#getthefutureyouwantturbocharging software with gen ai: how organizations can realize the full potential of generative ai for software engineering#getthefutureyouwanthow organizations can realize the full potential of generative ai for software engineeringturbocharging software with gen ai table of content2capgemini research institute 2024turbocharging software with gen ai: how organizations can realize the full potential of generative ai for software engineering 3capgemini research institute 2024turbocharging software with gen ai: how organizations can realize the full potential of generative ai for software engineering executive summary organizations are reaping multiple benefits from leveraging generative ai for software engineering. • the leading benefits for organizations are enabling more innovative work, such as developing new software features/services (observed by 61% of surveyed organizations), improving software quality (49%), and increasing productivity (40%).• organizations using generative ai have seen a 7–18% productivity improvement1 in the software engineering function as per early estimates. this is highest for specialized tasks such as coding assistance2 (34% as the maximum potential for time savings with 9% on average) and creating documentation (35% as the maximum potential for time savings with 10% on average). this research analyzed time savings in various software engineering tasks using generative ai tools and not cost savings which can be significantly different.• organizations are utilizing these productivity gains on innovative work such as developing new software features (50%) and upskilling (47%). very few aim to reduce headcount (4%). • generative ai is having a positive impact on software professionals’ job satisfaction.• 69% of senior software professionals and 55% of junior software professionals report high levels of satisfaction from using generative ai for software.• 78% of software professionals are optimistic about generative ai’s potential to enhance collaboration between business and technology teams.78lapgemini research institute 2024turbocharging software with gen ai: how organizations can realize the full potential of generative ai for software engineering executive summary generative ai adoption is at an early stage but will accelerate sharply. • adoption of generative ai for software engineering is still in its early stages, with 9 in 10 organizations yet to scale.• 27% of organizations are running generative ai pilots, and 11% have started leveraging generative ai in their software functions.• three in four (75%) large organizations (annual revenue greater than $20 billion) have adopted (piloted/scaled) generative ai compared to 23% of their smaller counterparts (annual revenue between $1–5 billion). • adoption (including pilots) is expected to increase significantly in the next two years from 46% of software workforce using generative ai tools today (for any kind of training, experimenting, piloting, and implementing, with authorized or unauthorized access) to an estimate of 85% in 2026.• generative ai is expected to play a key role in augmenting the software workforce with better experience, tools and platforms, and governance (assisting in more than 25% of software design, development, and testing work by 2026).• coding assistance is the leading use case, but generative ai also finds applications in other software development lifecycle (sdlc) activities (test case generation, documentation, code modernization, ux design assistance, etc.)• most use cases have yet to be adopted by a majority of organizations (39% are focusing on coding assistance and 37% on ux design assistance as top adopted use cases).5capgemini research institute 2024turbocharging software with gen ai: how organizations can realize the full potential of generative ai for software engineering executive summary lack of foundational prerequisites and unofficial usage of generative ai pose significant functional, security, and legal risks. • 27% of organizations have the platforms & tools, and 32% have talent prerequisites in place, to implement generative ai for software engineering.• over 60% lack governance and upskilling programs for generative ai for software engineering. • of those software professionals who use generative ai, 63% use unauthorized tools.• nearly a third of the workforce is self-training on generative ai for software as less than 40% of employees are receiving training from their organizations.• using unauthorized tools without proper governance and oversight exposes organizations to functional, security, and legal risks like hallucinated code, code leakage, and ip issues.6capgemini research institute 2024turbocharging software with gen ai: how organizations can realize the full potential of generative ai for software engineering executive summary how can organizations harness the full potential of generative ai for software engineering? • select and prioritize high