Artificial intelligence (AI) is transforming the world of modern software development, with use cases that range from data processing to generating code. In this blog post, we explore the future of AI in software development from the perspective of professionals involved in software development who hold leadership positions[1]. We first consider how their opinions differ from their counterparts in non-leadership positions and then move on to breaking down their beliefs by company size and region. These insights provide a window into how the adoption of AI is evolving across the industry and where beliefs may diverge depending on organisational and geographical contexts.
This blog post is based on data collected from over 4,500 technology professionals who answered questions about AI in the 28th edition of SlashData’s global Developer Nation Survey, which was fielded in Q4 2024.
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Most important future use cases for AI in software development according to technology leaders
When looking at the opinions of technology professionals in leadership roles and comparing them to those who work in non-leadership roles, we see a lot of broad similarities but also a selection of distinct differences. For instance, both groups show strong recognition of intelligent development assistants (30% vs 29%) and data processing, analytics and visualisation (26% vs 26%) amongst the most important future use cases of AI in software development.
In terms of differences, we find that technology leaders are significantly more likely than their counterparts to emphasise the importance of AI in the future of cybersecurity (25% vs 20%). While this is likely due to the differences between these two groups in terms of the scope of their responsibilities, the popularity of this particular use case points to AI playing a critical role in enhancing security against an ever-growing landscape of threats.
Technology leaders are also more likely to believe in the future importance of areas such as AI for DevOps (22% vs 18%) and predictive project management (16% vs 13%), highlighting their focus on optimising workflows and managing their teams. However, they are less likely than those in non-leadership roles to consider code generation (25% vs 29%) as important. This suggests that those who work closer to the code are more likely to see immediate benefits from automating coding tasks.
Most important future uses cases of AI in software development by company size
On looking closer at what technology leaders think, we find an interesting set of patterns when segmenting their beliefs by company size. While certain trends remain the same, our findings also show that the future importance levels of some use cases are perceived very differently across different company sizes.
In terms of similarities, there is little variation in the perception of use cases, such as intelligent development assistants, when we consider company size. This suggests that technology leaders expect future AI tools targeting such use cases to be just as useful for developers who work for small businesses as those who work for larger firms. This also points to a potential shift in the dynamics of the developer workforce as a whole, where developers can take on more strategic roles and focus on the bigger picture while leaving routine coding tasks to AI.
We find that leaders who work for large companies are significantly more likely than average to place emphasis on code generation (35%) when considering the future of AI in software development. This suggests that larger companies see greater potential in using AI-generated code in their applications. This may be because these companies often have extensive codebases that require a lot of developer resources.
Large companies may be the most likely to use AI-generated code in the next three to five years
Similarly, we see that the perceived importance of AI for cybersecurity is strongly linked to company size. As businesses grow, they also increase the attack surface of their systems and require more complex security measures. This is reflected in our data, with technology professionals in leadership roles at large companies being the most likely to mention cybersecurity (31%) in their beliefs of the most important use cases. This drops to 27% amongst technology leaders at midsize companies and further down to 20% at small companies. This suggests that smaller businesses may be less likely to prioritise advanced cybersecurity solutions when considering AI.
Most important future uses cases of AI in software development by region
Regional differences in culture, regulations and socio-economic circumstances often play important roles in technology. As such, it is no surprise that these differences extend to the opinions of technology leaders about which use cases for AI in software development will be most important in the next three to five years.
As with the case of company sizes, some use cases receive similar favourability from technology leaders across Europe, North America and the Rest of the World. This suggests that certain use cases, like intelligent development assistants and performance monitoring and optimisation, show universal promise of addressing challenges and opportunities in the landscape of modern software development.
The benefits of intelligent development assistants are perceived to be not only company-size agnostic but also region-independent.
Technology leaders working in Europe are the most likely to perceive cybersecurity as one of the top use cases for AI in the near future of software development (30% vs 26% in North America and 21% in the Rest of the World). While this is partly due to Europe having an above-average concentration of large companies, it also highlights the greater emphasis placed on topics such as data protection in this region due to regulations.
Despite this, these technology leaders also recognise the potential that AI has to bring to their future applications. In fact, technology professionals in leadership roles working in Europe are significantly more likely than their counterparts in other regions to believe that adding AI functionality to applications will be amongst the most important future use cases of AI (25% vs 19%). Furthermore, we also see that they are disproportionately more likely to consider bug detection and fixing as important than their counterparts in other regions (27% vs 20%).
Key takeaways
Technology leaders foresee AI playing a crucial role in software development, with strong recognition of intelligent development assistants and data processing. They also emphasise cybersecurity, AI for DevOps, and predictive project management more than those in non-leadership roles. Leaders in larger companies are more likely to believe in the growing importance of code generation and cybersecurity in the future. We also see some interesting regional differences, with European technology leaders placing a higher emphasis on cybersecurity, adding AI functionality to applications, and bug detection/fixing. These insights highlight the evolving adoption of AI in the industry and varying favour based on organisational and geographical contexts.
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[1] We consider those who self-identify to be in at least one of the following roles as technology leaders: “tech/engineering team lead”, “CIO / CTO / IT manager”, “CEO/management”.
About the author
Nikita Solodkov, Market Research and Statistics Consultant
Nikita is a multidisciplinary researcher with a particular interest in using data-driven insights to solve real-world problems. He holds a PhD in Physics and has over five years of experience in data analytics and research design.