The AI Revolution: Redefining the CX Game in the Digital Era

AI (along with automation and real-time intelligence) has rejigged the way brands approach CX, ushering in an era of unprecedented content personalization, efficiency and innovation. Organizations that have embraced this shift are not only exceeding customer expectations but also unlocking new opportunities for customer loyalty, revenue growth and competitive advantage.

But for brands that are still playing catch-up, how can they get better at their AI game?

We spoke to several in-house experts on this topic (and more). We’ll be sharing their take in this blog, so strap in — it’s time to dive deep!

‘Start with simple use cases’

When it comes to AI adoption, approach AI as you would a tech solution — take a structured, goal-oriented approach rather than a haphazard or experimental one.

Here’s a six-step guide to ensuring a seamless implementation that drives both meaningful customer engagement and business success.

1. Strategic planning: Define clear business objectives before deciding on an AI vendor.

2. Problem-solution fit: Identify specific challenges AI can solve.

3. Building a solid foundation: Ensure data readiness, select the right AI models and secure leadership buy-in.

4. Integration with existing systems: See to it that AI complements and enhances current workflows rather than disrupting them.

5. Pilot programs: Run small-scale AI initiatives to test feasibility and effectiveness before scaling. “Start with your simple use cases... Maybe start with those repetitive tasks that AI is really good at — things like returns, billing, balance... but in that managed, kind of conversational way rather than picking options from a list,” says Rick Cudd, VP of Solutions Consulting, Europe, Sprinklr.

6. Risk management: Create governance protocols, address data privacy and ethical concerns, and meet regulatory compliance and standards.

While the steps above are non-negotiable, it is equally important to prioritize your workforce and data. Simply handing your team members AI tools and expecting them to adapt doesn't guarantee success — make sure they have the right support, training and strategy to make AI work for them.

Ultimately, achieving long-term success comes down to having data that’s ready to be consumed by AI tools. So, the real differentiator is the high-quality customer data in your possession — access to well-structured data ensures AI can make a tangible, strategic impact across the organization.

Here are three reasons why brands struggle with data and insights in the age of AI:

AI enhances human potential, doesn’t replace it

Once AI is implemented and its use cases are in full swing, finding a perfect harmony between human effort and AI especially in a setting like that of contact centers is far more challenging than you’d imagine.

Balance isn’t just referring to contact center efficiency here. “There’s another balance to consider which is between efficiency and personal human interaction,” Cudd says.

He lists three things that you can do to maintain that balance:

1. AI excels at handling repetitive, routine tasks like processing returns. By automating these functions, you can free up human agents to focus on more complex customer issues — ones that require “critical thinking, empathy and a human touch.”

Related Read: How AI-powered self-service is elevating the customer experience

2. Another key approach is a “blended model,” where AI supports human agents rather than replacing them. This goes beyond just providing help articles — it can assist with real-time coaching. “So, maybe telling an agent in real time, ‘Hey, you’re speaking too fast.’” AI can also analyze conversations post-call to offer insights for training, helping agents refine their skills and take the best possible actions.

Pro Tip: Sprinklr’s AI-powered Agent Assist instantly fills in call details and updates cases for your agents — so they spend less time on tedious after-call work and more time helping customers. 

3. Track and compare performance between automated systems and human agents, identifying which approach works best for different types of calls. It’s crucial to measure the right metrics — like recognizing that as human agents take on more complex issues post-AI deployment, average handling time may naturally increase. Ultimately, AI should be seen "an enhancement rather than a replacement” to human capability.

Uber has been using Sprinklr AI since 2020 to scale its social care team’s ability to triage and respond to the company’s massive volume of inbound customer service requests. Here are its top use cases:

• Enable global teams to efficiently manage and publish brand content across multiple channels and from hundreds of social handles
• Help its rapid response team to proactively listen for critical safety concerns and route them to appropriate teams for resolution
• Allow agents to serve more customers faster from a single, unified platform

Recommended Read: What is Agentic AI and How Can it Help Enterprises

Challenges involved in enterprise-wide AI implementation

Our team of experts feel that when it comes to AI, we shouldn’t let perfect get in the way of getting started. But the fact of the matter is that many companies are still a little bit underprepared. The main reasons are lack of skill/talent, cost concerns, the build vs. buy dilemma.

If you're waiting for the perfect AI team, you’re wasting precious time. Learn to work with less-than-perfect solutions that work in less-than-ideal conditions. Turn your attention to high impact and low complexity use cases to deliver quick wins.

Did you know about these four GenAI innovations that can radically transform your customer interactions? 

Aramex, a multinational logistics, courier and package delivery company based in the Middle East, relied on legacy systems to run its support operations for a long time. These systems, however, lacked integration with modern channels like WhatsApp and couldn’t deliver the real-time analytics and insights required to serve customers' demands across regions, time zones and platforms.

Using native integration within Sprinklr Service, Aramex adopted WhatsApp as its primary channel for customer interactions, deploying a WhatsApp chatbot that facilitates address capture and seamless shipment scheduling. The result: 99% bot containment rate, 20.2 million cases deflected annually and 1.3 million hours saved.

Also, when it comes to building AI solutions in-house versus outsourcing them, the sweet spot is the hybrid model that accelerates time-to-market and affords you the space to customize. For example, collaborate with experts in the field to fast-track innovation and deploy your own solution for very specific business goals and needs. But at the same time, be flexible enough to work with different LLM providers.

The next frontier for AI and CX

The X post below went viral recently and for all the right reasons. It alludes to our experts’ take on why it’s important to focus on using AI to take care of the low complexity, high impact use cases.

"Over the next year, you’re going to see a continuing trend towards hyper-personalization to drive CX. So, this is organizations leveraging AI to churn through billions of rows of customer data points... to tune and personalize the entire customer journey. We see that now and I think we’re going to continue to see that going into the next year – the next 18 months or so,” Cudd says.

Other than using AI to automate workflows and improve operational efficiency, enterprises are also going to be investing in AI programs that help upskill employees so they can better leverage the latest tech innovations in their day-to-day operations. “One of the biggest concerns that businesses have is have they actually got the skills on the people side? There’s going to be more and more demand for folks with these skills and there’s going to be more and more demand for programs as well built around skilling up your workforce to make the most of these tools,” Cudd adds.

Find out why mass personalization is no longer enough to build lasting customer experiences in the video below: 

Here are a few 2025 CX trends to help you decide how and where to use AI:

1. Integration of virtual and augmented reality (VR/AR): The fusion of VR and AR technologies with AI will create immersive customer experiences, allowing for interactive product demonstrations and virtual try-ons

2. Omnichannel harmony: AI will play a pivotal role in ensuring a seamless customer journey across channels, whether online, in-store or via mobile apps

3. AI-powered quality assurance: AI will enhance quality assurance by analyzing customer interactions to ensure consistent and high-quality service delivery

4. Predictive analytics for customer retention: AI's predictive capabilities will help identify at-risk customers and implement strategies to prevent churn, thereby maintaining a loyal customer base

5. Emphasis on trust and transparency: As AI becomes part and parcel of CX, maintaining customer trust through transparent AI practices will become even more crucial

Are you fully capitalizing on AI to drive meaningful outcomes in your organization? You’ll find answers to this and many such questions in our white paper, The Intelligent CX Revolution: How AI Is Changing the Game.