Making Smart Use of AI in Your Business
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Mastercard developed an AI-powered tool that watches social media trends in real-time. Because it caught those trends early, their marketing campaign engagement jumped by over 40%, and they saved almost a third of their costs. If AI can do that for a giant like Mastercard, think about how it could transform your marketing and daily operations. [Source]
These days, AI pops up in almost every business chat. But the real question isn’t just “Can we use AI?” It’s more like, “Where does AI actually help us — and how do we use it the right way to create real value?”
Busting Some Common AI Myths
Before you dive in, let’s clear up a few things that often stop businesses from using AI:
- AI is too expensive or complicated. Not really. Many ready-to-use AI tools are available that can handle common tasks. You only need custom AI if you face really unique problems.
- You need huge amounts of data. Nope! Even small, well-organized datasets can help AI do useful things like tagging, predicting, or searching.
- AI will take people’s jobs. Actually, the right AI takes over boring, repetitive work so your team can spend time being creative and building relationships.
- AI works like magic right out of the box. Not exactly. You need clear goals and regular checks, or AI might make mistakes or show biases.
Where AI Fits in Your Work
AI shines when it handles repetitive, time-consuming tasks that don’t need human judgment — while letting humans stay in control.
Ask yourself:
- What repetitive tasks eat up your team’s time?
- Where could automation speed things up or spark creativity?
Here are some easy ways AI can help:
- Smart sorting and routing: AI can automatically sort emails or support tickets by urgency so your team can respond faster and keep customers happy.
- Auto-tagging and classification: AI can label and organize your documents or content, cutting mistakes and saving time.
- Personalized recommendations: AI suggests products or content based on what customers like, improving their experience and boosting sales — plus, being open about it builds trust.
- Early problem detection: AI spots unusual activity quickly, helping you prevent fraud or costly errors before they happen.
Custom vs. Plug-and-Play AI: What’s Right for You?
Not every business needs a custom AI model. Consider plug-and-play tools when:
- Your problem is common and well understood (like invoice processing or language translation).
- Speed is a priority.
- Moderate accuracy is acceptable.
Go for custom AI when:
- Your problem or data is unique and mission-critical.
- Accuracy and control matter a lot.
- You face specialized or niche challenges.
Custom AI requires ongoing monitoring to catch bias, errors, or unintended effects.
Custom vs. Plug-and-Play AI: What’s Right for You?
You don’t need a full data science team right away, but you do need:
- Clear business goals: Instead of “We want AI,” aim for something measurable like “Cut support ticket triage time by 30% to reduce costs and improve loyalty.”
- Relevant, clean data: This could be user actions, documents, or responsibly gathered customer feedback.
- A way to measure success: Define what success looks like — speed, accuracy, cost savings, customer satisfaction — and track it over time.
- A feedback loop: AI is not “set and forget.” Let users report issues, and regularly review and improve the system.
Common Pitfalls to Watch For
AI promises a lot but comes with risks:
- Don’t rely on AI alone for critical decisions — always have humans review results.
- AI can reflect bias in its training data, which can harm your brand and customers.
- Beware of hidden costs like ongoing monitoring, data upkeep, and updates.
- Respect data privacy and comply with relevant laws.
When choosing an AI vendor, ask:
- How do you handle data privacy and security?
- What safeguards prevent or detect bias?
- How easy is it to override or correct AI decisions?
- What ongoing support do you offer?
AI in Practice: Real Examples from Our Team
AI isn’t just theory for us — it’s something we’ve put into practice to solve real problems for our clients. Here are a few examples:
- Content Moderation in Group Chats and Social Feeds: We built AI systems that automatically detect and filter out inappropriate or harmful content, helping keep communities safe and positive without slowing down user engagement.
- Audio Classification for Smart Devices: For a smart health device, we leveraged on-device Machine Learning model to classify snore sounds. When snoring is detected, the app sends Bluetooth signals to trigger helpful actions, improving users’ sleep quality.
- Document Summarization in Claims Handling: We created an AI-powered answering assistant that reads and summarizes documents in insurance claims apps. It helps adjusters quickly get the info they need, speeding up decisions and improving customer experience.
These examples show how AI can be tailored to fit unique challenges and deliver tangible benefits — whether it’s making communication safer, enhancing smart devices, or boosting workflow efficiency.
Start Smart, Start Responsible
AI isn’t just for tech giants. With clear goals and responsible use, it can help businesses of all sizes work smarter and delight customers. Start small, measure impact, and build from there.