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Artificial Intelligence of Things
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2024³â¿¡ 141¾ï ´Þ·¯·Î ÃßÁ¤µÇ´Â »ç¹°ÀΰøÁö´É(AIoT) ¼¼°è ½ÃÀåÀº 2024³âºÎÅÍ 2030³â±îÁö CAGR 24.0%·Î ¼ºÀåÇÏ¿© 2030³â¿¡´Â 513¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÌ º¸°í¼­¿¡¼­ ºÐ¼®ÇÑ ºÎ¹® Áß ÇϳªÀÎ AI ¼ÒÇÁÆ®¿þ¾î/Ç÷§ÆûÀº CAGR 20.8%¸¦ ±â·ÏÇÏ¸ç ºÐ¼® ±â°£ Á¾·á½Ã¿¡´Â 177¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. AI ¼­ºñ½º ºÐ¾ßÀÇ ¼ºÀå·üÀº ºÐ¼® ±â°£ µ¿¾È CAGR 26.7%·Î ÃßÁ¤µË´Ï´Ù.

¹Ì±¹ ½ÃÀåÀº 37¾ï ´Þ·¯·Î ÃßÁ¤, Áß±¹Àº CAGR 22.9%·Î ¼ºÀå ¿¹Ãø

¹Ì±¹ÀÇ »ç¹°ÀΰøÁö´É(AIoT) ½ÃÀåÀº 2024³â¿¡ 37¾ï ´Þ·¯·Î ÃßÁ¤µË´Ï´Ù. ¼¼°è 2À§ °æÁ¦ ´ë±¹ÀÎ Áß±¹Àº 2030³â±îÁö 79¾ï ´Þ·¯ÀÇ ½ÃÀå ±Ô¸ð¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµÇ¸ç, ºÐ¼® ±â°£ÀÎ 2024-2030³â CAGRÀº 22.9%¸¦ ±â·ÏÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ±âŸ ÁÖ¸ñÇÒ ¸¸ÇÑ Áö¿ªº° ½ÃÀåÀ¸·Î´Â ÀϺ»°ú ij³ª´Ù°¡ ÀÖ°í, ºÐ¼® ±â°£ µ¿¾È CAGRÀº °¢°¢ 21.5%¿Í 21.1%·Î ¿¹ÃøµË´Ï´Ù. À¯·´¿¡¼­´Â µ¶ÀÏÀÌ CAGR ¾à 16.9%·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.

¼¼°è »ç¹°ÀΰøÁö´É(AIoT) ½ÃÀå - ÁÖ¿ä µ¿Çâ ¹× ÃËÁø¿äÀÎ Á¤¸®

AI¿Í IoTÀÇ À¶ÇÕÀ¸·Î ÀåÄ¡¿Í ½Ã½ºÅÛ Àü¹Ý¿¡ °ÉÃÄ Â÷¼¼´ë ÀÎÅÚ¸®Àü½º¸¦ ±¸ÇöÇÏ´Â ÀÌÀ¯´Â ¹«¾ùÀϱî?

ÀΰøÁö´É(AI)°ú »ç¹°ÀÎÅͳÝ(IoT)ÀÇ À¶ÇÕÀÎ AIoT(Artificial Intelligence of Things)´Â ¿§Áö ¹× Ŭ¶ó¿ìµå¿¡¼­ ½Ç½Ã°£ ÀÚÀ²Àû ÀÇ»ç°áÁ¤À» °¡´ÉÇϰÔÇÔÀ¸·Î½á µð¹ÙÀ̽º, ±â°è ¹× ½Ã½ºÅÛÀÇ »óÈ£ ÀÛ¿ë ¹æ½ÄÀ» ÀçÁ¤ÀÇÇϰí ÀÖ½À´Ï´Ù. Ä¿³ØÆ¼ºñƼÀÇ ÀÎÇÁ¶ó¸¦ Á¦°øÇϰí, AI´Â µ¥ÀÌÅ͸¦ ºÐ¼®Çϰí, ÆÐÅÏÀ» ÀνÄÇϰí, °á°ú¸¦ ¿¹ÃøÇϰí, Àΰ£ÀÇ °³ÀÔ ¾øÀÌ ¿î¿µÀ» ÃÖÀûÈ­ÇÒ ¼ö ÀÖ´Â ÀÎÁöÀû ´É·ÂÀ» Á¦°øÇÕ´Ï´Ù. ÀÌ·¯ÇÑ À¶ÇÕÀ» ÅëÇØ µð¹ÙÀ̽º°¡ ¹®¸ÆÀû ÀλçÀÌÆ®¸¦ ±â¹ÝÀ¸·Î ÇнÀ, ÀûÀÀ, ÀÚ±â ÃÖÀûÈ­ÇÒ ¼ö ÀÖ°Ô µÇ¾î ¹ÝÀÀÇü ÀÚµ¿È­¿¡¼­ »çÀü ¿¹¹æÀû ÀÎÅÚ¸®Àü½º·ÎÀÇ ÀüȯÀÌ °¡´ÉÇØÁý´Ï´Ù.

