AI Maturity Model

Five Perspectives on AI Maturity

As artificial intelligence (AI) transforms industries, its impact on organizations varies based on strategic objectives, AI maturity and approach, and leadership vision. For executives in IT and strategy, understanding AI’s multifaceted role is essential to navigating its challenges and opportunities. Each perspective reflects a choice about how you’re going to use AI. For example, are

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Strategy
AI Investments

Why AI Investments Are Falling Short

Artificial Intelligence (AI) holds unparalleled potential to revolutionize industries, from automating routine tasks to delivering real-time insights and enabling hyper-personalized customer experiences. Yet, despite billions of dollars poured into AI initiatives, businesses struggle to translate their investments into tangible value. Many AI programs stall in pilot phases or fail to scale, leaving executives questioning whether

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Culture
AI powered application

Building an AI Powered Application

Recently, I was approached by a company that aimed to enhance its enterprise sales enablement by evolving to an AI powered application that streamline processes, facilitates real-time skill enhancement, and fosters adaptive learning. The company had ambitious goals but quickly encountered significant challenges—user resistance, misunderstandings of AI’s capabilities, and complex data integration issues. This request

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Technology

Developing an Enterprise Data Strategy

Developing Your Data Strategy: A CIO Call to Action Data is a crucial resource for fostering innovation and maintaining a competitive edge. To fully unlock its potential, more than technological advancements are required. A shift in organizational attitude and perspective is imperative. This guide not only offers ideas for transitioning from working in data silos

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Data

Data Maturity Assessment – Level 4

Level 4 – Business Process Improvement Data Strategy Goal: GovernData Maturity: Repeatable and Managed approach to enterprise data management IT Builder: The focus on data governance at Level 4 marks a significant shift in the evolution of data management inside enterprises. IT builders are accountable for putting in place robust data management policies and processes

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Data
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