AISMI–AISM Model™

Strategy-Centered AI Maturity Assessment

Executive Brief

This assessment evaluates how effectively artificial intelligence is aligned with your organization’s enterprise strategy, leadership decision-making, and long-term value creation.

It is designed to identify whether AI is functioning as a coordinated strategic capability or operating as fragmented initiatives across the organization.

What to Expect
Confidentiality Note:
Information provided is used solely for assessment and research purposes. No information is shared or distributed.

This assessment is structured across 7 strategic pillars (5 questions each). You will complete one section at a time, with your overall positioning provided immediately upon completion.

Participant Information (for assessment context)

Contact details are collected to support assessment context, research, and additional insights if required. All information remains confidential.

Pillar 1 - Strategic AI Alignment

AI absent from enterprise strategy
AI referenced inconsistently; departmental interpretations vary
AI included in select strategic domains; limited enterprise coherence
AI embedded in enterprise strategy with leadership oversight
AI fully integrated into long-term strategic architecture shaping business direction
No link between AI and competitive strategy
AI contributes to isolated enhancements; limited strategic relevance
AI informs competitive differentiation in selected business units
AI consistently supports enterprise-level differentiation and value creation
AI is a core component of sustained competitive positioning and market leadership
AI not included in planning cycles
Ad-hoc or departmental-level inclusion
Integrated into annual planning with limited strategic influence
Embedded into multi-year enterprise planning; cross-functional governance
Fully integrated into adaptive strategic planning informing enterprise foresight
Fragmented, uncoordinated AI spending
Basic alignment efforts; ROI unclear
Portfolio alignment within select business units
Enterprise-level investment governance with measurable ROI
Investments aligned to strategic priorities with continuous optimization mechanisms
No exploration of AI-enabled business model changes
Early-stage pilots testing potential use cases
Emerging business model shifts in select domains
Enterprise progression toward AI-enabled business model integration
AI strategically transforms and evolves the enterprise business model

Pillar 2 - Executive Leadership & Strategic Competence

Minimal executive awareness
Foundational awareness; limited strategic understanding
Functional knowledge applied inconsistently across leadership
Executives demonstrate strategic AI competence informing decision-making
Executives exhibit enterprise-level mastery in guiding AI-enabled transformation
Ownership unclear or delegated downward
Some leaders involved without defined accountability
Designated AI champions exist but with limited enterprise authority
Clear enterprise-wide leadership accountability for AI strategy
Executives collectively own and govern AI as a strategic enterprise priority
AI not used in strategic decisions
Limited use of AI insights in select decisions
AI used regularly but inconsistently across units
AI informs enterprise-level decision-making processes
AI enhances strategic decisions through integrated, organization-wide insight flows
Leaders resistant to AI-driven change
Leaders reactive; inconsistent change advocacy
Leaders enable change in select functions
Leaders drive enterprise-wide AI change, supported by a clear AI transformation narrative
Leaders consistently champion strategic, organization-wide AI transformation
Fragmented leadership perspectives
Partial awareness and scattered alignment
Some strategic coherence but inconsistent prioritization
Strong, cross-functional C-suite alignment governing AI strategy
Fully aligned leadership team operationalizing AI as a unified strategic priority

Pillar 3 - Governance, Ethics & Responsible AI

No governing policies
Basic principles; limited guidance
Policies established within select domains
Enterprise governance framework applied consistently
Governance fully integrated with corporate strategy and monitored enterprise-wide
No ethical principles defined
Initial ethical discussions or pilot principles
Ethics applied inconsistently across projects
Ethics integrated across enterprise governance
Ethical standards embedded into corporate values and strategic decisions
Ad-hoc, unstructured risk handling
Basic risk awareness with inconsistent practices
Formal risk processes in select programs
Enterprise-wide, standardized AI risk governance
Continuous risk monitoring aligned to organizational strategic priorities
No clear accountability
Defined roles for isolated initiatives
Distributed roles across multiple functions
Enterprise accountability structure with leadership oversight
Clear accountability embedded across business functions and governance layers
No transparency practices
Minimal discussions; no formal mechanisms
Partial transparency in selected use cases
Standardized enterprise transparency and reporting practices
Transparent governance integrated with audit, compliance, and reporting systems

