Security teams are facing new challenges in AI deployments, with common assumptions about AI security leaving enterprises exposed. Four prevalent myths include thinking a well-aligned model means a secure application, treating a passed red team test as certification, believing traditional security frameworks suffice for AI, and assuming securing text prompts covers the attack surface. To stay secure, teams must enforce security at the application layer, conduct continuous testing, and add indirect prompt injection detection.
Another often-overlooked security layer in AI deployments is the infrastructure around the model, including agents, connectors, and tool integrations. This creates a new attack surface that traditional application security models weren't designed to address. Organizations should treat agent ecosystems as a distinct security layer, applying the principle of least agency and mapping trust boundaries across connectors and tool integrations.
In other news, China's Communist Party is exploring ways to keep humans employed as AI is embedded in every industry. A Chinese lab recently unveiled GLM-5.2, a powerful and affordable AI model that's almost as good as Anthropic's latest model but runs at a much lower cost. This development is part of China's plan to avoid mass displacement of humans by AI in the labor market.
Agentic AI is becoming crucial in modern customer service, helping companies improve efficiency and reduce costs. The technology can deliver immediate ROI by replacing guesswork with evidence-based automation. However, adoption has outpaced execution, with only 20% of companies achieving significant ROI.
Enterprises have concerns about Frontier AI, including model selection, automation, and measurable results. To separate genuine AI capabilities from marketing hype, enterprises should ask vendors six key questions. These questions include understanding model providers, specific models used, automation capabilities, context, results, and validation.
New AI-powered tools are being launched to make recycling and product identification easier. PaintCare, for example, has unveiled an AI-powered product recognition tool that uses image recognition to identify common paint and paint-related products.
A recent report found that nearly half of organizations lack full visibility into employee AI tool usage, which can lead to security risks and compliance issues. Organizations should monitor and control employee AI tool usage to ensure data security and integrity.
The University of Wisconsin-Madison has launched the College of Computing & Artificial Intelligence to explore and inform technological change for societal benefit. The college brings together three established departments: Computer Sciences, the Information School, and Statistics.
The Bank of England has warned that AI trading agents could trigger the next market crisis, as they could herd into identical decisions at machine speed, amplifying market stress. The Bank is collaborating with international counterparts to model cross-border herding behavior.
Lastly, the EvilTokens campaign has revealed a significant increase in device code phishing attacks, powered by AI. Phishing attacks increased 1,380% between July-December 2025 and January-April 2026, with AI being used to generate believable, tailored lures at scale.
Key Takeaways
• Security teams must enforce security at the application layer and conduct continuous testing to stay secure in AI deployments. • Organizations should treat agent ecosystems as a distinct security layer, applying the principle of least agency. • China's GLM-5.2 AI model is a powerful and affordable alternative to Anthropic's latest model. • Agentic AI is crucial in modern customer service, delivering immediate ROI through evidence-based automation. • Enterprises should ask vendors six key questions to separate genuine AI capabilities from marketing hype. • Nearly half of organizations lack full visibility into employee AI tool usage, posing security risks. • The University of Wisconsin-Madison has launched the College of Computing & Artificial Intelligence. • The Bank of England warns that AI trading agents could trigger the next market crisis. • AI-powered phishing attacks have increased 1,380% between July-December 2025 and January-April 2026. • PaintCare has unveiled an AI-powered product recognition tool to make recycling easier.Four Common AI Security Myths Exposed
Security teams have four common assumptions about AI security that are leaving enterprises exposed. These assumptions include thinking a well-aligned model means a secure application, treating a passed red team test as a certification, believing traditional security frameworks are enough for AI, and assuming securing text prompts covers the attack surface. However, these assumptions hide gaps that leave organizations vulnerable to attacks. To stay secure, teams should enforce security at the application layer, conduct continuous testing, and add indirect prompt injection detection.
The Overlooked Security Layer in AI Deployments
Many teams focus on large language model safety but overlook the infrastructure around the model, including agents, connectors, and tool integrations. This creates a new attack surface that traditional application security models were not designed to address. AI agents can be tricked into acting with full authority, allowing attackers to manipulate instructions and abuse permissions. Organizations should treat agent ecosystems as a distinct security layer, applying the principle of least agency and mapping trust boundaries across connectors and tool integrations.
China's Plan to Save Jobs from AI
China is thinking about how to keep humans employed as it embeds AI in every industry. A Chinese lab recently unveiled a powerful and affordable AI model called GLM-5.2. The model is almost as good as Anthropic's latest model but runs at a much lower cost. China's Communist Party fears a restive proletariat and is working to avoid mass displacement of humans by AI in the labor market.
Why Agentic AI is Key in Modern Customer Service
Agentic AI is becoming crucial in modern customer service as companies face pressure to improve efficiency. The technology helps with large customer service operations, which can cost $12.50 per minute. Adoption of AI has outpaced execution, with only 20% of companies achieving significant ROI. Agentic AI can deliver immediate ROI by replacing guesswork with evidence-based automation.
Six Questions to Ask Security Vendors about Frontier AI
Enterprises have concerns about Frontier AI, including model selection, automation, and measurable results. To separate genuine AI capabilities from marketing hype, enterprises should ask vendors six key questions. These questions include understanding model providers, specific models used, automation capabilities, context, results, and validation.
PaintCare Unveils AI-Powered Product Recognition Tool
PaintCare launched an AI-powered product recognition tool to help consumers identify paint products quickly. The tool uses image recognition to identify common paint and paint-related products and provides guidance on whether they are covered by the PaintCare program. The tool aims to make recycling leftover paint easier and more accessible.
Nearly Half of Organizations Lack Visibility into Employee AI Usage
A recent report found that nearly half of organizations lack full visibility into employee AI tool usage. This lack of visibility can lead to security risks and compliance issues. Organizations should monitor and control employee AI tool usage to ensure data security and integrity.
University of Wisconsin Launches College of Computing & Artificial Intelligence
The University of Wisconsin-Madison officially launched the College of Computing & Artificial Intelligence. The college will explore and inform technological change for societal benefit. It brings together three established departments: Computer Sciences, the Information School, and Statistics.
Bank of England Warns of AI Trading Agent Risks
The Bank of England warned that AI trading agents could trigger the next market crisis. AI agents executing trades autonomously could herd into identical decisions at machine speed, amplifying market stress. The Bank is collaborating with international counterparts to model cross-border herding behavior.
EvilTokens Campaign Uses AI for Device Code Phishing
The EvilTokens campaign reveals a significant increase in device code phishing attacks, powered by AI. Phishing attacks increased 1,380% between July-December 2025 and January-April 2026. AI is being used to generate believable, tailored lures at scale, making detection and human recognition harder.
Sources
- The Four AI Security Myths Leaving Enterprises Exposed
- The Security Layer AI Deployments Most Teams Are Ignoring
- China’s Plan to Save Jobs From A.I.
- Why Agentic AI Is Becoming the Defining Capability in Modern CX
- Frontier AI: Six Questions Every Enterprise Should Ask Security Vendors
- PaintCare Unveils New AI-Powered Product Recognition Tool
- Nearly Half of Organizations Lack Full Visibility Into Employee AI Usage
- The future is now: College of Computing & Artificial Intelligence officially launches
- The Bank of England is warning that AI trading agents could trigger the next market crisis
- EvilTokens Campaign Reveals Device Code Phishing Ticks Up 1,380%, Powered by AI
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