The Future of Work Tech: Intelligence, Automation and ... Virtual?
At the start of any new year, the pundits come out of the woodwork with their predictions for the next 12 months. I'm as guilty as the next, as you will see later in the article. So on this, the last day of January 2023, I turn to an even bigger topic: "the future of work technology," and namely, where intelligence, automation and virtual environments fit into that future. Let's address each of these in turn.
Adding Intelligence to the Workplace
What does it mean to add ‘intelligence’ to a process or to software? We often talk about making something smart, so how do we do that? A variety of artificial intelligence technologies (AI) are available to add to applications, depending on the business process and the outcomes you are trying to improve. Generic use cases might be found in the legal industry, where they want to process text in legal documents. Those in the insurance industry may want to focus on automated processing of images attached to insurance claims as evidence. People working in physical security may turn to AI techniques to help automate their analysis of video feeds or files, for capabilities like face recognition.
Most people understand that the term AI does not mean a “general artificial intelligence” like HAL 9000 in "2001: A Space Odyssey" or Skynet in "The Terminator" films (thank goodness!). The application of AI technologies like deep learning, machine learning (ML) and natural language processing (NLP) provide ‘intelligence’ to a very specific task or step of a process, which may be a small slice of your overall business process. In fact, within an overall end to end business process, you may apply different types of AI, from different vendors, at different points.
As AI is now no longer new and mysterious, a lot of the focus is on improving algorithms and improving their application to particular business problems. As such, the application of AI in the workplace is going to get broader, more common and become a standard part of our toolkit for solving business problems. All of this requires the creation of new roles and acquisition of new skills — so do you build your own team of data scientists to develop custom machine learning models? Or do you acquire those from third parties — or rely on vendors? Either way, my expectation is that our business processes are increasingly going to have some intelligence embedded in them. And while AI is never perfect, an 80% success rate in a given task is worth the effort.
Related Article: The Intelligent Digital Workplace Is Already Here
Automation Builds Efficiencies Into Workflows
Automating business processes is a key method to improve process efficiency. An example of early automation includes the efficiencies of central scanning centers, where giant scanning machines digitized paper documents rather than having humans rekeying data from the paper into software. We have come a long way since then, with complex middleware running on servers in our data centers orchestrating the automation of business processes for the back office, all the way to tools which allow business users to automate their daily tasks and the more recent advent of robotic process automation (RPA) — having software carry out what were often highly repetitive manual tasks. However the global pandemic, the great resignation, the phenomenon of quiet quitting and a very, very competitive talent market have recently brought automation into focus as a way to mitigate these factors or influences.
Automation is, much like intelligence above, a very broad topic area, with many aspects to it. Its importance will only grow, regardless of what form it takes — whether it's the connectivity between different applications based on their APIs and data and metadata standards, the ability for business teams to create solutions using No Code/Low Code solutions to automate front end processes, or the increased use of RPA to tackle more sophisticated use cases. Going back to the previous topic, AI can be an enabling technology for the various automation technologies, or vice versa. Your industry and your business goals will dictate where you put the most effort, and where you put scarce investment dollars, so a full evaluation of any automation tools and platforms you're considering will be necessary to make sure they can provide the business outcomes you want.
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Virtual Environments Remain Niche While AR Grows
In terms of virtual environments, my first reaction is to roll on the floor laughing. Sorry Mr. Zuckerberg, but I really don’t see the metaverse taking over a business environment were I join my colleagues for a business meeting via avatars (that don’t have legs). I am old enough to have worked at the Open University in the UK during the early 2000s when a lot of effort was put into teaching classes in Second Life and in providing the tens of thousands of distance learning students with a virtual campus. And while I believe that campus still exists, Second Life did not replace normal synchronous and asynchronous learning.
A lot has changed in the 20 or so ensuing years. As a grumpy old man, I admit I am possibly wrong about the metaverse. But the value so far has been found in the use of the (slightly less immersive) augmented reality (AR) technologies. From healthcare to aviation, to architecture practices and civil engineering, there are truly valuable applications of AR, which uses displays in glasses or goggles to put a virtual overlay on the real world — whether that is a virtual map of pipes inside the real wall in front of you, or access to instruction manuals and graphics/videos of how to vent and drain that wing fuel tank in your Boeing 777.
So virtual environments have their place, but personally I think they are going to remain niche for quite some time when compared to the application of AI and automation technologies.
And finally, a caveat: I don’t have access to a crystal ball, and I could be wrong. I come at things from a very data and information management/governance angle, which leads me back to my confession in the opening paragraph: my 2023 predictions conversation with the CEO of Shinydocs, which you can read here.
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About the Author
Jed Cawthorne is principal evangelist at Shinydocs, focusing on spreading the message of the benefits of good data and information management. Jed has over 20 years experience in information and knowledge management, and over 25 years in IT.