Management Risk Strategy 
CIO Business Intelligence
DECEMBER 11, 2024
Primary among these is the need to ensure the data that will power their AI strategies is fit for purpose. According to Richard Kulkarni, Country Manager for Quest, a lack of clarity concerning governance and policy around AI means that employees and teams are finding workarounds to access the technology.
O'Reilly on Data
JUNE 27, 2023
Welcome to your company’s new AI risk management nightmare. Before you give up on your dreams of releasing an AI chatbot, remember: no risk, no reward. The core idea of risk management is that you don’t win by saying “no” to everything. So, what do you do? What Can You Do?
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CIO Business Intelligence
MARCH 4, 2025
With AI agents poised to take over significant portions of enterprise workflows, IT leaders will be faced with an increasingly complex challenge: managing them. Analysts say the big three hyperscalers and cloud management vendors are aware of the gap and are working on it.
O'Reilly on Data
MAY 14, 2020
In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.
Speaker: William Hord, Vice President of ERM Services
A well-defined change management process is critical to minimizing the impact that change has on your organization. Leveraging the data that your ERM program already contains is an effective way to help create and manage the overall change management process within your organization. Organize ERM strategy, operations, and data.
CIO Business Intelligence
NOVEMBER 21, 2024
Ninety percent of CIOs recently surveyed by Gartner say that managing AI costs is limiting their ability to get value from AI. In many cases, small wins that show quick value may be a better bet than huge, high-risk projects, Miller advises. Doing so can help ensure costs are manageable and the solution will scale.
O'Reilly on Data
MARCH 31, 2020
If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools.
Speaker: Chris McLaughlin, Chief Marketing Officer and Chief Product Officer, Nuxeo
After 20 years of Enterprise Content Management (ECM), businesses still face many of the same challenges with finding and managing information. He will share compelling stories from customers that have chosen a different path, and best practices for Information Management professionals to help them along their way.
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This whitepaper offers real strategies to manage risks and position your organization for success. IT leaders are experiencing rapid evolution in AI amid sustained investment uncertainty. As AI evolves, enhanced cybersecurity and hiring challenges grow.
Speaker: Ryan McInerny, CAMS, FRM, MSBA - Principal, Product Strategy
With 20% of Americans owning cryptocurrencies, speaking "fluent crypto" in the financial sector ensures you are prepared to discuss growth and risk management strategies when the topic arises. May 18th, 2023 at 9:30 am PDT, 12:30 pm EDT, 5:30 pm BST
Speaker: Jon Harmer, Product Manager for Google Cloud
You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap. Understand how your work contributes to your company's strategy and learn to apply frameworks to ensure your features solve user problems that drive business impact.
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They rely on data to power products, business insights, and marketing strategy. From search engines to navigation systems, data is used to fuel products, manage risk, inform business strategy, create competitive analysis reports, provide direct marketing services, and much more.
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Unfortunately, data replication, transformation, and movement can result in longer time to insight, reduced efficiency, elevated costs, and increased security and compliance risk. How a next-gen data lake can halt data replication and streamline data management. What to consider when implementing a "no-copy" data strategy.
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