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Levels of the
AI Maturity Model
Maturity
Level
AI
Ignorance
LEVEL-01 LEVEL-02 LEVEL-03 LEVEL-04 LEVEL-05
AI
Awareness
AI
Adoption
AI
Operationalization
AI-First
Enterprise
Strategy and
Vision
No clear AI
strategy; AI is
seen as a
futuristic or
unnecessary
initiative.
Awareness of AI
potential, but the
strategy is vague
and
unstructured.
Defined AI strategy
aligned with
business goals;
early-stage
leadership buy-in.
AI is a core
strategic pillar;
leadership
invests heavily in
AI-driven
transformation.
AI is embedded
in every aspect
of business
strategy and
culture.
Data and
Infrastructure
Data is siloed,
unstructured,
and largely
unused for
decision-making.
Initial data
collection and
storage efforts;
basic data
governance
introduced.
Cloud and
on-premise
hybrid
infrastructure
established; data
governance is
improving.
Centralized,
scalable data
infrastructure
with real-time
processing
capabilities.
Fully automated,
AI-driven data
ecosystems with
autonomous
decision-making.
AI Development
and Deployment
AI is non-existent
or limited to
basic rule-based
automation.
Experimentation
with AI in
isolated projects,
mostly PoCs.
AI models are in
production but
not fully
integrated;
moderate
automation.
AI is deeply
integrated into
operations,
continuous
model training,
and optimization.
AI systems
self-improve
with
reinforcement
learning and
adaptive AI
techniques.
Governance
and Ethics
No governance,
leading to
security and
compliance risks.
Emerging
discussions on AI
ethics, security,
and risk
mitigation.
Ethical AI
principles are
being defined
and risk
management
frameworks are
in place.
A strong
governance
framework
ensures fairness,
transparency,
and compliance.
AI governance is
a global
benchmark,
ensuring trust,
ethics, and
regulatory
compliance.
Business
Impact
Minimal to no
business impact
from AI.
Early AI-driven
efficiencies in
select processes,
but no
large-scale
impact.
Cost reductions
and productivity
gains are seen,
but innovation is
still limited.
Competitive
advantage
through
AI-driven
innovation and
new revenue
streams.
AI is the
foundation for
business growth,
continuously
creating new
markets and
disrupting
industries.
Leadership and
Culture
Leadership lacks
AI awareness; no
AI-driven culture.
Leadership
begins engaging
in AI discussions;
minimal
workforce
alignment.
Leadership
innovators AI
initiatives; early
cultural shifts in
the workforce.
AI-first mindset
across
leadership and
employees;
reskilling
initiatives in
place.
Leadership is
AI-native, driving
an AI-first
organization; AI
fluency is
universal.
Competitive
Advantage
No competitive
edge; falling
behind market
trends.
Early adopters
gain a slight
competitive
advantage.
Competitive
differentiation
emerges through
AI-driven
efficiencies.
AI fuels market
leadership;
disruptive
innovations
emerge.
Unparalleled
market
dominance
through
AI-driven
business models.
www.veritis.com
connect@veritis.com
972-753-0022

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AI Maturity Model for Enterprise Excellence

  • 1. Levels of the AI Maturity Model Maturity Level AI Ignorance LEVEL-01 LEVEL-02 LEVEL-03 LEVEL-04 LEVEL-05 AI Awareness AI Adoption AI Operationalization AI-First Enterprise Strategy and Vision No clear AI strategy; AI is seen as a futuristic or unnecessary initiative. Awareness of AI potential, but the strategy is vague and unstructured. Defined AI strategy aligned with business goals; early-stage leadership buy-in. AI is a core strategic pillar; leadership invests heavily in AI-driven transformation. AI is embedded in every aspect of business strategy and culture. Data and Infrastructure Data is siloed, unstructured, and largely unused for decision-making. Initial data collection and storage efforts; basic data governance introduced. Cloud and on-premise hybrid infrastructure established; data governance is improving. Centralized, scalable data infrastructure with real-time processing capabilities. Fully automated, AI-driven data ecosystems with autonomous decision-making. AI Development and Deployment AI is non-existent or limited to basic rule-based automation. Experimentation with AI in isolated projects, mostly PoCs. AI models are in production but not fully integrated; moderate automation. AI is deeply integrated into operations, continuous model training, and optimization. AI systems self-improve with reinforcement learning and adaptive AI techniques. Governance and Ethics No governance, leading to security and compliance risks. Emerging discussions on AI ethics, security, and risk mitigation. Ethical AI principles are being defined and risk management frameworks are in place. A strong governance framework ensures fairness, transparency, and compliance. AI governance is a global benchmark, ensuring trust, ethics, and regulatory compliance. Business Impact Minimal to no business impact from AI. Early AI-driven efficiencies in select processes, but no large-scale impact. Cost reductions and productivity gains are seen, but innovation is still limited. Competitive advantage through AI-driven innovation and new revenue streams. AI is the foundation for business growth, continuously creating new markets and disrupting industries. Leadership and Culture Leadership lacks AI awareness; no AI-driven culture. Leadership begins engaging in AI discussions; minimal workforce alignment. Leadership innovators AI initiatives; early cultural shifts in the workforce. AI-first mindset across leadership and employees; reskilling initiatives in place. Leadership is AI-native, driving an AI-first organization; AI fluency is universal. Competitive Advantage No competitive edge; falling behind market trends. Early adopters gain a slight competitive advantage. Competitive differentiation emerges through AI-driven efficiencies. AI fuels market leadership; disruptive innovations emerge. Unparalleled market dominance through AI-driven business models. www.veritis.com connect@veritis.com 972-753-0022