For the second year in a row, Techreviewer has run an online survey about AI’s role in software development. We use our global network of software development providers to track how AI adoption is changing across teams, regions, and company sizes. You can find last year’s survey, from 2024, here: Impact of AI in Software Development: A Survey-Based Analysis 2024.
In 2024, most companies were experimenting with AI in software development and cautiously trying it out. They tested tools, looked at different use cases, and measured the results, often using unique strategies and with limited in-house experience. Many software developers also asked, “Will programmers be replaced by AI?”
The 2025 survey takes a closer look at how AI adoption has changed over the past year. It examines what’s working, where companies and developers face challenges, and how attitudes and skills are developing. With input from professionals around the world, this research gives a clear picture of where the industry is now and where it’s going.
Executive Summary
By 2025, companies moved from experimenting with AI to making it part of their daily work. Now, 97.5% of companies of all sizes use AI as a key part of their internal processes.
Key use cases include code generation, documentation generaThe main ways companies use AI are for code generation, creating documentation, reviewing and improving code, and automating testing and debugging. The impact is clear: 82% of respondents saw at least a 20% boost in productivity, and 25% saw gains of over 50%
Companies are building in-house AI expertise instead of relying on third-party tools or providers. 63.3% of respondents nurture the skills of their employees through in-house training programs.
AI maturity presents challenges, as transparency, ethics, and data privacy have become significant concerns. The question is no longer if artificial intelligence should be used, but how to govern and sustain it responsibly.
2025 is a turning point. The industry is moving from simply adopting AI to taking responsibility for how it is used.
Respondent Profile
Demographics
The majority of survey respondents represent small to mid-sized software development companies. Specifically:
Over 80% of respondents work at companies with fewer than 250 employees.
The largest segment (27.2%) consists of small businesses with 10–49 employees.
Only 1.2% of responses came from large enterprises with more than 1000 employees.
The company size distribution reflects the presence of small- to medium-sized companies that embrace innovations and are inclined to implement new technologies quickly.
Respondent Roles
The survey reached a broad mix of roles in software development companies, including executives, leadership, strategies, and more:
Nearly 67% of respondents hold executive-level roles, including CEOs or Presidents (35.4%) and Marketing Managers (31.7%).
Technical leadership was represented through CTOs (8.5%) and Project Managers (4.9%).
Additional respondent roles are CMOs (7.3%), Sales (3.7%), HR (2.4%), Digital/SEO/Marketing executives (2.4%), founders (1.2%) and 2.4% for roles that didn’t fit into standard categories.
This breakdown shows that adopting AI is important for all roles in a company, not just for engineering teams.
Office Location
Respondents came from a wide geographic range, with the majority headquartered in several tech hubs:
India (27.2%) and the United States (23.5%) together account for over half of all responses.
Other notable contributors include Poland (7.4%), Vietnam (6.2%), and Canada (6.2%).
Bangladesh, Estonia, Pakistan, Ukraine, Armenia, Lithuania, and the United Kingdom each made up around 2.5% of the total.
An additional 12% of participants, with a few respondents from each region, include those from Zimbabwe, Hungary, China, Portugal, Croatia, North Macedonia, Spain, Brazil, Cyprus, Hong Kong, and the Netherlands.
This wide range of participants shows that AI in software development is being adopted around the world, not just in traditional tech hubs.
Artificial Intelligence Adoption: Where Are We Now?
Key Insights:
97.5% of companies have adopted artificial intelligence in software engineering, up from 90.9% in 2024.
Artificial Intelligence adoption is approaching industry-wide saturation.
2.5% of non-adopters cite cost, integration complexity, and unclear ROI as main barriers.
Current Adoption Rate
Question: Are you currently integrating AI technologies in your software development processes?
According to the 2025 survey:
Ninety-seven point five percent of companies report that they are currently integrating AI technologies into their software development processes.
Only 2.5% of respondents have not yet adopted AI.
In comparison, the 2024 survey showed that 90.9% of companies had already adopted AI, while 9.1% had not. This year-over-year shift indicates a clear trend: AI is transitioning to near saturation in the industry.
Reasons for Not Implementing AI
Among the small minority (2.5%) of companies that have not yet adopted AI, several key barriers were identified:
High implementation costs or a lack of financial resources to initiate AI implementation for software development.
The complexity of integrating artificial intelligence with existing systems or workflows (mentioned twice, indicating a recurring concern).
No clear business need or uncertain benefits from Artificial Intelligence adoption.
These challenges show that the few companies not using AI are not skeptical about it, but are more concerned about whether it fits their needs, works with their systems, or will pay off.
Future Plans for Artificial Intelligence Adoption
Among those 2.5% who have not yet adopted AI:
50% of companies have no intention of integrating AI in software engineering in the foreseeable future.
50% indicated a timeline of 12+ months, suggesting a slower, more cautious approach.
This shows that while almost all companies are adopting AI, a small group is still unsure about its value for software engineering or simply doesn’t have the resources to use it.
AI in Action: Use Cases, Implementation Approaches, Goals, Results
Key Insights:
AI is now core to the SDLC: 72.2% use it for code generation, 67.1% for documentation and review.
Adoption is moving upstream: 53.2% use AI in requirements analysis and 48.1% in UI/UX, marking a shift from execution to planning.
New mainstream areas in 2025: DevOps automation (38.0%), code review, and predictive analytics. AI now supports full-cycle delivery.
13.9% report custom use cases: From architecture to marketing, the industry shows growing creativity beyond developer tooling.
Maturity is rising: 49.4% have used artificial intelligence for more than 1 year (vs. 32.5% in 2024); only 2.5% are new adopters.
