Over the past 12 months there has been a shift in focus back to customer experience after a long period of AI being the main talk of the town. Customer experience is once again the topic dominating the beginning, middle and end of conversations we are having with businesses from all industries. That’s not to say it ever went away, but there was a tendency by organisations to lead conversations with AI, and customer or employee experience would follow.
This change has come about now that AI is a part of our everyday language, its capabilities and constraints well documented, and the reality that its value is inextricably linked to a clear strategy and understanding of what is achievable.
Whilst many analyst houses are forecasting AI investment growth, with a figure of $151billion being spent on GenAI solutions by 2027 being quoted by IDC forecasts, and there is much excitement about this, businesses are now hunkering down to execute on their strategies and unsurprisingly customer experience dominates. Where customer experience leads, revenue will follow.
Conversational AI solutions continue to be one of many tools in the customer service arsenal of businesses, with a large majority already using conversational AI to deliver better customer service. They may have a bot that can be accessed directly by customers, via a website for example, which can answer all their queries. And a bot that is specifically used by agents within a contact centre, helping them deliver a better customer experience. It could also be that organisations have a bot performing actions such as completing a sale or executing marketing activities. The use case possibilities are numerous.
The above examples cite relatively standard bot 1.0 capabilities. Technology advances, customer expectations and demands, employee requirements, and business challenges and pressures have moved the dial considerably when it comes to bot capabilities. We have moved way beyond simple FAQ type interactions, with expectations that engaging with a bot is as good as, or even better than, the experience with a human. We expect human to bot interactions to be quicker, on our terms, and what we want or need to be resolved instantly.
With competition for customers at an all-time high it is no surprise that customer experience is back leading business conversations. A clear articulation of the customer experience strategy lends itself to the development and deployment of successful, value-adding conversational AI solutions.
It is now a given that customer service bots are a base standard, delivering one dimension, often reactive, of an overall multi-dimensional customer experience. Organisations are now layering standard customer service bot capabilities with embedded ‘experience’ layers that offer a new level of customer experience. When conversational AI solutions are aligned to customer experience strategies bots are transformed from reactive to proactive so that they are delivering personalised retail experiences, personalised banking experiences, personalised travel experiences and so on. Bots are now marketers, product experts, salespeople, advisors, consultants, and customer service agents. They meet customers where they choose, whenever they want, and are available on-demand.
Although competition for customers is high, within certain regulated industries the race to competitive advantage is being tempered by governance requirements. Legislative requirements regarding the use of AI are evolving rapidly. For example, the EU AI Act was just approved on 13 March this year. In the US 25 states have introduced AI laws, but there is no single legislation for the country. In APAC there is the ASEAN Guide on AI Governance and Ethics which is said to be taken as a reference only.
Organisations must be able to effectively and rapidly adapt to any new legislation that is introduced. This can be mitigated when organisations start with a customer experience strategy and look to conversational AI as an execution tool.
Ensuring that an organisation always controls the AI is critical and having this ability must be available to a business directly via the conversational AI platform that an organisation chooses to use. With control over the AI, control over content, a business retains control over their reputation. In short, this level of control means that customers can confidently trust that the information they are given is correct and that they are interacting in a highly secure and safe environment.
Information accuracy continues to be a topic that attracts fantastical headlines because they are sometimes a bit scary. However, these headlines are often because the underlying source data has inconsistencies and/or inaccuracies and these are feeding the ‘responses’ especially when generative AI is the sole programme used.
Generative AI cannot correct the inaccuracies in the data. This is one of the reasons why a blended approach that leverages both generative AI and rules-based enables organisations to build and deliver trusted conversational AI powered bots. Each of these approaches has certain applicability across different use cases and industries and the right conversational AI platform will enable a business to choose the best approach and language model to meet their specific requirements, governance and risk profiles.
A clear customer experience strategy and importantly an understanding of the capabilities and constraints of AI is critical for the implementation of value-adding conversational AI solutions. The customer experience strategy will influence the solution design, ensure data and governance issues are mitigated, and highlight that control of the AI is central to building trust. With a clearly articulated customer experience strategy organisations will be driven to take the large number of data insights and use these to deliver rich personalisation.
Customer experience is top of the boardroom agenda for a reason. It is driving value for customers and employees. And it is conversational AI that is transforming the customer and employee experiences and delivering real business value.
