Software Development Statistics for 2026

Software is now one of the largest line items in the global economy, and the numbers behind how it gets built keep moving fast. We pulled together the most useful software development statistics for 2026, grouped into market size, developer talent, project outcomes, outsourcing, and AI in development. Every figure below carries a named source and a link. Where research firms disagree, we say so rather than picking one number and hiding the rest.

If you are scoping a build, pair these numbers with our guides to custom software development and app development cost in 2026. Use the sections below to jump straight to what you need: market size and growth, developer talent and pay, project success rates, the state of outsourcing, and how far AI has actually moved into day-to-day coding.

Market size and growth

• Worldwide IT spending is projected to reach $6.31 trillion in 2026, up 13.5% year over year (Source: Gartner, April 2026).
• The global custom software development market is forecast to reach $146.18 billion by 2030, a 22.6% CAGR from 2025 to 2030, with enterprise software the largest type segment at over 60% of 2024 revenue and cloud the leading deployment mode at 57% (Source: Grand View Research, 2025).
• Revenue in the IT outsourcing market is projected at $618.36 billion in 2026, growing at a 5.85% CAGR to roughly $821.55 billion by 2031 (Source: Statista Market Insights, 2026).
• Spending on low-code development technologies was forecast to hit $44.5 billion by 2026, with Gartner also projecting that 75% of new enterprise applications would be built on low-code platforms by 2026 (Source: Gartner, via InfoWorld).
• Gartner also predicted that by 2026, developers outside formal IT departments would account for at least 80% of the user base for low-code tools, up from 60% in 2021 (Source: Gartner, via InfoWorld).

Takeaway: Demand for software keeps outrunning overall economic growth, and custom and cloud-delivered work is the fastest-expanding slice. Low-code is pulling a growing share of simple internal apps toward business users, which frees professional engineers to focus on the hard, differentiated builds. For teams, the practical read is that budgets are growing but so is competition for delivery capacity.

Developers and talent

• 180 million developers now build on GitHub after more than 36 million joined in the past year, which the company frames as roughly one new developer every second (Source: GitHub Octoverse 2025).
• Using an independent bottom-up model, SlashData estimates 47.2 million active developers worldwide, of whom about 36.5 million are professional programmers (Source: SlashData, 2025).
• In the United States, employment of software developers, QA analysts, and testers is projected to grow 10% from 2025 to 2035, much faster than the all-occupation average, with about 106,100 openings per year, at a median wage of $134,040 as of May 2025 (Source: U.S. Bureau of Labor Statistics).
• JavaScript remains the most-used language at 68.9% of professional developers, while Python climbed 7 percentage points year over year to 58% (Source: Stack Overflow Developer Survey 2025).
• On GitHub, TypeScript became the most-used language for the first time in August 2025, with 66% year-over-year growth in contributors, the largest language shift the platform has seen in more than a decade (Source: GitHub Octoverse 2025).
• Global median pay in the 2025 survey was $79,742 for back-end, $72,509 for full-stack, and $62,015 for front-end developers, based on 49,009 respondents (Source: Stack Overflow Developer Survey 2025).
• Pay is heavily geographic: in the United States, reported medians reached $175,000 for back-end and $145,000 for front-end developers in the same survey, far above the global figures (Source: Stack Overflow Developer Survey 2025).
• SlashData's model shows the mix shifting toward professionals, with the professional-programmer count rising from 21.8 million to 36.5 million while hobbyist numbers fell by more than 1 million in a year (Source: SlashData, 2025).

Takeaway: The talent pool is large and still expanding, but population estimates vary widely by methodology, so treat any single headcount as a range. The wide US-versus-global pay gap is the single biggest reason distributed and offshore teams remain attractive. Language preferences are shifting toward typed and AI-friendly stacks, which matters when you choose a stack you will maintain for years.

Project outcomes

• In the most cited industry benchmark, 31% of projects were successful, 50% were challenged (late, over budget, or under-scoped), and 19% failed outright (Source: Standish Group CHAOS Report 2020).
• Across more than 5,400 projects studied with the University of Oxford, large IT projects (initial budgets above $15 million) ran on average 45% over budget and 7% over time while delivering 56% less value than predicted, and 17% went so badly they threatened the company's existence (Source: McKinsey and University of Oxford).

