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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. Looking for a broader business perspective? Discover how Sales & Marketing use Generative AI in our free report . 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. What type of AI data are you looking for? Maybe we already have what you need. Get in touch with us. [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.

The Internet of Things (IoT) is transforming how we interact with technology and the world around us. This blog post explores the key players driving this transformation - companies building in the IoT space. We will examine the regional distribution of IoT professionals, analyse how organisations participate in the IoT supply chain, and conclude by focusing on Industrial IoT and the markets these companies are focusing on. The data in this blog post comes from the 27th edition of SlashData’s global Developer Nation survey, fielded in Q3 2024. This survey gathered responses from over 7,500 technology professionals, including more than 900 individuals professionally involved in IoT projects - over 50% of whom are decision-makers - spanning both Industrial IoT and Consumer IoT. If you want to look at the general IoT developer population, you can have a look at our full report .  Where IoT professionals are located Before exploring how organisations engage in the IoT supply chain, we’ll first look at the regional distribution of IoT professionals to provide a general context that can help understand IoT industry dynamics. The professional IoT ecosystem is heavily concentrated in North America and Western Europe, which together account for 55% of the world’s IoT professionals. This concentration is likely due to the presence of mature ecosystems, advanced infrastructure, numerous market leaders, and strong business networks in these regions. North America leads the pack, hosting nearly one-third (30%) of the global IoT workforce. North America and Western Europe together account for 55% of the world’s IoT professionals When compared to the broader technology landscape, North America and Greater China stand out as hotspots for the IoT industry. The concentration of IoT professionals in these regions surpasses the concentration of all technology professionals by at least five percentage points, indicating a stronger interest and focus on IoT. In contrast, South Asia presents a different scenario. Despite being home to 17% of the world’s technology workforce, the region accounts for only 9% of IoT professionals. This disparity could be attributed to infrastructure limitations, skill gaps, or market dynamics that prioritise other technology sectors over IoT. Deep dive into the dynamics of the IoT supply chain The digital backbone Supplying software solutions and operating IoT services are the most common ways organisations participate in the IoT supply chain, with 28% and 26% of professional IoT developers engaging in these activities, respectively. Both activities form the backbone of the digital side of the IoT ecosystem and are deeply interconnected. Software suppliers create the platforms and tools that enable IoT systems to function, while IoT service operators leverage these platforms to deliver solutions such as connectivity management and device monitoring directly to customers. Likely due to this close collaboration and interdependence, we observe that many organisations involved in these activities are leveraging their synergies to expand their value propositions. According to our data, approximately one-third of software suppliers are also operating IoT services and vice versa. Completing the digital side of the IoT chain are network operators, engaging 19% of IoT professionals, who provide the connectivity infrastructure that enables IoT devices to communicate and exchange data, acting as bridges between physical devices and digital platforms. Similarly, we also observe that many network operators are diversifying their offerings within the digital IoT space, extending beyond infrastructure services. According to our data, at least one-third of IoT professionals working for network operators are also engaged in providing software solutions (40%) or operating IoT services (33%). The device side On the physical side of the IoT supply chain, Original Equipment Manufacturers (OEMs) lead the pack. 19% of professional IoT developers work for organisations that design, develop, and market products under their own brands. Other manufacturing-related activities –those performed by EMSs, CEMs, OCMs, and ODMs– each account for 15% or less of organisations in the IoT ecosystem. However, when accounting for overlaps, we find that about half (52%) of IoT professionals are engaged in manufacturing or design activities, closely mirroring the 54% involved in the digital side of the IoT chain. This near-parity highlights how hardware remains just as integral as software and services in shaping the IoT ecosystem. 19% of IoT professionals work for OEMs, which design, develop, and market products under their own brands. Similar to the digital side, we find strong synergies between different manufacturing activities. Many companies engage in multiple activities to capitalise on operational efficiencies and expertise. For example, 31% of Original Design Manufacturers (ODMs) are leveraging their design capabilities to produce their own branded products, effectively becoming OEMs, while continuing to create custom designs for other customers. Similarly, 30% of Contract Electronics Manufacturers (CEMs) are combining their contract manufacturing capabilities with in-house product development. Despite the overlaps and synergies observed across both the digital and physical sides of IoT, fully integrated organisations (those managing all aspects of design, manufacturing, software development, and service delivery) remain relatively rare, with only 11% of IoT professionals working for fully-integrated businesses. This suggests that most companies prefer to leverage synergies within closely related areas rather than taking on the complexity of full vertical integration. By focusing on adjacent activities, companies can diversify revenue streams and reduce reliance on a single business function while maintaining operational focus and avoiding the challenges associated with managing end-to-end operations. The services side  Beyond the core building blocks of the IoT ecosystem (services and devices), technical consultancies (22%) hold a notable presence in the IoT supply chain. This likely reflects the complexity of IoT deployments, where organisations rely on external expertise for solution design, system integration, and implementation strategies. Lastly, at the bottom of the chart, we find value-added resellers and distributors, accounting for only 10% of IoT professionals. These entities play a crucial role in bridging gaps between hardware manufacturers, software providers, and end-users by customising solutions to meet specific needs. Markets targeted by Industrial IoT professionals Now that we understand how IoT professionals participate in the IoT supply chain, let’s examine the markets they are currently targeting. For the purpose of this blog post, the analysis focuses exclusively on Industrial IoT (ΙΙοΤ). If you want to explore more insights on consumer IoT, get in touch. We observe a strong inclination towards industrial and infrastructure-related markets, likely driven by IoT’s ability to enhance operational efficiencies and reduce costs in these areas. Manufacturing is, by far, the most commonly targeted sector, with 35% of IIoT professionals focusing on it, likely driven by the shift towards smart factories under the Industry 4.0 movement . The second most targeted market is smart cities and infrastructure, attracting 24% of IIoT professionals. This highlights the growing role of IoT in urban development, supporting applications such as traffic management, waste management, and public safety systems. Following closely behind is a diverse set of markets, each targeted by 16% to 20% of IIoT professionals, highlighting the versatility of these solutions. Environmental monitoring (20%) leads this group, likely driven by sustainability initiatives and increasing regulatory requirements. Lastly, the least targeted markets include hospitality and tourism (13%), retail (12%), and defence (7%). While these sectors leverage IIoT for specific applications such as customer experience enhancement or security, they remain less attractive to IoT professionals, likely due to lower overall demand or fewer opportunities to effectively leverage IoT in these markets compared to others. Are you involved in IoT? Or simply curious about IoT market analytics? This blog post is just a glimpse into the demographic and firmographic insights of IoT professionals that we can offer. For a deeper dive into the world of IoT, we have a wealth of additional data and insights waiting to be explored. Get in touch , and we can talk about the details. About the author Álvaro Ruiz, Research Manager Álvaro is a market research analyst with a background in strategy and operations consulting. He holds a Master’s in Business Management and believes in the power of data-driven decision-making. Álvaro is passionate about helping businesses tackle complex strategic business challenges and make strategic decisions that are backed by thorough research and analysis.

