Two of the most significant advancements in technology in the last decade have been IoT and artificial intelligence (AI). Wired mentions that recent investment within the corporate arena has seen businesses exploring the use of AI alongside IoT deployments. There has been a lot of publicity about AI working hand-in-hand with IoT. Opinions have centered around the inseparability of these emerging technologies. Businesses that have sought to adopt IoT have leaned towards AI when it comes to processing collected data. However, do these technologies need each other to work, or can they be implemented separately just as effectively? For more answers on the above, check this link.
Artificial Intelligence as an Innovation
AI has been a part of popular culture since the fifties, with the wide circulation of science fiction. While today’s systems are a far cry from Arthur C. Clarke’s HAL 9000, they are far more practical in the things they can do. Their prevalence in business applications has led to a change in how companies interact with their consumers. Information Age mentions that businesses are adopting intelligent automation and machine learning in several aspects of their operations. From customer experience to business analytics, enterprises have embraced the benefits that AI has offered them to help grow their companies. With each day, the quality of AI improves as the machines learn more about their functions.
IoT in Enterprise
Businesses have already started adopting IoT for the collection of data and monitoring of states throughout their supply and distribution networks. McKinsey notes that 98% of subjects in a recent survey cited the implementation of enterprise IoT initiatives for a wide range of applications ranging from service provision to increasing insight into operations. Currently, IoT devices have been used with some success in supply-chain management and insurance industries. Most commercial sectors have seen an emergence of IoT in one form or another over the last five years, and this trend is likely to continue well into the twenty-first century.
Giants of Emerging Technology
Future Mind mentions that the most business investment into emerging tech has gone into IoT, with AI following close on its heels. Both of these emerging technologies can be used alongside each other. One of the most common uses of IoT is data collection. However, with the sheer amount of incoming data, human researchers and data scientists can’t derive any meaningful insight within a reasonable time frame. AI and machine learning come to the rescue, allowing data scientists to automatically clean, process, and categorize data, and then suggest possible action based on the results. However, this application is only the start of what is possible.
Artificially intelligent IoT devices would need a lot less human interaction. Forbes terms this the “Artificial Intelligence of Things” (AIoT), and the premise has a vital impact on how businesses use IoT in the future. From automatic retail outlets that leverage AI to use facial recognition to charge users’ accounts directly to the management of vehicles and, soon, autonomous fleets, the AIoT can be a disruptive force to how things have been done traditionally. IoT’s real power can be unlocked by the strategic implementation of AI to utilize the data that the devices generate.
Enterprise Accessibility For Integration
Knowing that IoT and AI are stronger together is one thing, but how easy is it to integrate these systems? Emerging technologies have a reputation for being difficult to work with because of a lack of documentation. However, neither AI or IoT are brand new technologies anymore. Cloud providers like Azure, AWS, and Google Cloud already offer interfaces for both IoT and Ai applications to run natively in the cloud. Easy implementation removed one of the most significant hurdles preventing widespread adoption of enterprise-level AI and IoT systems working alongside each other.
A Necessary Union?
IoT in and of itself is an independent technology. It works by collecting data to inform other connected devices and doesn’t require AI to function correctly. The same could be said of artificial intelligence – it may be implemented as a stand-alone system without the need for a data collection service. However, utilizing a system that combines both of these technologies can be a boon to business. The ability to use IoT data collection effectively to generate timely insights falls heavily on the use of AI. Machine learning is, similarly, important to applications such as speech and facial recognition. Smart implementation of AI and IoT increases business efficiency and allows it to avoid unplanned downtime.
IoT doesn’t necessarily need AI, but the integration of both systems can benefit an enterprise immensely. Companies that are looking to develop more robust systems for dealing with their data analysis would do well to explore creating frameworks that integrate both of these technologies. Together, they might even point businesses in directions they might not have otherwise considered.