These two datasets come from different eras and definitions, but they point the same direction: the larger and more rigid a project, the worse its odds. The CHAOS figures count a project as successful only if it shipped on time, on its original budget, and with the agreed feature set, so anything that slipped on cost, schedule, or scope lands in the challenged bucket.

Takeaway: Scope discipline beats raw effort. Smaller, incremental deliveries have historically outperformed big-bang projects, which is one reason a focused MVP development approach reduces risk. For a step-by-step path, see how to build an MVP.

Outsourcing and offshore delivery

• The IT outsourcing market is projected at $618.36 billion in 2026 and is expected to keep compounding through 2031 (Source: Statista Market Insights, 2026).
• Why companies outsource has shifted: the share of executives naming cost reduction as their primary driver fell from 70% in 2020 to 34%, as access to talent and speed to market rose in importance (Source: Deloitte Global Outsourcing Survey 2024).

That reframing matters when you read the market-size number above. A $618 billion market that is increasingly bought for talent and speed rather than for the lowest hourly rate rewards partners who can show delivery track record, not just a cheap blended rate. It also explains why the gap between US and global developer pay keeps distributed delivery attractive even as cost slides down the list of stated reasons.

Takeaway: Outsourcing is no longer mainly a cost play. The most defensible reason to partner externally in 2026 is speed and access to specialized skills you cannot hire fast enough in-house. For how that translates into pricing, compare top custom software development companies in 2026.

AI in software development

• More than 84% of developers now use or plan to use AI tools, up from 76% a year earlier, yet only 29% trust AI output for accuracy and 46% actively distrust it (Source: Stack Overflow Developer Survey 2025).
• Two-thirds (66%) of developers say AI answers are "almost right but not quite," and 45% report losing significant time debugging AI-generated code (Source: Stack Overflow Developer Survey 2025).
• Nearly 80% of new developers adopted GitHub Copilot within their first week, and the Copilot coding agent authored more than 1 million pull requests from May to September 2025, across an ecosystem of 4.3 million AI projects on the platform (Source: GitHub Octoverse 2025).
• In a controlled experiment with 95 developers, those using an AI assistant completed a defined coding task 55.8% faster (1 hour 11 minutes versus 2 hours 41 minutes), a statistically significant result (P=.0017) (Source: GitHub Research, 2022).
• Fully autonomous agents are still early: in the 2025 survey, 52% of developers either do not use AI agents or stick to simpler tools, and 38% have no plans to adopt agents at all (Source: Stack Overflow Developer Survey 2025).

Takeaway: AI assistance is now the default, and it measurably speeds up well-specified tasks, but trust is falling and review overhead is real. The honest framing for 2026 is that AI accelerates good engineering practices rather than replacing them.

How to cite these statistics

You are welcome to reference any figure on this page. When you do, please cite the original named source (for example, "Stack Overflow Developer Survey 2025" or "GitHub Octoverse 2025") rather than this page, and link to the source URL listed next to each statistic. If you would like to credit this roundup as the place you found a figure, a link to this article is appreciated but not required.

Methodology and a note on comparing figures

Every statistic here comes from a named primary or widely recognized source and is dated to its publication. We deliberately left out numbers we could not trace to a specific report. A few cautions when you reuse these figures: market-size estimates differ because firms define "custom software" and "outsourcing" differently, so a 2026 custom-software figure from one firm will not match another. Developer-population counts range from roughly 29 million to 180 million depending on whether a source counts professional developers, all active developers, or every account on a platform. Finally, the 55.8% AI productivity figure describes one controlled task and does not generalize to an entire sprint or a large legacy codebase. Read each number alongside its definition, not in isolation.

Related software guides

• How Much Does It Cost to Build an App in 2026
• Top Custom Software Development Companies in 2026 (Compared)
• How to Build an MVP: A Step-by-Step Guide (2026)

Ready to move forward? See our services or MVP development.