The road ahead
Yes, it’s that time of year, when we are bombarded with top-10 lists with all manner of technology predictions. Here, I will only bombard you with one single significant development for the year to come.
For the year ahead, 2020, after many years of rising expectations, we see technology democratization come to fruition in a big way. That is, users — even those with the minutest technical training — will gain access to tools and data that they will be able to put to work in their daily jobs, without the need to run to their IT departments to set things up.
Consider the forces making this democratization possible. There have been cloud solutions, apps and mobile technologies on the scene for some time now. So users have been able to do shadowy IT things, and enterprises have become accepting of that. Now, we also have a generation of so-called low-code and no-code solutions arriving on the scene, which provide a platform for non-tech types to assemble their own solutions — with IT watching the plumbing and security underneath, of course. Lately as well, artificial intelligence has been evolving as well, relieving IT departments from technical tasks and automatically provisioning technologies to those who need it, at the moment they need it.
There is also the rise of APIs, and more non-developers now work with them than ever before, a recent survey of more than 10,000 respondents by Postman, an API development firm, finds. Developers are actually now in the minority for API development — 47% of respondents identified as being either a front-end or back-end developer, the survey finds — compared to 59% a year ago. “Working directly with APIs has become part of a surprising number of positions, including non-developers such as executives and technical writers,” says Abhinav Asthana, Postman’s co-founder and CEO.
However, this doesn’t mean an entire workforce will be building their own apps anytime soon. The term used for this phenomenon, “citizen developer,” may be a bit of an exaggeration, says Ryan Duguid, chief of evangelism and advanced technology for Nintex. “’Citizens’ implies ‘everyone,’ and we’re really talking about empowering only a portion of knowledge workers to build solutions,” he points out. “We might go from two percent to 20%, but that’s still far from a majority.” Plus, these empowered end users aren’t exactly full-bore developers, as “that term implies procedures — testing, staging — as well as code.” Much of this foundational work will still be left to developers.
AI will help pave the way to increased end-user self-development and self-service as well. Parameswaran Venkataraman, chief design officer for Fractal Analytics, says many AI applications will be “augmenting and improving the way human beings work, rather than replacing their work. Therefore, focusing on the people who will use or be impacted directly or indirectly through the applications of AI, will become more important. This will mean focusing a lot more on understanding people, their current scenarios, behavior and needs, and how AI can help them in their goals. This will also mean designing AI solutions that are simple, intuitive and delightful in their experience.”
The rise of easy-to-use AI and other tech, combined with a declining fear of tech, means end users will be much less inhibited about applying it to innovation. “If you graphed ‘ease of use’ rising and ‘fear of tech’ declining, there’s a massive new space for innovation where the two lines cross,” says Duguid. “Vendors have to provide governance and management in order to support innovation at scale, but we’re approaching that nexus and starting to see the emergence of a class of people with the combination of skills and mental aptitude to drive massive innovation.”
Don’t muddy the waters with talk of DevOps or other initiatives, no matter how transformative, Duguid cautions. “If a non-tech person has to be aware of DevOps – and has to think about development, test, staging, and production — we’ve missed the point,” he says. “The person building solutions shouldn’t have to think about questions like, ‘what happens if app scalability requirements increase?’ They should be able to count on their SaaS provider to just have them covered.”
Ultimately, it’s about removing technology concerns entirely from users’ pallets, Duguid says. “The closer we can pair the person with the problem to the person with the solution, and not worry about infrastructure, scale, or error-handling, the better off we’ll be.”
Previous half-baked predictions:
2015: Cloud computing becomes just “computing”
2016: Cloud becomes corporate innovation machine
2017: The rise of the Internet of Things
2018: Cloud morphs into fog computing
2019: Artificial intelligence becomes the force that saves AI
