When you read this article, it’s reasonable to assume that a human has created it. Yet in the near future, it will be just as likely that a machine has written the words you are reading. And that’s thanks to the rise of generative AI.

In November 2022, the public had an early glimpse of this paradigm shift in AI when OpenAI launched a chatbot called ChatGPT. It is one of the most discussed of a growing class of AI models which use algorithms to produce content. This includes text, pictures, computer code, and much more based on natural language “prompts”. 

The rise of AI models and their success

ChatGPT is powered by an AI model called Generative Pre-Trained Transformer 3 (GPT-3). Other models such as DALL-E2 can produce images, whilst Github CoPilot writes computer code. All of these models allow computers to perform creative, sophisticated tasks which were once exclusively reserved for humans. And they’re just getting started. 

In March 2023, OpenAI demonstrated GPT-4, an upgraded version of the model which can achieve “human-level performance” on many professional tests. It has already aced several exams, writing answers that scored a grade in:

  • the 90th percentile on a bar exam
  • the 93rd percentile on an SAT reading exam
  • the 89th percentile on the SAT Mathematics exam

To achieve these remarkable feats, generative AI uses deep learning models that are trained on gigantic data sets. As it is fed more and more data, the AI becomes smarter and more capable. This technology is not just about automation, but augmentation and acceleration.

Generative AI enables CX professionals and people working in many other sectors to automate time-consuming tasks. It will not replace humans, but it will transform many jobs. It will require employees to learn new skills related to AI and data, and how best to combine human and machine. 

Witnessing ChatGPT writing text in real-time or DALL-E generating an uncannily creative piece of artwork is a profound experience. While the technology is far from perfect, often generating incorrect and in some cases, harmful responses, it’s too important to risk missing out on the competitive advantage its use will bring CX professionals. 

Generative AI in practice 

There are many ways in which AI can have a transformative effect across the CX value chain. Here are just a few of the advanced tasks generative AI can perform: 

  • Equip customer service teams to deliver a superior customer experience. AI could help an agent throughout the entire lifecycle of a customer service interaction. For example, before and during a customer interaction with an agent, virtual assistants or conversational chatbots can help gauge the reason for the conversation and provide quick assistance. Intelligent AI agents could also address advanced queries and provide intuitive and seamless interactions. 
  • Improve customer satisfaction. Integrating AI could help understand customer emotions and purchase intention ona real-time basis. Also, the conversational ability of AI can create human friendly, well-crafted responses forcustomers. Following interactions, AI can help document notes of the conversation, and provide customers with a personalised experience. 
  • Help achieve specific business goals by driving desirable customer behaviour. By improving the overall experience for individual consumers at scale and delivering personalised services, AI can help organisations achieve their wider business goals. AI could provide personalised consumer journeys including tailored product recommendations and content based on purchase history, individual consumer profiles and browsing behaviour.  
  • Improve sales efficiency. The ability of AI to structure and generate sales descriptions based on historical success can drive efficiencies. AI could identify and predict trends from unstructured data such as consumer sentiment or behaviour data. It could then generate accurate cross-selling leads based on an in-depth, data-led understanding of consumer behaviour and purchase history. 

The next big trend in CX

When deployed across the apparel, fashion, and luxury sectors, generative AI could uplift operating profits by a conservative estimate of $150 billion and potentially up to $275 billion. Technology could play a central and growing role in bringing clothes and accessories to the market – selling them more effectively, and improving CX at every touchpoint. 

A fashion business that deploys generative AI could enhance many aspects of its CX. A generative AI “representative” could handle service queries across any platform to reduce customer service wait times and improve response times. They will be able to take orders, process customer feedback and mimic the interactions consumers might have. Whether with a tailor, shoemaker or any other designer that processes inputs such as size data, the AI can then produce relevant outputs. This includes bespoke, one-of-a-kind garments.

Generative AI agents could also perform advanced tasks. including clienteling. This is a retail strategy in which sales associates develop long-term relationships with high-spending customers. It encourages purchases and improves loyalty through one-on-one interactions.

Clienteling drives a conversion rate between 60-70% in luxury boutiques. Today, it relies on the traditional process of human interaction in person or on the telephone. Generative AI could continue the conversation long after the shopper’s interaction is over. It could provide personalised communications about new products and analyse customer profiles to interpret feedback. Then, use data gathered throughout the journey to further personalise and improve the experience. 

Prepare for the change in 5 steps

The CX benefits that generative AI enables will be equally impactful across many–if not all– customer-facing industries. To prepare for the change, leaders can take five steps: 

  1. Focus on value. Outline areas of the business where generative AI could have a positive impact. It is essential to clarify which all aspects of the business. 
  2. Identify risks and their mitigants. Understand how AI could cause issues such as copyright infringement or any other sector-specific risk, and the challenges that a wrong/biased recommendation could create. Design protocols to test and scale safely.
  3. Upskill the workforce. Train team members throughout the organisation (from data and analytics teams through to the front line) to use generative AI. Show them how it will benefit their day-to-day work. 
  4. Partner with tech support. Deploying new technology creates risk. It is important to ensure 24/7 support is on hand to solve problems. 
  5. Create learning loops. Applications of this technology are evolving fast. The winners will be those that embed the ability to innovate, iterate and learn into their processes to always bring the best to their customers.

Over the next few years, generative AI will unlock many use cases and allow CX professionals to create new journeys and experiences. These will undoubtedly be more personalised than ever before. The transformation and disruption will be significant, and the possibilities are endless. Generative AI has the potential to change CX forever and give customers new, unique experiences. All whilst driving significant growth for businesses. 

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