5_2_Maturity_Level_Definitions.xlsx

	A	B	C	D	E	F
1	AI Adoption Maturity Level Definitions
2	Comprehensive maturity model across all readiness dimensions
3
4	Readiness Dimension	Level 1 Initial/Ad Hoc (Score 0-1.0)	Level 2 Developing/Aware (Score 1.1-2.0)	Level 3 Defined/Capable (Score 2.1-3.0)	Level 4 Managed/Proficient (Score 3.1-4.0)	Level 5 Optimizing/Advanced (Score 4.1-5.0)
5	Leadership & Strategy	No AI strategy Ad hoc initiatives Limited awareness No sponsorship	Emerging interest Discussing potential Some champions Initial exploration	Clear AI strategy Executive sponsor Defined roadmap Budget allocated	Mature strategy Active leadership Multi-year plan Proven governance	AI as differentiator Board-level focus Continuous evolution Industry leadership
6	Organizational Culture	Resistant to change Risk-averse Silo mentality Limited collaboration	Growing openness Cautious innovation Some cross-team work Building trust	Change-ready Data-driven Strong collaboration Learning culture	Innovation-driven Risk-intelligent Seamless teamwork Growth mindset	Transformation leader Experimentation norm Fluid organization Continuous learning
7	Technical Infrastructure	Legacy systems Limited integration Basic capabilities Manual processes	Upgrading systems Some cloud adoption Improving integration Basic automation	Modern platforms Cloud-enabled Good integration Scalable infrastructure	Advanced architecture Cloud-native API-first design Automation-ready	Cutting-edge tech Fully cloud-native Real-time integration AI-optimized
8	Data Readiness	Poor data quality Silos and gaps No governance Limited access	Improving quality Some integration Basic governance Growing awareness	Good data quality Integrated sources Formal governance Broad accessibility	High data quality Enterprise view Mature governance Self-service enabled	Excellent quality Real-time data Advanced governance Data as product
9	Skills & Capabilities	No AI expertise Limited tech skills Digital literacy gaps Minimal training	Hiring begins Upskilling started Growing awareness Basic training	Core AI team Solid tech skills Good digital fluency Training programs	Strong AI capability Deep expertise Advanced skills Continuous learning	World-class talent Thought leadership Center of excellence Innovation culture
10	Process Maturity	Undefined processes Ad hoc approach No standardization Reactive mode	Basic documentation Some standards Improving practices Less reactive	Documented processes Standardized approach Proactive management Continuous improvement	Optimized processes Best practices Proactive monitoring Data-driven optimization	Industry benchmark Innovative practices Predictive management Continuous evolution
11	Change Readiness	No change plan Limited awareness High resistance Weak communication	Planning begins Growing awareness Some resistance Basic communication	Change plan ready Good awareness Managed resistance Effective communication	Strong change support High engagement Minimal resistance Proactive communication	Change excellence Full engagement Change advocates Continuous adaptation
12
13	OVERALL READINESS INTERPRETATION
14	Level	Readiness Interpretation
15	Level 1 (0-1.0)	NOT READY - Significant foundational work required before AI adoption
16	Level 2 (1.1-2.0)	EMERGING - Multiple critical gaps must be addressed; pilot projects only
17	Level 3 (2.1-3.0)	CAPABLE - Ready for pilot initiatives with managed scope and risk
18	Level 4 (3.1-4.0)	PROFICIENT - Ready for production AI deployment at scale
19	Level 5 (4.1-5.0)	ADVANCED - Ready for complex, transformative AI initiatives
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100