The tech landscape evolves at a breakneck speed, with constant technological innovations impacting the way business is conducted across every industry. Organizations are now focusing on collecting data through the Internet of Things (IoT) and analyzing it with machine learning to create efficiencies at all stages of the business process, from more precise manufacturing to upgraded customer service. With this increased ability to leverage data analytics has come huge demand for tech professionals with the skills to use the IoT and Artificial Intelligence (AI) to improve business. Read on to learn how the IoT, AI, and machine learning are shaping businesses and the future of IT.
The IoT has revolutionized the way organizations collect data, putting a massive quantity of information at their fingertips. Businesses across the globe have realized the power of this amount of data, and the International Data Corporation projects that IoT hardware will be the largest technology category this year. Furthermore, Gartner predicts that by 2020, IoT technology will be incorporated into 95% of electronics for new product designs as a result of consumer demand for the level of user monitoring and control that such features provide.
AI, in turn, is the key to unlocking the potential of the IoT. As a part of AI initiatives, machine learning identifies patterns and anomalies in the large data sets that IoT provides in order to create more accurate predictions. In fact, Gartner predicts that by 2022, more than 80% of IoT projects will incorporate AI, a significant rise from only 10% in 2017. The growth of AI isn’t only seen in established companies that are using the technology to analyze their data; it’s also a cornerstone of the startup market, as startups focused on creating and leveraging AI systems have increased three-fold since 2010.
Organizations’ data analytics teams are using large swaths of IoT data and the analytical capabilities of machine learning to make better business decisions and facilitate faster growth. The use of AI is creating new predictive features that can filter through past data to more accurately predict future behaviors and impact. This type of analysis, previously a part of more general business intelligence initiatives, can now be done on a massive scale. Machine learning can turbo charge analytics dashboards, processing a much wider array of data much more quicklythan was previously possible to create more accurate forecasts and analysis.
“With rapid improvements in machine learning tools and techniques, we can now solve tough problems quickly, specifically with existing models in the cloud. However, many businesses leaders remain unsure of how this can be applied in specific situations. We use a simple framework to find use cases for specific organizations. We will soon see better, more effective business processes and customer experiences across the board.” – Chuck Chekuri, Data Science Executive
These developments have turned business intelligence from static reports into living dashboards where analysts can investigate trends and causes in order to more effectively grow their businesses and improve their products. This is driving a trend towards more data-driven decision making, and companies doing so are proving to be both more profitable and more productivethan their competitors. Organizations are more able to utilize strong business analysis than ever before, all facilitated by IoT and AI. This focus on data analytics as the core feature of business intelligence is at the heart of the future of IT.
With the industry in the midst of an IT talent shortage, professionals who are well-versed in the most in-demand areas, like those affected by these emerging technologies, are among the hardest to locate and hire. There has been tremendous job growth in these sectors, and Machine Learning Engineer, Data Scientist, and Big Data Developer all rank in the top 5 of LinkedIn’s Top 20 Emerging Jobs. A wide variety of tech professionals with skills in development, hardware, analytics, and security are required to fill these positions, and it has become difficult for many employers to fill positions for IT Engineers, AI Specialists, and other critical roles that contribute to their data and machine learning initiatives. As 45% of organizations see the skills shortage as a challenge for deploying IoT technology, it is clear that those who lead the future of IT will be the organizations who are able to secure the talent they need to execute on their data analytics strategies.
Businesses who are effectively able to capture the insights these technologies can provide will be the most likely to thrive moving forward. Leveraging the data that the growing IoT collects through machine learning facilitates better decision making and ultimately greater growth and profit for companies who remain on the cutting edge of technology. As businesses move toward this goal, their hiring strategies for attracting the top tech talent necessary will be a critical component of long-term success.