Published on the 07/09/2018 | Written by Pat Pilcher
Smart Bots, whatever next?…
It is not easy being a CIO. What used to be a predictable trickle of technologies has become an unpredictable flood. Enterprises are bombarded with over-hyped technologies and enough buzzwords to give even the slackest apiarists a chance at winning buzzword bingo.
So in which tech should a CIO invest? Backing the right technological horse can transform a business, sharpening its competitive edge. Choosing the wrong tech can, however, saddle a company with a bottomless money pit.
“By 2020, ordinary employees making use of insights will surpass data scientists when it comes to the amount of advanced analysis produced.”
Gartner’s 2018 Hype Cycle for Digital Workplaces aims to ease the Dilbertian-like agony of many a CIO and provide a glimpse at which technologies are going to be big for business.
Top of the list this year is speech recognition, which Gartner says has reached the ‘plateau of productivity’, where mainstream adoption starts to take off. Gartner says its uptake will hit peak adoption by 2020. According to Matthew Cain, digital workplace analyst at Gartner, speech recognition is already well entrenched and intersecting with other technologies.
“The effects of speech recognition can be seen on a daily basis. Consumers and workers increasingly interact with applications without touching a keyboard, Speech-to-text applications have proliferated due to the adoption of chatbots and virtual personal assistants (VPAs) by businesses, and consumer adoption of devices with speech interactions including smartphones, gaming consoles and specifically, VPA speakers.”
Call centres have also long used speech recognition. Looking for an efficient and scalable way for customers to self-serve as well as reducing call loads, a growing number of call centres have embraced interactive voice response systems.
IVR systems may be replacing the dreaded ‘press one for sales’ keypad maze with voice recognition, but it has also seen frustrated consumers learning that instead of stabbing at their phone’s zero key, they must instead scream the words ‘technical support’ down the phone.
Increasingly accurate and context-aware speech recognition technologies are also meeting with another tech riding high on the Hype Cycle: Chatbots or virtual assistants. By using artificial intelligence and machine learning, chatbots can, in theory, assist people and automate tasks by being able to listen to and observe interactions to build data models that allow them to recommend actions.
From a business perspective, chatbots make sense – they allow brands to personally engage at scale with people on platforms that they’re already spending time on. Chatbots are also versatile – they can be connected to a variety of data sources to deliver information and services. Where customer service gets seen as a cost centre for non-digital businesses, chatbots offer digital companies a low-cost way of enhancing their customers experience as shoppers migrate online.
Gartner says although chatbots are an emerging category, they will experience considerable growth. While less than four percent of organisations said they had have deployed chatbots, Gartner found 38 percent were planning to or were experimenting with them.
As tantalising as the upsides look, the reality is that many chatbots are as thick as a proverbial brick. Many serve up pre-scripted lines through keyword matching. According to Gartner’s Hype Cycle, it is early days, and chatbots will steadily improve, even if poorly designed and implemented chatbots have the potential to put people off using the technology.
Augmented analytics and personal analytics also found a place in this year’s Hype Cycle. Both take the arcane science of analytics and make it accessible to non-statistics boffins. Augmented analytics is powered by ML which takes the complexities out of developing, consuming and sharing data. Gartner says augmented analytics will become a crucial part of digital transformation by delivering advanced business insights to more users throughout businesses.
The analyst firm predicts that, by 2020, ordinary employees making use of insights will surpass data scientists when it comes to the amount of advanced analysis produced.
Along with augmented analytics are personal analytics. Nick Ingelbrecht, research director at Gartner, says this “is the analysis of contextually relevant data to provide personalised insights, predictions and/or recommendations for the benefit of individual users”.
While both have the potential to make insights from data more pervasive, there are pitfalls. Businesses used to analysing insights once a week/month/quarter need to adopt an entirely different approach to dealing with a constant flow of real-time data. As compelling as analytics can be, the reality is that if augmented and personal analytics do not get implemented correctly, businesses unused to handling high volumes of real-time data could find that wrong analysis will lead to more business problems.
Part and parcel of this trend, Gartner predict that by 2020 more than 40 percent of data science tasks will get automated, resulting in increased productivity and broader usage.
