Current trends with the Internet of Things (IoT) and artificial intelligence (AI) stand to make a sizable impact on the functionality of existing systems and the ease of incorporating new technologies. The buzzwords IoT and AI are thrown around a lot lately, but we are finally at the stage where the enterprise is affected by these trends in a big way.
Both subjects are centered on the same things: data and control. Large companies are turning toward IoT solutions because the prevalence of those devices means more control over their environment, while also yielding more data — from business intelligence to security. AI can then be utilized to transform those millions of data points into meaningful and actionable items, giving businesses that deploy these solutions more opportunities to automate different aspects of their business. This is an exciting time for enterprises because, finally, three major trends are coming together to enable enterprises to realize significant value from IoT and AI deployments.
1. The Shift to the Edge
A core purpose of IoT technologies is usually gathering vast amounts of data for processing. As processing power becomes cheaper and power consumption becomes more efficient, more and more capabilities are being pushed out to the edge in the devices themselves. This means that image or other sensor data can be reviewed locally, sending only the core information back to the central infrastructure or cloud. For example, with sensors distributed across a large campus, the bandwidth needed to stream raw data such as 4K HD video to the cloud for processing can be prohibitively expensive and lead to reliability issues. By putting AI-powered computer vision technology into the sensors themselves, only the output of the processing needs to be transferred – something that can be done at extremely low data rates and wirelessly over long distances. This shift allows artificial intelligence to handle data without that transfer, which can reduce the strain that a new technology is likely to put on an existing infrastructure.
2. Connectivity Optionality
Every application for IoT technologies is at least a little bit different and must function within an enterprise’s legacy infrastructure. Each environment may have existing connectivity options or lend itself to use of a particular connectivity technology. As a result, to be successful, IoT providers must support a wide variety of connectivity options, from wired ethernet and Wi-Fi to 4G and 900MHz. This increases complexity of device manufacture and deployment, but having that flexibility is crucial for a provider to be successful in today’s marketplace. The wide range of options for connectivity that are available for IoT means more flexibility in the actual application and better outfitting end users with the technology that will work best for them.
3. The value of open APIs
Connected IoT devices — everything from cameras to emissions sensors to smart parking systems — can generate torrents of data. However, data only has value if you have the opportunity to make it actionable and available to the people and systems that need it. Many technology providers take the perspective that data should stay within their own environment, but this is now an outdated philosophy. With open APIs, data won’t remain siloed in one system but will instead be available to the entire ecosystem within the enterprise. App developers in other divisions can discover unanticipated uses of the data, and automation can be enabled by connecting decision-making systems to the APIs containing sensor data.
For example, a stadium could issue connected cards to VIP season ticket holders that guarantee a parking place. That same card could be used as a credential to enter the parking area, automatically process the parking payment, and place an order for delivery of their favorite beer to their seats a few minutes post-arrival. Concessions and parking systems don’t usually communicate, but it is easy to imagine scenarios like this when APIs are available to make it possible. By capitalizing on these trends, enterprises can generate enormous value from the implementation of IoT and AI systems. While these individual concepts have existed on a standalone basis for a long time, only recently have they begun to converge in a way that enterprises can generate real value from large-scale IoT and AI deployments. 
