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While generative artificial intelligence (AI) makes it possible to create computer code at the snap of a finger, handling AI-generated code effectively is not for the untrained citizen developer. Instead, generative AI has become a powerful tool for professional developers. 

"The direct impact of AI on the productivity of software engineering could range from 20 to 45 percent of current annual spending on the function," according to a McKinsey analysis. A team of analysts across the business insights company worked on the 68-page report. 

Also: How to use ChatGPT to write code

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The Intersection of Generative AI and Engineering

The surge of generative AI can harness tremendous potential for the engineering realm. It can also come with its challenges, as enterprises and engineers alike figure out the impact of AI on their roles, business strategies, data, solutions, and product development. What does the future roadmap look like for bringing generative AI into the software fold? decodes from all angles.

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Generative AI helps developers reduce time spent on certain activities, including "generating initial code drafts, code correction and refactoring, root-cause analysis, and generating new system designs." By accelerating the coding process, "generative AI could push the skill sets and capabilities needed in software engineering toward code and architecture design."

As a result, at least for professional developers, generative AI and no-code development are becoming synonymous. Both techniques provide ways to quickly generate code by specifying certain routines. But there are distinct differences between the techniques as well -- generative AI assists professional developers, while low- and no-code technology is targeted more at non-developers. 

A 2023 survey of 2,000 IT executives released by Microsoft found that 87% of CIOs and IT professionals believe increased AI and automation embedded into low-code platforms would help them better use the full set of the technology's capabilities. This is "a trend we are seeing across low-code tools," remarks Richard Riley, general manager for Microsoft's Power Platform.

"Generative AI certainly appears to be another way for code to be automatically generated," says Dr. James Fairweather, chief innovation officer at Pitney Bowes. "It's showing the potential to be a great aid in bridging the gap between the intent of a person and the computer programming required to solve a task."

However, software development is a much more complex experience than simply pumping out code, Fairweather adds. "The generative capabilities we are seeing in language and image models are a small subset of the topics that will need to be modeled for generative AI to take a larger role in automated software development," he points out. 

"Every software system has additional considerations -- like logical and physical system architecture, data modeling, build and deployment engineering, and maintenance and management activity -- that still appear to be well beyond current generative AI capabilities."

Also: How to use ChatGPT to create an app

The most compelling possibility for AI is its potential to ultimately serve "as a way to enable low-code and no-code environments," says Leon Kallikkadan, vice president of technology at Atrium. 

"I also think that as other partnerships can come onboard it will make low code and no code more of a possibility. I believe it will be a phased approach whereby as you, the human developer builds it, an AI component will start creating a vision or future step. The long-term possibilities depend on how deep the integration is, but yes, it can go that far to become a low-code, no-code environment."  

Generative AI is more suitable for development work that requires high-level expertise. "For building apps, I don't think it is as much about low- or no-code environments as we currently imagine them," says Louis Landry, engineering fellow with Teradata. "Building things always requires code. Rather, it's about simplifying and speeding up the coding process for the programmer."

Low-code and no-code technology is likely more geared towards non-coders, says Jesse Reiss, CTO of Hummingbird. "It provides organizations with the ability to reimagine business processes without obtaining steep IT expertise. This is crucial for small- to medium-sized businesses, especially during the ongoing labor challenge where they can be short-staffed or do not have the resources to support business operations."

Also: I'm using ChatGPT to help me fix code faster, but at what cost?

Ultimately, generative AI will serve to help make low-code more no-code. "One of the most significant benefits of generative AI is its ability to bridge the gap between low-code and no-code environments," says Oshri Moyal, cofounder and CTO at Atera.

"By providing pre-built models and code templates, generative AI allows developers to create sophisticated applications without requiring extensive coding skills. This democratizes the development process and opens up opportunities for a broader range of individuals to participate in building technology solutions."  

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