AIoT´Â Á¦Á¶¾÷(¿¹Áöº¸Àü, °øÁ¤ ÀÚµ¿È­), ÇコÄɾî(¿ø°Ý Áø´Ü, ½º¸¶Æ® ¿þ¾î·¯ºí), ½º¸¶Æ® ½ÃƼ(±³Åë Á¦¾î, ¿¡³ÊÁö ÃÖÀûÈ­), ³ó¾÷(±âÈÄ ¸ð´ÏÅ͸µ, ÀÚÀ² °ü°³) µî »ê¾÷ Àü¹Ý¿¡ °ÉÃÄ Â÷¼¼´ë ¾ÖÇø®ÄÉÀ̼ǿ¡ ¹ÚÂ÷¸¦ °¡Çϰí ÀÖ½À´Ï´Ù. ·Îº¿°ú °°Àº ¿§Áö µð¹ÙÀ̽º¿¡ AI ¸ðµ¨À» Á÷Á¢ ÅëÇÕÇÔÀ¸·Î½á ½Ã½ºÅÛÀº ½Å¼ÓÇÑ ÀÇ»ç°áÁ¤À» ³»¸®°í, µ¥ÀÌÅÍ Àü¼Û ¿ä±¸»çÇ×À» ÁÙÀ̸ç, ¿¬°áÀÌ Á¦ÇÑÀûÀ̰ųª °£ÇæÀûÀÏ ¶§¿¡µµ ¼º´ÉÀ» À¯ÁöÇÒ ¼ö ÀÖ½À´Ï´Ù. Àü ¼¼°èÀûÀ¸·Î µðÁöÅÐ ÀüȯÀÌ °­È­µÇ°í ÀÖ´Â °¡¿îµ¥, AIoT´Â ½º¸¶Æ®Çϰí È®Àå °¡´ÉÇϸç ź·ÂÀûÀÎ »çÀ̹ö ¹°¸® ½Ã½ºÅÛÀ» ±¸ÃàÇÏ´Â µ¥ ÀÖ¾î ±âº» ·¹À̾ µÇ°í ÀÖ½À´Ï´Ù.

¿§Áö AI¿Í Ŭ¶ó¿ìµå ÀÎÅÚ¸®Àü½º°¡ AIoT ¾ÆÅ°ÅØÃ³ÀÇ ÁøÈ­¸¦ ¾î¶»°Ô ÃËÁøÇϰí Àִ°¡?

¿§Áö ÄÄÇ»ÆÃ, ÀúÀü·Â AI Ĩ, ºÐ»êÇü ¸Ó½Å·¯´×ÀÇ ¹ßÀüÀº AIoTÀÇ Àü°³ ¸ðµ¨À» Å©°Ô Çü¼ºÇϰí ÀÖ½À´Ï´Ù. ¿§Áö AI´Â µ¥ÀÌÅ͸¦ ·ÎÄÿ¡¼­ ó¸®ÇÒ ¼ö ÀÖ°Ô ÇÏ¿© Áö¿¬ ½Ã°£, ´ë¿ªÆø ¼Òºñ, Ŭ¶ó¿ìµå ÀÇÁ¸µµ¸¦ ³·Ãä´Ï´Ù. Nvidia Jetson, Intel Movidius, Google Coral°ú °°Àº Àü¿ë AI ÇÁ·Î¼¼¼­´Â ÃÖ¼ÒÇÑÀÇ ¿¡³ÊÁö ¼Òºñ·Î ¿§Áö¿¡¼­ÀÇ ½Ç½Ã°£ Ãß·ÐÀ» °¡´ÉÇÏ°Ô Çϰí, Á¦ÇÑÀûÀΠȯ°æ¿¡¼­µµ ½Ç½Ã°£ Ãß·ÐÀÌ °¡´ÉÇϸç, Áö¿¬ ½Ã°£, ´ë¿ªÆø ¼Òºñ, Ŭ¶ó¿ìµå ÀÇÁ¸µµ¸¦ ÁÙÀÔ´Ï´Ù. Á¦¾àÀÌ ¸¹Àº ȯ°æ¿¡¼­µµ È®Àå °¡´ÉÇÑ AIoT ±¸ÇöÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù.

