CIOs assess generative AI's risk and reward for software engineers
There's tremendous hype about the potential impact of generative artificial intelligence (AI) tools in software development and engineering.
Some experts believe these tools cloud boost productivity by reducing the repetitive tasks that slow IT professionals down.
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Other experts believe the rapid rise of generative AI could mean the end of software development and engineering as we know it.
So, what's the truth?
Jarrod Phipps, CIO at auto specialist Holman, says a sense of perspective is crucial.
Yes, generative AI tools, such as OpenAI's ChatGPT and GitHub Copilot, have the potential to transform the work activities of developers and engineers.
However, that transformation isn't going to happen overnight. What's more, these AI tools won't work in isolation but will instead generate benefits as an adjunct to human IT professionals.
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"I call it an exoskeleton," says Phipps, who talks with ZDNET about the potential impact of generative AI. "It makes you stronger, faster, more agile. The way AI could wrap around all the pieces of our business is an exoskeleton that makes people better at what they do. Generative AI is not necessarily a direct threat, it's a compliment. And we want to wrap an exoskeleton around our developers to make them more efficient at writing code."
While some generative products can already write code, Phipps is not focused on the ability of these tools to provide an all-encompassing approach to software development.
"I'm interested in how these tools can help guide the development process, so the developer is still in full control and has some level of creative responsibility," he says.
Phipps says the idea of a personal assistant for software developers is a "no-brainer" for most enterprises.
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At the other extreme, he says the thought of letting AI go off and write code by itself is simply a no-go: "I'm not necessarily sure when generative AI is going to write all our code. In fact, I don't see a time when that would happen."
Mukul Agrawal, director of technology at Vistaprint, has a similar view: "Never think about AI replacing people. Some of the tasks might get replaced, but not people."
Agrawal explained to ZDNET how he -- like every other IT professional right now -- is trying to figure out what AI means for developers and engineers.
"My two cents is that AI will have its own space, and some of the mundane tasks will go away," he says. "And then our teams will have the opportunity to focus on higher value work."
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Agrawal says big tech-focused organizations like Vistaprint will eventually benefit from AI-enabled software development and engineering -- but not yet, and the explanation comes down to key reasons: costs and risks.
In terms of costs, he says businesses will need to see a return on investment: "You have to really think about the long-term value of any investment in this space."
When it comes to risks, Agrawal says Vistaprint must be careful about data privacy.
"Given our business has so much secret sauce, we worry about it, because anything that goes to ChatGPT is being fed into a public system," he says. "You cannot use those tools for your secret sauce."
Avivah Litan, distinguished VP analyst at Gartner, also recognizes that while generative AI could lead to code-generation productivity increases, there are also significant challenges that need to be overcome before the tools can be used in an enterprise context.
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"You have three main risks," she says. "Number one, your code is full of bugs, number two, your code is full of vulnerabilities and security errors, and number three, you're infringing on someone's licensed code."
Litan told ZDNET in an interview that now is the time for senior managers to start talking with their personnel about how generative AI might be exploited safely in the longer term.
"Companies need to spend time educating their personnel, including their developers, about the opportunities and the risks," she says.
While most CIOs are choosing to keep generative AI tools away from production environments, it might not be long before IT professionals start using generative AI for disparate elements of the software development and engineering process.
"The main message I have is to get your staff up to date and put the resources into training, and then take advantage of it," she says. "It's incredible what you can do with code generation now. I could build an entire application without knowing any JavaScript or how to code. But you must be educated on all the pluses and the minuses -- and that doesn't happen overnight."
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That's a sentiment that resonates with Omer Grossman, global CIO at CyberArk. In an interview with ZDNET, he suggests now is the time to start exploring generative AI.
"Leaders should make decisions," he says. "And I'm emphasizing that point because if you don't make any decisions because you are risk-averse, you risk missing out."
For business leaders who are thinking about how to use generative AI in areas such as software development and engineering, Grossman suggests a range of steps. "The first thing is to make sure you build responsible guardrails that promote innovation while keeping it secure," he says.
At CyberArk, Grossman has put in place a framework and guidelines that are adjusted as new challenges and opportunities in AI emerge.
"I decided we will promote innovation no matter what, but we'll do it responsibly," he says. One of the key supporting elements for this approach is a cross-organization tiger team, which meets on a bi-weekly basis to discuss new developments and potential implications.
"You need to make sure this team is not only full of tech guys, but also legal, because there are some fresh risks you need to mandate," Grossman says. "Having a bi-weekly meeting ensures you don't have a backlog that's big and that you're responsive to the requests for AI as they evolve."
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Grossman says generative AI vendors will continue to push out new services and features -- and business leaders must develop a strategy that gives professionals in key areas, such as software development and engineering the opportunity to explore the tools safely.
"Every time OpenAI or Microsoft comes up with their next product, we get many requests -- everybody wants to experiment," he says. "You must be responsible for the education of employees. As an executive, you must be more agile in the way you think and less waterfall-like. And generative AI is a great example of how that approach can pay dividends."