Generative artificial intelligence (gen AI) paves the way for anyone to become their own software developer. But at the same time, AI can make many extraordinary skills redundant.
That’s the word from Babson College’s Thomas Davenport and Ian Barkin, a venture capitalist, in their latest book, All Hands on Tech: The AI-Powered Citizen Revolution. To start, they point out that with low-code and no-code tools, robotic process automation and now AI, the gates of software development are open to everyone.
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“Technology is no longer owned by one specific functional department,” they explain. “Data and its analyzes are no longer the property of PhD students and the hard-core number crunchers. From now on, all employees have the opportunity to be system designers, data analysts, coders and makers.”
Davenport and Barkin note that generative AI will take citizen development to a whole new level. “The first is through conversational user interfaces,” they write. “Virtually every software vendor today has announced or will soon announce a generative AI interface.”
“Now or in the very near future, anyone interested in programming or accessing/analyzing data need only make a request to a plain language AI system for a program that contains a set of specific functions, a automation workflow with key steps and decisions, or a machine learning analysis involving certain variables or characteristics.”
As the authors mention, part of this future – not yet fully formed – involves specialized bots designed to perform specific types of work. “There are digital workers from RPA vendors and other start-ups who claim to do a lot of work, even though our research so far shows that in reality they only perform a few tasks and are certainly less flexible than human workers.”
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This includes emerging software development bots, which vendors claim can “write software programs from start to finish,” Davenport and Barkin say. “Our assessment is that these bots will be able to make human citizens more productive in the coming years, but will not replace them.”
Gen AI will feel like the ultimate research assistant or programmer, she added, “because it generates code for this analysis. It will elicit what you want, work very quickly and allow you to change your mind an infinite number of times when specifying of your app. automation or model.”
“Gen AI will also make it easier to find existing models, features or software components that you can use to start your citizen project,” they conclude.
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Looking beyond this early start, with the growth of AI, RPA and other tools, “some citizen developers will likely no longer be needed, and every citizen will have to change the way they do their work,” Davenport and Barkin speculate. Gen AI will take on much of this work, including application code generation, automations, and data science analytics.
Dominic Ligot, CEO and CTO of CirroLytix, echoes Davenport and Barkin’s observations in a recent HackerNoon article, noting how he enabled semi-technical individuals in a class to use data science tools:
“The participants, mainly CISOs who typically do not code, found the exercises, created with the help of AI, intuitive and hands-on. My goal was to immerse them in working directly with data and code. They especially appreciated the opportunity to manually explore what modern cyber threat monitoring and SIEM platforms typically automate, giving you insight into the processes happening ‘under the hood’.”
At the same time, Ligot also suggests that citizen developers and data scientists don’t necessarily need technical skills, as AI takes on much of this work. “My key teaching experience was surprisingly counterintuitive: data science, as we know it, will eventually be replaced by AI,” he said.
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“The emergence of AI-driven tools that can handle data analysis, modeling and insight generation could force a shift in the way we view the role and future of data science itself,” Ligot said. “Tasks like data preparation, cleaning, and even basic qualitative analysis – activities that take up much of a data scientist’s time – can now be easily automated by AI systems.”
“What’s worse (or better, depending on where you stand) is that AI is faster, more accurate, and less prone to human error or fatigue.”
Still, it will take time to reach the point where development and data science are delivered seamlessly via AI, Davenport and Barkin clarify. “It seems likely that gen AI and conversational AI will broadly form the front-end for all citizen applications in the future,” they say. “That’s possible with many tools today, but it takes at least some level of sophistication to create prompts that give you the first impression of an app, a data analysis, or an automation workflow that you want. for code generation, and it’s one of the reasons why experienced programmers have better luck than inexperienced ones.”
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However, they continued, “within a year or two it will be possible to have an iterative discussion with a generational AI interface over a machine learning analysis.”
