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OpenAI Unveils Secure MCP Tunnel for Enterprise Data Privacy
AI News & Trends

OpenAI Unveils Secure MCP Tunnel for Enterprise Data Privacy

OpenAI has introduced the Secure MCP Tunnel, which may let companies keep their Model Context Protocol servers inside their own networks while still using tools like ChatGPT and Codex. The tunnel uses outbound-only HTTPS connections, so companies do not have to change inbound firewall rules. The security setup appears to lower risk by avoiding open ports and using cloud IAM roles instead of long-lived API keys. There is no confirmation yet of formal security certifications, so compliance might depend on how companies set up their own security controls. Early use seems to be for secure data access and automation inside companies, but exact adoption numbers are not available.

Okta reports Q1 revenue up 11% to $765M amid AI demand
AI News & Trends

Okta reports Q1 revenue up 11% to $765M amid AI demand

Okta's revenue for the first quarter rose 11% to $765 million, which was higher than expected. This growth appears linked to rising demand for identity services as more companies use AI agents that act as non-human users. Okta's management says they saw strong cash flow and record operating profits, and future growth may continue but at a slightly slower rate. Analysts seem mostly positive on Okta, though some want more proof that AI-linked demand will last. The company may invest more in new security and machine-identity features while aiming to keep profits high.

Investors demand new metrics for agentic coding ROI, costs
Business & Ethical AI

Investors demand new metrics for agentic coding ROI, costs

Investors are seeing many bold claims about agentic coding, but costs may rise quickly and are hard to predict. Field studies and reports suggest that most of the spending goes into input tokens and code reviews, with ratios as high as 25 input tokens for each output token. The best metrics for understanding value may include speed, quality, cost per feature, and business impact, but there are risks if companies cannot clearly explain costs and outcomes. Some signs of concern might be vague answers about token usage, no baseline data, or using only basic productivity measures.

New AI Agent Governance Checklist Updates Security, Cost Controls for CTOs
Business & Ethical AI

New AI Agent Governance Checklist Updates Security, Cost Controls for CTOs

The updated AI Agent Governance Checklist gives CTOs and security teams new ways to control security and costs as they use more autonomous coding agents. It suggests using strong tracking, clear agent identities, and real-time controls instead of only static policies. Studies point out that spending problems may happen quickly, so teams should set strict spending limits and alerts. The checklist also recommends regular reviews, strict data privacy measures, and careful management of agent permissions to prevent risks. Some risks, like personal data leaks or shared accounts, may still happen but can be reduced with these steps.

Anthropic, Parasoft guidance forms new enterprise AI code safety checklist
Business & Ethical AI

Anthropic, Parasoft guidance forms new enterprise AI code safety checklist

Enterprises using autonomous coding tools may need to follow a new checklist to make sure agent-written code is safe and meets legal and security standards. The checklist suggests steps like human review, layered testing, restricted agent permissions, and careful logging of changes. Legal and audit needs appear to require storing evidence for every action, and the rules for liability and copyright of AI-generated code are not fully settled yet. Pilot programs and graduated reviews might help reduce risk as organizations adopt these tools. These practices are meant as a starting point and can be adapted as needed.

Agentic AI shifts enterprises from SaaS seats to workflow platforms
Business & Ethical AI

Agentic AI shifts enterprises from SaaS seats to workflow platforms

Enterprises moving from seat-based SaaS to workflow platforms may face technical and organizational challenges. Agentic AI appears to work best in workflow systems that track and manage entire processes, which may explain why this shift is happening. Experts suggest starting with small, focused projects and measuring real business results early on. Good governance, careful integration planning, and clear communication with teams are recommended to avoid problems and support adoption. Studies suggest most agentic AI projects have not yet scaled fully, often due to gaps in process redesign and team alignment.

Cognition AI Raises $1B+ at $26B Valuation, Nears $500M Revenue
AI News & Trends

Cognition AI Raises $1B+ at $26B Valuation, Nears $500M Revenue

Cognition AI has raised over $1 billion at a $26 billion valuation, and its revenue run rate grew from about $37 million in May 2025 to $492 million by early 2026. The company sells an autonomous coding agent called Devin that can do multi-step tasks with little human help, but how widely Devin is used is not clear. Cognition faces competition from code assistants and AI-powered IDEs, and its future profit may depend on controlling costs and keeping users. Many AI firms, including Cognition, appear to be spending heavily, so profitability may be years away. It is also uncertain if Devin's current momentum will turn into a large and stable customer base.

Companies Expand AI Investment for Workflow Automation in 2026
AI News & Trends

Companies Expand AI Investment for Workflow Automation in 2026

Many companies plan to spend more on AI for workflow automation in 2026, with surveys suggesting 70 to 85 percent are increasing budgets. Reports say that executives see automating workflows and using real-time analytics as important new uses for AI, but there may still be challenges in moving from small pilot projects to full-scale use. Main reasons for this investment may include saving costs, filling staff shortages, and handling complex data. Some experts warn that few companies have strong systems to manage these new AI tools. While early returns on investment appear to be modest, combining AI with redesigned workflows might improve results, and most believe tracking clear metrics will help companies see real gains from automation.

Executives Prioritize AI Inventory, Governance to Avoid Failure
Business & Ethical AI

Executives Prioritize AI Inventory, Governance to Avoid Failure

Executives may be focusing more on AI inventory and governance to prevent project failures. Interviews suggest that leaders now discuss the quality of training data first and follow steps like mapping use cases to business goals, assigning clear ownership, and keeping a register of all AI systems. Common governance frameworks mentioned are the NIST AI Risk Management Framework and ISO-IEC 42001:2023. Many failures appear to come from poor data, unclear ownership, or pilot projects that never scale. There may also be resistance from some managers, suggesting that responsible AI training for staff could be important.

Google Unveils Universal Commerce Protocol, AI Checkout for Shopping
AI News & Trends

Google Unveils Universal Commerce Protocol, AI Checkout for Shopping

Google has launched new shopping tools that use AI and aim to keep shoppers on Google's own platforms. These tools may help people buy products directly in Google Search or the Gemini app, and can answer questions using a brand's own voice. Experts suggest that brands might need to improve product data so agents can find and show their items. Amazon and TikTok Shop are still strong competitors, and it appears Google wants to close the gap. It is not clear yet if shoppers and brands will use these new features enough for Google's plan to work.

Agentic AI Shoppers Could Drive $5T E-commerce by 2030
AI News & Trends

Agentic AI Shoppers Could Drive $5T E-commerce by 2030

AI shopping agents, also called agentic shoppers, may drive $190B - $385B in U.S. online sales and $3T - $5T globally by 2030, according to forecasts. These agents could handle up to one in five e-commerce dollars in the U.S. by the end of the decade. Agentic commerce means AI systems find, check, and buy products for consumers, which appears to make data quality more important than website design. Retailers might need to update product data and APIs so AI agents can easily find and pick their products. The exact growth of agentic shopping before 2030 is still uncertain, depending on factors like consumer trust and regulations.

Game studios face new AI agent copyright and liability risks
Business & Ethical AI

Game studios face new AI agent copyright and liability risks

Game studios may face new risks when using AI agents, including copyright and liability problems. AI systems might remix or copy original content without proper credit, and outputs made only by AI may not be protected by copyright. Legal experts warn that when AI uses large datasets, it becomes easier to accidentally copy parts of protected works. Because of these risks, studios are advised to use strong controls and human oversight when letting agents access curated data. Continued legal uncertainty suggests that studios should document human input and sources carefully to protect their work.