As organisations accelerate digital innovation in 2025, they must also navigate the complexities of AI-driven workflows, evolving regulations, and the heightened risks associated with rapid technological change.
To stay competitive, businesses will need to embrace automation, robust security frameworks, and agile development practices that ensure both scalability and resilience in an ever-evolving digital landscape. In this article, we explore some of the key trends impacting software development.
AI productivity and cultural transformation
AI productivity gains will increasingly depend on companies transforming their workflows and cultures, not just adopting tools. The executive mandates and accompanying budget redirection driving AI adoption will continue, but many initiatives may fail to deliver promised returns without strategic cultural shifts.
AI fragmentation—the scattering of AI initiatives across multiple systems and platforms—poses a significant challenge for many organisations, leading to inefficiencies and wasted resources. To address this, enterprises are shifting towards AI solutions that are fully integrated into workflows rather than relying on standalone tools.
By prioritising integrated systems, businesses can transform workflows holistically, moving away from siloed implementations and custom-built AI systems. Instead, they can adopt standardised, vendor-provided solutions that not only reduce the burden on internal engineering teams but also align AI capabilities more effectively with business needs.
As this takes effect, 2025 will likely see AI deliver tangible, incremental benefits rather than overhyped expectations.
AI and cybersecurity challenges
Data leakage and security risks will remain significant concerns as AI adoption grows. The focus will shift to managing data pipelines and ensuring compliance with privacy regulations like PII protection. However, just as attackers increasingly leverage AI in their Black Hat strategies, AI will also play a critical role in combating evolving cybersecurity threats.
AI-powered tools can enhance security testing within the software development lifecycle (SDLC) by identifying vulnerabilities and mitigating risks more efficiently. The key to leveraging AI effectively lies in thorough vendor analysis and understanding how AI tools are being used. By ensuring proper diligence in vendor selection and integration, organisations can mitigate risks associated with AI adoption.
Additionally, incorporating AI into security testing enables a continuous improvement model. Organisations must regularly assess and enhance their secure pipelines, ensuring they stay ahead of increasingly sophisticated threats. As attackers innovate with AI, businesses must do the same to maintain resilience, leveraging AI tools to adapt to the ever-evolving threat landscape and ensuring their cybersecurity measures remain robust and effective.
Regulation and AI testing
AI regulation will remain firmly on the agenda for 2025, with frameworks continuing to evolve with a focus on ensuring transparency, ethical use, and compliance. ISO and other international standards will guide compliance efforts, but regional regulations will add complexity, requiring adaptive testing and governance strategies.
Continuous and thorough testing will be critical for organisations to guarantee their AI products and systems not only meet new and evolving regulations, but also customers’ growing expectations of efficiency and safety. Testing processes will need to adapt to new regulatory requirements, particularly for high-risk or sensitive applications. We will also see greater differentiation between testing AI systems to ensure models and pipelines are secure and compliant and using AI tools for testing to enhance software quality and security.
Averting outages
As software ecosystems grow more complex, the risk of outages will escalate in 2025. 2024’s CrowdStrike incident illustrated how a single unchecked code change can bring business operations to a halt, underscoring the need for robust quality assurance practices that can keep pace with increasingly demanding release schedules and intricate deployments.
Software teams will continue to face mounting pressure to deliver rapid releases, but overlooking testing is a costly mistake. To avoid becoming the next ‘lesson learned’, organisations must prioritise assessing risks, focusing testing efforts strategically, and continuously refining testing and deployment strategies.
By embedding software testing into the broader DevOps and AI-driven workflows, businesses can mitigate risks, maintain uptime, and ensure seamless customer experiences. As we push toward agile and automated processes, testing will remain a cornerstone of operational resilience and technological success.
Thriving in the SaaS era
In 2025, the shift from on-premises to the cloud will require fundamental operational changes among enterprises. While the initial move to SaaS solutions like Oracle and SAP was driven by the promise of modern infrastructure and reduced overhead, enterprises are now realising the critical need to adapt to the faster release cadences these platforms demand.
For many organisations, the shift is reaching a tipping point. Legacy systems are nearing end-of-life, forcing migrations to modern SaaS platforms. At the same time, companies that have already transitioned are seeking to fully leverage the agility and innovation SaaS offers.
The complexities associated with managing faster and more frequent updates across interconnected enterprise ecosystems will require businesses to adopt advanced AI-driven automation tools to remain competitive and manage updates seamlessly. Success will ultimately depend on embracing this new operational paradigm – one where agility, automation, and continuous adaptation are essential to thriving in today’s SaaS era.
Balancing innovation and resilience
Success in 2025’s software development landscape will depend on balancing innovation with security, compliance, and efficiency. As AI reshapes workflows, cloud ecosystems expand, and cybersecurity threats evolve, organisations must adopt strategic approaches that enhance agility and operational resilience. By leveraging automation, continuous testing, and AI-driven insights, businesses can not only mitigate risks but also unlock new opportunities for growth, ensuring they remain at the forefront of technological advancement.
Andrew Power is Head of UKI at Tricentis. Tricentis is a global leader in continuous testing and quality engineering. The Tricentis AI-powered, continuous testing platform provides a new and fundamentally different way to perform software testing. An approach that’s totally automated, fully codeless, and intelligently driven by AI. It addresses both agile development and complex enterprise apps, enabling enterprises to accelerate their digital transformation by dramatically increasing software release speed, reducing costs, and improving software quality. Widely credited for reinventing software testing for DevOps, cloud, and enterprise applications, Tricentis has been recognized as a leader by major industry analysts, including Forrester, Gartner, and IDC. Tricentis has more than 2,500 customers, including the largest brands in the world, such as McKesson, Accenture, Allianz, Telstra, Dolby, and Vodafone.
