Observed Signal · Mar 18, 2026 · Product Launch · Source: https://martechseries.com/feed/ · Impact: 2/5 · Sentiment: Positive
AI Speeding Up Code, But Quality Takes a Hit
SmartBear released a survey of 273 software leaders and developers finding that 70% are concerned application quality has already degraded as AI accelerates code development. The survey found widespread adoption of AI coding tools (93%), with 40% of respondents using AI to generate more than 40% of code and 60% expecting similar levels within 12 months. Respondents reported testing gaps—60% experienced quality issues in the past year and many still rely heavily on manual testing—creating fears of testing bottlenecks. In response, SmartBear launched BearQ, an agentic autonomous QA system designed to explore and test applications continuously. Most respondents view autonomous testing positively and are increasing testing budgets.
Survey highlights testing and quality risks from rapid AI-driven code generation and SmartBear launched an autonomous QA product (BearQ) aimed at addressing those gaps—relevant for software reliability across MarTech/AdTech platforms but not a major platform policy or market-shifting event.
Track Funnel Signals & Market Shifts in Real-Time
Polaris7 autonomous intelligence agents track regulatory filings, primary sources, executive changes, and deal flow 24/7. Create your free Explorer workspace to monitor these entities.
Key Takeaways & Evidence Grounding
- Survey of 273 CTOs, CIOs, developers, QA directors and others (mostly mid‑size to enterprise software and SaaS firms).
- 70% of respondents are concerned application quality has already degraded due to faster AI-driven development.
- 93% of respondents have adopted AI coding tools; 40% use AI to generate more than 40% of code.
- 60% experienced quality issues in the past year as development outpaced testing; 68% worry faster AI development will create testing bottlenecks.
- SmartBear launched BearQ, an agentic autonomous QA system for continuous application testing and integrity.
Connected Companies & Entities
1 Entity mappedOntology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
AI Adoption Surges While Quality Slips — Applause Report
Applause published its fourth annual State of Digital Quality in Testing AI report, finding rapid enterprise and consumer AI adoption but declining quality of AI experiences. Based on surveys of more than 1,000 developers and QA professionals and over 4,000 consumers, the report says 55% of organizations have released AI-powered features but that more than half of AI initiatives fail to reach full production due to integration, cost and quality challenges. Reported user issues — hallucinations, misunderstood prompts and shallow responses — are rising. Human evaluation remains central (61% of organizations), while 33% use "LLM-as-judge" approaches. The report recommends hybrid testing models combining AI-driven tools, automated methods and substantial human validation to create reusable benchmarks, close testing gaps, and reduce risk as multimodal AI functionality becomes critical.
Survey: AI's Impact on Software Engineers in 2026
The Pragmatic Engineer published a survey analysis (over 900 responses) detailing how AI tooling affected software engineers in 2026. Respondents reported both benefits (less time on repetitive work, faster prototyping) and downsides (unrealistic business expectations, degraded code quality). Companies find scaling AI adoption difficult—success depends heavily on pre-existing engineering culture, documentation, testing and guardrails. The survey indicates codebase quality and review rigor are declining, shifting maintenance burdens to fewer experienced engineers. Junior engineers often find AI less helpful, incur higher token costs, and may lose growth opportunities when seniors bypass delegation. Other recurring themes include addictive usage patterns around agentic tools and only modest net sentiment improvement since 2024. The article cites recent Microsoft research showing similar trends for productivity tools like Microsoft 365 Copilot.
AI Agents May Slow Development and Harm Quality
The article argues that while AI agents and coding tools can increase engineering output, they may simultaneously reduce product quality, introduce outages, and create long-term technical debt. It cites examples: Anthropic’s Claude-powered development (reportedly 80%+ of production code) shipped a persistent UX bug that affected paying users until public complaint prompted a fix; Amazon experienced outages tied to AI-assisted changes (AWS reported a 13-hour interruption after an agentic tool deleted and recreated an environment), triggering mandates for senior sign-off on junior AI-assisted changes; and large firms (Uber, Meta) are using AI-usage metrics in performance assessments, pressuring engineers to adopt agents. Startups and researchers report short-lived velocity gains followed by maintenance burdens. The piece recommends stronger architecture, formal validation, and renewed QA practices to manage agentic risks.
Track Real-Time Market Signals & Shifts
Set up custom watchlists to receive automated, evidence-grounded executive digests whenever material signals or shifts occur across your tracked landscape.