There’s a huge opportunity which businesses are now realising the potential of when implementing virtual assistants in their organisation to automate tasks both internally and externally.
We caught up with Dave Parsin, VP at NLP specialists Artificial Solutions to find out how they see the market evolving.
AI Business: How do you see the enterprise AI market evolving over the next five years?
Dave Parsin: There is growing interest from companies with whom we engage, wanting to provide richer, more intelligent experiences direct to their customers and to do this consistently across a variety of different applications and delivery channels. We’re finding that this is increasingly being achieved through the provision of speech-enabled, intelligent interfaces that truly understand the user. It’s technology that understands the user rather than the other way around! The demand for this started with natural language applications like Siri, Google Now and Cortana and is now growing to many, many different areas of technology from home automation and automotive to natural language enabling apps for the enterprise.
All of these applications are training the consumer to expect a certain level of intelligent, voice-driven experience in their interactions with technology. As a result, enterprises of all sizes are starting to recognise that this is the minimum level of user experience demanded by their customers when they engage with brands across multiple devices.
Of course, enterprises across the many different verticals will continue to invest in their direct customer experiences, but they’re also going to do it realising they need to make it pervasive across multiple channels … and they’re going to need to give it an artificially intelligent, natural language component to meet their customers’ expectations.
AI Business: What market barriers do you see for an enterprise looking to adopt such technologies?
Dave: I think many companies are still underestimating how pervasive intelligent natural language capabilities. Within five years, we believe it will be as critical a technology to enterprises as websites are today.
This is because of two main drivers. Firstly consumers are already expecting a natural language component to devices and applications and as the technology further improves and becomes even more established, it will become ubiquitous. Secondly, it provides a powerful differentiator for enterprises. By listening in to the conversations, capturing the natural language data, interpreting it and then using it to improve their products and services and to target relevant offers, enterprises will improve the customer experience. And with it, they will not survive!
In short, the technology is broadly in place; the biggest barrier is lack of vision from enterprises themselves.
AI Business: So educating the market is the barrier?
Dave: Yes, I would say the market is starting to move into a second generation of use of AI and virtual assistant capability.
If we push back ten years, business leaders were watching the emerging market for self-service or agent-assisted services; some companies dipped their toes in the water however this first generation of capability often didn’t deliver all that it was promised. In short, they weren’t always as intelligent and sophisticated as they needed to be resulting in some cases to a fatigue and inherent distrust in the technology. In a way their use of first-generation technology has become a barrier to second-generation adoption.
The second generation of AI orientated natural language apps however are able to offer massively improved capabilities that are much more humanlike and capable.
AI Business: Which technologies do you think are really driving the development of AI at the moment, and which do you see having the biggest influence on enterprises and the future of work?
Dave: Part of this may sound a bit like a biased answer, but I think it’s those technologies that are front and centre in driving the experience with the user and how they interact with that particular product or application. It’s the quality of the user experience and to do this, there needs to be a level of intelligence best described as a local intelligence.
We get this when we interact with each other face-to-face. We can adapt our terminology, how we speak, how we respond to the other person to make the experience much more fulfilling. When I communicate with a device or indeed a company, I don’t want to have to use specific terminology or learn how to ask things – I want to use my own terminology and ask the same question potentially in multiple ways. I want a human-like experience.
In other words, I want a capability that can not only understand a variety of topics, subject areas and domains and to potentially perform many different actions. I want it to remember what I’ve asked in previous queries and potentially in different conversations, I want it to remember my preferences, and I want it to infer meaning.
Part two is coming up where we take a closer look at how Artificial Solution’s platform actually works, and what it is enabling businesses to do in reality!