Pillar 4 - Organizational Design & Operating Model

Manual processes; no redesign
Isolated pilots assess limited processes
Select functions redesign processes for AI use
Enterprise redesign addressing structural constraints and workflows
AI integrated across core processes with consistent enterprise alignment
Traditional structures without AI roles
Emerging roles but limited coordination
Cross-functional AI teams in select areas
Enterprise-wide role clarity and integrated AI-enabled teams
Fully aligned organizational structure supporting AI-driven operations
Decisions fully manual
Basic decision-support tools
Semi-automated decision capabilities in key areas
AI-enabled decision processes standardized enterprise-wide
Strategically integrated decision processes leveraging advanced analytics
Fragmented, siloed data
Early-stage data pipelines in select domains
Standardized pipelines applied across functions
Enterprise data integrated and governed for AI readiness
Data flows strategically aligned, enabling all enterprise AI use cases
Traditional, non-adaptive operating model
Hybrid models emerging in limited domains
Pilots exploring AI-enabled operating models
Enterprise operating model adapted for AI at scale
Operating model integrates AI as a core component of enterprise operations

Pillar 5 - Culture, Mindset & Change Readiness

Fear, skepticism, limited trust
Neutral; unclear expectations
Growing optimism with inconsistent adoption
Enterprise-wide positive orientation toward AI
Organization embraces AI as part of strategic identity and future direction
Rare experimentation
Isolated pilot initiatives
Frequent experimentation in select units
Enterprise-wide experimentation culture
Consistent application of experimentation supporting strategic innovation
Minimal literacy or training
Basic knowledge across some areas
Functional literacy across broad segments
Enterprise-wide competency supporting AI adoption
Workforce demonstrates strategic AI literacy enabling organizational transformation
Static mindset; limited innovation
Occasional innovation with low adoption
Innovation in several functions
Enterprise innovation processes supported by AI
Innovation fully aligned with strategic AI objectives
Highly siloed collaboration
Limited cross-department engagement
Coordinated efforts across select domains
Enterprise-wide collaboration supporting AI integration
Collaboration embedded in organizational routines supporting strategic outcomes

Pillar 6 - AI Value Realization & Strategic Impact

No formal measurement
Inconsistent or anecdotal tracking
Functional-level ROI measurement
Enterprise-wide ROI tracking with governance
Value measurement aligned to strategic business objectives
Minimal efficiency improvements
Documented improvements in isolated projects
Gains in multiple domains
Enterprise-level efficiency gains integrated with strategy
Efficiency improvements enable strategic reinvestment and transformation
No measurable strategic impact
Limited impact through pilot projects
Strategic impact in multiple functional areas
AI materially contributes to enterprise-level outcomes
AI consistently delivers measurable strategic value
Decisions unaffected by AI
AI informs limited decisions
AI informs multiple decision domains
Enterprise-wide AI-informed decisions
AI insights systematically enhance decision quality across the enterprise
No competitive benefits
Minimal, isolated competitive advantages
Noticeable advantages in select domains
Enterprise-wide competitive benefits
AI is a sustained source of enterprise differentiation

Pillar 7 - AI Roadmap Execution & Strategic Planning Capability

No roadmap
Ad-hoc or single-domain roadmap
Roadmap in select units
Enterprise-wide multi-year roadmap
Roadmap integrated with enterprise planning and regularly updated
Ad-hoc prioritization
Basic metrics used inconsistently
Structured prioritization in select areas
Enterprise-level prioritization aligned with strategy
Prioritization consistently aligned with strategic outcomes
Unclear resource allocation
Basic allocation with gaps
Cross-functional alignment in select domains
Enterprise-wide strategic resource planning
Resource allocation optimized to support strategic AI initiatives
No monitoring mechanisms
Informal or isolated oversight
Standard monitoring in select functions
Enterprise governance overseeing roadmap execution
Continuous monitoring linked to strategic objectives and KPIs
Rigid and slow to adapt
Moderate responsiveness in limited areas
Improved adaptability in select functions
Enterprise-level agility supported by AI insights
Adaptability integrated into strategic planning and execution cycles