CIO Business Intelligence
OCTOBER 29, 2024
The premise was that enterprises needed to secure their critical data more stringently in the wake of data hacks and emerging AI processes. I wrote, “ It may be even more important for the security team to protect and maintain the integrity of proprietary data to generate true, long-term enterprise value. Years later, here we are.
CIO Business Intelligence
OCTOBER 30, 2024
To overcome those challenges and successfully scale AI enterprise-wide, organizations must create a modern data architecture leveraging a mix of technologies, capabilities, and approaches including data lakehouses, data fabric, and data mesh. To learn more about how enterprises can prepare their environments for AI , click here.
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CIO Business Intelligence
NOVEMBER 7, 2024
The UK government has introduced an AI assurance platform, offering British businesses a centralized resource for guidance on identifying and managing potential risks associated with AI, as part of efforts to build trust in AI systems. About 524 companies now make up the UK’s AI sector, supporting more than 12,000 jobs and generating over $1.3
CIO Business Intelligence
OCTOBER 23, 2024
Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said. This creates new risks around data privacy, security, and consistency, making it harder for CIOs to maintain control.
Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase
Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.
O'Reilly on Data
APRIL 19, 2021
During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. When we asked respondents with mature practices what risks they checked for, 71% said “unexpected outcomes or predictions.” Risks checked for during development. But has it matured?
O'Reilly on Data
MARCH 18, 2020
The update sheds light on what AI adoption looks like in the enterprise— hint: deployments are shifting from prototype to production—the popularity of specific techniques and tools, the challenges experienced by adopters, and so on. Managing AI/ML risk. 2 risk factor among companies still evaluating AI. It ranks high (No.
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.
Speaker: William Hord, Senior VP of Risk & Professional Services
Enterprise Risk Management (ERM) is critical for industry growth in today’s fast-paced and ever-changing risk landscape. Do we understand and articulate our bank’s risk appetite and how that impacts our business units? How are we measuring and rating our risk impact, likelihood, and controls to mitigate our risk?
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. Strategies to avoid the risks of modernization by future-proofing your organizational infrastructure. You'll come away from the webinar understanding: Why ECM still poses business challenges.
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