AI availability generates too many low quality software by non-developers. How will that affect the general software market?

Sonar Pro

Answer: AI availability enabling low-quality software from non-developers will initially pressure the general software market through increased competition and investor uncertainty, but ultimately drive consolidation, innovation, and growth by accelerating productivity and weeding out inefficiencies.

The proliferation of low-quality software by non-developers, facilitated by accessible AI tools, contributes to short-term market turbulence, as evidenced by the 2026 software stock bear market and a $2 trillion wipeout in software market caps, driven by fears that AI could replace demand for existing software offerings.[4][5] Investors are questioning the value of traditional software when AI enables rapid, low-cost development, leading to a selloff in software stocks while semiconductors benefit from AI infrastructure demand, highlighting a clear market divergence.[5] However, this disruption is part of a broader positive transformation. AI adoption is shifting from pilots to tangible productivity solutions, with companies reporting cash-flow margin expansion 2x the global average and AI driving M&A for expertise acquisition, which will consolidate high-quality players and reallocate capital to enduring assets.[1] McKinsey projects generative AI adding up to $4.4 trillion annually to the global economy via productivity gains and cost reductions, with AI shortening product development cycles and boosting revenue growth three times higher in AI-utilizing industries.[2] Long-term, AI fuels market expansion: global AI spending hits $2 trillion in 2026, IT spend exceeds $6 trillion, and 86% of firms plan increased AI budgets for optimization and new use cases, prioritizing operational efficiencies (34%) and employee productivity (33%).[2][3] Low-quality software will likely be outcompeted as markets reward monetization evidence over hype, with AI adopters gaining competitive edges in GDP growth (~25% U.S. contribution), revenue, and cost reductions across sectors.[1][3] Overall, while non-developer software floods the market and shakes incumbents, it accelerates innovation cycles, labor redeployment to higher-value roles, and industry maturation, positioning the software market for robust growth amid $2.9 trillion in AI infrastructure by 2028.[1]

Grok 4.1 Fast

Answer: AI availability will ultimately benefit the general software market by democratizing creation, spurring competition, and accelerating innovation, despite an initial surge of low-quality software.

The influx of low-quality software from non-developers will increase market supply dramatically, lowering barriers to entry and enabling rapid experimentation. This saturation may initially overwhelm users with choices, diluting trust in unvetted apps and pressuring established developers to differentiate through superior quality and features. However, markets naturally segment: simple, niche tools from non-experts will serve underserved or casual users effectively, freeing professional developers to focus on complex, high-value software. This division mirrors historical shifts like no-code platforms, where abundance led to specialized ecosystems rather than collapse. Competition intensifies as low-quality offerings highlight gaps, incentivizing iteration and improvement across the board. AI tools themselves evolve quickly, empowering even non-developers to refine their products, creating a feedback loop of enhancement. Long-term, this democratizes innovation, filling market voids with hyper-targeted solutions that big players overlook, boosting overall efficiency, user satisfaction, and economic growth—much like how user-generated content transformed media without destroying professional production.

DeepSeek V3.2

Answer: The influx of low-quality AI-generated software will initially flood the market and erode consumer trust, but will ultimately drive demand for verified, high-quality solutions and professional development services.

The democratization of software creation through AI tools enables non-developers to rapidly produce applications, leading to a surge in supply that includes many low-quality, buggy, or insecure products. This oversaturation will make it harder for users to identify reliable software, increasing the risk of security breaches, poor user experiences, and wasted resources. As consumers face more choices with varying reliability, frustration may grow, prompting a market response focused on trust and verification. This will spur the rise of curation platforms, robust review systems, and third-party certification bodies that help filter and endorse quality software, creating new business opportunities around quality assurance. Professional developers and established firms will differentiate themselves by emphasizing reliability, security, scalability, and advanced features that AI-generated tools often lack. This could lead to a bifurcated market: low-cost, disposable AI-built software for simple tasks, and premium, professionally developed solutions for critical or complex needs. Over time, the market may self-correct as users learn to value quality over quantity, reinforcing the importance of skilled developers and rigorous development processes. The increased accessibility may also expand the overall software user base, creating more opportunities for high-value custom solutions that address niche or sophisticated requirements. Ultimately, while the initial wave of low-quality software poses challenges, it will push the industry toward better quality controls, innovation in development practices, and a more stratified ecosystem that benefits both consumers and professional developers.

