Developers are embracing AI agents in software development
AI is changing software development, and developers are fully on board. The old narrative of AI skepticism doesn’t hold up, developers see AI as an advantage, not a threat.
According to Salesforce’s State of IT survey, 96% of developers worldwide believe AI will positively impact their work, and over 90% say they’re optimistic about its effect on their careers. That level of enthusiasm doesn’t happen by accident. It comes from real benefits, AI removes the tedious, repetitive work and lets developers focus on higher-value tasks.
In the UK and Ireland, more than four in five developers predict AI agents will become invaluable in app development. This means AI is becoming core to how software is built. Companies that invest in AI now are setting themselves up to lead.
AI agents are driving efficiency by automating repetitive tasks
Developers are using AI agents to automate the tasks that slow them down, namely debugging, data cleaning, software testing, and code integration. These are necessary but time-consuming. AI eliminates the grunt work, freeing up developers to focus on system design, performance optimization, and architecture.
AI is making software development faster, more efficient, and more enjoyable. When you take away repetitive tasks, developers can use their expertise where it actually matters, solving complex problems and driving innovation.
But automation isn’t perfect. AI-generated code still needs oversight. Poor-quality data or weak AI models can lead to inefficiencies instead of improvements. That’s why the companies getting the most out of AI aren’t just using it, they’re refining it, training it, and integrating it into their workflows with precision.
Developers want to be measured by impact, not output
For a long time, developer performance was measured by lines of code written or features deployed. That’s changing. AI-driven development is shifting the focus from quantity to impact.
92% of global developers now prefer to be assessed on the value of their work rather than sheer output. This means measuring problem-solving, architecture, and system efficiency rather than code volume. AI is playing a major role in this transition. With AI handling routine tasks, developers are taking on more strategic roles, overseeing AI workflows, designing scalable systems, and improving security.
This shift is a major win for both developers and businesses. Companies that prioritize impact over output will attract top talent, retain skilled engineers, and build more comprehensive, future-proof systems.
AI usage varies by region, but the trend is clear
AI adoption is strong everywhere, but the way developers use it depends on the region. In the UK, developers focus on using AI to refine AI-generated code and collaborate with business stakeholders. The priority is making AI-generated work more precise and aligning it with business goals.
In Ireland, developers are taking AI a step further, using it for code optimization, oversight, and even full code generation. This suggests a more aggressive adoption of AI-driven development, where AI is actively writing and improving software.
“Companies need to adapt AI strategies based on how their teams work best. Those who figure this out early will gain a major competitive edge.”
Low-code and no-code platforms are expanding AI access
Low-code and no-code platforms are making AI tools accessible to developers of all skill levels. These platforms simplify AI integration, reducing the time and expertise needed to deploy AI-powered solutions.
The numbers back this up. In the UK, 78% of developers using AI already work with low-code/no-code tools. In Ireland, that number is slightly higher at 79%. Adoption is only increasing, with 80% of UK developers and 78% of Irish developers saying these platforms are key for democratizing AI development.
This shift is important. It means AI is making innovation available to a much larger group of professionals. Businesses that invest in these platforms will be able to scale AI initiatives faster, reduce costs, and stay ahead in a rapidly growing market.
AI adoption is accelerating development timelines
Speed matters. AI-powered development is dramatically cutting down the time it takes to build, test, and deploy software. Instead of months, projects are now being completed in weeks, or even days.
Companies that integrate AI into their workflows are already seeing the benefits. A prime example is Secret Escapes, a luxury travel company that used Salesforce’s AI Agent Builder tools to improve customer service. Their developers built, tested, and deployed an AI agent in just two weeks, something that previously would have taken six months.
This is what AI does best: it eliminates bottlenecks. Development teams that embrace AI aren’t just becoming more efficient; they’re moving at a pace that competitors relying solely on traditional methods won’t be able to match. The result is faster innovation, quicker iteration cycles, and reduced operational costs. Businesses that hesitate risk falling behind.
Infrastructure and data quality are key challenges
AI is only as good as the infrastructure supporting it. Many organizations still lack the computing power, storage capabilities, and software frameworks needed to fully deploy AI agents. Without the right foundation, AI implementation will be limited in scope and effectiveness.
Data quality is another challenge. AI systems rely on accurate, well-structured data to produce reliable outputs. When data is incomplete, outdated, or biased, AI can generate flawed recommendations, introduce inefficiencies, or even create compliance risks.
These aren’t minor issues. 78% of UK developers and 84% of Irish developers say their companies need infrastructure upgrades to deploy AI effectively. Nearly half of respondents also highlight concerns about the accuracy and reliability of their data. Businesses that want to capitalize on AI need to invest in better infrastructure and establish stronger data governance policies.
Testing bottlenecks and skills gaps are slowing AI implementation
While AI adoption is accelerating, it’s not without obstacles. One of the biggest challenges is testing. AI-generated code introduces new complexities that traditional testing frameworks aren’t fully equipped to handle. If testing processes don’t evolve, they risk becoming a major bottleneck.
Another challenge is the skills gap. AI is changing what it means to be a developer. While 81% of UK developers and 68% of Irish developers believe AI knowledge will soon be a core skill in their profession, more than half, 51% in the UK and 54% in Ireland, feel they lack the expertise to thrive in an AI-driven environment.
Bridging this gap requires investment in training and education. Organizations need to rethink how they support their development teams, providing ongoing AI education, upskilling programs, and resources to ensure their teams stay ahead of the curve. Without this, AI’s potential won’t be fully realized.
AI agents are seen as career boosters, not job replacements
The fear that AI will replace developers is unfounded. Developers see AI as a tool that increases their abilities and makes their work more valuable. AI is shifting their roles from repetitive coding to high-impact problem-solving.
Salesforce’s research confirms this. 96% of developers globally are optimistic about AI’s impact on their careers, and 92% believe AI improves their job prospects rather than diminishes them. This perspective is key. Instead of fearing automation, developers are embracing it as a way to focus on more meaningful, strategic work.
The best developers want to work in environments where AI is integrated effortlessly, so they can do more with their skills. Companies that use AI effectively will attract and retain top engineering talent.
The agentic era marks a generational shift in software development
Salesforce’s study, which surveyed more than 2,000 global software development leaders, highlights this turning point. AI agents are redefining what it means to be a software engineer, moving developers toward more strategic, architecture-focused roles.
Low-code and no-code platforms are accelerating this transition, making AI development accessible to a wider range of professionals. Businesses that invest in the right infrastructure, upskill their teams, and integrate AI into their workflows will be the ones defining the next generation of innovation.
Final thoughts
Developers are driving the AI shift. AI agents are eliminating tedious tasks, accelerating project timelines, and making development more strategic. Businesses that recognize this and integrate AI into their workflows will gain a competitive edge.
The challenges are real, outdated infrastructure, data quality concerns, and skills gaps need to be addressed. But companies that invest in AI-ready systems, upskill their teams, and refine AI testing processes will be positioned to lead.
This is a defining moment for the industry. Organizations that move fast and execute well will set the standard for innovation. Those that hesitate will struggle to keep up. The choice is clear: adapt now or get left behind.
