These Four Tech Trends Will Dominate Enterprises in 2020
A brave new world, one where robots, artificial intelligence and edge computing do even more of our thinking for us, has arrived.
For both people and companies, more challenges and missteps will arise as we adopt and adapt to new technologies at an astoundingly fast rate.
AI is better than humans at several tasks. Content identification and searching, image recognition, and transformation of unstructured to structured data are all in the wheelhouse of AI.
Throughout 2020, ITWorldCanada.com predicts that both the enterprise and the public sector will apply AI to address challenges such as data privacy, cybersecurity, and ethical risks.
Enterprises should learn to crawl before they walk, however. Institutions hoping to make use of big data are advised to start with data lakes as what Scott Mullins calls “a stepping stone to the development of AI and machine learning, allowing data to be secured in its original form and then cataloged, and indexed.” Mullins is the head of worldwide financial services and business development for Amazon Web Services.
Recognizing the challenges in enterprise’s adoption of AI, PWC has come up with five insights into how business and tech executives can benefit from AI.
Edge computing chips bring more computing power to devices. The chips allow the devices to perform complicated procedures independently, even if they lose connection with their network.
Small enough to be integrated into handheld devices and non-consumer devices (think robots), the chips do the work that used to require hundreds of traditional chips that took up more space while delivering better usability, speed, data security, and privacy. Machine learning tasks are performed and/or accelerated on the device rather than in a remote data centre.
In the next year, an increasing number of AI chips will find their way into an increasing number of consumer devices, including high-end smartphones, tablets, speakers, and wearables. Deloitte predicts that enterprises will find many applications for the technology in robots, cameras, sensors, and other IoT devices. Edge AI for enterprises includes autonomous drones capable of navigation and obstacle avoidance in real-time and completely on-device with no network connection.
Through IoT applications, companies can significantly increase their ability to analyze (not just collect) data from connected devices and convert this analysis into action while avoiding the cost, complexity and security challenges of sending vast amounts of data into the cloud.
Issues that edge AI chips can help address include: data security and privacy (by allowing large amounts of data to be processed locally), low connectivity (internet connection is unnecessary), (too) big data (by analyzing data in real-time, a device can transmit only what is relevant for further analysis to the cloud), power constraints (by allowing even devices with small batteries to perform AI computations), and low latency requirements (by performing AI computations on the spot).
“Smart machines powered by AI chips could help expand existing markets, threaten incumbents, and shift how profits are divided in industries such as manufacturing, construction, logistics, agriculture and energy,” reads Deloitte’s report Technology, Media, and Telecommunications Predictions 2020. “AI chips will be necessary for video monitoring, virtual reality, autonomous drones and vehicles, and more, bringing the intelligence to the device.”
Automation & the rise of service robots
The enterprise robotics industry serves two markets: industrial and professional services. The market for service robots has been gaining steadily.
The mechanical arm is an example of a typical industrial robot. Professional service robots are mainly used outside of manufacturing to assist humans. Many are designed with wheels to make them mobile. So far, pro service robots have been most popular in retail, hospitality, health care, and logistics (warehouses and fulfillment settings) industries, as well as space and defence, agriculture and demolition.
Fueled by 5G and AI chips, professional service robots’ applications are expected to improve and increase. Deloitte predicts that a new generation of more capable and flexible robots will increasingly impact decisions about where to manufacture goods, which goods to manufacture, and how to cope with the challenges of scarce or high-cost labour.
2019’s LifeLabs data breach was one of the worst in Canadian history and marked a record year for cyber attackers. And things likely aren’t going to get better.
In 2020, we’re likely to see more attacks using combined tactics, says Ed Dubrovsky, managing director for incident response at Toronto-based Cytelligence.
Unfortunately, many firms remain complacent in the face of imminent danger. Cybersecurity experts encourage businesses to take threats to the privacy of their client, customer, and employee data more seriously.
Fernando Montenegro, a Toronto-based information security analyst at 451 Research, expects to see more companies decentralize the work of cybersecurity. “If you look at how teams are looking to deploy modern solutions, they are doing it in a decentralized fashion, by decentralizing the work of cybersecurity,” he said.
More cybersecurity functions will be outsourced to machine-learning and AI due to a skills shortage as colleges and universities struggle to churn out enough people with cybersecurity skills, notes Howard Solomon at ITWorldCanada.com.
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