages directly to customers’ doorsteps. These self-driving solutions eliminate the need for human drivers and significantly reduce delivery times. Similarly, drone delivery services pioneered by organisations are transforming last-mile delivery. These unmanned aerial vehicles efficiently transport packages to remote areas and urban centres, bypassing traffic congestion and traditional logistical hurdles. Locker and parcel pickup points offer greater flexibility for consumers. Retailers and logistics providers are expanding parcel lockers and self-service pickup point networks in supermarkets and gas stations. These stations enable customers to collect packages at their convenience, enhancing accessibility. Additionally, real-time tracking technologies provide customers accurate delivery updates, reducing uncertainty and improving satisfaction. Click-and-collect services bridge the gap between online and physical retail. In-store pickup options allow customers to order items online and retrieve them from a nearby store, offering an ideal solution for time-sensitive purchases like groceries or electronics. Meanwhile, curbside pickup services deliver a seamless, contactless experience, allowing customers to collect their orders directly from their vehicles, saving time and enhancing safety. The integration of AI and Machine Learning further optimises delivery processes. AI-driven algorithms streamline routing by analysing real-time traffic data and other variables, minimising fuel consumption and delays. Predictive analytics enable retailers to forecast customer demand and manage inventory efficiently, ensuring products are available when needed while avoiding stockouts or overstocking. Sustainable delivery practices are at the forefront of European logistics innovation. Retailers and logistics providers embrace eco-friendly solutions, such as electric delivery vehicles, optimised packaging, and route planning to reduce carbon emissions. Some companies commit to carbon-neutral delivery through investments in renewable energy and carbon credit programs, setting a benchmark for environmentally responsible operations. Ongoing technological advancements and innovative solutions shape the future of delivery in Europe. As consumer expectations evolve, retailers and logistics providers must proactively adapt by implementing seamless delivery strategies. By harnessing AI, automation, and sustainable practices, the European logistics sector can achieve exceptional levels of convenience and speed for customers while significantly reducing its environmental footprint. ...Read more
With its diverse markets and stringent data protection regulations (GDPR), Europe presents a unique landscape for big data innovation. Businesses across the continent increasingly leverage data analytics to gain competitive advantages, predict market trends, and deliver personalised customer experiences. The European Big Data Landscape A robust regulatory framework, diverse industry adoption, and a growing emphasis on artificial intelligence, machine learning, and sustainability shape Europe's big data ecosystem. The General Data Protection Regulation (GDPR) has set a global benchmark for data privacy, compelling businesses to implement stringent data governance measures that enhance data quality and drive responsible innovation. Across industries—from manufacturing and pharmaceuticals to finance and retail—big data plays a transformative role in optimising operations and decision-making. Cloud-based solutions further accelerate this shift, making advanced data analytics more accessible to companies of all sizes. Moreover, European businesses increasingly leverage data to align with sustainability goals, using analytics to optimise resource consumption and reduce environmental impact in line with the EU’s Green Deal. Predicting Trends with Big Data in Europe Big data enables European companies to anticipate market trends, mitigate risks, and identify emerging opportunities. In retail, companies like Zalando utilise historical sales data, social media trends, and weather patterns to forecast demand, optimising inventory management and minimising waste. Supermarkets, in turn, analyse real-time sales and loyalty program data to predict fluctuations in demand for perishable goods. Banks and insurers employ big data analytics in the financial sector to assess credit risk, detect fraudulent activities, and forecast market volatility. At the same time, fintech firms use machine learning algorithms to enhance security and compliance. Similarly, manufacturers rely on sensor data to monitor production performance, predict maintenance needs, and streamline logistics, with companies like DHL leveraging real-time tracking and predictive analytics to optimise delivery routes. Meanwhile, organisations harness social media data, search trends, and online reviews to gauge consumer sentiment and identify evolving market dynamics. Smart meter data informs demand forecasting and grid management in the energy sector. At the same time, cities integrate sensor data to enhance urban sustainability by monitoring air quality, traffic patterns, and waste management. Enhancing Customer Experience with Big Data European businesses also leverage big data to refine customer engagement, personalise services, and strengthen relationships. E-commerce platforms such as ASOS analyse browsing history, purchase behaviour, and demographics to offer tailored product recommendations while streaming giants like Spotify and Netflix curate content based on user preferences. Targeted marketing has become