Every day and with every article written, the excitement surrounding conversational AI grows. Companies around the world are increasingly vocal about their capabilities and progress, which are for a good part, theoretically real, but also equally very much imagined when it comes to reality.
Are the theoretical technology breakthroughs in AI we are reading about translating into effective commercial solutions that deliver real business value? Maybe. Sometimes. Not always.
We are bombarded with stories of AI as an easy and quick fix to a plethora of business issues. This is simply not the case. Without doubt, the payoff of a good conversational AI solution can and will be huge if businesses know and take heed of the realities.
Significant effort is required to implement value-generating conversational AI solutions and the effort is most definitely well worth it. However, expertise and experience in equal measure are critical for conversational AI to deliver on its promises.
So why isn’t the widely articulated value-adding payoff of conversational AI materialising for businesses at the speed of technological developments? The answer is personal.
AI and personalisation
A lot has been said about the use of AI, in various ways, across all industries. Some of these ways, amongst many, include: customer service, employee support, customer relationship management, e-commerce, customer recommendations, security, voice assistance and for customer understanding.
And no matter who is talking about these use cases – a scholar, business-person, consumer, technologist, futurist, designer or anyone else – the AI discussion will inevitably touch on the rise and importance of personalisation.
Customers everywhere now demand a certain level of personalisation. It is imperative that brands deliver if they are to remain in the game, relevant and have a future.
We have all become slightly impatient and demand and expect resolutions, answers and information when, where and how we decide. Anything less is deemed a ‘bad experience’.
We also expect all brand interactions to be relevant to ‘us’ as an individual. This requires conversational AI to think, understand and respond as a ‘human’ would. There must be synchronicity between the ‘artificial brain’ and the ‘human brain’.
Personalisation and expectations
“Human-like interactions”, “more personal”, “better consumer and employee experiences” are all phrases we commonly read when conversational AI is the topic of discussion.
However, we all know that humans are complex and unpredictable, each with their own needs, perspectives, and preferences. Conversational AI can easily make simple tasks quicker and easier – but humans aren’t simple.
Yes, humans do need to complete simple tasks and conversational AI can handle this, when the solution is correctly architected, the content management and workflow robust, and deployment enables fast, easy, anywhere, anytime accessibility.
We also need to complete complex tasks, and very complex tasks. These require an understanding of emotion, empathy, and context if the interaction is to be at all ‘human-like’.
Humans want to be able to speak naturally and be understood. We expect the chatbot or virtual assistant to understand us and respond naturally, and get frustrated by robotic, irrelevant, corporate-toeing interactions. And we definitely don’t want to be asked to phrase a question differently!
Meeting customer information needs
Our information needs are always evolving during the course of a conversation as does our behaviour. It is natural for humans to remember conversations, and during our conversations we change our minds, throw in questions we have just remembered, get interrupted, or move to a new topic. But we can continue any thread of the conversation without having to repeat or explain ourselves again …. when we are speaking with a human.
To meet the needs of customers, chatbots, voicebots, virtual assistants must be able to remember the context from an entire conversation and the information already gathered, and this will have involved an undetermined number of back and forth interactions. And we expect the chatbot, voicebot or virtual assistant to know all about us – personally – our likes, dislikes and preferences.
Conversational AI platforms
There is complex programming behind a chatbot, voicebot or virtual assistant that can carry on a ‘human-like’ conversation, involving multiple topics, requirements and resolutions.
The conversational AI platform powering the bot is the root of its intelligence.
The platform should be the single place where businesses can access the right technology – LLMs, NLU, NLG, NLP etc., giving it advanced AI capabilities, for example sentiment analysis. It must be the architecture for the execution of omnichannel communications, be the library for content management, data and workflows, seamlessly integrated with the apps and systems a business currently uses, and have embedded security and scalability protocols.
Customers want information that has been curated specifically for them and meets their needs. Conversational AI can most definitely transform customer and employee experiences when it is aligned to shifting customer expectations. It can also transform business models.
Real business value
Conversational AI technology is great and can deliver huge value in a timely manner. But if businesses want to get personal, and elevate customer and employee experiences, they need to speak with conversational AI providers who have real experience and expertise. There is a lot of talk of what is possible but very few doing the possible.
If you would like to see how our V-Studio platform can help your business elevate customer and employee experiences, book a demonstration with one of our consultants and we will take you for a tour inside our platform.