While some business leaders are just starting to see the performance potential of the combination of Artificial Intelligence and the Internet of Things – the Artificial Intelligence of Things, or AIoT – others are already beginning to put it to use. According to a recent global study from IDC of 450 business leaders across major industries, AIoT is making a faster and greater impact than expected.

Study respondents report that not only is AIoT already generating results, but for organisations that are pursuing an IoT strategy, they say they cannot compete effectively without using AI.

Those who have developed an AIoT capacity report much stronger results across a number of critical organisational goals – everything from their ability to speed up operations and introduce new digital services, to improving employee productivity and decreasing costs. In every case, there are double-digit percentage differences between those who say they are achieving significant value, and those who aren’t – with AI making the difference.

In the recent IDC study, it’s clear that implementing IoT solutions in isolation is imperfect. Without seriously considering strategies around managing the considerable data produced, gaining maximum benefits from the technology will represent a serious challenge.

Chetan Gadgil, Director of IoT at Intel, summarises this perfectly, “In an IoT environment, AI closes the loop. At that point you have the data, and you have AI capabilities learning from that data, and ultimately automating important choices and actions…AI integration is key because these phases require significantly stronger analytical capabilities.”

Once you have the AI capability to analyse the data collected via IoT technology, it becomes a much more appealing prospect to businesses. In fact, many of the successful IoT implementations currently in place today are actually AIoT operations, demonstrating the advanced power and opportunity of combining data and intelligence into something much more effective.

To be clear, the decision to implement AIoT is almost exclusively related to business initiatives, and not technology initiatives, with a focus on achieving higher levels of operational efficiency, enhancing customer engagement and experience, and improving top-line growth.

Companies that rely on IoT data to inform day-to-day decision-making use it overwhelmingly for operational decisions (68%), using spreadsheets and other non-AI technology. Only 12% of respondents use such data to inform planning decisions. However, when AI enters the picture, the number of respondents using this data for day-to-day planning nearly triples, increasing to 31%.

While there are a wide range of business goals for IoT initiatives, increased revenue tops the list for senior leaders across geographies, industries and companies of all sizes. Jason Mann, Vice President of IoT as SAS, states “We see huge implications for efficiency with the IoT, but at the same time we are very aware that company leaders are facing huge pressure to deliver top-line revenue growth…those who are responsible for combining AI and IoT capabilities for their organisations would do well to remember this as they develop their long-term strategies and continue down the path to implementation.”

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As with any new or swiftly advancing technology, adoption tends to pick up speed when proven commercial solutions become more widely available – particularly those that target repeatable, known problems or opportunities. While combined AIoT solutions targeting specific, clearly defined challenges are not yet broadly available, they’re on the way, and will accelerate the pace of AIoT adoption across all industries.