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CRM technology trends

See how AI, machine learning, and other new technologies are transforming CRM and customer experiences.

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New technology for customer experience transformation

The days of competing solely on product and price are over. Today, business revolves around the customer—and the experiences you provide them will make or break your brand. Today’s CMOs and digital, sales, and service leaders must consistently maintain profitable growth, scale operations as touchpoints multiply, and draw clarity from increasingly complex, disconnected data.

So, how do you create the kind of experiences that attract prospects, inspire customers, and keep everyone returning for more? Let’s take a look at technology trends that use customer experience (CX) and CRM technologies such as AI, augmented reality (AR) and virtual reality (VR), and the Internet of Things (IoT) to transform your customer experiences.

AI in CRM: Turning data into value with AI in CRM

Customer and market data volumes are exploding—streaming into CRM systems from more channels and sources than ever before. But humans cannot keep up, at least not without AI and machine learning. These technologies can make sense of big data, harness it, and learn from it in ways we simply can’t.

For example, consider AI copilots in the flow of work. Embedded copilots summarise customer histories and interactions, prepare meeting briefs, draft sales or service follow-ups, and suggest next steps. They do all this within the tools teams already use, so the effort shifts from assembling context to progressing the conversation.

Customer expectations—including concerns regarding how organisations use their personal data—have risen along with costs and operational complexity. Today, data resides across more systems and channels than ever before, and teams struggle to act quickly with confidence. Modern CRM is shifting from reactive engagement to real-time customer service orchestration—anticipating customer needs, and then coordinating actions across marketing and service using AI-driven signals. Drivers behind this change include:

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Intelligent CRM automation

By automating key CRM processes, sales, service, and marketing teams can free up their time to focus on more valuable activities, such as meeting customer needs and enhancing their experiences. Automation can also help you widen your net as it gives you the capacity to nurture more relationships throughout the buyer’s journey, identify cross- and up-sell opportunities, and increase your overall revenue.

For example, lead scoring used to be based on salesperson intuition and educated guesses. With AI, machine learning algorithms can study massive data sets, understand how deals are won and lost, recognise patterns, and identify triggers in the customer’s journey. The algorithm can then automatically apply its learning to the entire sales pipeline and score each lead based on fact, not instinct.

With autonomous workflows, CRM now coordinates end-to-end sequences—from lead assignment and approvals to renewals and case resolution. As signals change, the workflow adapts: it assigns the correct owner, schedules steps, and updates records, all without manual handovers.

Hyper-personalisation

Traditional personalisation includes strategies such as using a customer’s first name in a subject line or sending out a special offer to everyone tagged with the same buyer persona. Hyper-personalisation takes much more data into account, not just customer profiles and transaction history, but also online behaviour, social media posts, conversational styles, timing and context of past purchases, device type, and even GPS data.

Using this big data along with AI, organisations can more accurately interpret customer intentions, pick up on subtleties, and deliver highly tailored customer experiences. Hyper-personalisation allows companies to display specially curated products, and to offer services, promotions, content, and recommendations customised to each customer—automatically and at scale.

CRM chatbots

Multimodal customer interactions now drive conversational flows that blend voice, chat, and images in a natural, increasingly human manner. Chatbots not only help customers find answers to basic questions much more quickly than a representative can, but they can also act as virtual assistants for the sellers, marketers, and customer service agents who use CRM, making agents’ jobs easier and improving their productivity and effectiveness.

A unified conversational AI layer can support both customer-facing interactions and internal copilots. How? The same conversational layer can power copilots within the CRM workspace. The conversation engine that interprets language, understands intent, processes context, and retrieves information for customers is the same engine that can:

So instead of building separate systems—one for customer chatbots and another for internal AI assistants—organisations can use a single conversational engine to reduce complexity and increase the value of embedded AI across teams and workflows.

AI-powered customer analytics

Too often, there is a mismatch between what customers want and what companies think they want. AI-powered CRM analytics can resolve this issue by analysing a vast amount of data from multiple sources—including customer interactions, internal systems and operations, product usage, and third-party and external data—to uncover customer insights that would otherwise remain hidden. AI can research and analyse thousands, even millions, of customers to pinpoint their needs, preferences, and interests. AI-enhanced analytics also help customer-facing teams deliver the products, services, content, and experiences they truly want—in real time.

