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Rushing for AI ROI? Chances are it will cost you

CIO Business Intelligence

Many organizations have struggled to find the ROI after launching AI projects, but there’s a danger in demanding too much too soon, according to IT research and advisory firm Forrester. Measure everything Looking for ROI too soon is often a product of poor planning, says Rowan Curran, an AI and data science analyst at Forrester.

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The Future of AI and ROI for the Enterprise

Dataiku

For many years, AI was an experimental risk for companies. Recently, Dataiku spoke with Mike Gualtieri, VP & Principal Analyst at Forrester , in “The Future of AI and ROI for the Enterprise, featuring Forrester” webinar about the current state of the market and what AI success looks like going forward.

ROI 110
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How to Set AI Goals

O'Reilly on Data

Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. They don’t automatically generate revenue and growth, maximize ROI, or keep users engaged and loyal. automated retirement portfolio rebalancing and maximized ROI).

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What you need to know about product management for AI

O'Reilly on Data

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. What delivers the greatest ROI? How do you select what to work on?

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When is the right time to dump an AI project?

CIO Business Intelligence

On the one side, Forrester recently warned organizations not to look for AI ROI too soon, because they could miss out on AI’s benefits. Still, a 30% failure rate represents a huge amount of time and money, given how widespread AI experimentation is today. The ROI may be coming from many of these less tangible things,” she says.

ROI 135
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5 best practices to successfully implement gen AI

CIO Business Intelligence

This is why many enterprises are seeing a lot of energy and excitement around use cases, yet are still struggling to realize ROI. So, to maximize the ROI of gen AI efforts and investments, it’s important to move from ad-hoc experimentation to a more purposeful strategy and systematic approach to implementation.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

It is also important to have a strong test and learn culture to encourage rapid experimentation. What do you recommend to organizations to harness this but also show a solid ROI? A properly set framework will ensure quality, timeliness, scalability, consistency, and industrialization in measuring and driving the return on investment.

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