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Manchester, 3/11/2025 SlashData has released new findings revealing the real-world adoption of AI in late 2025.  As early adopters and reliable predictors of technology trends, developers provide a window into where AI is heading next. Based on their responses, SlashData highlights three trends transforming the AI landscape: Agentic AI goes mainstream, AI coding tools preferences, Gen AI adoption blockers. AI coding tools: ChatGPT and Copilot dominate ChatGPT (64%) and GitHub Copilot (49%) lead in adoption and satisfaction among professional developers using AI coding tools. JetBrains AI shows low adoption and high satisfaction, signalling a growth opportunity. Adoption varies by experience: “Satisfaction with ChatGPT drops notably among experienced developers, as they appear less happy with its accuracy, scalability, and ease of use compared to newcomers” says Bleona Bicaj, Senior Market Research Analyst at SlashData Agentic AI goes live: half of adopters already in production 50% of professional developers adopting AI functionality have already deployed Agentic AI into production, marking the end of the experimental era. Text generation, summarisation or translation (28%) is the top use case for Agentic AI. AR/VR and IoT projects lead adoption. Reliability and security concerns might be slowing the adoption of agentic AI in backend systems.  “Large enterprises’ governance complexity may be neutralising their resource advantages in agentic AI deployment” says Alvaro Ruiz Cuber, Market Research Analyst at SlashData Data privacy & security fears slow down AI rollout Organisations face two core hurdles: privacy risks that delay approval and quality concerns that undermine developer trust as only 25% of professional developers are currently building applications powered by Generative AI.  “Organisations must prioritise enterprise-level safeguards to prevent projects from stalling under compliance reviews.” urges Nikita Solodkov, Market Research and Statistics Consultant at SlashData Full analysis and 29 charts instantly available to all through the SlashData Research Space .   The insights come from 12,000 developers surveyed in Q3 2025. The six State of Developer Nation reports cover AI, FinOps, Cloud and Language communities. About SlashData SlashData is an AI analyst firm. For 20 years, we have been working with top Tech brands like Google, Microsoft and Meta. We track software technology trends to empower industry leaders to make product and marketing investment decisions with clarity and confidence, and drive the world forward with technology.

You don’t need another hype post. No one does. What the Tech world needs are the clear signals developers are actually sending: where adoption is real (and measurable), where it stalls, and how to present this at a board-level.  Developer Signals, Not Vendor Noise The latest State of the Developer Nation (DN30) series from SlashData gives you that edge across: Agentic AI architectures being implemented The AI coding tools developers rely on The barriers to adopting Generative AI applications  The current stage of Backend/Cloud Sizing the language communities FinOps in 2025 Responses from 12,000 developers are combined into 6 in-depth reports, filled with data and analyst commentary. The insights within, curated by our analysts, experts in their field, will help you make go/no-go decisions faster and with confidence.  Think developer sentiment, adoption curves, regional differences, and tech maturity, not guesswork. Below is a quick, exec-ready tease of what’s inside each report and how to dig deeper. What’s New in AI, According to Developers AI coding tools: concentration + clear satisfaction leaders Only 20% of professional developers currently use AI-assisted coding tools, and usage is heavily concentrated in ChatGPT (~65% of AI-tool users) and GitHub Copilot (49%).  65% of AI tool users use ChatGPT Both also top satisfaction (CSAT 78 each), with JetBrains AI close behind on 76 despite only ~10% adoption — a classic high-satisfaction/low-awareness opportunity.  Attribute-level scores explain why: ChatGPT leads on ease of use and setup; Copilot wins on integration and in-IDE workflow fit.  Insights Source: Which AI coding tools do professional developers rely on? Agentic AI: single-agent now, multi-agent building blocks next Among developers who’ve implemented agentic AI in the past six months, 56% ship single-agent systems, while 44% use multi- or hybrid-agent designs.  Text generation/summarisation/translation is the top use case (~28%), with multi-agent setups over-indexing on tasks like multimedia creation, web retrieval, and database querying — building blocks for orchestration.  Adoption varies by context: immersive (AR/VR/games) and IoT projects lead; backend and web services lag, where reliability/security constraints make autonomous agents a tougher sell.  Insights Source: The state of agentic AI adoption in software projects GenAI barriers: privacy first, then quality, skills and ROI 77% of developers not adding GenAI cite specific blockers. The top is data privacy/security (22%), with budget (16%), limited expertise (15%), output quality (14%), and integration complexity (13%) close behind.  As company size rises, privacy and compliance hurdles climb too.  Source: Barriers to adopting generative AI in applications Backend & Cloud: Hybrid Peaks Mid-Size; Private Cloud Scales with Risk Larger organisations are more likely to use private cloud, driven by security and compliance, while hybrid cloud adoption peaks in mid-sized companies and drops at the very large and very small.  Multi-vendor strategies remain the norm across sizes; smaller firms average 3.8 cloud providers vs. 3.3 for enterprises. Optimisation over consolidation.  Look at sector patterns: financial services lead on containers (40%) and orchestration (21%), while  AI model/service companies top MLaaS usage (29%).  One nuance worth watching: container usage dips at 501–1,000-employee “large businesses”. While we might generally expect container usage to increase as organisations grow and they have a greater need for the flexibility and scalability of containers, this low container adoption instead gives us insight into how platform teams are changing the developer experience and removing direct interaction with specific technologies. Insights Source: Benchmarking Backend and Cloud Technology Strategies  FinOps: Wide Adoption, Clear Regional Spread Two in three developers say their teams practice FinOps (66%), with mid-sized organisations leading as cloud bills and complexity bite. Regionally, adoption is highest in the Greater China Area (88%) and strong in North America (73%), while South America trails at 22% — signalling big upside for early movers in emerging markets. Visibility (budget monitoring/reporting) is the common entry point. Insights source: State of FinOps in 2025 Programming Language Communities: Scale, Momentum, and Who to leads JavaScript remains the largest community (~26.9M) with Python (24.4M) now ahead of Java (23.1M).  Over the last year, JavaScript usage dipped from 61% to 56% — maturity, not a collapse.  Momentum stories: C++ adds 7.6M developers over two years, expanding across embedded, desktop, games, even web and ML. Ruby doubles to 4.9M in the same period. Experience curves matter: Python skews earlier-career; PHP and C# adoption rises with tenure: Languages often “learned on the job” inside established stacks.  Insights Source: Sizing programming language communities Why this matters For CTOs & Heads of AI: De-risk platform bets. Align agentic AI architecture choices to today’s real use cases; prioritise privacy, evaluation pipelines, and governance to unblock GenAI adoption. For Product Managers, PMMs and DevRel: Position to developer reality. Back the tools and languages developers actually rate and use; target regions and segments where FinOps and cloud maturity shift the buying criteria. Next step: Talk to an analyst for a briefing and a go/no-go view for your roadmap or AI rollout. Or access all State of the Developer Nation insights if you want to drill into charts, regions, and cohorts yourself, in the SlashData Research Space : Which AI coding tools do professional developers rely on?  The state of agentic AI adoption in software projects  Sizing programming language communities State of FinOps in 2025 Benchmarking Backend and Cloud Technology Strategies  Barriers to adopting generative AI in applications  About the author Stathis Georgakopoulos, Product Marketing Manager at SlashData Stathis leads product marketing and loves building helpful content that turns complex research into practical decisions. He focuses on setting the table for launches and campaigns, and has a soft spot for content marketing.

