AI is changing the economics of website development, but its growing role in engineering workflows has not translated into uniformly lower project prices, according to new research from GoodFirms. The B2B research and reviews platform says 98% of surveyed respondents now use AI in web development, while the cost of complex website projects continues to depend on functionality, technical complexity, developer location and experience.

The rapid adoption of generative AI has created an expectation that software development costs should fall as machines take over more coding and production tasks. Website development, however, is showing a more complicated pattern.

According to GoodFirms' latest website construction cost survey, 98% of respondents use AI in their web development workflows. The research suggests that AI is particularly effective at reducing the cost of basic websites and minimum viable products, while custom and feature-intensive projects continue to require conventional engineering expertise.

That distinction is important for businesses budgeting new digital experiences. A brochure-style website, landing page or relatively simple MVP can increasingly be assembled with AI-assisted development tools, reducing the amount of manual work required for initial production. More sophisticated projects still involve architecture, integrations, security, databases, performance engineering, testing and ongoing maintenance.

GoodFirms Senior Research Analyst Kusum Motiani describes the change as a widening gap between straightforward website production and engineering-intensive development. In the company's assessment, AI can substantially reduce the cost of basic builds, while factors such as geography and developer expertise remain relevant when projects require deeper technical work.

The result is that AI is altering how website-development costs are calculated rather than eliminating traditional pricing variables.

For enterprises, the implications extend beyond the number of developer hours saved. AI-assisted coding can accelerate prototyping and repetitive implementation, potentially allowing development teams to spend more time on architecture, user experience, integration and quality assurance. However, the need for human oversight can remain substantial when websites connect to enterprise systems or handle sensitive customer and business data.

The findings also arrive as businesses have more options for sourcing development work globally. GoodFirms has published updated lists of web development companies across markets including the United States, India, the United Kingdom, Canada and Australia.

Among the companies appearing on its regional lists are SDLC Corp, Instinctools, Empat, Closeloop Technologies and Unico Connect in the U.S.; Promatics Technologies, OpenXcell, Probey Services, Innovacio Technologies and Ajackus in India; and JPLoft, Utility, ELEKS, Sigli and Geeks Ltd. in the UK.

GoodFirms says its rankings evaluate companies using factors including quality, reliability and ability, with portfolio reviews, experience assessments, interviews, background checks and client reviews forming part of its verification process.

The broader development-market shift is significant because AI is lowering barriers to entry for simple web projects while potentially increasing the value of specialized engineering for complex builds. Businesses therefore face a more segmented vendor market: low-complexity work can increasingly be automated or AI-assisted, while high-complexity digital infrastructure remains dependent on technical judgment.

That distinction may also change how marketing and technology leaders evaluate agencies. Instead of asking only how much a website costs, buyers increasingly need to assess which parts of a project can be accelerated by AI and which require experienced engineering teams.

Market Landscape

AI coding assistants and generative development tools are compressing the time required for several routine software-development activities, including code generation, documentation, debugging and prototyping. Website creation is particularly exposed because many basic projects rely on established frameworks and reusable components.

Complex enterprise websites present a different cost structure. Integrations with CRM, commerce, analytics, identity, content-management and customer-data systems can introduce requirements that AI-assisted code generation alone does not resolve.

This creates a two-tier development environment in which AI can reduce production friction without necessarily reducing the total cost of sophisticated digital projects.

Strategic Outlook

The next phase of AI-assisted web development is likely to shift vendor evaluation from simple labor pricing toward engineering capability, AI adoption, governance and project complexity.

For marketing organizations, the practical question is increasingly whether an agency can use AI to accelerate delivery while retaining the human expertise needed for architecture, security, performance and business-system integration.

GoodFirms' research suggests that AI is already changing the baseline cost of simpler websites. For larger digital properties, however, the traditional variables of scope, complexity and engineering expertise remain important.

Top Insights

• GoodFirms reports that 98% of surveyed web-development professionals use AI, signaling widespread adoption across website-production workflows.
• AI can reduce development costs for basic sites and MVPs, but complex builds continue to require specialized engineering and technical oversight.
• Website pricing remains influenced by functionality, project complexity, developer location and experience despite broader AI adoption.
• The changing cost structure could push businesses to evaluate development partners based on AI capabilities alongside engineering expertise.
• The web-development market is increasingly separating automated production tasks from complex architecture, integration, security and performance engineering.

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