AI touches nearly every corner of the modern enterprise. It dials up efficiency, automation, and organizational intelligence. Yet, the technology also introduces risks — including the potential for misuse, abuse, and data leakage — without AI security policies.
“Most SMBs are unaware of the capabilities of today’s AI models,” said Chris Ploessel, president of Aliso Viejo, CA-based RedNight Consulting. “They don’t realize that even if they haven’t purchased AI tools, they are at risk because employees may use free publicly available tools.”
Chris Ploessel
The upshot? MSPs and MSSPs can play a key role in helping clients adopt and integrate AI into their businesses. One way to do that is to establish relevant security policies that surround the use of the technology. “Employees must know what is allowed and what isn’t allowed,” Ploessel insisted. “Written policies surrounding AI are essential.”
Policy Matters
As MSPs explore opportunities with both public and private AI models, it’s vital to understand how data privacy, cybersecurity, and compliance issues intersect with AI — and how they potentially change the stakes for clients.
One thing that makes AI risky is that it’s remarkably easy for sensitive data to land in an AI system. That’s particularly true of a proprietary large language model (LLM) that runs chatbots and other systems. It can include payroll data, legal records, intellectual property (IP), and proprietary customer data.
When tapping into the benefits of AI, many SMBs overlook the potential negative impact on their businesses, cautioned Eric Long, president of TeraCloud, an IT services provider with offices in Texas, Florida, and Oklahoma. This can include financial harm, reputational damage, and fines.
Consequently, policies must focus on ways to use AI ethically, safely, and responsibly. The goal is to maximize both business opportunities and protections. This requires a deep understanding of how people will access the technology and what constitutes appropriate use cases.
Eric Long
“There is a need to label what data is private, who owns the data, and which groups have access to data,” Ploessel explained. This extends to both customer and employee data.
At that point, it’s possible to establish AI policies that determine which data winds up in a proprietary LLM — and what can flow out of it. Notably, an organization can decide who has access rights to a particular system and how they can use it and share it.
Policies like these curtail the risk of an employee spilling proprietary data into a public AI model.
Model Citizens
There are five core areas at the center of best practice AI security policies that experts recommend organizations adopt:
- Data privacy safeguards. These policies focus on how an organization collects, stores, processes, shares, and retains data across systems and vendors. It’s vital to consider regulations such as GDPR, HIPAA, and CCPA.
- Data integrity and accuracy. Governance standards determine how an organization sources, cleanses, validates, and reuses data. Effective policies minimize the risk of biased or incorrect AI predications and declarations.
- Ethical AI usage. These rules involve critical issues such as fairness, transparency, model explainability, and accountability. They cover potential risks such as discrimination and ensure that decisions are explainable.
- AI security and incident response. This framework protects AI models, data, and infrastructure from cyberattacks. It includes provisions for security audits, patch management, risk assessments, and training requirements.
- IP and data ownership issues. These policies cover who owns the data that potentially goes into a model. It may include rules about data sharing, licensing, and proprietary AI technology ownership.
AI Rules
AI will evolve and MSPs can play a pivotal role in keeping systems and data safe. This includes updating security measures, staying informed about the latest AI trends, and establishing strong and trusted connections with clients. The latter is important to cater to clients’ specific needs — and upsell, when appropriate.
MSPs should develop a template that guides clients through the process of developing AI security policies, Ploessel suggested. For example, he introduced an AI starter package that delivers 10 licenses for a fixed project fee. This allows a client to get up and running with AI — and RedNight Consulting will develop appropriate policies, safeguards, and training.
By offering a holistic set of AI security services — including writing policies — MSPs and MSSPs can help SMBs navigate the increasingly complex world of AI. This will help them ensure that clients are well-positioned for future success.
It’s a chance MSPs shouldn’t pass up, Ploessel said. “There is a significant opportunity to help SMBs get on track with AI.”
Image: iStock
