Fraudsters don’t have governance committees or budget cycles. They just act. New research by @TheACFE + SAS asks whether organizations can move fast enough to keep up with #deepfakes & other AI-charged #fraud threats. Spoiler: most can’t yet.
ENTERPRISE AI
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Agents in Production: Unpredictability and Monitoring Challenges
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New Conceptual Guide: You don’t know what your agent will do until it’s in production With traditional software, you ship with reasonable confidence. Test coverage handles most paths. Monitoring catches errors, latency, and query issues. When something breaks, you read the
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AI Hackathons with Auth0 and $10K Prize Pool
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AI Hackathons, hosted by @Devpost Authorized to Act: Auth0 for AI Agents by Okta PRIZES: $10,000 in cash DEADLINE: Apr 7, 2026 Build an agentic AI application using Auth0 for AI Agents Token Vault JOIN THE HACKATHON: https://
bit.ly/auth026i ZerveHack by Zerve AI -
Huawei Showcases 115 Industrial AI Solutions at MWC2026
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At #MWC2026, Huawei and its customers released 115 industrial intelligence showcases, demonstrating how AI and digital infrastructure are being applied in real operational environments. My latest article explores key insights from the Industrial Digital and Intelligent
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AI Leaders in Regulated Industries Gather at Rev 26
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Pharma. Financial services. Insurance. The leaders scaling AI across some of the world's most regulated industries are coming to Rev 26. @capitalone | @bmsnews | @helvetia Join us in Philadelphia, New York, and London: https://
hubs.ly/Q048j9zG0 -
Intelligent Agents: Natural Language Automation Across Systems
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Enter intelligent agents (the practical layer): Ask in natural language. The agent pulls context across systems, then acts—send an alert, generate a report, flag an anomaly. Result → faster cycles, clearer visibility, and automation you can trust across existing
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Enterprise Intelligence Future: Context Engineering Over Larger Models
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Bottom line: the next era of enterprise intelligence won’t be “bigger models”—it’ll be better context. Watch the full video: Context Engineering—Defining the Next Era of Enterprise Intelligence. In partnership with Elastic. Check out the full article:
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Data governance: From collection to actionable insights for executives
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Why this matters to execs: → From collection → comprehension: you stop hoarding and start explaining. → Accuracy scales because answers come from your ground truth. → You finally get explainability you can take to a board meeting.
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Context Engineering: Why Quality Data Beats Volume for AI
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Most teams think “more data = smarter AI.” I make the opposite case: context beats volume. When LLMs are grounded in your company’s own signals—not just the internet—they deliver accurate, explainable decisions at scale. A thread on Context Engineering and why it changes
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AI Translation for Enterprises: Navigating Technical Documentation Nuance
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Translation is honestly one of the most underrated AI use cases for enterprises. As a French-Canadian working in English daily, I see firsthand how much nuance gets lost even between two languages I speak fluently. Curious how this handles technical docs. It's a struggle even for