Generative AI will be an integral part of software work in the near future, and not just for code generation. According to a recent Gartner analysis, the majority of software industry leaders will soon integrate generative AI into their daily work.
By 2025, more than half of software engineering manager job descriptions will explicitly require generative AI oversight, the consultancy estimates. It is therefore urgent to extend the function of software manager (often called lead dev) well beyond the limits of application development and maintenance.
Team management, talent management, development and ethical compliance will be part of generative AI oversight, according to Gartner analyst Haritha Khandabattu. Generative AI won’t replace developers, but it has the ability to automate some aspects of software engineering,” she adds. Although it “can’t replicate creativity, critical thinking, and problem-solving abilities that humans possess”, it serves as a force multiplier.
Generative AI is not just a productivity tool for developers
Industry leaders agree that generative AI is not just a productivity tool for developers. It also represents business opportunities. “AI projects aren’t just technology projects,” says John Roese, chief technology officer at Dell Technologies. “Good projects are aligned with business outcomes. AI projects almost inevitably break organizational structures, and it’s not about technical decisions. Every investment and move to automation leads to the demise of existing jobs and creates new jobs responsible for making this automation work.”
Expect an expansion of the teams lead devs participate in or lead. “Breakthroughs in AI have spawned a new level of technical expertise, such as AI specialists and machine learning engineers, who develop and deploy AI algorithms and neural networks,” says Bryan. Madden, head of AI marketing at AMD. “AI and its deployment are evolving at a rapid pace. AI projects require a holistic approach to ensure that not only practical and technological factors are taken into account, but that governance, policy and ethics also follow.”
While most AI efforts are led by the CEO, CIO, or engineering lead, “employees from different departments should collaborate together, building internal use cases to accelerate product capabilities for customers,” said Naveen Zutshi, CIO of Databricks. “Business teams can work with engineers, those who report to CIO and IT, to build internal LLM models that improve business processes across all departments.”
Increasing emphasis on learning in context
As a result, the success of AI “will depend on partnerships and collaboration between technology, business and society,” says Madden. “As AI becomes more pervasive in industries such as healthcare, finance and education, it will take experts to provide context and insights to AI application developers. This knowledge will help refine applying AI in the best possible way, for the greatest benefit of their customers”.
According to Zutshi, there is also a growing emphasis on prompt engineering or learning in context. “This is a new ability for developers to optimize (prompt) prompts for large language models and create new capabilities for customers.
Another area where software engineering leaders need to take the lead is the ethics of AI. They “must work with an AI ethics board, or create one, to develop guidelines that will help teams responsibly use generative AI tools for design and development,” says Ms. Khandabattu. They will be required to identify and help “mitigate the ethical risks of any generative AI product developed in-house or purchased from third-party vendors.”
Recruitment, development and talent management will also be boosted by generative AI, adds Khandabattu. Generative AI applications can speed up recruiting and hiring tasks, such as job analysis and transcribing interview summaries. For example, software maintainers “may enter a prompt asking for keywords or keyphrases related to skills or experience.” In addition to recruitment, generative AI supports skills management and development. “It will help software engineering leaders rethink roles by identifying skills that can be combined to create new positions and eliminate redundancies.”
Source: “ZDNet.com”