Chapter 1The Business Case for Analytics and Artificial Intelligence
In this chapter, we will examine the following:
- Modern AI—evolution and competitive advantage
- The democratization of AI and competitive advantage
- Real-world applications of AI and generative AI
- Analytics and AI investment trends
- Justifying investments with concrete outcomes
Five years from now, the leaders who succeeded in this moment may say they made the right call on artificial intelligence (AI). The others may talk about the “hype cycle” and wonder where their advantage went. We are at a generational inflection point. AI is being embedded in daily workflows and reshaping how we compete. From predictive analytics to generative and agentic AI, organizations are discovering new ways to cut costs, boost productivity, and open new markets.
But chasing hype is not a strategy. Too many leadership teams are trying to pilot chatbots, co-pilots, and generative tools without the solid data foundations, governance, or operational models to make them stick. The result can be proof-of-concepts that don’t scale and security and compliance risks that they didn’t anticipate. If you want AI to create measurable value, you need to start with a clear business case, one that ties investment to strategy, outcomes, and the capabilities required to deliver them.
This chapter examines the business case for AI, exploring its history, how it is evolving, and how it can create value.
Modern AI—Evolution and Competitive Advantage ...
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