Embedded AI and predictive engagement extend these capabilities even further. Analytics moves from static reports to early signals—such as propensity, sentiment, usage shifts, and overall account health—that feed autonomous workflows. Instead of reacting to a lost deal or an escalated case, teams can intervene earlier with a relevant offer, message, or solution.

AI customer analytics can also dramatically improve sales forecasting, enhance behaviour and sentiment analysis, predict potential churn and retention issues, and power one-to-one marketing initiatives.

Immersive customer experiences

The immersive technologies of AR and VR, together with low-cost hardware, have helped forward-thinking companies enhance their marketing, sales, e-commerce, and customer service to provide delightful and distinctive experiences throughout the customer journey. For example, an organisation can help customers use AR to scan a malfunctioning product or invite prospects into a VR demo to explore a complete environment such as a factory or construction design.

Virtual reality

VR enables users to step into a computer-generated environment and interact with it. Immersive VR experiences are delivered using headsets, smartphones, hand-held controllers, and even full-room set-ups.

Some VR examples include:

Augmented reality

AR, on the other hand, overlays digital content onto the existing environment. AR-based customer experiences can be delivered through smart glasses, AR applications on smartphones, or specialised screens.

Examples of AR include:

VR and AR in customer service

Businesses are taking AR and VR beyond marketing, sales, and e-commerce, and applying them to customer service, for example:

As multimodal interactions expand, these conversational and visual interfaces can now share context directly with CRM, meaning AR and VR activity no longer sits in a silo. Instead, what a customer views, tries, or troubleshoots in AR and VR automatically informs the next step in sales, service, or marketing without anyone needing to manually re-enter details.

Internet of Things (IoT)

To strengthen their service operations, many companies now use Internet of Things (IoT) technology, which are connected products that can send real-time information about how they are performing. Embedded AI transforms these live signals into useful guidance by detecting early signs of issues, recommending the appropriate time for maintenance, and even drafting customer updates. When something requires human attention, the AI passes the case to a service representative with all the relevant details already organised. This proactive approach helps resolve problems sooner, improves customer experiences, and makes work easier and more efficient for support teams and engineers. It’s a win-win.

IoT in customer service and field service

Before IoT, the customer would have to explain a problem as best they could to a service representative who would try to troubleshoot, and, failing that, dispatch a technician. By connecting IoT device feeds to CRM, the CRM system can automatically create a service ticket, order parts, and schedule a field service engineer. Even better, service departments can monitor product data, detect lapses in performance, and identify the cause of the problem before the customer even notices there’s an issue.

IoT in marketing and sales

In marketing and sales, sensor data flowing into your CRM system can let you know how, when, and where individual customers use your products. Predictive usage signals can then drive the next best action, triggering anything from replenishment reminders to value‑based offers through autonomous workflows. With IoT data, sales and marketing professionals can gain a much deeper understanding of customers' needs, wants, and behaviours—and provide the kinds of experiences that make them feel valued and understood.

Mobile CRM

Mobile CRM—applications that enable sales, service, and marketing teams to access their most important tools whilst on the move—has featured on every major CRM technology list for a decade. But it’s not a thing of the past. Mobile usage has only continued to grow, as have remote working and flexible hours. This means companies need to provide employees with intuitive CRM applications to enable them to be at their most productive. Today, mobile copilots provide field teams with quick briefings, capture notes by voice, summarise previous interactions, and schedule follow-ups—reducing administrative time between visits.

Employees expect to be able to access customer information, track and complete daily tasks, receive notifications and reminders, easily respond to customers, nurture relationships, and collaborate with their teams—from anywhere. Integration with third-party tools such as calendars is essential, as is high-quality activity tracking, excellent security, and an offline mode.

In addition to empowering employees on the move, mobile CRM can help your team ensure customers receive the best possible experience at all times. With real-time notifications and alerts, your staff can quickly respond to customers on any channel, including social media. And with access to up-to-date information, they do so with the right background and context.

When AI, automation, immersive tools, and connected data come together, CRM becomes a catalyst for growth rather than a system of record. By adopting these technologies with intention, businesses can turn challenges into momentum and expectations into lasting loyalty.