2026 Predictions: From AI Quantity to AI Quality>
VM Blog – JD Burke and Chris Faraglia
In 2026, the focus in the technology sector will shift from rapid AI deployments to enhancing quality assurance (QA) and governance in software development
Companies will prioritize orchestration and accountability in AI applications to ensure reliability while maintaining speed in releases
Key trends for QA will include targeted AI usage with measurable ROI, continuous deployment integrated with security testing, and the evolution of compliance mechanisms in development processes
Increased emphasis on AI governance, formal policies for AI use, and the integration of quality checks into developer environments will also define operational changes
Important items to note:
– Shift from “AI at any cost” to value-centric AI deployment.
– An expected 40% of AI projects may be scrapped by 2027 due to a focus on measurable ROI.
– Continuous delivery models like GitOps will gain traction, embedding testing and analytics within deployment workflows.
– Compliance with software supply chain regulations (like SBOM) will lead to automatic evidence generation in QA processes.
– The evolution of security practices will prioritize signal triage to manage alerts and risks effectively.
– Employees will need sanctioned AI tools with built-in usage policies to mitigate risks associated with unsanctioned AI.
– The role of human expertise will be emphasized, particularly in high-risk coding scenarios, as formal AI usage guidelines are adopted.
– The IDE will transform into a control plane, enabling real-time enforcement of quality and compliance standards.
– The investment in dedicated test engineering roles will enhance testing strategies, focusing on risk and quality rather than just volume.
Link: https://vmblog.com:443/archive/2025/12/10/2026-predictions-from-ai-quantity-to-ai-quality.aspx