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Artificial Intelligence in Commerce
»óǰÄÚµå : 1744969
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¹ßÇàÀÏ : 2025³â 06¿ù
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2024³â¿¡ 33¾ï ´Þ·¯·Î ÃßÁ¤µÇ´Â »ó¾÷¿ë ÀΰøÁö´É(AI) ¼¼°è ½ÃÀåÀº 2024-2030³â°£ CAGR 14.6%·Î ¼ºÀåÇÏ¿© 2030³â¿¡´Â 74¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. º» º¸°í¼­¿¡¼­ ºÐ¼®ÇÑ ºÎ¹® Áß ÇϳªÀÎ E-Commerce Ç÷§ÆûÀº CAGR16.0%¸¦ ³ªÅ¸³»°í, ºÐ¼® ±â°£ Á¾·á½Ã¿¡´Â 55¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀνºÅä¾î(in-store) Ç÷§Æû ºÎ¹®ÀÇ ¼ºÀå·üÀº ºÐ¼® ±â°£Áß CAGR 10.9%·Î ÃßÁ¤µË´Ï´Ù.

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¼¼°èÀÇ »ó¾÷¿ë ÀΰøÁö´É(AI) ½ÃÀå - ÁÖ¿ä µ¿Çâ°ú ÃËÁø¿äÀÎ Á¤¸®

¿Ö ÀΰøÁö´ÉÀº Ãʰ³ÀÎÈ­, ÀÚµ¿È­, ½Ç½Ã°£ ÀÎÅÚ¸®Àü½º¸¦ ÅëÇØ »ó°Å·¡¸¦ À籸¼ºÇϴ°¡?

ÀΰøÁö´É(AI)Àº µðÁöÅÐ ¹× ¹°¸®Àû ¼Ò¸Å »ýŰè Àü¹Ý¿¡ °ÉÃÄ ´õ ½º¸¶Æ®Çϰí, ´õ ºü¸£°í, ´õ °³ÀÎÈ­µÈ »óÈ£ÀÛ¿ëÀ» °¡´ÉÇÏ°Ô ÇÔÀ¸·Î½á Àü ¼¼°è »ó°Å·¡ ȯ°æÀ» º¯È­½Ã۰í ÀÖ½À´Ï´Ù. µ¿Àû °¡°Ý Ã¥Á¤ ¹× ¼ö¿ä ¿¹Ãø, °í°´ ¿©Á¤ ¿ÀÄɽºÆ®·¹À̼Ç, Àç°í ÃÖÀûÈ­ µî AI´Â ¹æ´ëÇÑ ¾çÀÇ Á¤Çü ¹× ºñÁ¤Çü µ¥ÀÌÅÍ¿¡¼­ ½Ç¿ëÀûÀÎ ÅëÂû·ÂÀ» µµÃâÇÒ ¼ö ÀÖ´Â ÈûÀ» ºñÁî´Ï½º¿¡ Á¦°øÇÕ´Ï´Ù. ¿È´Ïä³Î ¼Ò¸Å ¹× ¼ÒºñÀÚ Á÷Á¢ ÆÇ¸Å(D2C) ¸ðµ¨ÀÇ ±Ô¸ð°¡ È®´ëµÊ¿¡ µû¶ó AI´Â °æÀï·Â Â÷º°È­, ¿î¿µ ¹Îø¼º, ¼öÀͼº È®´ë¿¡ ÇÙ½ÉÀûÀÎ ¿ªÇÒÀ» Çϰí ÀÖ½À´Ï´Ù.

°³ÀÎÈ­´Â »ó°Å·¡¿¡¼­ AIÀÇ °¡Àå µÎµå·¯Áö°í ¿µÇâ·Â ÀÖ´Â ÀÀ¿ë ºÐ¾ß Áß ÇϳªÀÔ´Ï´Ù. ¼Ò¸Å¾÷ü¿Í ÀüÀÚ»ó°Å·¡ Ç÷§ÆûÀº ¸Ó½Å·¯´×(ML) ¾Ë°í¸®ÁòÀ» Ȱ¿ëÇÏ¿© °í°´ÀÇ Çൿ, ¼±È£µµ, ±¸¸Å ÀÌ·ÂÀ» ºÐ¼®ÇÏ¿© ¸ÂÃãÇü Ãßõ »óǰ, °³ÀÎÈ­µÈ ÇÁ·Î¸ð¼Ç, ¸ÂÃãÇü ¼îÇÎ °æÇèÀ» ½Ç½Ã°£À¸·Î »ý¼ºÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ±â´ÉÀº ÀüȯÀ²°ú Àå¹Ù±¸´Ï Å©±â¸¦ Çâ»ó½Ãų »Ó¸¸ ¾Æ´Ï¶ó À¥, ¸ð¹ÙÀÏ, ¸ÅÀå ³» ÀÎÅÍÆäÀ̽º Àü¹Ý¿¡ °ÉÃÄ ¹®¸ÆÀ» °í·ÁÇÑ ÀΰÔÀÌÁö¸ÕÆ®¸¦ »ý¼ºÇÏ¿© °í°´ Ãæ¼ºµµ¸¦ ³ôÀÔ´Ï´Ù.

