Released
The New Skills in Finance Report 2022
In a digital-transforming era, there is a widening skills gap for those who cannot adapt to the new digital world in finance.
CFTE and Elevandi published the report with the discussion with leading experts to help governments, organisations and individuals address the current skills gap in finance and build a digital-resilient workforce in the industry.
Key Insights
Key takeaways from "Game changer: The startling power generative AI is bringing to software development" report published by KPMG
CFTE summarised “Game changer: The startling power generative AI is bringing to software development” report by KPMG. The report predicts that software development is on the verge of a dramatic leap thanks to generative AI.
Key Aspects
- It highlights how generative AI is rewriting the traditional approaches to building and maintaining software, with significant implications for developers and corporations.
- The report emphasises the role of generative AI in creating original content, including code, and its adoption in the corporate environment. It also addresses the rapid user adoption of platforms like ChatGPT, which demonstrates the growing interest and potential of generative AI in technology and business.
Table of Contents
- Introduction to Generative AI in Software Development
- Paradigm Shift in Technology Comparable to Cloud or DevOps
- Value of Fine-Tuning Generative AI on Proprietary Code
- Diverse Applications of Generative AI in Software Development
- Overcoming Challenges and Risks in Generative AI Adoption
- The Importance of Early Adoption and Experimentation
- KPMG’s Role in Leveraging Generative AI for Businesses
Key Findings and Insights
This report will give you an insight into:
- Generative AI's Role in Software Development: The technology is set to revolutionise software development by enabling developers to hand off repetitive tasks, enhancing productivity, and speeding up deployment.
- Fine-Tuning on Proprietary Code: Training generative AI on a company's source code and technical documentation could lead to significant productivity gains and change the economics of software creation and maintenance.
- Applications in Development Processes: Generative AI is being used to explain code functionality, provide guidance on code classes, improve code consistency, simplify code, generate unit tests, translate code, write documentation, and accelerate debugging.
- Lowering Barriers for New Developers: It enables rapid onboarding of developers, enhances flexibility across various platforms, and reduces dependence on legacy codebase knowledge.
- Challenges and Risks: Issues include potential flawed results, transparency and traceability concerns, management skepticism, and intellectual property considerations.
- Importance of Early Adoption: Engaging with generative AI technology now is crucial to position organizations to rapidly adapt as the technology advances.