Everyday AI – it’s not just about robots

We live in an age where, according to Gartner, in just one year AI will be taking on many of the mundane tasks in our lives.

Digital assistants – such as Microsoft’s Cortana, Apple’s Siri and Google Now – might not yet be able to take out the rubbish or wash the dishes but they can recognise voice instructions and connect different search terms with sophisticated data sets to offer users relevant information. This autonomous or artificial intelligence (AI) – or in-app AI – will take the Internet of Things (IoT) to a new level.

I hate to break it to you but we’re not quite living in an Isaac Asimov novel just yet – no robot butlers I’m afraid. While we still have to stack the dishwasher and empty the bins, AI in the form of sophisticated decision-aware software will, however, sit on our smart devices doing increasingly clever things.

What exactly these things are is still up for debate but voice-powered assistants will soon be able to decide for themselves when to serve unsolicited, context aware information. This version of AI will bring with it a wealth of business opportunity and Gartner predicts that AI-powered digital assistants will vastly improve consumer shopping experiences. With this in mind, companies should start to plan how they will bring their employees and customers the benefits in productivity and information access it provides.

Cortana - more than just your digital friend?

The Internet of Things today is based on data capture and connectivity: predetermined rules are then used to put that data into action. Apps act as the intelligent plumbing for that data. The next step, and one expected to happen within a year, is the ability for digital assistants to take on mundane everyday tasks such as grocery replenishment and filling out forms quickly.

While this is great and a significant time saver, I always hoped for more from AI and I’m sure you did too; thankfully it doesn’t look like we’ll be disappointed. Soon, the likes of Siri and Cortana will positively and autonomously generate the next decision or suggestion for us, unprompted. This might be in the form of an alert when a road block could mean a missed flight or a helpful reminder to take your umbrella in the morning because that sunny sky isn’t likely to hold up past lunchtime.

While this may happen to some extent today, this autonomous decision-making will be on a grander scale and involve many independent and complex data-sets, analysed in unison, and acted on dynamically based on user preference.

AI means business

Gartner also predicts that in 2016 digital assistants will be responsible for $2 billion dollars’ worth of autonomous purchasing decisions annually. This translates to 2.5 per cent of mobile users spending at least $50 a year through buying services via a digital assistant app. For businesses, the opportunity to collaborate with those in the supply chain to deliver ultra-personalised, real-time offerings from which AI-powered assistants can choose is enormous.

This may mean that businesses build their own digital assistants and platform offerings or chose to integrate their data with existing or new AI tools and offerings. While there is no guarantee that such offerings will be selected by such an advanced search and decision engine, services will need to be available and readily marketed. Internal business apps may perform in exactly the same way. Digital assistants have the ability to serve up the right information for employees, software suggestion or calendar invite reminder based on the user’s interaction with their smart device.

These benefits will increase productivity for consumer and employee alike, building a compelling case for internal apps as well as introducing a new marketing avenue to capture additional revenue streams.

What can developers do to prepare for this AI-driven future?

The first step is to grow comfortable and adept at dealing with large-scale datasets, how these interact, integrate and can be used to scale with sophisticated tools. In fact, a recent global survey of developers commissioned by Progress and undertaken by Harbor Research found that 30 per cent already experience data overload and feel overwhelmed trying to manage it all for contextualised IoT apps.

It’s not just about understanding large pools of disparate data independently, rather how they relate to and can be integrated with one another. Externally there are experts on hand to help with data processing and integration.

Technologies such as Hadoop and NoSQL provide platforms to enable scalable, flexible, cost effective, rapid and resilient solutions. Many organisations will have a combination of both structured and unstructured data.

Prepare for the AI future today

The opportunity that AI brings to better engage consumers and employees alike for productivity or buying benefits are plentiful. To reap the benefits sooner than later, businesses and the developers need to prepare for an AI eventuality. The keystone to ensuring businesses are as prepared as possible for the AI trend will be the ability to set a strategy for managing data and use the right tools for doing so.

There is a race to figure out how to use complex data for sophisticated and autonomous decision engines begins now. Competitiveness and innovation will depend on the ability to find a solution to this as soon as possible.

Mark Armstrong, VP & MD EMEA, Progress