Right between the first pumpkin spice beverages and gift exchanging, now is the season when we all sit down and set our strategy for the year to come.  What are your goals for 2025:  Increasing conversions from free to paid?  Driving engagement or  Boosting adoption?  No matter what you strive for, you need data to ensure all your decisions are based on concrete data. To help with that direction, in this article, we will touch the surface of 2 of the 6 State of Developer Nation 27th Edition industry reports, just made publicly available and open to all to access and download . You can follow the links to access the full free report to dive deeper into the technology industry and use clean data to drive your 2025 successes. On February 25, we ran a webinar on AI chatbots and Network APIs. Watch it now or keep reading for the report insights. Let’s explore together what is new in programming language communities and AI chatbot usage. Developer Research Report: Sizing programming language communities Always on time for our biannual check-in with programming language communities, we see in Q3 2024 that JavaScript reigns supreme again, with a thriving community of 27.4M developers. JavaScript’s dominance has been unchallenged for a while now, but it’s always exciting to see how these numbers evolve and what they reveal about shifts in developer interests. The choice of programming language shapes the kinds of projects developers work on, the communities they engage with, and even the career paths they follow. A language isn’t just a tool; it’s often a gateway to specialised fields and opportunities. Python and Java continue to battle closely to be the second-largest language community, but over the last year, Python has begun to solidify a leading position. At the same time, Go and Rust are the second and third fastest-growing languages. In this report, we estimate the global developer population using each of these languages and examine how coding experience and emerging tech trends shape language adoption across different fields. The JavaScript community grew by 4.8M users in the last 12 months. Here is a full breakdown of the size of programming languages communities: Explore the full report  in the SlashData Research Space to discover which types of developers are driving the growth of Go and Rust, and how the sizes of these language communities have evolved over time. Do you need data that is more tailored to your needs? Get in touch  or explore our case studies  on how we helped clients answer their questions.  Developer Research Report: The rise of AI chatbots for problem-solving Are AI chatbots the new go-to solution for problem-solving? Well, for 45% of technology professionals, hobbyists, and students, they are! From guiding users through complex troubleshooting to empowering businesses with 24/7 assistance, AI chatbots are now essential tools in our fast-paced world, reshaping problem-solving one query at a time. 45% of technology professionals, hobbyists and students use AI chatbots for problem-solving This report explores the use of AI chatbots for problem-solving by professionals, hobbyists, and students involved in technology projects. It also looks into how much the adoption of AI chatbots changed between Q1 and Q3 of 2024 across different role types, experience levels, and geographic regions. To understand adoption, we asked developers about the extent to which they rely on AI chatbots for different purposes - problem-solving, learning and research. While adoption rates for learning and research remained stable in the last six months, the percentage of those using AI chatbots for problem-solving increased from 40% in Q1 2024 to 45% in Q3 2024. To learn more about how the use of AI chatbots changes based on developers’ professional status, role, years of experience in software development, and regions, you can access the full report here . More developer insights are coming soon As I mentioned in the introduction, this is only a first taste of the first 2 of the 6-part series. Stay tuned for 2 additional previews of the reports coming in December:  Network APIs: The New Oil In The 5G Economy How developers build AI-enabled applications  What developers think about their teams  Comparing startups to established technology companies You can access everything (no strings attached) in the SlashData Research Space . The Developer Nation survey & State of Developer Nation reports Hopefully, this is not the first time you hear of SlashData, a market research firm with a passion for clean data and actionable insights. Every quarter, SlashData runs its Developer Nation survey, a global independent survey that measures the pulse of the technology ecosystem and how software developers feel about new technologies, tools, platforms, support from developer programs and more. Our expert analysts work on identifying key trends and translate raw data into actionable insights that professionals and companies addressing a developer audience can utilise to fine-tune their strategy and address developers’ needs and wants. The 27th edition of the Developer Nation survey reached more than 9,000 respondents from 130+ countries worldwide. The State of the Developer Nation report series highlights the key trends to look out for the beginning of 2025 and beyond.  About the author Stathis Georgakopoulos, Product Marketing Manager Always keen to see what’s next in the industry, Stathis is the Product Marketing Manager for SlashData, setting the table and running the marketing activities. He's our go-to guy for all things marketing and does not hide his love for content marketing and creating helpful content.

