AI – A broad brush term that means different things to different people. It can cover anything from shouting ‘Hey Siri’ into your phone, to analysing real time data and making decisions based on an ever improving knowledge base. But when you think about it, those two examples could be exactly the same thing, as the latter is exactly what Apple is going to do after you say the former.

Regardless of how you define AI, we all know ‘it’ is advancing, and ‘it’ has opened up many questions. Our focus today is on the concerns customers may have, which of course are a concern to the businesses that serve them. Again, because AI is a broad subject, I’m going to predominantly focus on conversational platforms and chatbots. This is because they can be a fantastic starting point for the implementation of AI and intelligent automation in terms of cost and deployment – and they have clear use-cases.

Transparency is key

First off, it’s worth pointing out that your business probably doesn’t need to beat the Turing test. If you’re using bots, there are arguments that maintaining an illusion of human interaction makes the customer experience better, but this approach isn’t compatible with trust. Whilst the technology is always advancing, its impossible to rule out a bot getting stuck and not understanding what someone meant, breaking the illusion regardless.

If a customer knows they’re speaking to a bot, and it is clear what that bot is there to do, the customer knows what to expect. At the end of the day, bots can provide answers to some questions much faster than a human agent who has to type out the answer, so long as the bot can understand the intent, or goal of the customer.

When designing bots, defining their purpose is more than just good practice of software development. Clear specific purposes mean that users intents are more accurate, meaning your data is more accurate. Whilst you can have as many bots as your (or your cloud’s) infrastructure can handle, narrower purposes also improve intent resolution, reduce development time and allow an organisation to ‘dip their toe’ into the world of AI.