AI is set to reshape software development in 2026
AI isn't replacing developers in 2026 - it's changing what they spend time on. Expect less routine coding and more work on architecture, design, and problem-solving. Teams that pair human creativity with AI will ship faster, build smarter, and keep users at the center.
A new trends report from Infragistics points to four themes that will define the next cycle: AI-driven intelligence, predictive UX, adaptive design systems, and strong data governance. The takeaway for engineering leaders is clear: bring product, platform, and privacy together or get left behind.
Privacy, transparency, and governance take priority
Users and regulators will demand clearer consent, tighter controls, and auditable data flows. As Jason Beres, COO of Infragistics, notes, the companies that win will bake transparency and governance into their products while staying agile. Customers will favor tools that can prove compliance and demonstrate ethical stewardship of personal data.
- Ship with consent management, data lineage, and audit trails built in.
- Give users control: easy export/delete, clear permissions, and explanations for decisions.
- Treat governance tooling as part of the core product, not an afterthought.
Developer roles evolve, teams expand
AI will change roles rather than erase them. Among companies already using AI, 55 percent report new job creation, with 63 percent adding up to 25 new roles, according to the 2025 Reveal Software Development Challenges survey.
Konstantin Dinev, director of product development, says the shift is practical: AI automates repetitive tasks so developers can focus on higher-leverage work. The best outcomes will come from teams that collaborate with AI tools instead of competing with them.
Analytics becomes conversational and contextual
Business intelligence will move beyond static dashboards. Insights will surface in context - inside the app, at the moment of need, and via plain-language queries. That means fewer "where's the report?" tickets and more direct answers for product, support, and sales.
- Embed conversational analytics where users work.
- Use semantic layers and metadata to keep answers consistent across teams.
- Log prompts, sources, and outputs to audit decisions and improve quality.
Work management: AI as a teammate
AI will do more than automate. It will coordinate resources, anticipate blockers, and suggest next steps across tools. Think backlog grooming, risk flags, dependency mapping, and capacity planning that adapts as the plan changes.
- Let AI suggest estimates, reviewers, and test scopes - humans approve.
- Connect code, tickets, incidents, and docs to give AI full context.
- Set guardrails: scope, privacy rules, and escalation paths.
What tech leaders should do now
- Governance by design: Maintain a live data inventory, define retention and access policies, and automate audits. Expose controls to users, not just admins.
- UX that learns: Use predictive and adaptive patterns to reduce friction, but explain why the system makes suggestions.
- AI in the SDLC: Standardize prompts, code review with AI assistance, and unit test generation. Track accuracy and drift like any other quality metric.
- Architecture that supports change: Favor modular services, clear contracts, and strong observability to keep AI-assisted changes safe.
- Skills upgrade: Teach developers effective prompting, model strengths/limits, and secure data handling. Pair-program with AI; don't outsource judgment.
- Measure outcomes, not hype: Define targets for lead time, defect rate, and cycle time. Keep what improves the numbers, drop what doesn't.
Practical checklist for teams
- Adopt an AI code assistant with org-wide policies and logging.
- Add data retention, consent, and audit features to your next two sprints.
- Embed conversational analytics in one high-impact workflow.
- Pilot AI-supported planning: backlog drafting, risk surfacing, and test suggestions.
- Create an internal AI usage guide: approved tools, red lines, and review steps.
Further reading and resources
Read the latest trends report from Infragistics for the full breakdown of predictions and recommendations: Infragistics.
If you need structured upskilling for your team - from AI-assisted coding to governance - explore practical learning paths here: Complete AI Training: Courses by Job.
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