Key technologies that will reach mainstream adoption in the next two to five years: Gartner

Speech recognition is one of the tech that will reach mainstream business adoption in the next two to five years

Key technologies that will reach mainstream adoption in the next two to five years: Gartner - CIO&Leader

Speech recognition will reach the Plateau of Productivity within the next two years and six other technologies will reach mainstream business adoption in the next two to five years according to the 2018 Gartner Hype Cycle for the Digital Workplace.

Two to Five Years Away from Mainstream Adoption

Chatbots and virtual assistants (VAs) represent a value-added implementation of speech recognition. VAs use artificial intelligence (AI) and machine learning (ML) to assist people or automate tasks. They listen to and observe behaviors, build and maintain data models, and predict and recommend actions.

Chatbots are expected to exhibit huge growth over the next few years. While less than 4% of organizations have already deployed conversational interfaces (including chatbots), 38% of organizations are planning to implement or actively experimenting with the technology according to Gartner’s 2018 CIO Survey

Although customer service is the area that uses the most chatbots, they are likely to be deployed elsewhere in the organization. When chatbots are used as application interfaces, the working pattern will change from “the user having to learn the interface” to “the chatbot learning what the user wants.” This will greatly stimulate onboarding, training, productivity and efficiency inside the workplace. 

In the same time frame, augmented analytics and personal analytics are making analytics available to more employees, allowing everyone the opportunity to become citizen data scientists.

Augmented analytics uses automated ML to transform how data is developed, consumed and shared. Data and analytics leaders should embrace augmented analytics as part of their digital transformation strategies to deliver more-advanced insights to a broader range of users – including citizen data scientists and, operational workers.

Gartner predicts that, by 2020, due in large part to the automation of data science tasks, citizen data scientists will surpass data scientists in terms of the amount of advanced analysis produced.

Personal analytics is the analysis of contextually relevant data to provide personalized insight, predictions and/or recommendations for the benefit of individual users.

This year, citizen data science enters the Hype Cycle. It forms the foundation of next-generation analytics. “It will make insights from data science and machine learning more accessible and pervasive in the organization,” said Carlie Idoine, research director at Gartner. “Central to enabling citizen data science are the aforementioned augmented analytics capabilities.”

Gartner anticipates that citizen data science will rapidly become an important part of the way we enable and scale data science capabilities throughout the organization. Gartner also predicts that, by 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists. 

Adaptive learning platforms adjust the way instructional content is presented to users based on their responses or preferences and are used to optimize workforce digital dexterity. The technology is sliding into the Hype Cycle’s Trough of Disillusionment and is on pace to reach the Plateau of Productivity in the next two to five years.

“Adaptive learning platforms offer an important way to support and supplement workplace learning but they are difficult to implement,” said Glenda Morgan, research director at Gartner. “CIOs should approach adaptive learning projects as a large-scale curricular redesign undertaking. To this end, they should seek to identify faculty champions, find ways to incentivize the faculty, and make sure they have broad buy-in for these projects.”


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