AI´Â ¶ÇÇÑ »óǰ űë, ºÎÁ¤ÇàÀ§ °¨Áö, 꺿 Áö¿ø, °ø±Þ¸Á ÀçÁ¶Á¤ µî ½Ã°£ÀÌ ¸¹ÀÌ ¼Ò¿äµÇ´Â ÇÁ·Î¼¼½º¸¦ ÀÚµ¿È­Çϰí ÀÖ½À´Ï´Ù. ÀÚ¿¬¾î ó¸®(NLP) ¹× ÄÄÇ»ÅÍ ºñÀü µµ±¸´Â īŻ·Î±× ÀÛ¼º, ¸®ºä ÃÖÀûÈ­, À½¼º »ó°Å·¡ °£¼ÒÈ­¿¡ »ç¿ëµÇ¸ç, ·Îº¸Æ½ ÇÁ·Î¼¼½º ÀÚµ¿È­(RPA)´Â ¼öÀÛ¾÷À¸·Î ¼öÇàµÇ´Â ¹é¿ÀÇǽº ¾÷¹«ÀÇ ºÎ´ãÀ» ÁÙ¿©ÁÝ´Ï´Ù. ¿ÀÇÁ¶óÀÎ ¼Ò¸Å¾÷¿¡¼­´Â AI¸¦ Ȱ¿ëÇÑ ºñµð¿À ºÐ¼®°ú IoT ¼¾¼­°¡ ½Ç½Ã°£ ¼±¹Ý ¸ð´ÏÅ͸µ, ¼îÇΰ´ È÷Æ® ¸ÊÇÎ, ºÐ½Ç ¹æÁö µîÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù. ÀÌ·¯ÇÑ ±â´ÉÀÇ °áÇÕÀº Æ®·£Àè¼Ç Ä¿¸Ó½º¿¡¼­ Áö´ÉÀûÀÌ°í ¹ÝÀÀ¼ºÀÌ ³ôÀº Ä¿¸Ó½º »ýŰè·ÎÀÇ ÀüȯÀ» ÃËÁøÇÕ´Ï´Ù.

¿¹Ãø ºÐ¼®, »ý¼ºÇü AI, ¸®Å×ÀÏ ¹Ìµð¾îÀÇ ÅëÇÕÀº Ä¿¸Ó½º¿¡¼­ AIÀÇ ¹üÀ§¸¦ ¾î¶»°Ô È®ÀåÇϰí Àִ°¡?

AI¸¦ Ȱ¿ëÇÑ ¿¹Ãø ºÐ¼®À» ÅëÇØ ¼Ò¸Å¾÷ü´Â °í°´ÀÇ ¿ä±¸¸¦ ¿¹ÃøÇϰí Àç°í ¼öÁØÀ» ÃÖÀûÈ­ÇÏ¸ç °¡°Ý Àü·«À» º¸´Ù Á¤È®ÇÏ°Ô °­È­ÇÒ ¼ö ÀÖÀ¸¸ç, AI ¸ðµ¨Àº °ú°Å ÆÇ¸Å ½ÇÀû µ¥ÀÌÅÍ, °èÀý¼º, ÆÇÃË ÁÖ±â, °Å½Ã °æÁ¦ ½ÅÈ£¸¦ ºÐ¼®ÇÏ¿© ¼ö¿ä¸¦ ¿¹ÃøÇϰí Á¶´Þ, ¹èºÐ, °¡°Ý ÀÎÇÏ ÀÇ»ç °áÁ¤¿¡ µµ¿òÀ» ÁÙ ¼ö ÀÖ½À´Ï´Ù. °áÁ¤¿¡ µµ¿òÀ» ÁÝ´Ï´Ù. ÀÌ·¯ÇÑ ¼±°ßÁö¸íÀ» ÅëÇØ °úÀ× Àç°í, ǰÀý, ÇÒÀÎÀ» ÁÙÀ̰í Àç°í °ü¸®ÀÇ ¼öÀͼº°ú Áö¼Ó°¡´É¼ºÀ» Á÷Á¢ÀûÀ¸·Î Çâ»ó½Ãų ¼ö ÀÖ½À´Ï´Ù.