The Competitive Technology Landscape tracks the performance of competing technologies in awareness, adoption and developer satisfaction. Get developers to use your product The Competitive Technology Landscape looks at your offering, your competition and the market and helps you understand where you stand. What it tracks Awareness Adoption Developer satisfaction It allows you to understand which developers prefer what you are offering, the reasons why and how you can fine-tune it to invest in what matters most to developers. You can also track your offering’s awareness and benchmark it against the market. All these insights come directly from developers around the world. The Competitive Technology Landscape tracks the performance of competing technologies in What it answers How many developers are aware of, and how many are using your and your competitors’ solutions? Which solutions are developers adopting? Which are they abandoning? For what reasons is each solution rejected and adopted? Which tool aspects matter the most to developers? How do they score the solutions they use based on these attributes? How do competing solutions compare in terms of developer satisfaction score and NPS? What are the key weaknesses and strengths of each solution? Through this solution, you can answer questions such as Explore our latest research 20 March 2025 AI-assisted coding tools Competitive Technology Landscape Report Q1 2025 MORE 1 September 2024 Cloud-based development environments Market Landscape Report Q3 2024 MORE 1 July 2024 Payment APIs Market Landscape Report Q1 2024 MORE 1 May 2024 CI/CD tools Market Landscape Report Q1 2024 MORE 1 November 2023 Test Automation/Management Tools Market Landscape Report Q3 2023 MORE 1 June 2023 3rd Party Payment APIs Market Landscape Report Q1 2023 MORE 1 June 2023 Application Security Testing Market Landscape Report Q1 2023 MORE 1 March 2023 Application Performance Monitoring Market Landscape Report Q3 2022 MORE Do you want to effectively talk to developers in a specific sector or understand their needs? LET'S TALK

Track adoption, market share and satisfaction All Reports AI-assisted coding tools Competitive Technology Landscape Report Q1 2025 Track adoption, market share and satisfaction Access the Full Report About this Report What is the AI-assisted coding tools Competitive Technology Landscape? In our AI-assisted coding tools Competitive Technology Landscape report, we benchmark the main competing AI-assisted coding tools based on the responses of over 1,400 developers who used these tools in the last year. We look at which vendor products and technologies developers are currently using and we measure developer satisfaction across 14 different attributes. Our analysis provides deep insights on the criteria developers use to select products and how likely they are to recommend. Key Questions Answered - Which technologies have DevOps developers used in their software development projects in the past 12 months? - Which AI-assisted coding tools are developers aware of, which are they currently using and which have they abandoned? -Which attributes do developers consider most important when they select an AI-assisted coding tool? - Do developers rely on a single AI-assisted coding tool, or do they use multiple? - Why do developers stop using AI-assisted coding tools? - How satisfied are developers with each AI-assisted coding tool? How do they score the tools they use across the attributes they consider most important? - How likely are developers to recommend the AI-assisted coding tools products they are currently using? - How do the user bases of the most popular AI-assisted coding tools compare to one another? Click to expand ACCESS THE FULL REPORT Methodology The report is based on data collected from the 29th edition of the Developer Nation survey edition of the Developer Nation survey, a large-scale, online developer survey that was designed, hosted, and fielded by SlashData over a period of ten weeks between December 2024 and February 2025. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT

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