A recent study suggests that prompting AI models like ChatGPT in a stern or demanding tone may lead to improved performance in factual question answering. Researchers found that prompts using assertive language—such as "Think step-by-step and get this right"—significantly boosted accuracy compared to neutral or polite tones. While the technique enhances outcomes in controlled tests, it may foster negative habits in real-world interactions and raise ethical concerns about user behavior toward AI systems.
For businesses leveraging AI or Machine Learning models, prompt engineering plays a critical role in maximizing model performance. This insight underscores the importance of not just model training, but also how end-users interact with AI in production environments. A holistic approach to AI deployment includes optimizing both the backend algorithms and frontend UX design to maintain high user satisfaction and ethical standards.
In the context of marketing and martech, this research offers a compelling use-case. Brands can improve chatbot accuracy during high-stakes interactions—such as high-value customer queries or sales conversions—by training models on assertive prompt patterns or utilizing predefined prompt templates. Collaborating with an AI consultancy or AI agency offers an opportunity to co-create custom AI models tailored to brand tone and user expectations while preserving responsible AI engagement practices.
AI experts and strategists working within CRM ecosystems, like HolistiCrm, can apply these findings to boost AI-driven customer support or lead qualification tools. The key is to balance performance gains with a customer-first, emotionally intelligent interaction model.