µ¿½Ã¿¡ Ŭ¶ó¿ìµå ±â¹Ý AI´Â ¸ðµ¨ ÇнÀ, ÀÌ·Â ºÐ¼®, Àüü ½Ã½ºÅÛ ¿ÀÄɽºÆ®·¹À̼ÇÀ» À§ÇÑ ¿¬»ê ´É·ÂÀ» Á¦°øÇÕ´Ï´Ù. ÇÏÀ̺긮µå AIoT ¾ÆÅ°ÅØÃ³´Â ¿§Áö¿Í Ŭ¶ó¿ìµåÀÇ ±â´ÉÀ» ¸ðµÎ Ȱ¿ëÇÏ¿© ¼º´É°ú È®À强ÀÇ ±ÕÇüÀ» ¸ÂÃä´Ï´Ù. AWS, Azure, Google CloudÀÇ ¼ÒÇÁÆ®¿þ¾î Ç÷§ÆûÀº ¿§Áö ºÐ¼®, µðÁöÅÐ Æ®À©, ÄÁÅ×À̳ÊÈ­µÈ ¾ÖÇø®ÄÉÀ̼Ç, Çù¾÷ ÇнÀÀ» Áö¿øÇÔÀ¸·Î½á ¿§Áö ºÐ¼®, µðÁöÅÐ Æ®À©, ÄÁÅ×À̳ÊÈ­µÈ ¾ÖÇø®ÄÉÀÌ¼Ç ¹× Çù¾÷ ÇнÀÀ» Áö¿øÇÔÀ¸·Î½á µð¹ÙÀ̽º¿¡¼­ Ŭ¶ó¿ìµå·ÎÀÇ ¿øÈ°ÇÑ ÅëÇÕÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù. ÀÌ·¯ÇÑ ¾ÆÅ°ÅØÃ³ÀÇ À¯¿¬¼ºÀ» ÅëÇØ ±â¾÷Àº AI ¸ðµ¨ÀÇ ºñ¿ë È¿À²¼º, º¸¾È ¹× Áö¼ÓÀûÀÎ °³¼±À» º¸ÀåÇϸ鼭 ´Ù¾çÇÑ È¯°æ¿¡¼­ AIoT¸¦ ±¸ÃàÇÒ ¼ö ÀÖ½À´Ï´Ù.

AIoT µµÀÔÀÌ °¡¼ÓÈ­µÇ°í ÀÖ´Â °÷Àº ¾îµðÀ̸ç, ¾î¶² »ç¿ë »ç·Ê°¡ ½ÃÀå ¼ºÀåÀ» ÁÖµµÇϰí Àִ°¡?

AIoTÀÇ µµÀÔÀº Àü ¼¼°èÀûÀ¸·Î °¡¼ÓÈ­µÇ°í ÀÖÀ¸¸ç, ºÏ¹Ì¿Í ¼­À¯·´¿¡¼­ µµÀÔÀÌ ÁøÇàµÇ°í ÀÖ°í, ¾Æ½Ã¾ÆÅÂÆò¾ç¿¡¼­µµ ÅõÀÚ°¡ ºü¸£°Ô È®´ëµÇ°í ÀÖ½À´Ï´Ù. ¹Ì±¹¿¡¼­´Â AIoT°¡ »ê¾÷ ÀÚµ¿È­, ½º¸¶Æ®È¨ »ýŰè, ¹°·ù ÃÖÀûÈ­ÀÇ Áß½ÉÀÌ µÇ°í ÀÖ½À´Ï´Ù. À¯·´¿¡¼­´Â EUÀÇ µðÁöÅÐ Àü·«°ú Áö¼Ó°¡´É¼º ¸ñÇ¥¿¡ ÈûÀÔ¾î ½º¸¶Æ® ½ÃƼ °³¹ß, ¿¡³ÊÁö ±×¸®µå ÀÎÅÚ¸®Àü½º, ȯ°æ ¸ð´ÏÅ͸µ¿¡ AIoT°¡ Ȱ¿ëµÇ°í ÀÖ½À´Ï´Ù. ¾Æ½Ã¾ÆÅÂÆò¾ç, ƯÈ÷ Áß±¹, ÀϺ», Çѱ¹, Àεµ¿¡¼­´Â ´ë±Ô¸ð ÀÎÇÁ¶ó ÅõÀÚ¿Í Á¤ºÎ Áö¿ø µðÁöÅÐ ÀÌ´Ï¼ÅÆ¼ºê¿¡ ÈûÀÔ¾î ½º¸¶Æ® Á¦Á¶, °ø°ø¾ÈÀü, Á¤¹Ð³ó¾÷ ºÐ¾ß¿¡¼­ AIoT µµÀÔÀÌ ºü¸£°Ô ÁøÇàµÇ°í ÀÖ½À´Ï´Ù.

