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Bringing an AI Product to Market

O'Reilly on Data

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 362
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How Svevia connects roads, risk, and refuse through the cloud

CIO Business Intelligence

We put sensors in the vessels, and with the measurement data we receive, we can see how full they are and plan the routes accordingly,” says Andreas Bäckström, a business developer at Division Drift. Digital alerts Another project deals with slow-moving vehicles, something that increases the risk of accidents on the roads.

Risk 97
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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? encouraging and rewarding) a culture of experimentation across the organization. Encourage and reward a Culture of Experimentation that learns from failure, “ Test, or get fired!

Strategy 289
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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management. What Is Model Risk?

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Generative AI’s change management challenge

CIO Business Intelligence

Despite headlines warning that artificial intelligence poses a profound risk to society , workers are curious, optimistic, and confident about the arrival of AI in the enterprise, and becoming more so with time, according to a recent survey by Boston Consulting Group (BCG). For many, their feelings are based on sound experience.

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10 digital transformation roadblocks — and 5 tips for overcoming them

CIO Business Intelligence

Foster a culture of innovation: Digital transformation requires innovation and experimentation, and thus a culture for embracing new technologies and ideas. IT leaders help facilitate a shift in organizational mindset toward a willingness to take risks and learn from failures.

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How to become an AI+ enterprise

IBM Big Data Hub

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. Otherwise, the risks become too significant.