The latest advancements in large language AI models (LLMs) are set to revolutionize how CX leaders approach their strategies. These cutting-edge tools, now accessible to individuals, bring exciting opportunities for CX teams to harness generative AI for customer experience management. As always, the devil is in the details, and a learning curve remains, but early adopters can gain an edge by scaling their strategies with the help of AI.
In this article:
- Context for new features now available in the most popular generative AI models
- How CX leaders and their teams can leverage custom GPTs (aka “Agents” in Copilot)
- Example CX use cases
- Important considerations and where to start
AI in CX
The topic of AI isn’t new for CX leaders. As a professional community, we have been talking for a long time about how AI can enable better customer experiences through things like enhanced data analytics and experience personalization. And in the broader business context, a 2023 IBM CEO study revealed that 75% of CEOs surveyed believe that competitive advantage will depend on who has the most advanced generative AI. The implications for AI in CX have always been apparent, but the most advanced and sophisticated tools were often managed at an enterprise level, and not broadly available to all users.
We are, however, at the dawn of a new area with generative AI for customer experience. LLM tools such as ChatGPT, Microsoft Copilot and Claude are designed for individuals to use. People are becoming more comfortable using these platforms. And – most importantly – many of the most popular gen AI tools have recently introduced the ability to design custom GPTs. It may sound like a nuanced change, but this has far-reaching implications for CX leaders and their teams.
A new breed of CX tools, that you already have
ChatGPT had one of the fastest rates of new user adoption we’ve ever seen. Within just 5 days of its release, ChatGPT famously reached 1 million users, making it the fastest growing consumer application in history.
It’s no surprise that individuals quickly started exploring how generative AI could boost their productivity, and large organizations scrambled to understand how they could make this technology available for safe use in a business context. But until recently, it was difficult to scale individual use of LLMs in large organizations. These tools were ideal for once-off tasks, requested by users who had mastered prompt-writing. Gen AI tools assisted skilled users to quickly complete tasks such as analyzing unstructured data or summarizing meeting notes, which would have previously been time-consuming. The usefulness of generative AI has been closely linked to the skill and style of each unique user. Prompt writing – like any writing – is difficult to standardize across different authors, so the ideal use case for LLMs seemed to be limited to personalized productivity assistance.
The advent of custom GPTs (also known as “Agents” in Microsoft Copilot) has changed all of that. Now, users of ChatGPT, Claude, Google Gemini, and Microsoft CoPilot Studio can develop customized chats that provide assistance to multiple users on a specific topic. These custom GPTs are designed by their original author to help with a specific task, operating within pre-defined guidelines and referencing preloaded context information. For example, a custom GPT that is designed to assess adherence to a company’s brand voice, could review a document against a set library of terminology, “gold standard” brand voice examples, brand values, etc., and provide pretty consistent feedback to different users.
Think of custom GPTs like mini assistants with a highly specific role that remains constant even with different users. This new feature enables a degree of standardization and guidance across multiple users for common tasks, but without limiting the agility of the LLM. CX teams can leverage Custom GPTs to consistently apply CX strategy across teams, functions and even departments, without the risk of straying too far from their customer promise.
AI brings scalability and creativity to CX like never before. -Julia Ahlfeldt, CCXP
With this new capability, it seems that generative AI has the potential to eclipse other CX tools and become the savvy CX leader’s new secret weapon.
How to use generative AI for customer experience management
I have started using custom GPTs to help organizations achieve their customer-centricity goals. The opportunities to scale the use of generative AI for customer experience are almost limitless. These three innovative applications of generative AI in CX could opening new doors for teams everywhere:
- Persona Creator
Imagine a tool that helps your team distill insights from customer feedback surveys into actionable persona profiles in minutes. This ensures a standardized approach to identifying and synthesizing the most valuable insights from unstructured data. - Experience Auditor
Evaluate experiences—or even entire customer journeys—against a set of predefined experience principles. Align them with your customer promise or brand values for greater consistency and effectiveness. - Design Thinking Sidekick
Assist team members in applying user-centric design best practices during experience design.
Think of your CX strategy is an orchestra. Custom GPTs are like the percussion section—setting the rhythm, keeping everyone in sync, and making sure no one misses a beat. -Julia Ahlfeldt, CCXP
From interpreting insights to reframing ideas, this sidekick ensures every step is aligned with customer-centric goals.
Risks and considerations
When considering the use of generative AI for customer experience, it’s important to understand the potential risks, limitations and considerations for use. Whenever we talk about LLMs and generative AI for customer experience, data confidentiality is always top of mind. This technology is cutting-edge and the creators of enterprise AI tools want to assure us that they are safe, but this is all uncharted territory. Data confidentiality policies are constantly changing. Be sure to investigate an LLM’s data privacy policy before using it, and stay abreast of any changes.
The successful application of these new generative AI features will be highly dependent on how CX teams set them up, and how easily their team members adopt generative AI into their routine. It takes time and practice to hone the right skills to create custom GPTs. The underlying context information linked to any custom GPT also plays a big role in the ultimate usefulness of this type of generative AI for customer experience. As they say, “garbage in, garbage out”. Developing a great custom GPT means investing the time to compile or create the right context library, as well as build, test and refine the custom GPT itself.
And last but not least, we can’t forget about accuracy. LLMs are notorious for inventing fake information and presenting this as fact. Users of custom GPTs should be trained to engage with these helpers as thought partners, constantly assessing outputs while applying their own critical thinking skills. The AI-enabled workplace requires new ways of working, and we shouldn’t take for granted that people often default to accepting new information at face value.
Where to Start
With so much potential for CX teams to leverage generative AI for customer experience, it can be overwhelming to figure out where to begin. To leverage the full potential of generative AI for customer experience, start with these actionable steps:
- Reflect on Your CX Strategy:
Identify areas where standardization or overcoming roadblocks could have the greatest impact. - Brainstorm Solutions:
Determine what would enable teams to achieve consistency without sacrificing creativity. - Outline Mini-Assistant Roles:
Define the tasks and goals for custom GPTs that could assist your team in their efforts. - Start Small, Think Big:
Begin with one or two use cases, refine as you go, and expand to other areas of your CX strategy.
Let’s explore how generative AI can elevate your customer experience strategy. Get in touch to discuss tailored solutions for your team and uncover new ways to drive customer-centric transformation.
Julia Ahlfeldt is a customer experience strategist, speaker and business advisor. She is a Certified Customer Experience Professional and one of the top experts in customer experience management. To find out more about how Julia can help your business achieve its CX goals, check out her customer experience consulting services (including AI for CX upskilling, journey mapping, CX strategy development, experience innovation, leadership workshops and CX ROI measurement) or get in contact via email.
