Written by Mary Shacklett.
Many new technologies launched in 2018. In 2019, look for the refinement of those technologies as well as new technology to launch.
Here are eight emerging technology trends that we can expect to see more of in 2019.
1. Citizen development
Expect citizen development, where business users develop their own applications so that they don’t have to wait for IT, to grow in 2019.
“In 2018, we saw enterprises talking about citizen development more, and we see the adoption rate increasing, with most organizations in an exploration stage,” said Cory Phillips, executive VP at Crowd Machine, which provides low and no code software for citizen developers.
2. Drones and drone ops centers
Although drones are still highly regulated and limited in what they can do in the US, more companies will start using drones—and even establish drone operations centers with managers and pilots. The companies most likely to use drones will include those with logistic challenges such as areas of terrain that are risky or difficult to traverse or agencies and/or insurance companies that need to oversee disaster and accident sites. If a company wants to fly its own drones, it only requires a $150 fee per person to take and pass certification at any FAA test site.
3. Virtual workers
For years, IT has used consultants and contract programmers to make up for staff talent shortfalls. With talent shortfalls so acute in areas like data science, analytics, security, etc., there will be a continued move toward virtual workers who aren’t employed by the company, but who work on a retainer basis that guarantees a certain number of these specialists’ hours per month to the company. In this way, IT has guaranteed access to expert services, which might not be able to afford or gain access to otherwise.
4. Self-powered data centers
We’ve seen data centers get greener through the implementation of virtual servers and storage, energy efficient buildings, and greener HVAC. In 2019, we can expect to see the results of early data center pilots that take the data center entirely off the energy grid, with data centers actually running its own self-contained power plants.
5. Cloud-independent edge computing
Age-old distribute computing will make a comeback as companies realize that the computing they are moving to at the edge is actually run more efficiently locally and on real hardware—and not on the cloud. Don’t worry: Cloud will still play an important role in collecting and consolidating data from these remote processing outposts.
6. IoT integration
One year ago, 82% of respondents in an international Forrester IT survey said that they were unable to identify all of the devices connected to their networks. Of respondents, 54% were nervous about device security, and 55% were concerned about integration. More organizations will proceed with IoT implementations in 2019. An emerging concern will be how well different IoT devices from varying vendors can interoperate. IT wants a single plane of IoT management. Can vendors deliver?
7. More self-service IT for business users
2019 will be a year of IT innovation designed to build more trust and collaboration between IT and end users. One strategy that several companies tried out in 2018 was the idea of a self-service kiosk filled with IT tools, apps, and resources that users could choose from. Already vetted for proper access, clearances, and security, the self-service IT kiosk would enable users to log on and choose what they want for the apps that they build. Look for more companies to try self-service IT in 2019.
8. Convergence of AI, machine learning and deep learning
In 2019, there will be continued progress toward the integration of AI, machine learning, and deep learning in business applications. AI will deliver first-line-of-response business insights from data is analyzed with a baseline of algorithms. As computers and other mechanized appliances observe anomalies that conflict with baseline assumptions, they will refine their knowledge bases with the help of machine learning. If the insights yielded continue to be incomplete, they will invoke a deeper set of algorithms known as deep learning to operate on the data. The goal is greater accuracy of AI at all levels by getting AI and learning technologies to work together for best results.