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2023 has been a break-out year for generativeAI technology, as tools such as ChatGPT graduated from lab curiosity to household name. But CIOs are cautiously evaluating how to safely deploy generativeAI in the enterprise, and what guard-rails to put around it.
GenerativeAI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption. Vendors are adding gen AI across the board to enterprise software products, and AI developers havent been idle this year either.
As they take stock after the year-end frenzy of shopping the holiday season always brings, retail CIOs attending the National Retail Federation’s annual show, NRF 2024, may be wondering how they can improve their IT systems’ performance over the next 12 months. year on year in the first 11 months of 2023, AI or no AI.
Why open source AI lags behind commercial Lower costs, more flexibility, higher security whats not to love about open source? The gap has significantly narrowed in 2024, says Gartner analyst Arun Chandrasekaran. There was a wide gap in performance between open source and proprietary models, but last year was a long time ago.
Consider how fast generativeAI went from avant-garde to ubiquity: At under two years, it may be a record. That’s not hyperbole: TEKsystems’ 2024 State of Digital Transformation report found that 53% of organizations classified as digital leaders are confident that their digital investments will meet expected ROIs.
The overhype of generativeAI was unavoidable last year, yet despite all the distraction, unproven benefits, and potential pitfalls, Dana-Farber Cancer Institute CIO Naomi Lenane didn’t want to ban the technology outright. But allowing free, unfettered use of the public gen AI platforms was not an option.
Result: Disrupted production led to product shortages and a 23-28% loss in net sales for Q1 2024. Result: Though the full scope remains unclear, the breach affected almost all Okta customers and highlighted the potential risks associated with third-party vendorsmanaging sensitive data.
We’ve already seen many examples of corporate AIs not performing as intended. Late last year in California, for instance, a ChatGPT-powered chatbot promised a Chevrolet of Watsonville customer a 2024 Chevy Taho for $1, adding “and that’s a legally binding offer — no takesies backsies.”
Modernize Your Banking Ecosystem The global banking industry is undergoing a significant transformation driven by technological advancements in artificial intelligence (AI), machine learning (ML), and generativeAI (GenAI). AI-enabled Banking is the New Future AI in banking is now a reality.
Throughout late 2024, Microsoft continued to expand its agentic offerings with purpose-built agents for specific use cases. Then in November, the company revealed its Azure AI Agent Service, a fully-managed service that lets enterprises build, deploy and scale agents quickly. With AI, that percentage is flipped.
You might want to check out the Cloud Security Alliances new white paper AI Organizational Responsibilities: AI Tools and Applications. Each of those three areas is analyzed according to six areas of responsibility for teams deploying AI systems: Evaluation criteria : To assess AI risks, organizations need quantifiable metrics.
The longtime IT service management platform provider entered the CRM space in early 2025, but it rolled out several new capabilities at it Knowledge 2025 conference this week in direct competition with CRM giant Salesforce. No one model does it all, and theres going to be large swaths of models adopted at any and every enterprise.
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