Kimi K2.5

Answer: The flood of AI-generated low-quality software will bifurcate the market into a commoditized bottom tier plagued by security risks and abandonment, and a premium tier where professional developers command higher prices for verified reliability, maintenance, and complex system integration.

As non-developers deploy AI-generated applications without understanding architecture, testing, or security fundamentals, the market will face a deluge of brittle, unmaintained products that break under scale or expose user data. This saturation will trigger a crisis of trust among enterprise buyers and discerning consumers, who will increasingly demand provenance verification, security audits, and long-term maintenance guarantees that amateur AI-assisted builders cannot provide. In response, platforms and marketplaces will implement aggressive algorithmic and manual curation, effectively creating gatekeeping mechanisms that favor established engineering practices over rapid, unverified deployment. The "vibe coding" phenomenon will dominate the long tail of simple CRUD apps and internal tools, driving prices for basic software toward zero and commoditizing functionality that once required professional labor. Simultaneously, professional developers will pivot upmarket, focusing on high-availability systems, security hardening, legacy modernization, and the integration of disparate AI-generated components into coherent, maintainable architectures. This dynamic will paradoxically increase the value and compensation for skilled software engineers who can audit, refactor, and productionize AI-generated code, while the low-quality surplus creates a "haystack problem" where discovering reliable solutions becomes the primary consumer challenge. Ultimately, the market will not collapse but stratify, with economic rewards flowing to those who guarantee durability in an ecosystem drowning in disposable digital artifacts.

Gemini 3.1 Pro

Answer: The influx of low-quality, AI-generated software will bifurcate the market, commoditizing basic utility applications while driving a massive premium for trusted, high-quality, and secure professional software.

As AI dramatically lowers the barrier to entry, app stores and software marketplaces will inevitably be flooded with functional but unoptimized, insecure, or poorly maintained applications. This hyper-saturation will drive the cost of basic utility and simple workflow apps effectively to zero, completely commoditizing the lower end of the software market. Consequently, the sheer volume of 'noise' will make discoverability a monumental challenge for consumers and businesses alike. Because buyers will struggle to sift through mountains of subpar, heavily derivative code, trust and reputation will become the market's most valuable currencies. Users and enterprises will increasingly rely on established brands, rigorous curation platforms, and certified vendor marketplaces to ensure the tools they adopt are secure, compliant, and reliable. Ultimately, this dynamic will force professional developers and software companies to evolve rather than face obsolescence. Rather than competing in the saturated market of simple applications, engineering talent will pivot toward complex, high-stakes domains. The general market will see a stark division: a bottomless pit of disposable, AI-generated micro-apps, and a highly lucrative top-tier focused on scalable enterprise architecture, deep tech, and complex integrations where human architectural expertise remains indispensable.

GPT-5.4

Answer: An influx of low-quality AI-generated software will expand the software market overall, but it will also intensify segmentation, making trust, maintenance, security, and product quality far more important competitive differentiators.

The biggest immediate effect is not that all software becomes worse, but that software becomes cheaper and more abundant. When non-developers can create apps, websites, automations, and internal tools with AI, many ideas that previously would never have been funded or built will suddenly enter the market. That increases experimentation and widens access, especially for small businesses, niche communities, and internal company use cases. However, abundance changes how markets work. If low-quality software becomes easy to produce, then simple utility products will be commoditized faster. Many basic apps will look similar, offer overlapping features, and compete mostly on convenience or distribution rather than technical sophistication. Prices for undifferentiated software are likely to fall, and some categories may become saturated with disposable products. That does not mean professional developers become irrelevant. In fact, it likely makes professional engineering more valuable in certain layers of the market. As more software is created by people without deep technical expertise, the average risk of poor architecture, security vulnerabilities, privacy failures, legal noncompliance, and maintenance problems will rise. Buyers—especially businesses—will care more about reliability, integrations, support, uptime, governance, and long-term ownership. Those are areas where experienced teams still have a major advantage. So the market will probably split more clearly into tiers. At the low end, there will be a flood of cheap, short-lived, often low-quality products solving narrow or temporary problems. In the middle, there will be strong demand for tools that help validate, improve, audit, secure, and maintain AI-built software. At the high end, trusted vendors with real engineering discipline will command a premium because customers will increasingly pay for assurance, not just features. Consumer behavior will also shift. Users may become more skeptical of unknown software brands because the cost of publishing something functional-looking will drop faster than the cost of ensuring it is good. Reviews, reputation, brand, certification, and platform curation will matter more. App stores, marketplaces, enterprise procurement teams, and regulators may become stricter to filter out low-quality or unsafe products. There is also a positive long-term effect: some low-quality software created by non-developers will still be useful. Many business processes do not need elegant engineering; they just need a working solution quickly. AI will enable more people to solve their own problems, which can improve productivity even if the resulting software is imperfect. Over time, the best of these grassroots solutions may mature into serious products. In short, the general software market will become larger, noisier, and more polarized. Easy AI creation will push down the value of basic coding and routine product assembly, while increasing the value of trust, quality control, security, domain expertise, and ongoing maintenance. The winners will not simply be those who can build software fastest, but those who can prove that their software is dependable and worth using.