ÁÖ¿ä »ç¿ë »ç·Ê·Î´Â AIoT ½Ã½ºÅÛÀÌ ¼¾¼­ µ¥ÀÌÅ͸¦ ºÐ¼®ÇÏ¿© ÀåºñÀÇ °íÀåÀ» ¿¹ÃøÇÏ°í »çÀü À¯Áöº¸¼ö ÀÏÁ¤À» ¼ö¸³ÇÏ¿© ´Ù¿îŸÀÓÀ» ÁÙÀÌ´Â Á¦Á¶¾÷ÀÇ ¿¹Áöº¸Àü(predictive maintenance)À» µé ¼ö ÀÖ½À´Ï´Ù. ¼Ò¸Å¾÷¿¡¼­´Â AIoT°¡ ¸ÅÀå ³» ¼¾¼­¿Í ¿§Áö ÄÄÇ»ÆÃÀ» »ç¿ëÇÏ¿© ½Ç½Ã°£ Àç°í °ü¸®, ¼îÇΰ´ ºÐ¼®, °³ÀÎÈ­µÈ ÇÁ·Î¸ð¼ÇÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù. ½º¸¶Æ®È¨¿¡¼­´Â À½¼º ºñ¼­ ¹× Ä¿³ØÆ¼µå °¡ÀüÁ¦Ç°ÀÌ ÀûÀÀÇü Á¦¾î ¹× »ç¿ëÀÚ Çൿ ÇнÀÀ» À§ÇØ AI¸¦ ÅëÇÕÇϰí ÀÖ½À´Ï´Ù. ¹°·ù ±â¾÷µéÀº AIoT¸¦ °æ·Î ÃÖÀûÈ­, Â÷·® °ü¸®, ÄݵåüÀÎ ¸ð´ÏÅ͸µ¿¡ Ȱ¿ëÇϰí ÀÖ½À´Ï´Ù. ÇÑÆí, ÇコÄÉ¾î ºÐ¾ß¿¡¼­´Â AIoT°¡ ȯÀÚÀÇ Áö¼ÓÀûÀÎ ¸ð´ÏÅ͸µ, ÀÌ»ó ¡ÈÄ Á¶±â ¹ß°ß, Áö´ÉÇü º´¿ø ÀÚ¿ø ¹èºÐ, ¿ø°ÝÀÇ·á ¹× ¿¹¹æ ÀÇ·á ¸ðµ¨ÀÇ ÇÙ½É ¿ä¼Ò·Î Ȱ¿ëµÇ°í ÀÖ½À´Ï´Ù.

»ç¹°ÀΰøÁö´É(AIoT) ½ÃÀåÀÇ ¼¼°è ¼ºÀå µ¿·ÂÀº?

