Impacts of generative AI on… the customer service experience

In the customer service experience, massive amounts of unstructured data like images, emails, and text files of customer complaints and suggestions are generated at each key touchpoint in the customer journey – such as the customer’s first interaction with a business or at the point of purchase.

The collected customer data can vary widely in format, sequence, and frequency, posing significant challenges to businesses in determining what it all means and how to use these insights to improve the customer experience and the business overall.

Thanks to advances in generative AI, businesses potentially have access to innovative methods and techniques to analyse the data collected across the customer journey and generate new data. These new methods allow for more sophisticated data interpretation, helping businesses gain deeper insights and creating more personalised customer service interactions.

While generative AI tools such as ChatGPT may offer suggestions for relatively simple tasks such as crafting social media posts, the real game changer is customised Large Language Models (LLMs) that can use very large and diverse data sets to provide evidence-based, data-driven recommendations to a business.

LLMs can simultaneously work with textual data from various sources, such as customer blogs, customer chat groups, product review websites such as Yelp or TripAdvisor, industry and government reports, and the business’s own social media posts, survey and interview data.

Ultimately, these advancements should also drive significant improvements in employee productivity, business operations and strategic decision-making.

In particular, 5 important business functions could benefit from advancements in generative AI over the next 5 years:

1. Performing customer service duties, including responding to customer inquiries through various channels such as call centres, chatbots, emails, ticketing solutions and social media platforms.
2. Preparing draft business and marketing reports, summarising content, and generating brand and promotion copy.
3. Crafting posts for social media channels based on discussion points and threads among key target markets.
4. Problem solving and handling customer complaints by generating options personalised to the customer and recommending tailored recovery actions.
5. Maximising sales through understanding and recommending which offer(s) could be most relevant to customer segments and how to communicate these offers effectively.

To navigate the shift towards generative AI, service organisations should:

1. Invest in understanding the specific benefits that generative AI tools can offer them
2. Provide access to training for their staff
3. Be clear about the challenges of generative AI implementation in their particular business
4. Develop a plan to address the key challenges.

All of this will require careful planning and sufficient time and resources. Working with staff across the organisation to co-create an implementation plan designed to realise the benefits and address the challenges of generative AI will be crucial.

Leaders should develop frameworks, guidelines and guardrails to identify problems before they arise, and implement rules to avoid AI generating inappropriate text or tone. Building trust with staff will be vital, demonstrating how humans and generative AI can work together harmoniously to enhance customer experience, increase staff satisfaction, and drive overall business success.

For more information, contact Professor Janet McColl-Kennedy, FaBA Innovation Pathways Program Program Lead via j.mccoll-kennedy@business.uq.edu.au.

Read more about the impact of generative AI in Momentum, The UQ Business School Magazine.