Global AI Maturity Survey

Global AI Maturity Survey

Results of the 2022 Frost & Sullivan Global AI Survey

RELEASE DATE
02-Feb-2023
REGION
Global
Research Code: PDB9-01-00-00-00
SKU: IT04673-GL-CR_27444
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Description

AI holds the potential to deliver significant benefits to economies and societies—from enabling new business models and driving operational efficiencies to providing accurate predictive outcomes. As AI technology implementation shifts gears—from the proof-of-concept stage to enterprise deployment—failing to implement an enterprise-wide AI strategy and roadmap, to ensure data readiness, or to ensure regulatory and compliance measures may impede faster AI deployment. However, AI deployment is a journey that organizations start with exploring relevant technologies and use cases and move toward ubiquitous embedding of the technology across business functions. Therefore, it is important to analyze an organization's readiness or maturity for technology deployment. Frost & Sullivan has developed a 4-stage AI maturity framework that considers multiple dimensions, such as AI strategy and roadmap articulation; data readiness; regulatory, compliance, and policy alignment; and stage of technology deployment. To assess AI maturity, Frost & Sullivan conducted a global survey to analyze the maturity levels of nearly 600 organizations. The study highlights key findings in terms of AI maturity. The study offers technology vendors and service providers a perspective on AI readiness in terms of select parameters that assess potential opportunities to create customer value and help end users understand the level of maturity in the overall landscape.

Author: Hemangi Patel

Table of Contents

Research Objectives and Methodology

Respondent Profile

AI Maturity Framework

AI Maturity Framework (continued)

AI Technology Maturity and Implementation

Key Findings

AI Maturity by Industry

AI Maturity by Industry Use Case

AI Maturity—Dimensions

AI Maturity—Dimensions (continued)

Strategy and Roadmap Articulation

Strategy and Roadmap Articulation (continued)

Building AI Strategy and Roadmap

Data Readiness

Data Readiness Framework

Regulatory Compliance and Policy Alignment

Key Considerations While Designing AI Regulatory Compliance and Policy Measures

Technology Implementation

Technology Implementation—Scaling Up AI Deployments

The Way Forward

Strengthening Integration and Data Migration Support Service

Key Role of IT Software Services Vendors in AI Deployments

Build a Compelling Value Proposition

Growth Opportunities Fuel the Growth Pipeline Engine™

Why is it Increasingly Difficult to Grow?

The Strategic Imperative 8™

List of Exhibits

Legal Disclaimer

AI holds the potential to deliver significant benefits to economies and societies—from enabling new business models and driving operational efficiencies to providing accurate predictive outcomes. As AI technology implementation shifts gears—from the proof-of-concept stage to enterprise deployment—failing to implement an enterprise-wide AI strategy and roadmap, to ensure data readiness, or to ensure regulatory and compliance measures may impede faster AI deployment. However, AI deployment is a journey that organizations start with exploring relevant technologies and use cases and move toward ubiquitous embedding of the technology across business functions. Therefore, it is important to analyze an organization's readiness or maturity for technology deployment. Frost & Sullivan has developed a 4-stage AI maturity framework that considers multiple dimensions, such as AI strategy and roadmap articulation; data readiness; regulatory, compliance, and policy alignment; and stage of technology deployment. To assess AI maturity, Frost & Sullivan conducted a global survey to analyze the maturity levels of nearly 600 organizations. The study highlights key findings in terms of AI maturity. The study offers technology vendors and service providers a perspective on AI readiness in terms of select parameters that assess potential opportunities to create customer value and help end users understand the level of maturity in the overall landscape. Author: Hemangi Patel
More Information
Author Hemangi Patel
Industries Information Technology
No Index No
Is Prebook No
Keyword 1 Global AI Maturity Survey
Keyword 2 AI Maturity Framework
Keyword 3 AI Survey
Podcast No
WIP Number PDB9-01-00-00-00