{"id":49,"date":"2026-08-27T16:30:34","date_gmt":"2026-08-27T21:30:34","guid":{"rendered":"https:\/\/cyberdefendconsultants.com\/resources\/?p=49"},"modified":"2026-08-27T16:30:34","modified_gmt":"2026-08-27T21:30:34","slug":"how-business-leaders-can-manage-ai-power-user-risk","status":"publish","type":"post","link":"https:\/\/cyberdefendconsultants.com\/resources\/how-business-leaders-can-manage-ai-power-user-risk\/","title":{"rendered":"How Business Leaders Can Manage AI Power User Risk"},"content":{"rendered":"

Most small and midsized businesses have accepted that employees use generative AI. They draft customer communications, summarize meetings, research prospects, troubleshoot spreadsheets, and write code. Management often responds by focusing on the most visible tools: approve or restrict ChatGPT, Microsoft Copilot, Claude, or Gemini.<\/p>\n

That is necessary, but it may miss where risk is concentrated.<\/p>\n

Research from Akamai suggests the top 5% of AI users interact with AI models 12 times more often than the bottom half of employees. The average AI conversation lasts about five prompts; power users regularly conduct exchanges of 18 prompts or more.<\/p>\n

Long, iterative conversations are more likely to include internal context, documents, code, customer details, operational problems, and follow-up instructions.<\/p>\n

For an SMB, the highest-risk AI user is not necessarily careless. It may be a highly capable employee who has made AI central to the job: an operations manager automating reporting, a salesperson building proposal workflows, a developer relying on an AI coding assistant, or a finance employee using AI to interpret accounting exports.<\/p>\n

Business leaders need to know which workflows now depend on AI, what information those workflows expose, and who controls the tools involved.<\/p>\n

The risk extends beyond major AI platforms<\/h2>\n

A company can buy a managed AI product, require single sign-on, and still have substantial exposure elsewhere. Employees often use personal accounts, free subscriptions, browser plug-ins, AI-enabled SaaS products, and coding extensions that never pass through IT review.<\/p>\n

Akamai found that 47.11% of enterprise AI conversations occurred through personal identities rather than corporate-managed accounts. More concerning, 14.4% used corporate email addresses connected to personal freemium subscriptions.<\/p>\n

That can create a misleading sense of control. The employee is identifiable through a business email address, but the account may not be covered by the organization\u2019s contract, retention policies, administrative controls, or data-use commitments. Sensitive information entered into prompts may be handled under consumer terms and, depending on the service, could be eligible for model training.<\/p>\n

This is a governance problem, not simply an employee-policy problem. If the approved tool is slow, limited, unavailable for a particular task, or missing a useful feature, capable employees will find alternatives. A blanket ban rarely changes that incentive. It just drives usage further out of view.<\/p>\n

The practical objective is to provide a usable, approved path for legitimate work while making unmanaged alternatives harder to use with company data. For many SMBs, that starts with a short list of approved AI services, corporate accounts protected by single sign-on and multifactor authentication, and clear rules for what may not be submitted to public or personal AI tools.<\/p>\n

Those categories should be concrete: customer records, nonpublic financial information, credentials and API keys, source code, contracts, employee data, security incident details, and proprietary operational documents. Employees should not need a legal memo to understand the boundary.<\/p>\n

Extensions turn convenience into access<\/h2>\n

Browser and integrated development environment (IDE) extensions deserve special attention. These add-ons can summarize web pages, draft messages, analyze data, assist with coding, or connect AI capabilities to everyday work. They are also often granted broad permissions, including access to web sessions, clipboard content, local files, browser activity, or cloud applications.<\/p>\n

Akamai found that 17.7% of employees at midsize enterprises used at least one AI extension, compared with 9.53% at larger organizations. Nearly three-quarters requested high or critical permissions, and 16.31% contained known vulnerabilities\u2014higher than the rate across browser extensions generally.<\/p>\n

For a smaller company, a single risky extension on a finance, sales, executive, or developer workstation can matter more than an abstract percentage. An extension with access to an active browser session may see more than the employee realizes, potentially exposing authenticated cloud applications, internal data, session tokens, or proprietary code.<\/p>\n

This is also where newer attacks become more than theoretical. A compromised or malicious coding extension can steal keys or source code. A malicious web page can contain hidden instructions intended to manipulate an AI agent browsing or acting on the user\u2019s behalf. Attackers are increasingly targeting the AI assistant as a route into information and systems, not only trying to trick the human user.<\/p>\n

That does not mean every AI extension is dangerous. It means extensions should be treated as software with meaningful access, not harmless productivity widgets.<\/p>\n

Concentrate controls where dependence is greatest<\/h2>\n

SMBs do not need an enterprise-scale AI security program to materially reduce exposure. They need visibility and prioritization.<\/p>\n

Start by identifying the teams and individuals using AI most intensively. Do not approach this as a search for policy violators. Ask which tasks they use AI for, which tools are involved, whether business data is entered into prompts or uploaded, and whether the tool can take actions beyond generating text.<\/p>\n

A workflow that drafts generic marketing copy presents a different risk from an AI agent connected to inboxes, customer systems, repositories, or financial data.<\/p>\n

Establish a lightweight approval process for AI tools and extensions. It must be fast enough that employees will use it. The review should answer a few high-value questions:<\/p>\n