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Hidden Costs of Generic AI: Why customisation matters
- Businesses face various issues when using generic AI without customization, leading to inefficiency and wasted resources.
- Common risks include providing inaccurate or out-of-context responses to customers, damaging brand reputation, and lacking personalized results.
- Generic AI may not align with a company's brand voice, resulting in robotic, generic responses that confuse customers.
- Using uncustomized generative AI models for marketing activities can lead to distrust among consumers due to generic and inaccurate outputs.
- Correcting generic AI outputs repeatedly wastes time and money, hindering potential improvements in customer understanding and resource utilization.
- Customizing AI models involves fine-tuning, prompt engineering, instruction tuning, Retrieval-Augmented Generation (RAG), and building from scratch using company-specific data.
- Customized AI provides accurate, brand-aligned responses, enhances customer engagement, and optimizes operational efficiency.
- Tailored AI understands brand voice, streamlines processes, offers unique experiences, and provides relevant insights for better decision-making.
- While customizing AI models may incur initial costs, the long-term benefits include reduced manual work, improved efficiency, and cost savings.
- Customized AI is essential for long-term business success, avoiding the pitfalls of generic AI and offering improved experiences for customers.
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