If you have been following SlashData for a while, you know how we are not only tracking the latest technology trends, but are also early adopters ourselves. Now we are taking one more step forward.  SlashData has been tracking the developer ecosystem and economy for 20 years. We have been working on analysing the current state of software development, predicting software trends, and benchmarking industry leaders. All these, through expert analyst insights, backed by solid data.  SlashData’s reputation has been built on understanding developers and technology through research, including population sizing, tool adoption, and ecosystem trends.  In the age of AI, developers are the drivers of the technology trends.  Today, developers adopt technology first, followed by builders (aka vibe coders), followed by the rest of enterprise users and the world. The exponential evolution and adoption of AI tech has created enormous uncertainty in the world. We are here to provide confidence and clarity.   Our next step for SlashData is to become the trusted analyst firm specialising in AI technology, helping tech companies make the right decisions when adopting AI technology.  We focus on helping clients navigate AI technology decisions with confidence & clarity, through analyst guidance validated by data. This is more than a change in branding or service lines. It’s a strategic shift, a recommitment with a sharpened focus. We are doubling down on delivering not only where AI tech is heading, but also on why, and how, always backed by rigorous, data-validated analysis. Andreas Konstantinou (SlashData founder) is returning to the role of CEO to lead us through this shift in strategy and work with a technology he is very passionate about. Why we are shifting our resources to serve AI tech right now AI is the fastest adopted technology on the planet, and also the most disruptive.  It is the most profound change the industry and the world has ever experienced. AI updates dominate news, media, your timeline, Slack messages, and hallway conversations.  Here are the core reasons we believe the world and businesses need us to take this step now: Explosion of AI options & fragmentation. New models, platforms, tools, frameworks, and deployment choices are multiplying rapidly. What works in one context doesn’t in another. Without an analyst lens, many organisations are overwhelmed by choices and risk making the wrong investments, losing credibility and opportunity in the race for AI adoption. Gap between hype and reality. Vendors, online communities, influencers, media, even some internal teams often overpromise on what AI can do. The real effects: performance, cost, security, ethics, maintainability, scalability can diverge wildly. Organisations need grounded, evidence-based guidance to separate signal from noise. High stakes in adoption. AI decisions are no longer just technical decisions. They affect strategy, operations, governance, risk, and customer trust. Poor choices can lead to compliance violations, security incidents, ethical lapses, or wasted budget. The “analyst + data” combination helps mitigate those risks: our analysts provide an expert outlook, backed by solid datapoints. What SlashData can do for your AI needs  Strategic AI technology roadmaps.  We’ll help you choose which models, platforms, infrastructure, and partners make sense for your goals. Vendor and product benchmarking.  Compare capabilities, performance, costs, and trade-offs in real-world conditions. Use-case validation.  Before investing heavily, validate which AI use cases are likely to deliver the ROI you are going for. Regular data-grounded trend & forecast reports.  Not just “what is” but “what is coming,” and what it means for you. Building on our strengths If you’ve worked with us, you know that we have been tracking developer trends for two decades. We know that developer trends are the early signal of which AI platforms and technologies will win. Success lies within the developers at the heart of AI.  Our proven track record of working with industry leaders is a true testament to that. We have worked with teams that push the world forward at Google, Microsoft, CD Foundation, Cisco, Dell, DigitalOcean, Intel, Linux, Meta, Okta, Qualcomm, SAP, Sony, Stripe, and many more.  Additionally, our insights are: Elevated and validated by data:  Developer population sizing, adoption curves, performance metrics, competitive benchmarking, and usage patterns all serve to prove our point. Accessible : clear language, insightful framing for both technical and non-technical stakeholders. Trusted : We have been tracking developer trends and the technology landscape for 20 years. We are prepared and know how to track AI in a way that brings value and reduces friction. Let’s see how we can work together. Talk to our analysts .

