The software development landscape is in for a seismic shift in 2025. This year will be marked by the rise of artificial intelligence (AI) as a standard tool, but with this advancement comes a new set of challenges. DevPro Journal recently spoke with the team at Digital.ai to learn more and identify 13 key trends that could reshape your development experience in 2025.
Dan Shugrue, Application Security Product Marketing, Digital.ai:
- Smart Enterprises Will Move Beyond Vulnerability Scanning. As enterprises embrace AI tools to help them code faster, threat actors have worked in lockstep to write faster malware, analyze code, and get better at wreaking havoc. In 2025, smarter enterprises will harden their apps against reverse engineering through advanced obfuscation, anti-tamper, and threat monitoring.
- AI Tools Will Bleed into Security Teams. In 2025, expect security departments to adopt AI to keep up with the cybersecurity arms race. Early adopters will look to ML-assisted threat analytics to find patterns in attack behavior that better equip them to mitigate attacks.
Derek Holt, CEO, Digital.ai:
- AI-based code assistants go from early adopter to standardized driving both positive and negative impacts. While 2023 and 2024 saw a lot of experimentation with coding co-pilots with expanded adoption in startup companies and various forward-leaning enterprises, 2025 will be marked as the year coding co-pilots become a standard. Like all new technology adoption, this will have pros and cons. Expect to see more code developed more quickly, but keep an eye out for challenges with re-use, quality, security, and technical debt.
- New bottlenecks emerge in software delivery. While AI-assisted development will drive increased code creation and ultimately drive individual developer productivity gains, new bottlenecks will quickly emerge across the broader software delivery lifecycle. Organizations that have not invested in test automation, built in security, release orchestration, code scanning and more will struggle to translate more productive developers into faster time to market.
- The Emergence of xOps. As more and more “traditional applications” begin to adopt AI capabilities expect DevOps, DataOps, and ModelOps to converge into xOps. This new-found set of dependencies will dramatically accelerate “AI-aware” Release Orchestration while also challenging operations teams, support teams, QA teams, and more as the line between more traditional declarative applications blur with the new dependencies to LLMs and GenAI capabilities.
- Software Engineering Intelligence steps into the spotlight (and quickly gains predictive AI capabilities). While Value Stream Management continued to lose steam in 2024, we also saw the fast emergence of Software Engineering Intelligence (SEI) to take its place. SEI will have a breakout year in 2025 as more and more businesses realize they need to measure the end-to-end business process of software development and delivery in order to drive continuous improvement, truly deliver improved developer experiences and ultimately realize the potential gains for an AI-powered Software Development and Delivery capabilities. SEI is the key to each.
- Security and Change Risk Prediction Will Outperform Productivity Gains. As AI continues to impact the entire business process of planning, coding, building, testing, and delivering software, the importance of security and risk prediction will take another leap up the list of priorities. 2024 was marked by scale security breaches and huge change risk failures (let’s not forget walking through airport terminals looking at the blue screen of death)…..with AI driving more changes more quickly, enterprise businesses will continue to increase investment in security and risk prediction solutions.
Mike Woodard, VP of Product Management for Application Security, Digital.ai:
- The AppSec Arms Race Will Heat Up. In 2025, If it wasn’t obvious before, no one in application security can safely take a break. With the advantage of AI, reverse engineering and attack tools will become even more sophisticated. Threat actors will use these tools and techniques to better understand the operation of apps, uncover their secrets, and make malicious use of APIs.
- AI-Aided Threat Monitoring Will Become the Norm. SOC managers have the unenviable job of searching mountains of data for actionable information. AI-aided threat monitoring, such as pattern recognition, anomaly detection, and general classification of data, will become necessary for security teams to surface the most urgent threats so that proper mitigation steps can be taken in a timely manner.
Adam Kentosh, Field CTO, Digital.ai:
- Enterprise Software Development Leaders Will Make Choices That Come Back to Bite Them Success in 2025 will mean not just having AI in place but having it ready to scale and deliver consistent results. This will position organizations ahead in their industries through enhanced decision-making, operational efficiencies, and adaptive strategies driven by data-backed insights. But setting up AI without a way to measure it will be indefensible, and someone will pay the price of wasted efforts.
- Organizations Will Prioritize Measurement. Organizations will refine their software engineering processes to ensure AI can be effectively integrated, managed, iterated upon, and measured. The adoption of Software Engineering Intelligence (SEI) platforms will become critical to gaining the necessary insights to govern development, align with business goals, and monitor performance across production environments.
- Organizations suffer from “status quo” rather than make the tough decision to consolidate tools and processes. Some of this is happening today under the guise of Platform Engineering, however, many development teams are still just using the tools they already had available to them. We will likely continue to see businesses struggle with measuring their organizational performance because they have too many tools for every software engineering discipline (agile planning, DevOps, security, testing, etc.).
- Over-reliance of AI without governance. We will continue to see AI being leveraged without any proper form of governance around it which will lead to security concerns, ethical considerations, and more.
