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July 10, 2024

Discover how the future of software engineering is being shaped by generative AI. Capgemini Research Institute’s report, Turbocharging software with Gen AI, explores the benefits and opportunities that generative AI brings to software engineering.

One in two organizations adopting generative AI see improvements in enabling innovative work and quality of software.

Organizations with active* generative AI initiatives have seen 7–18% improvement in total productivity across the SDLC#

A senior technical leader from a multinational digital communications technology company elaborates:

One of the biggest drivers of generative AI adoption is innovation. Not just on the product side but also on the process side. While senior professionals are leveraging generative AI combined with their domain expertise for product innovation, junior professionals see value in AI process and tool innovation, and in automation and productivity optimization.

* active initiatives are those generative AI deployments that are in the pilot or scaling stages.
# Total productivity improvement refers to overall improvement in the productivity of the software professionals from all types of tasks accelerated by generative AI.

Drawing insights from a survey of 1,000 senior executives and 1,000 software professionals across organizations with annual revenues exceeding $1 billion, this report takes a look at the present and future impact of generative AI.

Some organizations are already reaping the rewards. Generative AI enables the development of innovative software features and services, as reported by 61% of surveyed organizations. It improves overall software quality, with 49% of respondents observing this benefit. And it boosts productivity, with 40% of organizations experiencing this positive outcome.

These productivity gains allow organizations to focus on innovative work. Organizations recognize generative AI’s potential to augment human creativity rather than replace it, and only a small fraction of organizations surveyed (4%) intend to reduce headcount.

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Adoption of generative AI in software engineering is in its early stages, but more than four in five software professionals are estimated to leverage* it by 2026

Director at a leading biopharma company:

“Not everyone is going to be an app developer. But generative AI will unlock the capabilities of business users to some extent and make them more independent, allowing them to self-create some code or apps as needed.”

The adoption of generative AI for software engineering is still in its infancy. Currently, 27% of organizations are actively exploring its potential through pilot projects, while 11% have already begun integrating generative AI into their software functions. However, the adoption rate, including pilot projects, is expected to experience a significant surge, more than tripling in the next two years.

Generative AI is increasingly – and rapidly – being integrated into everyday life. Yet only 27% of organizations have the necessary platforms and tools to harness its power. This lack of preparedness poses a significant risk, as employees may turn to unauthorized generative AI tools and solutions to stay ahead. In fact, our survey reveals that 63% of software professionals who use generative AI rely on unauthorized tools. This unchecked use of generative AI can expose organizations to a multitude of risks, including functional errors, security breaches, and legal issues such as hallucinated code, code leakage, and intellectual property problems, highlighting the need for proper governance and oversight.

Organizations lack the governance framework and upskilling and reskilling programs for leveraging generative AI for software engineering.

Source: Capgemini Research Institute, Generative AI in Software Engineering, Senior Executive Survey, April 2024, N = 1,092 organizations
represented by 1,092 software professionals.

Turbocharging software with Gen AI from the Capgemini Research Institute looks at how organizations can harness the full potential of generative AI for software engineering in a way that mitigates security risks, prioritizes the most impactful use cases, and puts people at the heart of this transformation.

How can organizations harness the full potential of generative AI for software engineering?

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