تحلیل چالش‌های یکپارچه‌سازی هوش مصنوعی و مدیریت ارتباط با مشتری
محورهای موضوعی : طراحی یک برنامه بازاریابی عمومی
شیروان کیوانی
1
,
مجتبی حیدری
2
,
رضا رستم زاده
3
1 - دانشجو/ دانشگاه آزاد اسلامی واحد ارومیه
2 - عضو هیات علمی
3 - دانشیار گروه مدیریت، واحد ارومیه، دانشگاه آزاد اسلامی، ارومیه، ایران
کلید واژه: چالش, ارتباط با مشتری, هوش مصنوعی, یکپارچه‌سازی,
چکیده مقاله :
ادغام هوش مصنوعی در حوزه مدیریت ارتباط با مشتری (CRM) دارای پتانسیل چشمگیری برای ارتقای کارایی سازمانی است. این فناوری نوین می‌تواند به شرکت‌ها در پیش‌بینی نیازها و ترجیحات مشتریان، بهینه‌سازی فرآیندها، ارائه خدمات شخصی‌سازی‌شده و بهبود تجربه مشتری کمک کند. با این حال، برای دستیابی به یک یکپارچه‌سازی موفق هوش مصنوعی و مدیریت ارتباط با مشتری، شرکت‌ها باید چالش‌ها و پیچیدگی‌های ویژه‌ای را که ناشی از ماهیت متمایز فرایندهای مدیریت ارتباط با مشتری است، مدنظر قرار دهند. هدف این پژوهش، شناسایی چالش‌هایی است که سازمان‌ها در طول مراحل مختلف ادغام هوش مصنوعی در مدیریت ارتباط با مشتری، از کشف اولیه تا پایداری نهایی، باید بر آن‌ها غلبه کنند. با توجه به تخصص‌های چندگانه مورد نیاز در این حوزه شامل هوش مصنوعی، مدیریت ارتباط با مشتری، علم داده و مدیریت کسب‌وکار، رویکرد تحقیقاتی انتخابی، مصاحبه‌های کیفی با خبرگان متعددی از این زمینه‌ها است. در این تحقیق، ده چالش خاص مرتبط با مدیریت ارتباط با مشتری مبتنی بر هوش مصنوعی شناسایی و در چهار مرحله پیاده‌سازی هوش مصنوعی (کشف، توسعه، پیاده‌سازی و پایداری) دسته‌بندی شده‌اند. یافته‌های این تحقیق به درک تجربی فرآیند یکپارچه سازی هوش مصنوعی و مدیریت ارتباط با مشتری کمک می‌کند و چشم‌انداز بلندمدت از به‌کارگیری هوش مصنوعی در روابط با مشتری ارائه می‌دهد. این مطالعه پایه و اساسی را برای بررسی فعالیت‌ها و قابلیت‌های ضروری جهت مدیریت چالش‌های یکپارچه‌سازی هوش مصنوعی و مدیریت ارتباط با مشتری فراهم می‌آورد و سؤالات اساسی را برای مدیرانی که قصد ورود به این حوزه را دارند، مطرح می‌کند.
The integration of artificial intelligence (AI) in the field of customer relationship management (CRM) has tremendous potential to enhance organizational efficiency. This novel technology can help companies in predicting customer needs and preferences, optimizing processes, delivering personalized services, and improving the customer experience. However, to achieve a successful integration of AI and CRM, companies need to consider the unique challenges and complexities arising from the distinct nature of CRM processes. The objective of this research is to identify the challenges that organizations must overcome during the different stages of integrating AI into CRM, from the initial discovery to the final sustainability. Given the multiple areas of expertise required in this domain, including AI, CRM, data science, and business management, the chosen research approach involves qualitative interviews with multiple experts from these fields. In this study, ten specific challenges related to AI-based CRM have been identified and categorized across the four stages of AI implementation (discovery, development, deployment, and sustainability). The findings of this research contribute to an empirical understanding of the process of integrating AI and CRM, and provide a long-term perspective on the application of AI in customer relationships. This study lays the groundwork for examining the essential activities and capabilities required to manage the integration challenges of AI and CRM, and raises fundamental questions for managers who intend to venture into this domain.
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