Generative AI, a cutting-edge technology, is transforming customer experience (CX) without exposing businesses to undue risk, according to new research from Forrester. While many CX professionals may be wary of this nascent technology, Forrester’s insights highlight the promise of generative AI in improving CX. Principal analyst David Truog explains that generative AI can answer questions without the need for search, occasionally assert falsehoods, and even exhibit humanlike creativity. By discovering the deep structure in a sample of existing data and modeling it, generative AI becomes a powerful tool known as supercharged autocomplete.
For CX professionals, leveraging generative AI leads to significant gains. One valuable application is the use of AI to generate synthetic data, which can mimic or extrapolate from the real world. This synthetic data is particularly useful for analysis when identifiable personal information cannot be utilized. Autonomous vehicle companies, for example, are using synthetic data to teach driverless cars how to navigate the roads. Forward-thinking businesses are also creating synthetic data sets for their entire organization, allowing them to run simulations and conduct scenario planning. This approach enables leaders to assess the impact of CX decisions prior to making any financial commitments.
However, Forrester warns that accuracy is crucial when using synthetic data. While AI can process vast amounts of data, it is essential to avoid the garbage in, garbage everywhere scenario by ensuring the original data is reliable. Customer experience heavily relies on understanding customer needs and delivering offerings that meet those expectations. Generative AI assists teams in summarizing customer feedback effectively, making a significant impact when it comes to distilling public feedback from large amounts of social media interactions. Additionally, generative AI can generate natural language summaries of unstructured data, aiding contact centers in creating condensed summaries of call transcripts.
In the realm of contact centers, the potential for chatbot support using generative AI is evident. Vendors are expected to leverage large language models (LLM) along with natural language query (NLQ) and natural language generation (NLG) techniques, allowing customer service teams to access deeper conversational insights with less effort. However, Forrester cautions that while generative AI has the potential to enhance contact center operations, it is not yet ready to be customer-facing.
In a separate report on customer experience, Forrester emphasizes the importance of aligning CX with employee experiences (EX) to drive business success. Despite numerous opportunities for collaboration, CX and EX teams often fail to work together and share data, metrics, and goals. This can be attributed to historical siloing within HR departments, which may be reluctant to share EX insights due to territory protection. Overlapping functions, such as training customer-facing employees, can also contribute to a competitive rather than collaborative relationship.
To bridge the gap between CX and EX, Forrester suggests three approaches: bringing CX and EX together under a single experience leader, giving both teams ownership of experiences, and establishing centers of excellence that promote collaboration. By fostering a more collaborative environment, organizations can unlock the benefits of aligning CX with EX.
Generative AI holds considerable potential for transforming CX and improving businesses’ understanding, service, and design of experiences for customers. While caution is advised when using AI, its positive impact on customer experience and contact center operations is becoming increasingly evident. By embracing generative AI and aligning CX with EX, businesses can enhance their overall performance and achieve their desired outcomes.
