AI-Empowered SAFe Assessments
The AI-Native Organization Self-Assessment
The AI-Native Organization Self-Assessment (also referred to as the AI Transformation/ AI-Native Readiness Assessment) from Scaled Agile evaluates how deeply an enterprise has integrated artificial intelligence into its culture, operating model, decision-making, and value-delivery systems.
Rather than viewing AI as a standalone software tool or isolated IT project, the AI-Native framework treats AI as part of the organization's core "DNA". The self-assessment provides a diagnostic baseline to identify where an enterprise stands on its AI adoption journey and highlights key capability gaps.
Provide every user with the full ecosystem of SAFe resources needed to master business agility by building AI into the DNA of your SAFe practice.
Build Your Organization's AI-Empowered Blueprint
AI integration requires more than adopting tools - it requires aligning people, process, and performance systems to unlock full-scale impact. Establish & define success from the start by creating a culture of continuous improvement throughout your SAFe journey - at the organization, team, and individual level, through data-driven insights.
AI-Empowered
Future-proof roles with AI-integrated training and guidance.
Certification
Validate team expertise with certifications and annual renewals for foundational and advanced levels.
Guidance
SAFe Framework, Workshops, Toolkits, and Studio for practical application.
Measurement
Benchmark progress with Comparative Agility and SAFe assessments.
Continuous Learning
Access to on-demand SAFe Skills for targeted, role-based learning paths.
Validated
Assessments are created by SAFe domain experts and validated by data scientists.
The AI Dilemma: Why 95% of AI Initiatives Fail to Deliver Impact
Billions are being invested in AI - yet most organizations struggle to translate experimentation into enterprise-scale value.
Two challenges stand in the way:
Upskilling the workforce to think, work, and lead in an AI-driven world.
Scaling AI initiatives from proof-of-concept to production-grade performance.
…What stood out for me was the focus on how AI can actually fit into real business workflows. It helped me see how the tools I've been experimenting with could be used more systematically — and it built a lot of confidence that I'm on the right track. That it's not about leaving it to IT but about using it in our day to day and to provide improved services.”
Jacinta Penn, Co-Founder at FleeceGrow
Sample Questions
AI Strategic Intent & Vision
Our executive team has a shared vision of why AI matters to our business and what outcomes we expect from it.
AI Money Map (Value-Led Prioritization)
Each AI initiative has a clearly identified business sponsor accountable for outcomes.
AI Money Map (Value-Led Prioritization)
We have a prioritized list of AI initiatives ranked by business value.
AI-Native Workforce
We invest in AI Role upskilling through structured training, not just basic AI awareness.
Governance & Ethics
We have named individuals who are explicitly accountable for the legal, financial, and reputational consequences of AI outputs in their specific domain.
Governance & Ethics
We consider the ethical, legal, and regulatory considerations every time we use AI across the organization.
Operational AI Technology
Our organization has a list of approved AI technologies and guidelines for their usage.
AI-Empowered Agility
Our organization embraces an approach of rapid experimentation when it comes to AI.
Human-Centric AI Culture
Experimentation with AI is psychologically safe, even when outcomes are uncertain.