AI-Powered Coding Tools Are Here to Help—Not Harm—Your Job, Insist IT Experts
Even as code development tools get more sophisticated, thanks to generative AI, vendors and other tech pros say nothing replaces the human touch
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Generative artificial intelligence tools designed to automate the process of writing computer code are unlikely to offset a shortage of software engineers—let alone put them out of a job, enterprise-technology leaders said.
Demand for software engineers, developers and programmers has long outpaced supply. In recent months, generative AI has given chief information officers and other corporate IT managers the ability to automate some tasks in the software-engineering life cycle, said Rafee Tarafdar, chief technology officer at Infosys, a business consulting, information technology and outsourcing services firm.
But AI tools aren’t yet sophisticated enough to build working business apps, Tarafdar said. While certain tasks may become outdated as AI-powered coding assistants take them over, “skilled coders will be needed to oversee generated code and documentation,” among other roles, he said.
Tarafdar said he is currently training the company’s engineers and developers to use automated coding tools, including Infosys’ internally built AI coding assistant.
Sparked in part by the popularity of OpenAI’s ChatGPT chatbot, released in November, veteran business software companies, as well as a growing number of tech startups, have been rolling out software applications over the past few months that leverage generative AI technology to write blocks of code from scratch. Trained on massive amounts of data, generative AI tools are designed to produce text, images and code based on users’ natural-language prompts.
Generative AI sales are expected to reach $3.7 billion this year, expanding by an annual growth rate of 58% to an estimated $36 billion by 2028, according to market researcher S&P Global Market Intelligence. Tools designed to generate code are the fastest-growing category, said S&P managing analyst Nick Patience. That growth reflects a dearth of software engineers, which can hinder business growth, Patience said.
Until recently, low- and no-code software development platforms, which are designed to require minimal input to develop apps, were among the few ways employers could bridge that gap, said Jithin Bhasker, a general manager and vice president at a cloud-based enterprise software firm ServiceNow. “Generative AI will empower every employee to build and deploy automation at scale,” he said.
Despite growing interest for the tools among companies across industries, it is still early days for adoption, with many use cases still in pilot. CIOs have voiced concern that tools designed to lower the bar for code creation could lead to increased technical debt and orphan code. Technical debt refers to imperfect technology deployed to meet immediate needs with the knowledge that its imperfections will require redress in the future.
Still, tech companies are moving fast to capture a share of the market. Databricks, a data-storage and management vendor, on Wednesday released a generative AI tool designed to enable employees to use natural-language prompts, rather than code, to mine a company’s data for business insights—handling a task typically left to data scientists and programmers.
But it isn’t meant to replace them outright, said Databricks Chief Executive Ali Ghodsi. By handling code, the tool allows developers to focus on more innovative, proactive projects, while employees outside of tech hubs still have access to business data without the need for special training or coding skills, Ghodsi said.
Similarly, an AI-powered coding assistant launched in March by software firm Sourcegraph is designed to answer users’ technical questions, fix bugs in existing code and generate new code. It is meant to enhance the work of engineers and developers, said CEO Quinn Slack, adding that developers will be freed up to perform higher-level projects, rather than get bogged down by endless lines of basic code.
Thomas Dohmke, CEO of Microsoft-owned coding-collaboration platform GitHub, said that more than 20,000 organisations are currently using GitHub Copilot, a code-generating tool created in partnership with OpenAI and launched last year. In March, GitHub released a ChatGPT-like version of the tool, designed to enable users to interact with the tool through natural-language prompts.
Dohmke said companies are using the new tool for everything from explaining blocks of code to proposing fixes for bugs. “Technology that is not sentient cannot replace human creativity, it can only help deliver it,” Dohmke said. “Right now, AI is really just a probability machine, a co-pilot that is symbiotically dependent on its human pilot to build the world’s software.”
Vlad Magdalin, co-founder and CEO at Webflow, which sells cloud-based software for building and hosting websites, said he has embraced the new automated coding tools. Speaking this week at Collision, a technology conference in Toronto, Magdalin said simplifying the task of writing code saves time and raises expectations of productivity for developers. “It doesn’t mean that a developer is working 30 hours fewer,” he said.
“It’s not a magical tool that removes the need for a human,” Magdalin said.
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Nvidia’s earnings will test Wall Street’s confidence in the AI boom.
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Chip makers are fighting to assure investors that the artificial-intelligence boom is racing forward. Wall Street might not believe it until Nvidia’s NVDA -0.98%decrease; down pointing triangle Jensen Huang says so.
