The latest technological developments in generative artificial intelligence (GenAI) offer powerful capabilities to small and medium enterprises (SMEs) as they facilitate the democratization of scalability and creativity. With little technical expertise or financial resources, SMEs can leverage this technology to streamline work processes and unleash innovation, improving their product offerings and long-term competitiveness. In this article, we discuss how SMEs can navigate both the promises and challenges of GenAI and offer a roadmap for deploying the technology. We then introduce a sailing metaphor that reveals key strategic dimensions for GenAI deployment: competency of employees, effective leadership and work values, organizational culture, collaboration and cooperation, and relationships with third parties. We conclude with practical recommendations for successfully deploying GenAI in SMEs.
Generative artificial intelligence (GenAI) technologies using LLMs (large language models), such as ChatGPT and GitHub Copilot, with the ability to create code, have the potential to change the software-development landscape. Will this process be incremental, with software developers learning GenAI skills to supplement their existing skills, or will the process be more destructive, with the loss of large numbers of development jobs and a radical change in the responsibilities of the remaining developers? Given the rapid growth of AI capabilities, it is impossible to provide a crystal ball, but this article aims to give insight into the adoption of GenAI with LLMs in software development. The article gives an overview of the software-development industry and of the job functions of software developers. A literature review, combined with a content analysis of online comments from developers, gives insight into how GenAI implemented with LLMs is changing software development and how developers are responding to these changes. The article ties the academic and developer insights together into recommendations for software developers, and it describes a CMM (capability maturity model) framework for assessing and improving LLM development usage.