increasingly data-driven, with companies segmenting audiences and utilising location-based analytics to deliver real-time personalised promotions. In customer service, AI-powered chatbots and virtual assistants enhance response efficiency, while sentiment analysis helps call centres proactively identify and address customer concerns. The healthcare sector is also undergoing a data-driven transformation, with providers personalising treatment plans based on patient data from wearable devices and remote monitoring systems. Furthermore, businesses refine loyalty programs through advanced analytics, ensuring rewards and incentives align with customer behaviours and preferences. The latest trends in data management reflect a shift toward more agile, intelligent, and sustainable practices. Companies increasingly adopt Data Mesh Architecture, a decentralised approach that enhances data accessibility and operational efficiency. Simultaneously, AI-powered automation is accelerating, with machine learning and artificial intelligence streamlining data analysis and decision-making processes. The rise of edge computing underscores the need for real-time data processing, bringing computation closer to the source to enhance speed and efficiency. Furthermore, data sharing and collaboration are gaining traction across industries, fostering innovation and addressing complex societal challenges. Sustainable data practices are becoming a priority as organisations seek to minimise the environmental impact of data storage and processing through energy-efficient infrastructure and responsible resource management. Big data transforms European businesses by enabling them to predict trends, enhance customer experiences, and drive innovation. By addressing the challenges and embracing the opportunities, European companies can leverage the power of data to gain a sustainable competitive advantage in the global marketplace. ...Read more
The automation revolution is taking Europe by storm, with Business Process Automation (BPA) leading the charge. A key shift is underway—moving from replacing human roles with technology to enhancing them. This transition captures the core concept of Human-Centric Automation (HCA). Smart packaging transcends traditional product protection by incorporating advanced technology directly into the packaging, creating an interactive and intelligent layer. This innovative approach includes features such as QR codes and NFC tags, which link consumers to secure online platforms for product authenticity verification. Radio-frequency identification (RFID) tags in the packaging allow brands to track products throughout the supply chain, identifying potential tampering or diversion. Tamper-evident seals and holograms provide visual cues if the packaging has been compromised, while colour-shifting inks and invisible watermarks—visible only under UV light or with specific scanners—add another layer of authentication. Additionally, blockchain technology offers a secure, distributed ledger that creates an immutable record of a product’s journey from production to consumer, ensuring transparency and traceability. The European Union has adopted a robust approach to combating counterfeiting. The Falsified Medicines Directive (FMD) and the Tobacco Products Directive (TPD) establish mandatory serialisation and traceability for pharmaceuticals and tobacco products. Vida by Property Vista is at the forefront of integrating advanced AI-powered solutions to streamline compliance with such regulations. Recently, Vida by Property Vista was awarded the Top AI Powered Leasing Platform by PropTech Outlook for their innovative use of AI technology to improve operational efficiency and regulatory compliance. These regulations facilitate the integration of advanced packaging solutions designed to effectively meet these compliance standards. Benefits of Smart Packaging for Brand Protection Smart packaging offers several vital advantages for brand protection. Enhanced authentication capabilities allow consumers to easily verify a product’s authenticity through their smartphones, empowering them to make informed purchasing decisions. Real-time traceability throughout the supply chain enables brands to identify and address potential counterfeiting attempts swiftly. Implementing advanced anti-counterfeiting measures serves as a deterrent to counterfeiters, thus safeguarding brand reputation and revenue. Furthermore, brands can strengthen consumer trust by demonstrating a commitment to product authenticity, particularly within the European market. Examples of Smart Packaging in Action European brands are already benefiting from smart packaging innovations. High-end fashion houses are employing NFC tags to authenticate luxury goods and combat counterfeiting. In the pharmaceutical sector, companies utilise serialisation and QR codes to ensure the safety and traceability of essential medications. Food and beverage companies adopt tamper-evident seals with QR codes to inform consumers about product origin and freshness. The Future of Smart Packaging in Europe The European smart packaging market is poised for significant growth in the coming years. Future developments will likely include the integration of Artificial Intelligence (AI), which can analyse data from smart packaging to detect counterfeit patterns in real time. Additionally, biometric authentication methods such as fingerprint or facial recognition could enhance verification processes. Sustainable smart packaging, combining anti-counterfeiting features with eco-friendly materials, will be a crucial area of focus in future advancements. Smart packaging has transitioned from a futuristic concept to a transformative solution in the battle against counterfeiting. By adopting this technology, European brands can protect their products, bolster consumer trust, and foster a more secure and transparent marketplace. Smart packaging will remain pivotal in safeguarding both brands and consumers throughout Europe as regulations develop and technology progresses. ...Read more
