Sponsored Article
Generative AI is the next frontier for the world of customer experience (CX).
In just a short amount of time, leaders have begun to fully understand the massive opportunities that leveraging artificial intelligence tools such as ChatGPT can unlock, from improving the agent experience to creating happier customers.
However, they’ve also had to grapple with the challenges that come along with this game-changing technology. I recently spoke with CMSWire to discuss further how companies can best move forward with incorporating generative AI into CX.
CMSWire: Why is it important for companies to start making investments in AI sooner rather than later?
Buddy Waddington: AI may seem intimidating and enigmatic, but for anyone working in customer-facing departments such as marketing and customer service, AI offers an unmatched opportunity to save time, improve processes and make customers happier. Investing in AI now is crucial for any business that wants to get a head start on implementing operational efficiencies and scaling AI across the company. The revenue gap between those that adopt AI and those that don’t will only grow as more companies improve the way they link AI strategies to business outcomes.
One of the biggest challenges most companies face when managing the customer experience is creating a unified approach to customer interactions across all channels. Customers should always get personalized, efficient service with the same brand message whether they reach out on Twitter, Facebook, Instagram, email or phone. With powerful AI, brands can create automated responses and workflows that ensure personalized responses on any channel.
CMSWire: How is generative AI augmenting current AI uses (Chatbots, automation, etc.) to improve customer service?
Waddington: By using generative AI in customer service, companies can provide rapid and more accurate responses, handle a large volume of inquiries and most importantly – enhance the customer experience.
For example, if you are online shopping and you have a question about a product, you could reach out to the brand’s customer service team on Twitter or on their website. The brand could respond with a generative AI-powered chatbot that would be able to understand your question, gather relevant information and provide personalized assistance. This keeps you from having to wait on hold for an agent, getting transferred or needing to switch channels. With generative AI, you get a seamless and efficient interaction.
Generative AI improves the agent experience as well. Rather than manually responding to frequently asked questions, agents can rely on AI-generated responses to answer common questions and AI-generated suggestions to help them find the right brand-approved response. Generative AI can also analyze customer inquiries and assist in creating knowledge base documentation to better serve and scale customer interactions.
At Sprinklr, we’ve spent a tremendous amount of time training AI models and building generative AI-powered capabilities to improve customer service. Sprinklr Service with Sprinklr AI+ can analyze customer interactions to understand preferences, purchase histories and commonly asked questions. It then automatically recommends knowledge base excerpts to include in responses, summarizes cases with clear action items and does much more to maximize efficiency and allow agents to focus on increasing customer satisfaction.
CMSWire: What are some of the most important ways generative AI should be leveraged for customer experience management?
Waddington: Sprinklr has always focused on helping brands reach, engage and listen to their customers across all major social and messaging channels. But with generative AI, brands can take reaching, engaging and listening to another level by helping them truly understand the voice of the customer and quickly translate this into action. From delivering compelling marketing content to providing personalized customer service, generative AI can be used across a brand’s front office to improve the customer experience.
For example, generative AI can be used to enhance insight analysis by building complex queries based on a natural language prompt. This lets analysts spend more of their time analyzing relevant data and increases their speed to insight. Additionally, generative AI can automate tedious, repetitive tasks, such as drafting or modifying social content copy based on tone, length, simplicity and language.
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Webinar
On demand
Insights to Action Rethinking the Contact Center for Real Business Impact
Join our exclusive webinar to hear CX executives share their innovative strategies for transforming service delivery.
Watch Now
Webinar
On demand
Accelerating Healthcare Ops with AI
Sign up to see how your peers are putting AI to work — and making it stick.
Watch Now
CMSWire: What are some of the reasons why some brands are struggling to implement AI for customer service?
Waddington: It’s important to set realistic expectations when implementing AI systems. Brands that want a “quick win” with AI and don’t have a clear strategy will struggle with AI success.
Building and deploying AI systems requires careful considerations such as scalability, performance, security and maintenance. AI systems require large amounts of high-quality data for training in order to provide accurate and unbiased information. Training and fine-tuning AI models takes time, so brands need to look for technology partners that have strong experience. Brands should also find a partner with strong enterprise-grade governance and a security framework to help ensure compliance with legal and ethical standards.
Additionally, a strong AI strategy ensures that AI initiatives are aligned with the overall business objectives and goals for improving the customer service function. Companies should have a technology partner that can offer a clear roadmap for implementation. This allows organizations to allocate resources effectively and manage expectations.
CMSWire: What other risks associated with AI should companies be prepared to address?
Waddington: Unpredictable, biased AI is one risk that brands should be aware of when thinking about an AI strategy for customer experience. To ensure customer loyalty, they need to provide AI-generated responses that are accurate and appropriate. This means that generative AI needs to be used via integration with AI platforms like Sprinklr that train AI models to ensure predictable, accurate results and understand the importance of having a human-in-the-loop user experience when appropriate across the platform.
Learn how Sprinklr’s Generative AI capabilities can drive higher productivity, better decision-making and more seamless experiences for customer-facing teams at sprinklr.com.
