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Generative AI for software Engineering

Generative AI is set to radically change how software is developed

Software plays a vital role in modern business, whether it’s integrated into enterprise apps or products. Software teams are under pressure to deliver more, faster, with expected quality, meaning the pace of technological evolution in software engineering is only accelerating. They continue to struggle with quality tests coverage, functional and technical defects, cybersecurity vulnerabilities and technical debt.

In recent years, software engineering has witnessed a significant shift towards more automation and simplification – from DevOps automation to low-code platforms – expediting many development processes to make life easier for developers.

Generative AI is the latest and, by far, the most groundbreaking evolution. Thanks to the rise of powerful large language models, it has catapulted onto the world stage and promises to elevate the way we do everything – including software engineering.

Generative AI Impact goes far beyond coding assistants

Using plain language, developers can describe the intended functionality of new software, then watch as generative AI codes their ideas to life. Andrej Karpathy, from OpenAI, recently turned heads by saying: “the hottest new programming language is English,” encapsulating the significance of this breakthrough.

Best of all, this remarkable capability can be integrated throughout the software development life cycle (SDLC), from business needs analysis and writing Agile user stories to software design, coding (and retro documentation), packaging, deployment, testing, and monitoring – augmenting the multitude of tasks software engineers perform.

Generative AI is the fastest growing technology we’ve ever seen, and CIOs are keen to explore the opportunity and reap the benefits: more productivity, better quality, and accelerated time to value. However, they must recognize the confidentiality and IP risks involved, the potential costs of uncontrolled generative AI use, and how the technology can impact the structure, skillset, and ways of working of their software engineering teams.

Generative AI Lab

Our Generative AI Lab is a dedicated team of experts specialized in artificial intelligence from various Capgemini teams around the world.

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Integrate generative AI across the full software life cycle

Rather than just implementing a one-time solution, leaving clients to navigate the ensuing generative AI challenges themselves, we transform the very core of the software engineering process and organization, then iteratively measure the progress to achieve continuous improved outcomes.

Kickstart your transformation with our Generative AI for Software Engineering blueprint

  • We assess your current software engineering life cycle, scanning the field of opportunities and selecting the most promising use cases and processes to focus on.
  • We design and secure the required foundations to select and deploy generative AI technologies for software engineering, to adapt software teams’ structure, skills and ways of working, at scale, safely and at a controlled cost, including setting guardrails to mitigate legal and cybersecurity risks.
  • We build a plan to progressively leverage generative AI at the different stages of the DevOps cycle.
Upskill and engage your teams through “hands-on” collaboration

  • Using our generative AI companions (software engineers trained on the latest generative AI technologies and methods), we establish a collaboration model that ranges from simple coaching to full-fledged partnership aimed at building your best-in-class generative AI-powered software house.
  • Our advanced Generative AI for Software Engineering Academy with a certification program, guarantees generative AI becomes an ingrained part of how your software teams operate.
Measure and improve together to set new software engineering market standards

  • We have developed an industrialized value measurement protocol that evaluates the objective impact of generative AI across the SDLC. It’s used to measure and compare your productivity, quality, and developer experience against our benchmark, which factors in all our related internal and external projects.

Latest insights

Capgemini Research Institute

Conversations for Tomorrow #9: Generative AI
Book

HBR guide to generative AI for managers
Report

World Energy Markets Observatory
Capgemini Research Institute

Generative AI in leadership

Why Capgemini?

We’re a global leader, with over 100K developers focused on custom software engineering.

  • We evaluate the potential best generative AI use cases and measure their impact through pilots conducted with industrial protocols.
  • We evaluate market tools and select the most appropriate ones for each phase of the SW lifecycle.
  • We develop a framework to understand our clients’ specific legal and compliance requirements, allowing us to identify mitigations for secure, safe generative AI usage.
  • We assess the impact on teams’ organization, pyramids, skills and ways of working.
  • We benefit from our global partnerships with technology and tools vendors.

At the forefront of software engineering transformation

If our foundational knowledge, methodologies, and past successes are any indication of our ability to continue to deliver outstanding results for clients, you can anticipate further excellence in how we can help you create value from applying generative AI to software engineering.

Are you ready to unlock the transformative power of generative AI? Take the first steps and embark on this cutting-edge journey with us.