Blockchain is maturing, artificial intelligence, and machine learning is improving cybersecurity, and edge computing is seeing higher adoption rates in 2020.
Fremont, CA : It is expected that in 2020 is the year when the distributed ledger technology matures, and we witness use cases that go way beyond cryptocurrency. The areas of growth are predicted to include data security, the supply chain, and electronic health records. The use of the blockchain will grow explicitly in 2020, and the genre in which it is flourishing is supply chain and provenance. Even pharma is now looking and investing heavily in blockchain options such as drug supply chain, clinical trial data, and opiates, especially, and electronic health records. With blockchain climbing out of the hype cycle, pragmatic use cases will increase, a few of which include payment processing, equity trading, data sharing, and contract tracking and keeping as well.
AI and Machine Learning
Machine learning (ML) and artificial intelligence will be leveraged in 2020, particularly in cybersecurity, production quality, and collaboration technology, and telepresence, most of which will be initially offered as a service. According to a survey, 43.9 percent of people are looking forward to AI-enhanced cybersecurity, which is a no brainer considering the increase in the number of cybersecurity incidents. Enterprises need help to identify threats and prevent the breaches which they face due to the shortage of cybersecurity professionals; AI can help them bridge that skill gap.
The use of AI and ML in meeting or collaboration management enables the calculation of floor space needed for conferences. Also, the power usage and general viability in brick-and-mortar spaces simply put it acts as a catalyst for justifying robots and telepresence.
IIoT, IoT, Edge Computing and Automation Rise in Importance
Internet of things (IoT), industrial internet of things (IIoT), edge computing, and robotic process automation (RPA) will gain traction. Manufacturers are harnessing the power of RPA and AI for improving their product quality and fastening the production cycle. These applications will require a fast network speed that edge computing provides to process the zettabytes of data that the IoT devices are going to generate.
Organizations are already investing in compute, storage, and networking gear at the edge, which also includes IoT gateways and hyperconverged infrastructure.
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