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»ý¼ºÇü AIÀÇ ¼ºÀå ±âȸGrowth Opportunities in Generative AI |
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Á¤º¸Åë½Å±â¼ú(ICT) »ýŰè´Â »ý¼ºÇü AI(GenAI) ´öºÐ¿¡ Å« º¯ÈÀÇ Á¶ÁüÀ» º¸À̰í ÀÖÀ¸¸ç, GenAI¸¦ Ã¥ÀÓ°¨ ÀÖ°Ô È°¿ëÇÏ¸é ±â¾÷Àº »õ·Î¿î ¼öÀÍ¿øÀ» âÃâÇϰí, Çõ½ÅÀûÀÎ ¼Ö·ç¼ÇÀ» °³¹ßÇϸç, »ç¿ëÀÚ¿Í °í°´¿¡°Ô °³ÀÎÈµÈ °æÇèÀ» Á¦°øÇÒ ¼ö ÀÖ½À´Ï´Ù. °³ÀÎÈµÈ °æÇèÀ» Á¦°øÇÒ ¼ö ÀÖ½À´Ï´Ù.
±â¾÷µéÀº ÁÖ·Î ÀºÇà/±ÝÀ¶¼ºñ½º/º¸Çè, Á¦Á¶, ÇコÄÉ¾î µî ¿©·¯ »ê¾÷ ºÐ¾ß¿¡¼ ¾÷¹« È¿À²¼ºÀ» ³ôÀÌ°í »ý»ê¼ºÀ» Çâ»ó½Ã۱â À§ÇØ GenAI¸¦ µµÀÔÇϰí ÀÖ½À´Ï´Ù. Frost & SullivanÀº °í°´ ¼ºñ½º ¹× Áö¿ø, IT ÇÁ·Î¼¼½º, ¿µ¾÷ ¹× ¸¶ÄÉÆÃ µî ¹Ýº¹ÀûÀÌ°í °¡Ä¡°¡ ³·Àº ¾÷¹«¿Í È¿À²¼ºÀ» ³ôÀÌ°í °í°´ °æÇèÀ» °³¼±Çϱâ À§ÇØ µµÀÔÀÌ ÁøÇàµÇ°í ÀÖ´Ù°í º¸°í ÀÖ½À´Ï´Ù.
±×·¯³ª ÀÌ·¯ÇÑ °¡´É¼ºÀÇ ¹°°á¿¡´Â µµÀüÀÌ µû¸£´Âµ¥, AI ¾Ë°í¸®ÁòÀÇ ÆíÇ⼺°ú AI°¡ »ý¼ºÇÑ ÄÁÅÙÃ÷ÀÇ ¾Ç¿ë °¡´É¼º¿¡ ´ëÇÑ À±¸®Àû °í·Á´Â À±¸®Àû ÇÁ·¹ÀÓ¿öÅ©ÀÇ °³¹ßÀÌ ÇÊ¿äÇÕ´Ï´Ù. ¶ÇÇÑ, °í¿ë Àüȯ°ú ¸ðµ¨ Ãâ·Â¿¡ ´ëÇÑ ¼³¸í °¡´É¼º ºÎÁ·¿¡ ´ëÇÑ ¿ì·Á´Â GenAI µµÀÔ¿¡ °É¸²µ¹ÀÌ µÉ ¼ö ÀÖ½À´Ï´Ù.
Generative AI Advancements Driving Transformative Growth Opportunities
The information and communication technology (ICT) ecosystem is on the cusp of a major transformation thanks to Generative AI (GenAI), as this powerful technology opens new possibilities. Responsible use of GenAI can help companies generate new revenue streams, develop innovative solutions, and provide users and customers with personalized experiences.
Businesses are primarily looking to adopt GenAI to drive operational efficiency and improve productivity across several industry sectors, such as banking, financial services, and insurance; manufacturing; and healthcare. Frost & Sullivan has observed that adoption is high for repetitive, low-value tasks as well as to enhance efficiency and boost customer experiences, such as customer service and support, IT processes, and sales and marketing.
However, this wave of possibilities comes with challenges. Ethical considerations surrounding biases in AI algorithms and potential misuse of AI-generated content necessitate the development of ethical frameworks. Additionally, concerns around job displacement and lack of explainability for model outputs may represent obstacles to GenAI adoption.