Agentic AI Accelerates Software Delivery from Pilot Purgatory
SoftServe and MIT Technology Review found that 98% of surveyed software engineering leaders expect agentic AI to significantly speed software delivery within two years. The global study reports 79% of teams have used AI assistants over the past two years, with coding and quality assurance cited as the largest early benefits at 44% and 38% respectively. Respondents predict broader adoption: 72% expect AI agents to manage most or all product lifecycles end-to-end in two years, and 51% already use agentic approaches in some capacity with another 45% planning adoption within 12 months. Investment intent is strong, with 84% saying agentic AI will be a leading engineering investment by 2029. Early improvements are expected to be incremental for many, but a meaningful minority foresee game-changing productivity gains. This signals a near-term shift from experimentation to operationalization of agentic engineering across the SDLC.
What happened
SoftServe and MIT Technology Review released a global study, Redefining the Future of Software Engineering, that finds 98% of respondents expect agentic AI to accelerate software delivery within two years. The report shows current usage and short-term projections: 79% have used AI assistants in the last two years, 51% already use agentic approaches to some degree, and 45% plan adoption within 12 months. Respondents expect agentic agents to manage most or all product lifecycles end-to-end, with 72% predicting this within two years and 41% within 18 months.
Technical details
The study frames the shift as movement toward what it calls agentic engineering, applying autonomous, goal-driven agents across the SDLC. Early benefits cited by practitioners include coding assistance (44%) and QA support (38%). The report also quantifies expectations: 14% expect slight improvements, 52% expect moderate improvements, 32% expect high impact, and 9% expect game-changing outcomes. Investment timelines show momentum: half of organizations list agentic AI as a top priority today, rising to 84% by 2029.
Context and significance
This survey captures a transition point from narrow AI assistants to more autonomous, orchestrating agents that can take ownership of multi-step engineering workflows. For practitioners, that means integrating agent orchestration, observable pipelines, stronger guardrails, and roles focused on agent governance. The split between incremental and transformative expectations is important: most organizations expect steady productivity gains, while a minority foresees major workflow redesigns that could reduce time-to-market and unstick long-standing "pilot purgatory" bottlenecks.
What to watch
Adoption risks and operational requirements will determine whether gains are incremental or disruptive. Track how teams implement agent orchestration, testing and verification for agent actions, data governance for training and feedback loops, and hiring for new roles such as agent operators and governance engineers. Measure velocity and defect metrics as organizations move from pilots to production to validate the report's optimistic timelines.
Scoring Rationale
The report signals a notable, near-term shift from pilots to operational agentic AI in software engineering, with broad practitioner intent and measurable adoption. It is influential for engineering leaders and tool vendors but does not by itself change model or infrastructure paradigms.
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