Impact is real: 92.4% report positive SDLC effects; 82.3% gained ≥20% productivity, 24.1% exceeded 50%.
Areas of Utilization
AI is being applied across nearly every stage of the software development lifecycle, from planning to deployment. The 2025 survey reveals a clear hierarchy of use cases, with certain areas showing particularly high adoption:
Code generation: leads the list, with 72.2% of companies using artificial intelligence to assist or automate code writing.
Documentation generation (67.1%) and code review and optimization (67.1%) follow closely, highlighting the role of artificial intelligence in producing comprehensive documentation and improving code quality.
Automated testing and debugging are used by 55.7% of companies, demonstrating AI’s role in enhancing software reliability.
Requirements analysis and design (53.2%) and UI/UX optimization (48.1%): show that artificial intelligence is extending into earlier and more subjective stages of the development process.
Predictive analytics for project management (39.2%) and deployment/DevOps automation (38%) round out the top categories.
In addition to the major categories, 13.9% of respondents mentioned niche or company-specific use cases grouped under “Other.” These included:
Architectural design.
DevOps pipelines and CI/CD.
Bug detection and fixing.
Voice interfaces and AI-powered design tools.
Security enhancement.
Refactoring and optimization.
Project management and scoping.
Client communication.
Marketing.
ATS integration.
AI project development is a core service.
These answers show that companies are finding more creative ways to use AI, not just for developer tools but also in wider business processes and products.
Areas of Utilization 2025 vs 2024 Comparison
AI is now deeply embedded across multiple stages of the software development lifecycle. According to the 2025 survey, the top areas where companies apply artificial intelligence include:
Key Shifts Since 2024
Code generation remains the leading application, with usage rising from 67.5% to 72.2%
Automated testing and debugging declined slightly in relative share (from 62.5% to 55.7%), possibly due to the diversification of use cases.
Requirements analysis, UI/UX optimization, and predictive analytics showed notable growth.
Documentation generation and code review/optimization emerged as new high-ranking use cases in 2025, absent from last year’s top list.
The rise of deployment and DevOps automation in 2025 shows that AI is now having a bigger impact on operations, not just on development.
Maturity and Timeline of Implementation
Nearly half of the companies (49.4%) have been using AI tools in software development for over a year.
34.2% started integrating artificial intelligence within the last 6–12 months.
13.9% began 3–6 months ago.
Only 2.5% are new adopters, having started within the last 3 months.
Maturity and Timeline 2025 vs 2024
In 2024, only 32.5% of companies had used artificial intelligence for over a year. This figure has jumped to 49.4% in 2025. Meanwhile, the proportion of recent adopters has declined, especially in the < 3 Months category (from 7.5% in 2024 to 2.5% in 2025).
Today, AI and software engineering are closely connected. This change shows that the industry is maturing, with more companies moving from trying out AI to making it a permanent part of their work.
Perceived AI Impact on Software Development Life Cycle (SDLC)
In 2025, the vast majority of respondents view artificial intelligence as a net positive in the software development lifecycle:
55.7% describe the impact as significantly positive
36.7% as somewhat positive
Only 6.3% were neutral, and 1.3% saw a negative impact
Compared to 2024, the perception has become more optimistic. A year earlier, only 40% of companies reported a significant improvement, and 17.5% were unsure of the impact.
Measured Productivity Gains
When as aked about actual productivity improvements in 2025:
58.2% of companies reported a 20–50% increase in productivity.
24.1% reported an increase of more than 50%.
11.4% saw an improvement of less than 20%.
6.3% observed no measurable improvement.
This marks a clear upward shift in the benefits of AI in software development from 2024, where:
52.5% reported a 20–50% gain.
Only 7.5% had improvements above 50%.
27.5% had minor gains under 20%.
Overall, the 2025 data show that people see more value in AI, and the real benefits in software development are clearer. Productivity gains are now bigger and more common.
AI Talent and Skill Landscape
Key insights:
In 2025, 59.5% of companies rely on in-house AI specialists, indicating a strong trend toward building internal Artificial Intelligence development teams.
Dependence on pre-built AI tools dropped to 17.7%, signaling a reduced appetite for off-the-shelf solutions.
Despite progress, 12.7% of companies still lack both in-house expertise and external support, pointing to resource gaps.The most common way companies train for AI is through in-house programs (63.3%), followed by online courses and hiring from outside. Still, almost 20% of companies don’t have a clear plan for upskilling.
Collaborations with universities have grown from 2.5% to 20.3%, reflecting the early stages of industry-academia alignment on AI.
The majority, 83.9% of companies, rate talent acquisition as very easy or neutral, and only 16.1% find it difficult, indicating that talent scarcity is no longer a universal bottleneck.
The main question has changed from “Will AI replace software engineers?” to “How can junior developers gain experience in the age of AI?”
Talent and Artificial Intelligence Expertise
In 2025, most companies prioritize internal capability building when it comes to AI:
59.5% have dedicated in-house Artificial Intelligence specialists, indicating a strong focus on nurturing internal expertise rather than relying on third-party tools and providers.
17.7% use pre-built AI tools and services: in second place, with a serious lag from the growing internal expertise.
12.7% report having no in-house expertise or third-party partnerships: these are likely early-stage adopters or companies with serious resource constraints.
7.6% partner with external Artificial Intelligence providers.
1.3% identify as Artificial Intelligence providers themselves or combine internal teams with external partners.
These numbers show that most companies prefer to build their own AI expertise, but a notable group still relies on outside tools or services.
Read the full research here: https://techreviewer.co/blog/ai-in-software-development-2025-from-exploration-to-accountability-a-global-survey-analysis
Originally published at Techreviewer.co.
Top comments (0)