»ý¼ºÇü AI´Â ÄÁÅÙÃ÷ Á¦ÀÛ, °í°´ Âü¿©, »óǰ °Ë»ö¿¡ ÀÖ¾î Çõ½ÅÀûÀÎ º¯È­¸¦ °¡Á®´Ù ÁÙ ¼ö ÀÖ´Â °èÃþÀ¸·Î ºÎ»óÇϰí ÀÖ½À´Ï´Ù. ¼Ò¸Å¾÷üµéÀº »óǰ ¼³¸í, À̹ÌÁö, ¿µ»ó ÄÁÅÙÃ÷, ±¤°í Ä«ÇÇ, °¡»ó ÇÇÆÃ °æÇèÀ» ÀÚµ¿À¸·Î »ý¼ºÇÏ´Â AI ÅøÀ» µµÀÔÇÏ¿© ½ÃÀå Ãâ½Ã ½Ã°£°ú Å©¸®¿¡ÀÌÆ¼ºê ¸®¼Ò½º¿¡ ´ëÇÑ ÀÇÁ¸µµ¸¦ ȹ±âÀûÀ¸·Î ÁÙÀ̰í ÀÖ½À´Ï´Ù. ´ë±Ô¸ð ¾ð¾î ¸ðµ¨(LLM)À» žÀçÇÑ Ãªº¿°ú °¡»ó ºñ¼­´Â º¹ÀâÇÑ ¹®ÀÇ¿¡ ´ëÀÀÇϰí, Á¦Ç° ±³À°À» ÃËÁøÇϸç, Àΰ£°ú °°Àº ´ëÈ­·Î ±¸¸Å °áÁ¤À» À¯µµÇÔÀ¸·Î½á ÆÇ¸Å Àü ¹× ÆÇ¸Å ÈÄ Áö¿øÀ» °­È­Çϰí ÀÖ½À´Ï´Ù.

¸®Å×ÀÏ ¹Ìµð¾î ³×Æ®¿öÅ©(RMN)´Â AI¸¦ Ȱ¿ëÇÏ¿© ÀÌÄ¿¸Ó½º Ç÷§Æû ¾ÈÆÆ¿¡¼­ Ÿ°ÙÆÃµÈ ±¤°í¸¦ ÁýÇàÇϰí ÀÖÀ¸¸ç, AI¸¦ ÆÛ½ºÆ® ÆÄƼ µ¥ÀÌÅÍ¿Í ÅëÇÕÇÏ¿© ºê·£µå´Â °íÀǵµ°¡ ³ôÀº ¼ÒºñÀÚ¿¡°Ô °ü·Ã¼º ³ôÀº ±¤°í¸¦ °ÔÀçÇϰí, ÀÔÂû Àü·«À» ÃÖÀûÈ­Çϸç, Ä·ÆäÀÎ ¼º°ú¸¦ ½Ç½Ã°£À¸·Î ÃøÁ¤ÇÒ ¼ö ÀÖ½À´Ï´Ù. AI´Â Æó¼â ·çÇÁ ¾îÆ®¸®ºä¼Ç, Å©·Î½º ä³Î ¸®Å¸°ÙÆÃ, µ¿Àû Å©¸®¿¡ÀÌÆ¼ºê ÃÖÀûÈ­¸¦ ÅëÇØ ¸®Å×ÀÏ ¹Ìµð¾î¸¦ ROI°¡ ³ôÀº ¼ºÀå µ¿·ÂÀ¸·Î ¸¸µé ¼ö ÀÖ½À´Ï´Ù. ºê·£µå ±¤°í ¿¹»êÀÌ ¼Ò¸Å¾÷ü°¡ ¼ÒÀ¯ÇÑ Ç÷§ÆûÀ¸·Î À̵¿ÇÔ¿¡ µû¶ó, AI´Â µðÁöÅÐ Ä¿¸Ó½º »ýŰè Àü¹Ý¿¡¼­ ¼öÀÍÈ­ ±âȸ¸¦ âÃâÇÏ´Â µ¥ ÇʼöÀûÀÎ ¿ä¼Ò°¡ µÇ°í ÀÖ½À´Ï´Ù.

