CIO Business Intelligence
APRIL 8, 2025
Risk is inescapable. A PwC Global Risk Survey found that 75% of risk leaders claim that financial pressures limit their ability to invest in the advanced technology needed to assess and monitor risks. Yet failing to successfully address risk with an effective risk management program is courting disaster.
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
JANUARY 14, 2025
For CIOs leading enterprise transformations, portfolio health isnt just an operational indicator its a real-time pulse on time-to-market and resilience in a digital-first economy. In todays digital-first economy, enterprise architecture must also evolve from a control function to an enablement platform.
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.
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.
O'Reilly on Data
JANUARY 21, 2025
TL;DR: Enterprise AI teams are discovering that purely agentic approaches (dynamically chaining LLM calls) dont deliver the reliability needed for production systems. A shift toward structured automation, which separates conversational ability from business logic execution, is needed for enterprise-grade reliability.
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.
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.
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