The impact of AI governance on consumer trust
Consumer trust in companies that use AI is falling. Only 23% of consumers trust companies to use AI responsibly with their data. The gap between adoption and governance is becoming a concrete reputational risk, as concrete as the regulatory risk that frameworks like GDPR, LGPD, and the EU AI Act already impose. This article explores […]
What AI governance tools exist for enterprises?
There are several categories of tools that cover different layers of AI governance: MLOps platforms to govern models, CASB and DLP to control access to AI tools, EDR to monitor endpoint behavior, SIEM to aggregate logs and correlate events, and GRC platforms for risk management and compliance. Most enterprise companies use more than one. What […]
What is AI governance and why does it matter for enterprises?
AI governance is the set of policies, processes, and controls that determine how a company develops, deploys, and monitors artificial intelligence systems. The goal: ensuring they operate within the legal, ethical, and security boundaries the organization has defined. This article explains what AI governance is, why it became urgent in 2026, and where to start. […]
How to Monitor AI-Created Scripts on Corporate Endpoints
The ease enabled by generative AI has created an irreversible phenomenon. Business users can now produce functional code in seconds. This speed, however, has introduced Shadow Python, a layer of invisible automations operating outside the visibility of IT and Information Security. AI-created scripts are already running on workstations across your organization. Monitoring these executions is […]
How to Govern the Use of Python in Enterprises in the Age of AI
Python is already part of the daily operations of large enterprises. It runs across data, automation, finance, marketing, and operations and increasingly in the hands of business users supported by generative AI. Python has grown faster than governance. Today, governing the use of Python in enterprises is no longer a technical best practice but a […]
Shadow AI: Data, Risks, and Governance Solutions (2026 Guide)
Artificial intelligence is no longer a futuristic bet—it has become the central engine of modern productivity. However, while companies plan to increase AI investments by 36% over the next two years, a silent and risky phenomenon is growing behind the scenes: Shadow AI. According to a recent SAP study with Oxford Economics, reported by Forbes, […]
Python+AI governance on endpoints: where to start?
Python has become the backbone of a lot of what happens inside companies: data, automation, AI, rapid integrations. At the same time, Python+AI governance on endpoints is still fragile—or nearly non-existent—in many organizations. Local scripts, notebooks “saved on the desktop,” and small AI agents end up running on workstations, VMs, and servers without real visibility […]
Python, AI and LGPD: how to prevent data leaks on endpoints?
When it comes to python lgpd, the conversation usually revolves around contracts, cloud databases, and privacy policies. But in practice, a major share of the risk lives somewhere else: Python scripts, AI-powered automations, and notebooks running directly on company endpoints. This is where “python lgpd” stops being an abstract legal discussion and becomes a very […]
AI Governance: Shadow AI and Python on Endpoints
The discussion around AI governance is no longer just theory. Today, generative AI, copilots, and local automations are already part of the daily routine of business areas, data teams, and operations. At the same time, the use of AI tools outside IT’s control is growing. This phenomenon has become known as Shadow AI. That’s where […]