Software leaders will manage generative AI efforts by 2025, as predicted by Gartner, with implications beyond application development.
Gartner predicts that by 2025, most software leaders will be involved in overseeing generative AI efforts, which will expand their responsibilities beyond application development. This shift will require them to manage teams, talent, business development, and ethical considerations related to generative AI. While AI won’t replace developers, it can automate certain aspects of software engineering and enhance efficiency.
Nicholas Berente and Bin Gu emphasize the crucial role of managers in AI’s societal transformation, as they make key decisions about AI, oversee its development and implementation, and govern its use. Managers must address challenges like aligning AI with business strategies, human-AI interfaces, and ethical, privacy, and security concerns.
Business alignment is seen as a key leadership capability, as AI presents not only productivity tools but also business opportunities. IT professionals can expect an expansion of their teams to include AI specialists and machine learning engineers, focusing on practical, technological, governance, policy, and ethical aspects of AI projects.
Collaboration is essential for AI’s success, with teams from different departments working together to accelerate product capabilities, Open partnerships and collaboration across technology, business, and society are crucial as AI becomes more prevalent across various industries.
AI ethics is a critical area where software leaders need to take the lead. They should work with or establish AI ethics committees to create policy guidelines for responsible use of generative AI tools, mitigating ethical risks.
Generative AI can also support talent management by speeding up hiring tasks, transcribing interview summaries, and helping identify skills that can be combined to create new positions or eliminate redundancies.
In summary, software leader’s roles are evolving to encompass oversight of generative AI, involving team management, talent development, ethical considerations, and business alignment to harness the potential of AI in various industries.
Source: zdnet.com
