Figure 2 IT Spend: Application Development Versus Application Maintenance And Support This shows the IT spend of app development as well as app maintenance and support for consumer durables, diversified financials, government, insurance, and retailing. On average, ISG’s global benchmarking data respondents said they spent 49.5% of application spend on app development and 50.5% on app maintenance and support. This graphic has an associated spreadsheet that includes all data presented.

Answers were: AI-infused applications, 41%; complete customer-facing applications — mobile and/or web, 39%; complete internal-facing applications — mobile and/or web, 38%; administrative apps for gathering, tracking, and reporting on data, 35%; business process/workflow applications, 33%; business analysis and reporting, 33%; core business applications, 30%; web and/or mobile frontends only, 28%; augmented/virtual reality apps, 26%; small automations, 23%; and IoT apps, 23%.

Figure 2 IT Spend: Application Development Versus Application Maintenance And Support This shows the IT spend of app development as well as app maintenance and support for consumer durables, diversified financials, government, insurance, and retailing. On average, ISG’s global benchmarking data respondents said they spent 47% of application spend on app development and 53% on app maintenance and support. This graphic has an associated spreadsheet that includes all data presented.

MAD Services Deliver Cool Products While Transforming Your Development Clients want more autonomy to better control their own innovation and development capabilities. Clients want to build modern, up-to-date custom applications leveraging all the latest and greatest technologies, including AI and generative AI (genAI). For a more precise market definition for MAD services, see The Modern Application Development Services Landscape, Q3 2024.

Application development is constantly evolving as developers look to innovate. At the same time, organizations seek to generate revenue growth and improve customer experience. This leads developers to seek out new applications, best practices, and techniques such as the agile methodology, low-code, and generative AI for software development (TuringBots). This report highlights application development trends from our latest data in Forrester’s Developer Survey, 2023.

Figure 2 IT Spend: Application Development Versus Application Maintenance And Support This shows the IT spend of app development as well as app maintenance and support for consumer durables, diversified financials, government, insurance, and retailing. On average, ISG’s global benchmarking data respondents said they spend 42% of application spend on app development and 58% on app maintenance and support. This graphic has an associated spreadsheet that includes all data presented.

Application development leaders want more collaboration, cocreation, and co-development partnership models with application development service providers. Forrester defines MAD service providers as: Service providers that work collaboratively with their clients to cocreate custom modern applications and, in parallel, assist them in the transformation and modernization of their software development capabilities and organization.

This data-driven report outlines important European application development benchmarks for budgets, staffing levels, outsourcing, development methodologies, release cycles, and testing. We share insights on four industries: business services and supplies, diversified financials, healthcare equipment and services, and insurance.

Agentic software development platforms target professional development engineers that custom build software. These platforms heavily leverage foundational LLMs specifically designed for the act of architecting, designing, and coding software. Companies use them to build custom apps or to customize packaged apps. For custom development, the SDLC is dramatically compressed, making experimentation of new ideas for application and platform development and engineering more creative and productive.

However, this approach produces siloed applications where every application is its own source of truth. The approach also struggles to provide enterprise scale because it favors a multitude of small, localized applications. A data-centric development methodology can’t keep up with business needs.