When Huang steps up to the mic for his company’s earnings call Wednesday, he will have the world’s attention. What he says about Nvidia’s present will preview the future of AI, dictate the path forward for a tech-crazed stock market and influence an American economy increasingly tethered to hopes that the boom won’t go bust.
The $5 trillion chip maker has provided the key building blocks for AI since the launch of ChatGPT in 2022 set off a race for dominance among OpenAI, Anthropic and established Silicon Valley giants. Now, as Nvidia backstops sprawling data-center projects and an exotic money pipeline to boost chip demand, the company’s influence is arguably bigger than ever.
But there are signs of trouble ahead. Political pushback to AI is growing. A bond selloff propelled borrowing costs to their highest levels in years. The hyperscalers that include some of Nvidia’s key customers—once cash-printing machines—are relying more on debt. OpenAI recently told investors its revenue rose by a tepid 18% in the second quarter while its losses deepened.
Nvidia is increasingly stepping in to shore up potential weak points across the market. Earlier this month, the company teamed up with six of Wall Street’s biggest firms on a $500 billion AI-financing plan, pledging to backstop lending to customers that can’t afford its chips otherwise. The chip maker last week also took a stake in Cloverleaf Infrastructure, which arranges power for data centers, and struck a $6 billion deal with startup Poolside aimed at developing a powerful open-weight AI model.
After watching shares in other chip makers and the so-called Magnificent Seven tech companies swing wildly in recent months, Wall Street is hoping Nvidia can beat expectations—again. The countdown is on.
“It’s kind of becoming more and more like the World Cup final than the Super Bowl at this point,” said Brian Mulberry, chief market strategist at Zacks Investment Management. “It’s just gotten to be that big.”
The company has smashed analysts’ earnings estimates for each of the 14 quarters since the AI boom kicked into high gear. Nvidia posted 210% annual growth in net income in its last three-month period, according to FactSet, making Wall Street’s 126% projection look pedestrian.
Expectations for a blowout second quarter have risen rapidly over the course of this year. All Nvidia will have to do to beat this target: outrun 95% annual earnings growth to more than $51.5 billion. Analysts project the chip maker will report record sales of $92 billion for the period, up from a forecast of $78 billion at the start of this year.
In July, big-tech earnings sparked volatility. Concerns about runaway capital spending spread across the sector after Alphabet’s and Tesla’s results, driving a $890 billion wipeout that contributed to the unwind of hedge fund Situational Awareness. Microsoft posted the largest one-day gain in market capitalization by any company, ever, after a quarter proving that it could still show investors the money. SpaceX rocketed higher after a record-breaking initial public offering, only to see $1 trillion in value evaporate.
Surging memory prices and borrowing costs have fueled fears that those and other companies will be unable to keep plowing more money into supplies including Nvidia chips. Shaia Hosseinzadeh, founder of OnyxPoint Global Management, has recently bought dips in AI-infrastructure stocks when Wall Street has strained to absorb massive debt issued by Silicon Valley.
“The macro data is really quite robust,” he said. “Of course, there’s a level at which everything breaks.”
Investors have kept pumping money into the AI trade despite concerns around chip consumers—and to the benefit of chip producers. That is why Nvidia’s outlook for semiconductor demand could send ripples through counterparts such as Micron Technology and Sandisk, developers of the data centers in which their chips reside, and a supply chain of power producers, contractors and other specialists that underpin the globe-spanning AI build-out.
“We joke internally that we’re all Nvidia analysts now,” said David Lefkowitz, head of U.S. equities at UBS Global Wealth Management.
The irony is that investors have tended to sell Nvidia stock immediately after blockbuster earnings, with shares falling each trading session after its four past quarterly reports. Some are betting that will be the case this time around, too.
The options market is pricing in a 5.3% swing, higher or lower, in Nvidia shares during the session following earnings, according to Option Research & Technology Services. That is higher than the 4.8% average move in Nvidia’s stock over the last 12 months after the company reports quarterly results.
In recent days, some of the most actively traded Nvidia options have been put contracts tied to the stock falling from its Friday value of $214.75 to $205 and $210 apiece, according to Cboe Global Markets data. Put options give the right to sell a stock by a set price and typically represent a bearish wager.
Many analysts remain optimistic. Frank Lee, global head of tech hardware and semiconductor research at HSBC Global Investment Research, recently raised his price target for Nvidia shares to $360 from $325, citing, among other things, Nvidia’s strategic partnerships with suppliers and its role as a top contributor to open-source AI.
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