Large language models (LLMs), the backbone of today’s generative AI, have quietly transformed the way machines understand and produce human language. What once seemed like a distant dream is now a reality—these models craft stories, compose poetry and tackle complex questions, unlocking a new era of AI-driven possibilities. The origins of LLMs can be traced back to the breakthrough paper on neural machine translation in 2014, which introduced the attention mechanism. This was further refined in 2017 with the release of the transformer model, significantly enhancing data processing efficiency. Modern LLMs, such as OpenAI’s GPT series and Google’s BERT, are built on this transformer foundation, driving the impressive capabilities witnessed today across the globe.  Innovations Shaping the Future of Modern LLMs Several influential LLMs are currently shaping the AI landscape, driving advancements in natural language processing and setting the blueprint for the next generation of intelligent systems. Here are a few models leading the charge: Claude Developed by Anthropic, Claude focuses on constitutional AI, ensuring that its outputs are guided by principles aimed at making interactions helpful, harmless and accurate. The most recent iteration, Claude 3.5 Sonnet, stands out for its improved ability to comprehend nuance, humour and complex instructions, making it adept at handling a wide range of tasks. In October 2024, Claude was further enhanced with the introduction of a computer-use AI tool, allowing it to operate a computer in a manner akin to human interaction. This new feature is available through the Claude iOS app and an API, making it more accessible for developers and users seeking a sophisticated, versatile AI experience. DeepSeek R-1 DeepSeek-R1 is an open-source reasoning model designed to tackle tasks that demand complex reasoning, mathematical problem-solving and logical inference. The model continuously refines its ability to solve intricate problems by leveraging reinforcement learning techniques, enhancing its overall effectiveness. It also excels in critical problem-solving scenarios by utilising self-verification, chain-of-thought reasoning and reflective processes, allowing it to approach challenges with a higher degree of accuracy and precision.  Merit Data and Technology , recently recognized as the Top AI-Driven Data Solutions Provider in UK by CIOReview Europe  has been at the forefront of utilizing data-driven solutions to optimize e-commerce platforms. Their innovative approach to AI integration and data management has made significant contributions to the industry's growth. Ernie   Since its launch in August 2023, the Ernie 4.0 chatbot has rapidly gained popularity, amassing over 45 million users. While Ernie is rumoured to be equipped with an impressive 10 trillion parameters, its capabilities extend beyond sheer size. The model excels primarily in Mandarin, offering highly refined performance in the language while also being proficient in other languages.  Falcon   Developed by the Technology Innovation Institute, Falcon is a family of transformer-based models renowned for its open-source nature and multilingual capabilities. The Falcon 1 series further expands the model's versatility with larger variants, such as Falcon 40B and Falcon 180B, designed to handle more demanding tasks and enhance performance.  Meanwhile, Falcon 2 stands out with an impressive 11-billion-parameter version that supports multimodal functionality, enabling it to process text and visual data. These models are freely available on GitHub and can also be accessed through major cloud platforms, including Amazon Web Services. Gemini  Replacing the earlier PaLM model, Gemini introduced a rebranding of Google’s chatbot from Bard to Gemini. This model can process text, images, audio and video, making it exceptionally versatile for various applications. Among the most notable recent updates is the Gemini 1.5 Pro, released in May 2024, which brought significant improvements in performance. Gemini is also accessible as a web-based chatbot through Google’s Vertex AI service and via API, allowing developers and businesses to tap into its capabilities. Early previews of the Gemini 2.0 Flash, introduced in December 2024, offer even more advanced multimodal generation capabilities, marking a significant leap forward in AI-driven content creation. Gemma With their open-source nature and versatile deployment options, Gemma models provide a valuable resource for a wide range of natural language processing tasks. Developed by Google, these open-source language models are trained on the same high-quality resources as Gemini. Its Gemma 2 model offers two distinct versions—a 9 billion parameter model and a 27 billion parameter model—each designed to cater to different performance needs.  As new models continue to emerge, enhancing and challenging the status quo, it becomes clear that the pace of innovation in this field shows no signs of slowing down. The future promises even more groundbreaking advancements, making it an exciting time for AI enthusiasts and developers. ...Read more
Top