»ó°Å·¡¿¡¼­ AI µµÀÔÀ» ÁÖµµÇϰí ÀÖ´Â »ó¾÷ ºÎ¹®°ú ¼¼°è ½ÃÀåÀº?

ÀüÀÚ»ó°Å·¡ Ç÷§Æû°ú ¼ÒºñÀÚ Á÷Á¢ ÆÇ¸Å(D2C) ºê·£µå´Â AI µµÀÔÀÇ ÃÖÀü¼±¿¡¼­ Áö´ÉÇü µµ±¸¸¦ »ç¿ëÇÏ¿© ¸¶Âû ¾ø´Â ¼îÇÎÀ» ½ÇÇöÇϰí, °í°´ È®º¸¸¦ ÃÖÀûÈ­Çϸç, ÁÖ¹® 󸮸¦ ÀÚµ¿È­Çϰí ÀÖ½À´Ï´Ù. ´ëÇü ¿È´Ïä³Î ¼Ò¸Å¾÷üµéÀº AI¸¦ µµÀÔÇÏ¿© ¿Â¶óÀΰú ¿ÀÇÁ¶óÀÎ °æÇèÀ» ÅëÇÕÇϰí, ¿¹Ãø ºÐ¼®°ú °³ÀÎÈ­ ¿£ÁøÀ» »ç¿ëÇÏ¿© µðÁöÅÐ ¸ÅÀå, ¸ð¹ÙÀÏ ¾Û, ¿ÀÇÁ¶óÀÎ ¸ÅÀå¿¡¼­ÀÇ Âü¿©¸¦ ÅëÇÕÇϰí ÀÖ½À´Ï´Ù. ±¸µ¶Çü ¸ðµ¨°ú ¸¶ÄÏÇ÷¹À̽ºµµ AI¸¦ Ȱ¿ëÇÏ¿© ÇØÁö ¿¹Ãø, ¾÷¼¿¸µ, ¸®ÅÙ¼Ç Àü·«À» ÅëÇØ Æò»ý °¡Ä¡¸¦ ³ôÀ̰í ÀÖ½À´Ï´Ù.

ÆÐ¼Ç, °¡Àü, ½Ä·áǰ ¼Ò¸Å¾÷Àº ¿ªµ¿ÀûÀÎ °¡°Ý Ã¥Á¤, ´ë·® SKU, °æÇè Áß½ÉÀÇ Âü¿©¿¡ ÀÇÁ¸Çϰí Àֱ⠶§¹®¿¡ °¡Àå Áøº¸µÈ ºÐ¾ß Áß ÇϳªÀÔ´Ï´Ù. ÆÐ¼Ç¿¡¼­´Â AI ÅøÀÌ Æ®·»µå ¿¹Ãø, »çÀÌÁî ¿¹Ãø, ½Ã°¢Àû °Ë»öÀ» °¡´ÉÇÏ°Ô Çϰí, ½Ä·áǰ¿¡¼­´Â ½Ç½Ã°£ ¸®ÇÊ, ÀÚµ¿ ÇÇÅ·, »óȲº° ÇÁ·Î¸ð¼Ç µîÀ» Áö¿øÇÕ´Ï´Ù. ·°¼Å¸® ºê·£µå´Â °³ÀÎÈ­µÈ °í°´ ÀÀ´ë, ºÎÁ¤ÇàÀ§ °¨Áö, ºê·£µå ¸í¼º¿¡ ºÎÇÕÇÏ´Â ¸ôÀÔÇü ½ºÅ丮ÅÚ¸µÀ» À§ÇØ AI¸¦ µµÀÔÇϰí ÀÖ½À´Ï´Ù.