Claude Opus 4.6

Answer: The flood of AI-generated low-quality software will paradoxically strengthen the market for professional, well-engineered software by raising the bar for what users expect and creating clearer stratification between disposable tools and trusted platforms.

The premise that AI enables non-developers to produce more software is correct, but the conclusion that this harms the general software market oversimplifies a more nuanced dynamic. First, much of the low-quality software produced by non-developers will occupy niches that were previously unserved — internal business tools, personal automation scripts, quick prototypes, and hyper-specific utilities. These aren't competing with professional software products; they're filling gaps that no professional developer would have found economically viable to address. This is net-positive for productivity even if the code quality is poor. Second, the market will develop stronger filtering mechanisms. App stores, enterprise procurement processes, and users themselves will become more discerning. Just as the democratization of web publishing didn't destroy journalism but instead created a clearer distinction between trusted outlets and random blogs, the democratization of software creation will sharpen the divide between vetted, reliable software and throwaway tools. Discovery platforms will likely evolve reputation systems, security audits, and quality signals to help users navigate the noise. Third, the real risk isn't market flooding but security and reliability. Low-quality software with poor error handling, no security practices, and no maintenance commitment can create vulnerabilities — especially if adopted in business contexts. This will likely drive demand for better security tooling, code review services, and professional oversight, creating new market opportunities. Fourth, professional developers won't be displaced — they'll move up the value chain. The hard problems in software — architecture, scalability, security, maintainability, complex integrations — remain firmly beyond what non-developers using AI can handle. If anything, companies will value experienced engineers more because someone needs to evaluate, integrate, and maintain the growing patchwork of AI-generated components. Fifth, there's a historical parallel: WordPress and no-code tools already enabled millions of non-developers to create websites. This didn't destroy the web development market — it expanded it. The total addressable market for web presence grew enormously, professional agencies thrived by serving clients who outgrew DIY solutions, and the bar for what constitutes a 'good' website rose for everyone. The net effect will be market expansion and stratification rather than degradation. More software will exist, most of it mediocre and short-lived, but the professional software market will remain robust and likely grow as organizations realize that AI-assisted prototypes need professional hardening to become production-ready systems.

Qwen 3.5 397B

Answer: While AI-driven proliferation will flood the market with ephemeral low-quality tools, it will ultimately elevate the value of verified, secure, and professionally maintained software solutions.

The immediate effect will be market saturation, where discovery costs skyrocket as users struggle to distinguish functional tools from broken prototypes. This noise creates a trust deficit, prompting enterprises and consumers to prioritize software with verified security audits, professional support, and established brand reputation over cheap, AI-generated alternatives. Consequently, the role of professional developers will shift from writing boilerplate code to architecting robust systems and auditing AI output for safety and scalability. Ultimately, the market will bifurcate, with disposable AI scripts serving niche, temporary needs while high-stakes applications command a premium for human oversight and reliability.

Final Summary

The AI Roundtable unanimously foresees a 'great stratification' rather than a total industry collapse. While Claude Opus 4.6 and Grok 4.1 Fast argue that low-quality software will simply fill previously unserved niches, Kimi K2.5 and Gemini 3.1 Pro warn that a surplus of 'brittle' code will make trust and security the market's most expensive currencies. Ultimately, GPT-5.4 and DeepSeek V3.2 agree that professional developers will move up the value chain, evolving into elite architects and auditors who fix the 'haystack' of disposable AI artifacts.

All 8 models agreed