Key Questions Answered What share of professional developers use AI-assisted coding tools, and which ones are the most popular? How do AI-assisted coding tools rank in terms of satisfaction? How does satisfaction vary based on developers’ experience? What are the key strengths of the top AI-assisted coding tools? Click to expand ACCESS THE FULL REPORT Methodology The 30th edition of the Developer Nation survey reached more than 12,000 respondents from 128 countries around the world. This research report series delves into key developer trends for Q3 2025 and beyond. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT All Reports Choosing the right AI coding tools for your team Usage, satisfaction, and trust among professional developers Access the Full Report About this Report The rapid rise of AI-assisted coding tools marks a pivotal moment in software development. What began as experimental add-ons has quickly evolved into a crowded market of products, each claiming to boost productivity and transform workflows. Yet with so many options and so much noise, it can be difficult to know which tools are truly delivering value. By examining adoption, satisfaction, and trust-related attributes such as accuracy, support, and security, this report provides a data-driven benchmark of which AI coding tools developers are embracing and which they rate most highly. The analysis reveals where usage aligns with satisfaction, where trust is earned through consistent delivery, and where gaps remain between expectations and reality. For engineering leaders making decisions about which tools to integrate and scale across their teams, the insights in this report help distinguish the coding tools that enable productivity from those that are still struggling to meet developer needs.

Key Questions Answered To what extent are developers building AI-powered applications? Which regions are leading in AI integration? Have developers begun deploying agentic AI architectures to production? How does the implementation of agentic AI vary by company size? How does the implementation of agentic AI vary by project type? What types of agentic architectures are being deployed in production? What use cases are developers targeting with agentic architectures? Click to expand ACCESS THE FULL REPORT Methodology The 30th edition of the Developer Nation survey reached more than 12,000 respondents from 128 countries around the world. This research report series delves into key developer trends for Q3 2025 and beyond. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT All Reports The state of agentic AI adoption in software projects The architectures developers use, and the use cases they target Access the Full Report About this Report Agentic AI is emerging as one of the most transformative shifts in how companies design and deploy intelligent systems. This mini-report analyses insights from over 8,400 professional developers to help CTOs and engineering leaders navigate the rapidly evolving agentic AI landscape and make informed architecture and use case decisions. We’ll explore how the implementation of agentic AI varies by company size and project type as well as looking at the types of agentic architectures that are being deployed to production, along with the use cases developers are targeting.

Key Questions Answered What are the main barriers preventing developers from integrating generative AI into their applications? What can software engineering leaders focus on to prepare for challenges that slow the adoption of generative AI? Click to expand ACCESS THE FULL REPORT Methodology The 30th edition of the Developer Nation survey reached more than 12,000 respondents from 128 countries around the world. This research report series delves into key developer trends for Q3 2025 and beyond. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT All Reports Barriers to integrating generative AI in applications Understanding what prevents developers from building generative AI features across different company types Access the Full Report About this Report Generative artificial intelligence (AI) is rapidly becoming an integral part of the modern software ecosystem, significantly transforming how developers innovate and deliver value in their applications. In fact, this technology has already begun redefining software capabilities and introducing new technical considerations around model selection, integration methods, and user experience design. As of Q3 2025, a quarter (25%) of professional developers are adding generative AI features to their applications. However, this means that a large share of the developer population is still not building applications that utilise this technology. To understand this from the perspective of developers, we asked over 7,000 professional developers about the main barriers preventing them from integrating generative AI into their applications. For software engineering leaders, these insights provide a benchmark against peers and industries, helping them prioritise technology investments and prepare mitigation strategies for the challenges most likely to slow adoption.