Mike Vizard summarizes the results of a BairesDev survey, showing developers are embracing AI faster than project managers, with implications for DevOps leaders and software teams.

Survey Finds Developers Adopting AI More Rapidly Than Project Managers

Author: Mike Vizard

A survey of 1,129 developers and 50 project managers, conducted by BairesDev, reveals that developers are outpacing project managers in adopting and applying AI within the software development process.

Key Findings

Developers save 7.3 hours per week on average through AI use, amounting to over a full working day.
AI creates 25% of developer code, highlighting the technology’s direct influence on daily tasks.
Most-cited AI benefits:
- Faster coding (65%)
- Accelerated learning (48%)
- Increased productivity (45%)
- Quicker prototyping (34%)
- Higher code quality (27%)
88% of developers see AI as a career gateway, fostering opportunities like automating repetitive tasks and pursuing AI/ML specializations.
Major upskilling methods: On-the-job training (66%), YouTube (58%), paid courses (48%), but only a minority use formal certifications (15%).
44% of developers would like more structured AI/ML training.

Project Manager Challenges

Slower AI adoption among project managers due to:
- Gaps in business/contextual knowledge (43%)
- Shortage of AI/ML specialists (41%)
- Lack of internal upskilling (38%)
- Limited ROI clarity, data privacy/security concerns, and resource constraints
Only 15% offer structured AI training for teams, showing a need for more proactive leadership.

Developer and DevOps Implications

DevOps and software team leaders are encouraged to gain hands-on AI experience to design effective upskilling programs and stay abreast of change.
The survey emphasizes ongoing code review and validation to mitigate risks such as technical debt or security vulnerabilities in AI-generated code.
The findings indicate AI is shifting from ‘if’ to ‘how much’ across software engineering contexts.

Practical Recommendations

Continuous learning—via self-directed and structured programs—remains critical for teams seeking to maximize AI benefits.
Project managers and DevOps leaders should prioritize AI training and understanding to maintain effective team leadership in rapidly evolving environments.

“In the age of AI, it’s simply not going to be possible to lead from the rear given the rapid pace of change occurring now on an almost daily basis.” — BairesDev CTO Justice Erolin

Links & Further Reading

AI adoption strategies
Managing technical debt with AI in software engineering
Building upskilling programs for software teams
Security and privacy risks in AI-driven development

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