Generative AI in Software Development Lifecycle Market Size & Share Report by 2033

Research Methodology – Generative AI in Software Development Lifecycle Market

At Straits Research, we adopt a rigorous 360° research approach that integrates both primary and secondary research methodologies. This ensures accuracy, reliability, and actionable insights for stakeholders. Our methodology for the Generative AI in Software Development Lifecycle Market comprises the following key stages:

Market Indicator & Macro-Factor Analysis

Our baseline thesis for the Generative AI in Software Development Lifecycle Market is developed by integrating key market indicators and macroeconomic variables. These include:

Factors considered while calculating market size and share

Trends in artificial intelligence technology and its application in software development
Market demand for Generative AI in different regions
The number of companies employing Generative AI in their software development lifecycle
Investment in research and development of Generative AI technologies
Market strategies adopted by key players in the industry
The marketâs historical growth rate and its potential development in the future
Regulatory policies impacting the market
Adoption rate of Generative AI in different industries

Key Market Indicators

Yearly spending on Generative AI in software development
Growth rate of the Generative AI market in software development
Market share of major players in this field
Number of new entrants in the market
Yearly growth in the demand for Generative AI in software development
Allocation of funds for research and development of Generative AI

Growth Trends

Increasing adoption of Generative AI in software development due to improved efficiency and reduction in the time taken for the software development lifecycle
Increased investment in artificial intelligence technology
Innovation and evolution in the applications of Generative AI in the software development process
Growth in the integration of Generative AI with other advanced technologies like machine learning and deep learning
Expansion in the usage of Generative AI in various industries such as healthcare, finance, retail, and more

Secondary Research

Our secondary research forms the foundation of market understanding and scope definition. We collect and analyze information from multiple reliable sources to map the overall ecosystem of the Generative AI in Software Development Lifecycle Market. Key inputs include:

Company-Level Information

Annual reports, investor presentations, SEC filings
Company press releases and product launch announcements
Public executive interviews and earnings calls
Strategy briefings and M&A updates

Industry and Government Sources

Country-level industry associations and trade bodies
Government dossiers, policy frameworks, and official releases
Whitepapers, working papers, and public R&D initiatives
Relevant Associations for the Generative AI in Software Development Lifecycle Market

Market Intelligence Sources

Broker reports and financial analyst coverage
Paid databases (Hoovers, Factiva, Refinitiv, Reuters, Statista, etc.)
Import/export trade data and tariff databases
Sector-specific journals, magazines, and news portals

Macro & Consumer Insights

Global macroeconomic indicators and their cascading effect on the industry
Demand–supply outlook and value chain analysis
Consumer behaviour, adoption rates, and commercialization trends

Primary Research

To validate and enrich our secondary findings, we conduct extensive primary research with industry stakeholders across the value chain. This ensures we capture both qualitative insights and quantitative validation. Our primary research includes:

Expert Insights & KOL Engagements

Key Opinion Leader (KOL) Engagements
Structured interviews with executives, product managers, and domain experts
Paid and barter-based interviews across manufacturers, distributors, and end-users

Focused Discussions & Panels

Discussions with stakeholders to validate demand-supply gaps
Group discussions on emerging technologies, regulatory shifts, and adoption barriers

Data Validation & Business POV

Cross-verification of market sizing and forecasts with industry insiders
Capturing business perspectives on growth opportunities and restraints

Data Triangulation & Forecasting

The final step of our research involves data triangulation ensuring accuracy through cross-verification of:

Demand-side analysis (consumption patterns, adoption trends, customer spending)
Supply-side analysis (production, capacity, distribution, and market availability)
Macroeconomic & microeconomic impact factors

Forecasting is carried out using proprietary models that combine: