14/03/2024
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AI: Can you avoid the risks it carries?
Are there risks to AI? Absolutely.
While some predict end-of-the-world scenarios, businesses face less extreme but very real dangers.
For instance, consider the area of content creation. Generative AI poses several risks, primarily regarding trustworthiness. You rely on AI to explain topics accurately. However, can you completely trust it? The answer is likely a qualified no. Since AI content depends entirely on its sources, this creates validity questions for readers.
Additionally, organizations must ensure they possess the rights to any AI-generated video, text, or images. You must ask: could this material infringe on copyright laws?
Furthermore, sectors like recruitment actively use AI. However, research suggests bias often infiltrates AI decisions due to flawed source data. This bias extends beyond hiring. It can taint marketing decisions or even skew medical and legal recommendations.
Consequently, AI requires monitoring. Humans must review outputs to improve accuracy. Unfortunately, this necessary step may reduce the efficiency AI promises.
Finally, consider compliance. AI tools like ChatGPT do not necessarily prioritize regulations. Many countries and US states now enforce strict data security laws to protect Personal Information. Since violations often carry civil penalties—or significant fines under the GDPR, negligence is costly.
If you are considering stepping into AI, your MSP can provide guidance. Our recent list bears repeating: Seven ways an MSP can help you approach an AI solution.
Step 1: Assess potential uses of AI. First, your MSP should have a solid understanding of your entire business and how AI might contribute. They can help you start with small steps and move forward from there.
Step 2: Understand your KPIs and organizational goals. Before jumping in and adopting AI just because it is available, evaluate your KPIs. Ask yourself: where do you perceive you need a boost?
Step 3: Propose a possible range of AI solutions. An MSP will know the variety of applications available. Therefore, they can lead you to select those most appropriate for your goals. Remember, these tools must directly assist KPI improvement.
Step 4: Estimate the solution’s ROI. Crucially, measurement is important because you cannot do everything. So, identify each potential AI solution’s ROI. As mentioned above, avoid treating AI as just a trendy tool to adopt without reason.
Step 5: Ensure compliance. For example, consider standards like HIPAA, PCI, HITRUST, ISO27001, SOC1, and SOC2. Since AI is a powerful and potentially intrusive tool, compliance is consequently critical.
Step 6: Implement the solution. Next, an MSP can implement the solution for you. Most business owners lack the resources available for what can be a time-intensive project.
Step 7: Manage tool-related risks. Finally, monitor your systems to ensure your outcomes with AI are accurate, trustworthy, defensible, and transparent. As previously noted, you must follow best practices to meet regulations.
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