NLP/AI systems have yet to live up to their promise in customer service in large part because the challenge has been defined as either full automation or failure to automate. As starting from the outside, trying to ‘deflect’ as much traffic/call volume as they can and punting to live serve reps when they fail. The result of this has been hundreds of millions of dollars spent on lowering the cost of customer contact – lots of ‘claimed success’ in terms of deflection rates – and no change in the cost of customer contact or improved customer service. How could this be?
The very essence of ‘conversations’ cannot be replicated by a chat bot with a programmable set of rules: If the customer says this – the bot says that and so on. That’s not how any but the most simplistic of conversations go. Conversations are inherently probabilistic – they involve turn taking which includes disambiguation, successive approximation, backing up and starting over, summarization, clarification and so on.
The future of work will be built on an AI-native platform that enables a powerful collaboration between people and machines.
The promise of conversational AI will be realized by a platform that has been designed – explicitly – to enable a collaborative conversation between service reps, AI-powered algorithms and customers – where technology works in concert with an agent to: automate parts of a conversation, hand it over to an agent when needed, make suggestions to agents about what to say next, listen and learn from what your ‘best’ agents are not only saying to customers but are ‘doing’ with your back-end systems, use machine learning to make all your agents as good as your best agent, and enable the customer to gracefully transition a conversation between their channels/device of choice without losing conversational integrity.
The platform should allow your service reps themselves to demonstrate confidence in the auto-suggestions by selecting them with increasing frequency and then the system can use those ‘confidence levels’ to transition from a ‘suggested response’ to an automated response. Automating 50% of 100% of your call volume is a lot better than automating 100% of 10% of your call volume.
The key paradigm shift here is an AI platform that has been built natively – from the ground up – to enable and foster the kind of man-machine collaboration that will be ‘the future of work’ – and NOT one that promotes a kind of ‘Frankenstein’ where AI components are bolted on to existing systems – hoping for transformational results.
The future of work will be built on an AI-native platform that enables a powerful collaboration between people and machines. This is what ASAPP delivers.
Judith Spitz is a recognized leader with over 20 years of advanced technology experience in the communications industry and the founder of an organization called Break Through Tech. She speaks regularly on the future of work in an AI-enabled digital world, about gender-based algorithmic bias and about the urgent need for more women in technology.