AIoT ½ÃÀåÀÇ ¼ºÀåÀº °¡¼ÓÈ­µÇ´Â µðÁöÅÐ Àüȯ, ¼¾¼­ÀÇ Áõ°¡, ½Ç½Ã°£À¸·Î ÀÛµ¿ÇÏ´Â ÀÚÀ²ÀûÀ̰í Áö´ÉÀûÀÎ ½Ã½ºÅÛÀÇ Çʿ伺ÀÌ °áÇÕÇÏ¿© ÀÌ·ç¾îÁö°í ÀÖ½À´Ï´Ù. Áß¿äÇÑ ¿øµ¿·ÂÀº IoT µ¥ÀÌÅÍÀÇ ±Þ°ÝÇÑ Áõ°¡·Î, AI ±â´ÉÀ» ÅëÇØ ½ÇÁúÀûÀÎ ÀλçÀÌÆ®¸¦ µµÃâÇÏ°í ´ëÀÀÀ» ÀÚµ¿È­ÇÒ ¼ö ÀÖ´Â AI ±â´ÉÀÌ ÇÊ¿äÇÕ´Ï´Ù. ±â¾÷µéÀº AIoT¿¡ ÅõÀÚÇÔÀ¸·Î½á ¾÷¹« È¿À²¼º Çâ»ó, ÀÎÀû ¿À·ù °¨¼Ò, ºñ¿ë Àý°¨À» ½ÇÇöÇϰí, µ¥ÀÌÅÍ ±â¹Ý Çõ½ÅÀ» ÅëÇØ °æÀï»ç¿ÍÀÇ Â÷º°È­¸¦ ²ÒÇϰí ÀÖ½À´Ï´Ù. ¿§Áö AIÀÇ ¹ßÀü, Çϵå¿þ¾î ºñ¿ëÀÇ Ç϶ô, 5G ¹× LPWAN ¿¬°áÀÇ ¼º¼÷À¸·Î ÀÎÇØ ¼ÒºñÀÚ¿Í »ê¾÷ ºÐ¾ß ¸ðµÎ¿¡¼­ È®Àå °¡´ÉÇÑ AIoT ±¸ÃàÀÌ ´õ¿í °¡´ÉÇØÁ³½À´Ï´Ù.

Á¤ºÎ ÀÚ±Ý Áö¿ø, ½º¸¶Æ® ÀÎÇÁ¶ó Àǹ«È­, »ê¾÷º° Ç¥ÁØ(Industry 4.0, ISO/IEC IoT º¸¾È ÇÁ·¹ÀÓ¿öÅ© µî)Àº Áö¿ª Àü¹Ý¿¡ °ÉÃÄ AIoT äÅÃÀ» Áö¿øÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, ¿ÀÇ ¼Ò½º AI ÇÁ·¹ÀÓ¿öÅ©, »óÈ£ ¿î¿ë °¡´ÉÇÑ Ç÷§Æû, µðÁöÅÐ Æ®À© ±â¼úÀº °³¹ß ¹× ÅëÇÕ ÇÁ·Î¼¼½º¸¦ °£¼ÒÈ­Çϰí ÀÖÀ¸¸ç, AIoT »ýŰ谡 È®ÀåµÇ°í ´õ ¸¹Àº µð¹ÙÀ̽º°¡ Áö´ÉÈ­µÇ°í »óÈ£¿¬°áµÊ¿¡ µû¶ó ¸Å¿ì Áß¿äÇÑ Áú¹®ÀÌ Á¦±âµÇ°í ÀÖ½À´Ï´Ù. Áß¿äÇÑ Áú¹®ÀÌ »ý±é´Ï´Ù. ¼¼°è AIoT »ýŰ谡 »ê¾÷, Áö¿ª, ¹Ì¼Ç Å©¸®Æ¼ÄÃÇÑ È¯°æÀ» ³Ñ¾î ÁøÁ¤À¸·Î ÀÚÀ²ÀûÀÌ°í ¾ÈÀüÇϸç ÀûÀÀ·ÂÀÌ ¶Ù¾î³­ ÀÎÅÚ¸®Àü½º¸¦ ´ë±Ô¸ð·Î Á¦°øÇÒ ¼ö ÀÖÀ»±î?

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Global Artificial Intelligence of Things Market to Reach US$51.3 Billion by 2030

The global market for Artificial Intelligence of Things estimated at US$14.1 Billion in the year 2024, is expected to reach US$51.3 Billion by 2030, growing at a CAGR of 24.0% over the analysis period 2024-2030. AI Software / Platforms, one of the segments analyzed in the report, is expected to record a 20.8% CAGR and reach US$17.7 Billion by the end of the analysis period. Growth in the AI Services segment is estimated at 26.7% CAGR over the analysis period.

The U.S. Market is Estimated at US$3.7 Billion While China is Forecast to Grow at 22.9% CAGR

The Artificial Intelligence of Things market in the U.S. is estimated at US$3.7 Billion in the year 2024. China, the world's second largest economy, is forecast to reach a projected market size of US$7.9 Billion by the year 2030 trailing a CAGR of 22.9% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 21.5% and 21.1% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 16.9% CAGR.

Global Artificial Intelligence of Things (AIoT) Market - