One Problem, Different Answers: How to Set Up AI to Provide Customized Support Based on Employee Position?

The same question, two completely different answers. This is not an AI error, but the ultimate expression of AI evolution—providing the most relevant and useful customised support based on the user's role. For resource-limited, time-pressed Hong Kong SMEs, this kind of "tailor-made" AI Rapid Development capability is precisely the crucial step from being "usable" to becoming "indispensable".

Why is "One-Size-Fits-All" AI Support Not Enough for SMEs?

Many AI tools currently on the market tend to provide a standardised, universal answer. For general inquiries (e.g., "Help me write a leave email"), this might suffice. But when AI is truly integrated into the core operations of a business, the drawbacks of "one-size-fits-all" become apparent:

1. Information Noise and Efficiency Bottlenecks: A junior clerk does not need to know the company's overall profit forecast, and the CEO does not want to be overwhelmed by trivial customer complaint details. When AI provides excessive irrelevant information, colleagues need to spend extra time filtering and digesting it, which actually reduces work efficiency.
2. Serious Data Security Risks: Internal company data, such as salaries, core client lists, profit margins, and future development strategies, are highly sensitive trade secrets. If colleagues of any rank can easily access this information through AI, the consequences could be unimaginable. An AI that doesn't know how to "provide information based on the person" could easily become the biggest security vulnerability within the enterprise.
3. Missing Decision-Making Opportunities: Data itself has no value; the value lies in the insights extracted from the data. A sales manager needs not just sales figures, but also needs to know which regions have growth potential and which product mix yields the highest profit. A general-purpose AI may only report numbers but fail to provide strategically valuable suggestions, causing management to miss the best decision-making opportunities. You can refer to our article: ChatGPT Can't Write Your "Exclusive Quotation": The Decisive Differences Between General AI and Enterprise AI.

Practical Application Scenarios: How Does AI "Tailor-Make" Answers for Different Roles?

Let's return to the initial "Smart Coffee Machine" sales question and deconstruct how AI provides precise support for different positions:

Technical Core: How to Configure AI to Achieve "Role-Based" Support?

Achieving this intelligent, customised support isn't as simple as buying an off-the-shelf AI software. It requires a rigorous and meticulous technical architecture behind the scenes. The expert team at Frasertec Limited typically builds such systems for SME clients through the following key steps:

How Can Hong Kong SMEs Take the First Step?

Reading this, you might think the technical barrier is high. In reality, applying this advanced AI strategy is not out of reach for SMEs. The key lies in taking gradual steps and seeking assistance from professional partners.

• Start Small: There's no need to rush to deploy company-wide all at once. You can start by selecting a pilot department where the pain points are most obvious and data is relatively concentrated (such as the Sales Department or Customer Service Department).
• Conduct a Data Inventory: Before introducing AI, first gain a clear understanding of what data your company has, where it's stored, its quality, and who has access to it. A clear data blueprint is half the battle.
• Seek a Professional Technology Partner: Building this type of customised AI system requires a combination of knowledge in cloud technology, database integration, AI model fine-tuning, and cybersecurity. Partnering with an experienced IT services company like Frasertec Limited can help you plan the most business-needs-aligned AI Rapid Development solution, avoiding detours and ensuring data security.