New role Overseeing generative AI for software leaders.

New role Overseeing generative AI for software leaders.

The Rise of Generative AI: A Paradigm Shift for Software Leaders

Generative AI

Generative AI, a technology that goes beyond code generation, is expected to become an integral part of software work in the near future. According to a recent analysis by Gartner, by 2025, over half of all software engineering leader role descriptions will explicitly require oversight of generative AI. This brings a sense of urgency to software leadership, extending their scope beyond application development and maintenance.

While generative AI will not replace developers, it has the potential to automate certain aspects of software engineering. “It cannot replicate the creativity, critical thinking, and problem-solving abilities that humans possess,” says Gartner analyst Haritha Khandabattu, “but it serves as a force multiplier.” This technology encompasses team management, talent management, business development, and the enforcement of ethics.

Industry leaders recognize generative AI as both a productivity tool for developers and a gateway to business opportunities that software leaders need to understand and embrace. John Roese, the Global Chief Technology Officer at Dell Technologies, emphasizes that AI projects should not be treated as mere technology endeavors. “The good ones are aligned to business outcomes,” he says. “Every investment and shift to automation causes legacy jobs to disappear and creates new jobs charged with making that automation operate.”

As generative AI projects continue to evolve rapidly, software leaders will find themselves participating or even leading expanded teams. AI breakthroughs have given rise to a new level of technical expertise, such as AI specialists and machine learning engineers. “AI projects need a rounded approach,” says Bryan Madden, Global Head of AI Marketing at AMD, “to consider practical and technological factors, as well as governance, policy, and ethics.” Collaboration between departments is crucial in building internal use cases that accelerate product capabilities for customers.

The success of AI depends on open partnerships and collaboration across technology, business, and society. As AI becomes more ubiquitous across various industries, domain experts will play a vital role in providing context and insights for AI application developers. Madden predicts that policy experts will also be brought into the realm of application development to ensure responsible use of generative AI.

Prompt engineering and in-context learning are emerging abilities for developers, allowing them to optimize prompts for large language models and build new capabilities for customers. This further expands the reach and capability of AI tools in software development.

Another area where software leaders must take the lead is in AI ethics. Khandabattu suggests that software engineering leaders establish an AI ethics committee to create policy guidelines. This committee will help teams responsibly use generative AI tools for design and development, while also identifying and mitigating ethical risks associated with in-house or third-party generative AI products.

Generative AI can also transform the recruiting, development, and management of talent. Applications powered by generative AI can speed up recruitment and hiring tasks such as job analysis and transcribing interview summaries. Skills management and development are also supported by generative AI, enabling software engineering leaders to identify skill combinations that create new positions and eliminate redundancies.

In summary, the rise of generative AI represents a paradigm shift for software leaders. It requires them to expand their responsibilities beyond traditional software development, encompassing team management, talent management, business development, and ethics. Collaboration and open partnerships across departments and industries will be crucial for the successful application and advancement of generative AI. With the right approach, software leaders can leverage generative AI to drive innovation, improve efficiency, and create new opportunities for their organizations.