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‘Tech adoption to drive power shifts across industries in 2019’

By IANS
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Singapore, Nov 4 (IANS) Increased adoption of disruptive technologies will lead to significant power shifts across industries in 2019, says a new report from global ICT solutions and services provider Dimension Data.

The often referenced but rarely accomplished transformation projects will start coming to life, thanks to the maturity of game-changing technologies like Artificial Intelligence (AI), Machine Learning and robotic process automation, said the “Tech Trends 2019” report released this week.

“We’ll see the most innovative companies showing off truly impactful examples of digital transformation in action in 2019 with many more coming to the market over the next three years,” Ettienne Reinecke, Chief Technology Officer of Dimension Data, said in a statement.

“They will then become so firmly embedded in the core processes and technologies we use that we’ll consider them commonplace. 2019 is the year that trailblazers will pull-away from fast-followers and we start to see significant power shifts across industries,” Reinecke said.

The report also identified several other trends that will come to define the business technology landscape in 2019.

The exponential growth in robotic process automation — such as Machine Learning, AI, and heuristic neural networks — will give companies the ability to combine scenarios, increase understanding, and make real-time predictive decisions about their customers’ needs and behaviour, reshaping customer experience in the process, the report said.

Even as companies start subscribing to multiple Cloud platforms and increasing their use of Software-as-a-Service (SaaS), Cloud-based security providers will gain more traction in 2019, according to the research.

In the coming year, applications gathering input from users and making changes to their own functionality to improve the user experience will become a reality, said the report.

–IANS
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(This story has not been edited by Newsd staff and is auto-generated from a syndicated feed.)
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