Áö¿ªº°·Î´Â ºÏ¹Ì¿Í ¼­À¯·´ÀÌ ³ôÀº µðÁöÅÐ ÀÎÇÁ¶ó, ³ôÀº ÀüÀÚ»ó°Å·¡ º¸±Þ·ü, °­·ÂÇÑ ÅõÀÚ »ýŰè·Î ÀÎÇØ AI ¼º¼÷µµ¿¡¼­ ¼±µÎ¸¦ ´Þ¸®°í ÀÖ½À´Ï´Ù. ¾Æ½Ã¾ÆÅÂÆò¾ç(ƯÈ÷ Áß±¹, Çѱ¹, ÀϺ»)Àº ¸ð¹ÙÀÏ ¿ì¼± ¼ÒºñÀÚ, ½´ÆÛ ¾Û »ýŰè, AI ±â¹Ý ¼Ò¸Å Çõ½Å¿¡ ÈûÀÔ¾î ºü¸£°Ô ¼ºÀåÇϰí ÀÖ½À´Ï´Ù. ¶óƾ¾Æ¸Þ¸®Ä«, Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«¿¡¼­´Â ÇÉÅ×Å©¿Í ¼Ò¸Å¾÷ÀÇ À¶ÇÕ, ¸ð¹ÙÀÏ Ä¿¸Ó½º ¼ºÀå, µðÁöÅÐ ¸¶ÄÏÇ÷¹À̽º¿¡ ´ëÇÑ ÅõÀÚ°¡ AI µµÀÔ¿¡ ¹ÚÂ÷¸¦ °¡Çϰí ÀÖÀ¸¸ç, AI°¡ ¼Ò¸Å¾÷ÀÇ ÇÙ½É ¾÷¹«¿¡ ÅëÇյʿ¡ µû¶ó ¼¼°è ¼Ò¸Å¾÷üµéÀº Çõ½Å°ú ±Ô¸ð È®ÀåÀ» À¯ÁöÇϱâ À§ÇØ ºÎ¹®º° AI ¼¾Å͸¦ ¼³¸³Çϰí ÀÖ½À´Ï´Ù. ºÎ¹® °£ AI ¼¾ÅÍ ¿Àºê ¿¢¼³·±½º(AI Center of Excellence)¸¦ ±¸ÃàÇÏ´Â ¿òÁ÷ÀÓÀÌ °¡¼ÓÈ­µÇ°í ÀÖ½À´Ï´Ù.

À±¸®Àû AI, µ¥ÀÌÅÍ °Å¹ö³Í½º, AI-as-a-Service ¸ðµ¨Àº ¾î¶»°Ô ½ÃÀå Àü·«À» Çü¼ºÇϰí Àִ°¡?

AI µµÀÔÀÌ »ó°Å·¡ Àü¹ÝÀ¸·Î È®»êµÊ¿¡ µû¶ó ¾Ë°í¸®ÁòÀÇ °øÁ¤¼º, µ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã, ¼ÒºñÀÚ ½Å·Ú¿¡ ´ëÇÑ ¿ì·Á°¡ µµÀÔ Àü·«À» À籸¼ºÇϰí ÀÖ½À´Ï´Ù. ¼Ò¸Å¾÷üµéÀº GDPR(EU °³ÀÎÁ¤º¸º¸È£±ÔÁ¤) ¹× CCPA¿Í °°Àº Áö¿ª µ¥ÀÌÅÍ º¸È£ ±ÔÁ¦¸¦ ÁؼöÇϸ鼭 AI ÀÇ»ç°áÁ¤¿¡ ÀÖ¾î ¼ÒºñÀÚ µ¥ÀÌÅ͸¦ À±¸®ÀûÀ¸·Î Ȱ¿ëÇØ¾ß ÇÕ´Ï´Ù. ºê·£µå ÆòÆÇÀ» º¸È£Çϰí ÄÄÇöóÀ̾𽺠¸®½ºÅ©¸¦ ÁÙÀ̱â À§ÇØ AI ¸ðµ¨°ú »ç¿ëÀÚ ÀÎÅÍÆäÀ̽º¿¡ ¼³¸í°¡´É¼º, Åõ¸í¼º, µ¿ÀÇ °ü¸® ±â´ÉÀÌ ³»ÀåµÇ¾î ÀÖ½À´Ï´Ù.

AIaaS(AI-as-a-Service) ¸ðµ¨Àº API ±â¹Ý ÅëÇÕÀÌ °¡´ÉÇÑ ¸ðµâÇü Ŭ¶ó¿ìµå È£½ºÆÃ AI ÅøÀ» Á¦°øÇÔÀ¸·Î½á Áß¼ÒÇü ¼Ò¸Å¾÷üµéÀÇ ÁøÀÔÀ庮À» ³·Ãß°í ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Ç÷§ÆûÀ» ÅëÇØ »ç¿ëÀÚ´Â »ç³» Àü¹® Áö½ÄÀÌ ¾ø¾îµµ Ãßõ ¿£Áø, ÀÌÅ» ¿¹Ãø µµ±¸, ºñÀü ±â¹Ý üũ¾Æ¿ô ¼Ö·ç¼Ç µîÀÇ ±â´ÉÀ» ÀÌ¿ëÇÒ ¼ö ÀÖÀ¸¸ç, AIaaS Á¦°ø¾÷ü´Â ÄÁ¼³ÆÃ, ±³À°, ¸ðµ¨ °Å¹ö³Í½º ±â´ÉÀ» Á¦°øÇÕ´Ï´Ù. ÄÁ¼³ÆÃ, ±³À°, ¸ðµ¨ °Å¹ö³Í½º ±â´ÉÀ» ¹øµé·Î Á¦°øÇÔÀ¸·Î½á °í°´ÀÌ ¿î¿µ °ü¸®¸¦ À¯ÁöÇϸ鼭 ±¸ÇöÀ» °¡¼ÓÈ­ÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇϰí ÀÖ½À´Ï´Ù.

¼Ò¸Å¾÷ü, Ŭ¶ó¿ìµå Á¦°ø¾÷ü, ¸¶Å×Å© Ç÷§Æû, AI ½ºÅ¸Æ®¾÷ °£ÀÇ Àü·«Àû ÆÄÆ®³Ê½ÊÀ» ÅëÇØ ´ë±Ô¸ðÀÇ Çõ½ÅÀÌ °¡´ÉÇØÁ³½À´Ï´Ù. ÀÌ·¯ÇÑ ÆÄÆ®³Ê½ÊÀº µ¶ÀÚÀûÀÎ ¾Ë°í¸®Áò, °øµ¿ ºê·£µå °í°´ °æÇè, »ýŰ迡 ƯȭµÈ AI µµ±¸ÀÇ °øµ¿ °³¹ßÀ» Áö¿øÇϰí ÀÖ½À´Ï´Ù. °æÀïÀÌ Ä¡¿­ÇØÁü¿¡ µû¶ó Â÷º°È­´Â AIÀÇ ´É·Â¿¡¼­ °í°´ ¿©Á¤ Àü¹Ý¿¡ °ÉÃÄ AI¸¦ ¾ó¸¶³ª È¿°úÀûÀ¸·Î ¹èÄ¡, °ü¸®, ¼öÀÍÈ­ÇÒ ¼ö ÀÖ´ÂÁö¿¡ µû¶ó ´Þ¶óÁö°í ÀÖ½À´Ï´Ù.

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Global Artificial Intelligence in Commerce Market to Reach US$7.4 Billion by 2030

The global market for Artificial Intelligence in Commerce estimated at US$3.3 Billion in the year 2024, is expected to reach US$7.4 Billion by 2030, growing at a CAGR of 14.6% over the analysis period 2024-2030. E-Commerce Platform, one of the segments analyzed in the report, is expected to record a 16.0% CAGR and reach US$5.5 Billion by the end of the analysis period. Growth in the In Store Platform segment is estimated at 10.9% CAGR over the analysis period.

The U.S. Market is Estimated at US$863.3 Million While China is Forecast to Grow at 13.6% CAGR

The Artificial Intelligence in Commerce market in the U.S. is estimated at US$863.3 Million in the year 2024. China, the world's second largest economy, is forecast to reach a projected market size of US$1.1 Billion by the year 2030 trailing a CAGR of 13.6% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 13.6% and 12.4% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 10.5% CAGR.

Global Artificial Intelligence in Commerce Market - Key Trends & Drivers Summarized

Why Is Artificial Intelligence Reshaping Commerce Through Hyperpersonalization, Automation, and Real-Time Intelligence?

Artificial Intelligence (AI) is transforming the global commerce landscape by enabling smarter, faster, and more personalized interactions across both digital and physical retail ecosystems. From dynamic pricing and demand forecasting to customer journey orchestration and inventory optimization, AI empowers businesses to extract actionable insights from massive volumes of structured and unstructured data. As omnichannel retail and direct-to-consumer (D2C) models scale, AI is becoming central to competitive differentiation, operational agility, and margin expansion.

Personalization stands as one of the most visible and impactful applications of AI in commerce. Retailers and e-commerce platforms leverage machine learning (ML) algorithms to analyze customer behavior, preferences, and purchase history to generate tailored product recommendations, personalized promotions, and curated shopping experiences in real time. These capabilities not only increase conversion rates and basket sizes but also enhance customer loyalty by creating context-aware engagement across web, mobile, and in-store interfaces.

AI is also automating time-intensive processes such as product tagging, fraud detection, chatbot support, and supply chain rebalancing. Natural language processing (NLP) and computer vision tools are used to streamline catalog creation, review moderation, and voice commerce, while robotic process automation (RPA) reduces manual back-office workloads. In physical retail, AI-powered video analytics and IoT sensors enable real-time shelf monitoring, shopper heatmapping, and loss prevention. Collectively, these capabilities are driving a shift from transactional commerce to intelligent, responsive commerce ecosystems.

How Are Predictive Analytics, Generative AI, and Retail Media Integration Expanding the Scope of AI in Commerce?

Predictive analytics powered by AI is enabling retailers to anticipate customer needs, optimize inventory levels, and enhance pricing strategies with greater precision. AI models analyze historical sales data, seasonality, promotional cycles, and macroeconomic signals to forecast demand and inform procurement, allocation, and markdown decisions. This foresight helps reduce overstocking, stockouts, and discounting, directly improving profitability and sustainability in inventory management.

Generative AI is emerging as a transformative layer in content creation, customer engagement, and product discovery. Retailers are deploying AI tools to automatically generate product descriptions, images, video content, ad copy, and virtual try-on experiences-dramatically reducing time-to-market and creative resource dependency. Chatbots and virtual assistants powered by large language models (LLMs) are enhancing pre-sale and post-sale support by handling complex queries, facilitating product education, and guiding purchase decisions with human-like interactions.

Retail media networks (RMNs) are leveraging AI to drive targeted advertising within e-commerce platforms and beyond. By integrating AI with first-party data, brands can serve hyper-relevant ads to high-intent consumers, optimize bidding strategies, and measure campaign performance in real time. AI enables closed-loop attribution, cross-channel retargeting, and dynamic creative optimization-making retail media a high-ROI growth engine. As brands shift ad budgets toward retailer-owned platforms, AI becomes critical to unlocking monetization opportunities across digital commerce ecosystems.

Which Commercial Segments and Global Markets Are Leading AI Adoption in Commerce?

E-commerce platforms and direct-to-consumer (D2C) brands are at the forefront of AI adoption, using intelligent tools to deliver frictionless shopping, optimize customer acquisition, and automate fulfillment. Large omnichannel retailers are deploying AI to integrate online and offline experiences, using predictive analytics and personalization engines to unify engagement across digital storefronts, mobile apps, and brick-and-mortar locations. Subscription-based models and marketplaces are also leveraging AI to drive lifetime value through churn prediction, upselling, and retention strategies.

Fashion, consumer electronics, and grocery retail are among the most advanced segments, given their reliance on dynamic pricing, high SKU volumes, and experience-centric engagement. In fashion, AI tools enable trend forecasting, size prediction, and visual search; in grocery, they support real-time replenishment, automated picking, and contextual promotions. Luxury brands are adopting AI to deliver personalized clienteling, fraud detection, and immersive storytelling that aligns with brand prestige.

Regionally, North America and Western Europe lead in AI maturity due to advanced digital infrastructure, high e-commerce penetration, and strong investment ecosystems. Asia-Pacific-particularly China, South Korea, and Japan-is scaling rapidly, driven by mobile-first consumers, super-app ecosystems, and AI-led retail innovation. In Latin America, the Middle East, and Africa, AI adoption is being fueled by fintech-retail convergence, mobile commerce growth, and investments in digital marketplaces. As AI becomes embedded in core retail operations, global retailers are increasingly building cross-functional AI centers of excellence to sustain innovation and scale.

How Are Ethical AI, Data Governance, and AI-as-a-Service Models Shaping Market Strategy?

As AI adoption deepens across commerce, concerns around algorithmic fairness, data privacy, and consumer trust are reshaping implementation strategies. Retailers must navigate regional data protection regulations such as GDPR and CCPA while ensuring ethical use of consumer data in AI decision-making. Explainability, transparency, and consent management are being embedded into AI models and user interfaces to safeguard brand reputation and mitigate compliance risks.

AI-as-a-Service (AIaaS) models are lowering entry barriers for mid-market and niche retailers by offering modular, cloud-hosted AI tools with API-based integration. These platforms allow users to access capabilities such as recommendation engines, churn predictors, or vision-based checkout solutions without extensive in-house expertise. AIaaS providers are increasingly bundling consulting, training, and model governance features to help clients accelerate implementation while maintaining operational control.

Strategic partnerships between retailers, cloud providers, martech platforms, and AI startups are enabling innovation at scale. These alliances support joint development of proprietary algorithms, co-branded customer experiences, and ecosystem-specific AI tools. As competitive intensity rises, differentiation is shifting from AI capabilities alone to how effectively they are deployed, governed, and monetized across the full customer journey.

What Are the Factors Driving Growth in the AI in Commerce Market?

The AI in commerce market is experiencing robust growth, underpinned by rising customer expectations, data-driven business models, and the need for operational efficiency at scale. Core growth drivers include personalization, automation, dynamic pricing, visual search, and content creation-all of which improve ROI and elevate brand experience in increasingly competitive environments.

As AI capabilities mature, retailers are moving from experimental pilots to full-scale enterprise deployments. Real-time analytics, generative tools, and AI-augmented commerce platforms are reshaping how products are discovered, experiences are delivered, and value is created. The convergence of AI with edge computing, 5G, and IoT will further deepen its impact in areas such as smart retail, cashier-less checkout, and immersive shopping environments.

Looking forward, the trajectory of AI in commerce will depend on how well enterprises balance technological advancement with ethical responsibility, cost scalability, and human-centric experience design. As AI transitions from back-end optimization to front-end engagement, could it become the defining driver of intelligent, anticipatory, and emotionally resonant commerce?

SCOPE OF STUDY:

The report analyzes the Artificial Intelligence in Commerce market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:

Platform (E-Commerce, In Store); Technology (Deep Learning, Machine Learning, NLP, Other Technologies); Application (Customer Relationship Management, Supply Chain Analysis, Fake Review Analysis, Merchandising, Warehouse Automation, Product Recommendation, Fleet Management, Other Applications); End-Use (Retail, Electronics, Logistics, Food & Beverages, Other End-Uses)

Geographic Regions/Countries:

World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 42 Featured) -

TARIFF IMPACT FACTOR

Our new release incorporates impact of tariffs on geographical markets as we predict a shift in competitiveness of companies based on HQ country, manufacturing base, exports and imports (finished goods and OEM). This intricate and multifaceted market reality will impact competitors by artificially increasing the COGS, reducing profitability, reconfiguring supply chains, amongst other micro and macro market dynamics.

We are diligently following expert opinions of leading Chief Economists (14,949), Think Tanks (62), Trade & Industry bodies (171) worldwide, as they assess impact and address new market realities for their ecosystems. Experts and economists from every major country are tracked for their opinions on tariffs and how they will impact their countries.

We expect this chaos to play out over the next 2-3 months and a new world order is established with more clarity. We are tracking these developments on a real time basis.

As we release this report, U.S. Trade Representatives are pushing their counterparts in 183 countries for an early closure to bilateral tariff negotiations. Most of the major trading partners also have initiated trade agreements with other key trading nations, outside of those in the works with the United States. We are tracking such secondary fallouts as supply chains shift.

To our valued clients, we say, we have your back. We will present a simplified market reassessment by incorporating these changes!

APRIL 2025: NEGOTIATION PHASE

Our April release addresses the impact of tariffs on the overall global market and presents market adjustments by geography. Our trajectories are based on historic data and evolving market impacting factors.

JULY 2025 FINAL TARIFF RESET

Complimentary Update: Our clients will also receive a complimentary update in July after a final reset is announced between nations. The final updated version incorporates clearly defined Tariff Impact Analyses.

Reciprocal and Bilateral Trade & Tariff Impact Analyses:

USA <> CHINA <> MEXICO <> CANADA <> EU <> JAPAN <> INDIA <> 176 OTHER COUNTRIES.

Leading Economists - Our knowledge base tracks 14,949 economists including a select group of most influential Chief Economists of nations, think tanks, trade and industry bodies, big enterprises, and domain experts who are sharing views on the fallout of this unprecedented paradigm shift in the global econometric landscape. Most of our 16,491+ reports have incorporated this two-stage release schedule based on milestones.

COMPLIMENTARY PREVIEW

Contact your sales agent to request an online 300+ page complimentary preview of this research project. Our preview will present full stack sources, and validated domain expert data transcripts. Deep dive into our interactive data-driven online platform.

TABLE OF CONTENTS

I. METHODOLOGY

II. EXECUTIVE SUMMARY

III. MARKET ANALYSIS

IV. COMPETITION

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