AI: Software's Disruptor or Rebirth? Investment Opportunities Emerge
When MTV launched in August 1981, its inaugural music video, The Buggles’ “Video Killed the Radio Star,” was a cheeky yet prescient nod to the seismic shift ahead for the music industry. Album sales might have dipped, but video play surged, birthing new stars, expanding distribution, and ultimately consolidating record labels. Decades later, despite initial resistance, the rise of streaming further propelled the industry, adding billions to the pockets of artists, producers, and record companies alike. This historical parallel now resonates deeply within the software investment landscape, as OpenAI, with its disruptive ethos and ubiquitous ChatGPT chatbot, emerges as the “MTV of artificial intelligence.”
The recent launch of GPT-5, hailed by OpenAI CEO Sam Altman as its most powerful version yet, has amplified concerns. Capable of complex tasks like coding, speech reasoning, and writing, GPT-5 represents a significant stride in AI development. Jordan Klein, a tech sector specialist at Mizuho, was blunt in his assessment, noting that the new version’s advanced coding and design features “added gasoline to the dumpster fire” of AI engines, agents, and co-pilots now rapidly transforming established front-office and development operations.
This apprehension is clearly reflected in the performance of major enterprise software companies. Salesforce shares have plummeted over 26% in the past six months, a stark contrast to the Nasdaq’s 8.5% gain. Similarly, ServiceNow and Adobe have seen their stock values slump by 15% and 25% respectively. While the iShares Expanded Tech-Software Sector ETF, the market’s largest, has edged up around 3.4% over the same period, this modest gain is largely attributed to its biggest holdings like Microsoft, Oracle, and Palantir. A broader view reveals that more than three-quarters of the ETF’s 113 constituent stocks are currently trailing the S&P 500 year-to-date, underscoring the widespread anxiety. Klein suggests that the “bear thesis” for software stocks is poised to gain further momentum as more AI coding and development tools emerge.
Yet, not everyone shares this pessimistic outlook. OpenAI’s Sam Altman contends there’s no evidence that AI coding tools are replacing software engineers. In fact, he believes the world has “badly underestimated how much additional software the world wants,” predicting that AI will enhance engineers’ productivity, lower software creation costs, and unlock immense opportunities for economic growth. This view finds some support in recent U.S. GDP data, which shows a massive 86.4% annualized gain in investment in computer equipment and an 18.0% gain in software investment. However, Paul Ashworth, chief North America economist at Capital Economics, cautions that software investment growth remains below average and a much larger surge in software and R&D investment will be necessary to translate AI advancements into significant worker productivity gains.
Despite the current market jitters, analysts like Brad Sills of Bank of America foresee a substantial uptick in investment. He estimates that spending on “agentic AI”—systems capable of performing tasks independently of human supervision—could skyrocket to $155 billion over the next five years. Sills believes industry analysts are “underestimating the medium-term uplift to software spending from AI agents” and even favors some of the recently underperforming stocks, including Salesforce, with its Agentforce tool, and ServiceNow, offering Now Assist. Such investment, he notes, could also serve as a crucial catalyst for monetizing the hundreds of billions hyperscalers are pouring into AI-powered data centers.
D.A. Davidson analyst Gil Luria echoes a nuanced perspective. While acknowledging that the core determinant of enterprise software sales—the number of human users—could shift if AI agents begin to take over tasks, he firmly believes the software industry is far from a crisis. Much like the music industry’s successful adaptation to video and streaming, many software companies are well-positioned for the AI revolution. Luria argues that even as large language models move into the application layer, the fundamental need for software that organizes, observes, and secures code and data will only intensify. Beyond tech giants like Microsoft, which are embedding AI into their product suites, he highlights companies such as Snowflake, Datadog, and JFrog as poised to thrive in this evolving landscape.
Just as video didn’t truly kill the radio stars but rather created a new platform for them to shine, AI is poised to do the same for software. It is not an extinction event, but a profound redefinition, ushering in an era of unprecedented innovation and demand.