Is your 2026 AI roadmap realistic?
Most enterprise AI plans haven’t tested the assumptions behind the decisions. Download the 40-question reality check.
After reviewing countless AI roadmaps across multiple sectors and geographies, the pattern is clear: ambitious use cases, broad stakeholder buy-in, and fatal gaps in execution logic.
Organisations commit to building solutions without named owners, buy platforms without stress-testing integration and approve budgets based on initial costs rather than three-year total cost of ownership.
Stress test your plan with this AI roadmap planning checklist.
This comprehensive guide provides you with a set of questions under five key themes, designed to uncover the gaps that need addressing in your roadmap to mitigate risk in 2026.
This guide covers five key decisions areas
Build vs buy trade-offs - Are you making these decisions strategically, or defaulting to one approach for everything?
AI-enabled SDLC - Can your development process actually deliver what you've committed to, or will it become the bottleneck?
Infrastructure and MLOps - Are you over-engineering for scale you won't reach, or under-investing and creating delivery constraints?
Risk and governance - Does your framework enable safe delivery, or just slow everything down?
Talent and operating models - Are you planning around people you haven't hired yet (and how can you mitigate for that)?
These questions will uncover the gaps and risks in your 2026 AI Roadmap - download the guide below.
