John Brown
Member
Brandon Hall Group has unveiled its AI Maturity Model for HR, a research-based framework developed from insights collected from 600 HR and business professionals globally. The model maps out how organizations can evolve from reactive, hand-rolled AI efforts to optimized, strategic HR functions that use AI as a core enabler.
The research reveals that 46% of currently sit in the reactive or standardized maturity phases, while only 16% claim they've achieved optimized HR excellence.
Meanwhile, Mike Cooke, CEO, emphasizes: knowing your current maturity phase and following a clear roadmap helps shift AI from being a risk to a strategic advantage.
Read related news - https://hrtech-news.com/job-talent-...s-evolves-into-ai-powered-workforce-platform/
The research reveals that 46% of currently sit in the reactive or standardized maturity phases, while only 16% claim they've achieved optimized HR excellence.
The Five Phases of AI Maturity in HR
Brandon Hall's model describes a progression across five distinct phases, each with growing capabilities, governance, and impact.- Reactive / Ad Hoc (21%)
HR functions are largely manual, with little structure or governance around AI initiatives. Projects are experimental and often isolated. - Standardized (25%)
Basic automation and pilot programs begin to take shape. Some structure is emerging but efforts are still fragmented and not unified with strategy. - Defined / Strategic (25%)
AI is aligned with HR strategy. Insights from AI help drive decisions proactively rather than reactively. - Managed / Transformational (13%)
Advanced AI capabilities, predictive analytics, and integration across HR systems become more common. - Optimized HR Excellence (16%)
Organizations reach continuous innovation. AI is deeply embedded in culture, governance, and everyday decision frameworks.
Key Dimensions & Transition Factors
To move through these phases, HR organizations must evolve across several dimensions:- Organizational & Governance: Establishing AI oversight structures, governance protocols, and accountability mechanisms.
- Technology Evolution: Moving from basic automation to machine learning, generative AI, agentic AI, and retrieval-augmented generation (RAG).
- People & Skills: Developing competencies in AI literacy, data fluency, interpretability, and change leadership.
- Process Transformation: Reworking talent acquisition, performance, learning, and other HR workflows to incorporate AI-enabled decisions.
- Critical Success Factors: Recognizing factors such as executive sponsorship, data quality, change management, and culture readiness.
Meanwhile, Mike Cooke, CEO, emphasizes: knowing your current maturity phase and following a clear roadmap helps shift AI from being a risk to a strategic advantage.
Implications for HR Leaders
- Many organizations are still in the early stages. Almost half (46%) are in phases 1 or 2, underscoring how much room there is to grow.
- Reaching “Phase 3: Defined / Strategic” is often a tipping point: AI moves from novelty to a driver of insights, alignment, and influence.
- After that, firms that push into “Managed / Transformational” and “Optimized HR Excellence” often distinguish themselves via predictive analytics, adaptive workflows, and talent agility.
- Organizations should assess their maturity honestly, build capability roadmaps, invest in skills, and ensure alignment with broader business priorities.
Read related news - https://hrtech-news.com/job-talent-...s-evolves-into-ai-powered-workforce-platform/
