Guest Blog: Artificial Solutions - 'Conversational apps deliver intelligence'

As part of techUK's AI Week, Andy Peart, Chief Marketing & Strategy Officer at Artificial Solutions has provided a blog on 'Conversational Applications Deliver the Intelligence Your Business Needs'

Natural language is at a tipping point and digital employees, bots and the IoT are only the start. By 2020, natural language will be a key interface between you, your staff and your customers, interacting through a myriad of applications and services from artificially intelligent digital employees to a speech-enabled cohesive IoT ecosystem.

Applications, services and devices are changing the technology landscape, and with it people’s expectations. Fuelled by smart devices in the home, using their voice to control devices and intelligent interactions with smart city devices, consumers are already used to technology understanding them and simplify their lives. Now they are expecting the same service from the companies they interact with everyday.

For businesses this is good news. People reveal a huge amount of information in natural language conversations, which opens up new revenue streams and opportunities to forge a closer relationship with customers. By analysing conversational data in real-time, organisations can not only study trends, but react immediately and and personalize the interaction.

But it does require a rethink about how to deliver the smooth, effortless and fast interaction that customers expect – simple layering a mobile app over existing channels won’t cut it anymore.

Developing a consistent, cross-channel way of interfacing with technology that delivers AI type understanding such as implicit personalization, requires a deeper interaction than most speech enabled apps deliver today. This deep understanding is achieved through real-time interpretation of natural language conversations, combined with the ability to access specific information related to an individual from other data sources. These might include a CRM system or a third party app that the user has authorized to link together.

Until recently, embarking on this type of implementation was a lengthy and complex process, only undertaken by computational linguistic specialists and technical experts. The end application was typically a fixed solution with no fast way to adapt to changing requirements. This rigid approach has stopped many fledgling projects in their tracks, as businesses realize the end results would be a sub-par product, incapable of doing its intended task.

But it doesn’t have to be that way.

The technology that enterprises choose to develop, deploy and analyze their natural language solutions will have a significant impact on how fast they can react in the future.

Delivering natural language applications to evolve with a business requires a reliable development and analytics solution that is scalable, multi-lingual and device independent; one that can seamlessly integrate with back end systems and third party applications. It also needs to be easy to use, delivering as much intelligence “under the hood” as it does to the end user.

Developing a strong natural language foundation that benefits you and your customers today will pay dividends in the next few years. And while, if they open up their APIs, you could develop applications to work alongside the tech giants such as Amazon or Facebook, there are still several questions to be answered. The most important one is—who owns the data?

Companies that act now and develop their own natural applications will not only have a closer interaction with their customers, but will remain in control of the future of their business.


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