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, 8 out of 10 leaders in Brazil are alarmed by employees using AI tools without IT approval.
This article dives into the causes of the phenomenon, the hidden risks, and why governance tools like Sentinel are the only viable response.
What Is Shadow AI?
Shadow AI (or “Parallel AI”) happens when employees use AI tools without the company’s knowledge or supervision.
It is driven by a behavior known as BYOAI (Bring Your Own AI).
According to the analysis:
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75% of professionals already use AI at work.
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Most prefer their own free tools over corporate solutions (often unavailable or slow).
The Root Cause: Daniel Lázaro (Accenture) sums it up well: “Employees don’t use Shadow AI out of malice, but in pursuit of efficiency.” They want to solve problems now—not wait for bureaucracy.
The Brazilian Landscape
Brazil is in a fast-paced stage of digital maturity, which paradoxically increases vulnerability. Forbes/SAP data shows a high-pressure scenario:
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Prevalence: 66% of Brazilian companies admit Shadow AI happens frequently.
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Integration: AI already supports 23% of corporate tasks in the country, and is expected to jump to 40% by 2027.
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Confidence: Although 68% of companies claim they are “prepared,” 70% distrust their own ability to integrate data securely.
The Real Risks of “Invisible AI”
The danger of Shadow AI isn’t the technology itself—it’s where your company’s data ends up.
When people use public tools without an enterprise confidentiality contract, the risks become critical:
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Intellectual Property Leakage: Pasting a sales strategy or source code into a public chatbot can effectively train your competitor’s model.
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LGPD Violations: Sensitive customer data leaves the company’s secure perimeter with no trace.
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Data Silos: Each department uses a different AI tool, creating conflicting and decentralized information.
The Technological Blind Spot: Why AI “Speaks” Python
To govern Shadow AI, you need to understand how it works in practice. Modern AI doesn’t live only on websites like ChatGPT—it is built and executed on Python.
Automation scripts, LLM integrations, and autonomous agents are, in most cases, Python code running quietly on employees’ computers.
The risk lies in traditional monitoring: if your security team focuses only on network traffic (URLs), it ignores what happens inside script execution.
This Python “blind spot” allows sensitive data to be processed and sent to external AI tools without leaving traces in common logs.
Why Banning Doesn’t Work
Many CISOs’ instinctive reaction is to block access. But experts agree that firewalls will lose this war.
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Ubiquity: AI is already embedded into browsers and text editors.
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Culture: If the company blocks it, employees use 4G or personal phones to keep producing.
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Innovation: Total blocking kills the discovery of new use cases that generate profit.
The solution is not blind blocking—it’s managed innovation.
The Solution: Active Governance with Sentinel
Because AI shows up through code, effective governance must operate at the execution layer. This is where Sentinel stands out, built on three core pillars:
1. Full Visibility (Discovery)
You can’t protect what you can’t see. Sentinel maps the digital environment to identify which AI tools are being used, by whom, and how often.
It brings AI out of the shadows and into audit visibility.
2. Monitoring and Data Loss Prevention (DLP)
Sentinel doesn’t try to “guess intent.” It brings Python + AI usage into governance through risk signals, policy-based controls, and traceable evidence.
In practice, it enables IT and Security to:
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identify execution patterns associated with risk (e.g., network libraries, external integrations, access to sensitive data, calls to AI services, database connections, vulnerable dependencies);
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classify and prioritize occurrences based on severity and context (what is running, where, and why it matters);
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enforce policies and controls to guide and restrict off-guideline executions (e.g., alert, log, block unauthorized runs, require sanctioned environments);
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generate auditable evidence (inventory + compliance trail + executive reports) to support audits and decision-making.
3. Safe Enablement
Instead of “No,” Sentinel enables “Yes”—but safely.
It enforces compliance policies in real time, allowing the company to adopt AI agility without compromising corporate integrity.
Practical Recommendations for Leaders
Based on the Forbes study and Sentinel’s capabilities, here’s the path to AI maturity:
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Don’t ignore it—manage it: Assume Shadow AI already exists. Use Discovery tools to measure the real scale of usage.
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Offer secure alternatives: Provide corporate sandbox environments where data won’t leak into public training.
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Implement governance: Use tools that automate oversight, like Sentinel—the first Python+AI monitoring agent already operating in production environments.
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Train on ethics and data: Teach employees that pasting an industrial secret into ChatGPT is as serious as posting it on social media.
How Does Sentinel Solve What the Firewall Can’t?
A firewall looks at the destination (the AI website). Sentinel looks at the origin (the Python script on the endpoint). That allows you to identify leakage before it even hits the network.
Sentinel was designed specifically for this “Agents and Automations” scenario. It acts as an endpoint governance layer, allowing you to:
✅ Discover the Invisible: Automatic inventory of Python scripts and agents running locally (where the firewall is blind).
✅ Map Real Risks: Identify exposed credentials or insecure data flows inside code.
✅ Enable Safe BYOAI: Let teams use the best tools—but under monitoring and clear compliance guidelines.
Conclusion
Shadow AI is a symptom of a workforce hungry for innovation. Brazilian companies that try to suffocate this demand will fall behind.
The secret—backed by the numbers—is investing in robust governance. With Sentinel, it’s possible to turn fear of the unknown into a measurable, secure competitive advantage.
👉 Learn more about Sentinel: https://www.botcity.dev/en/sentinel-4
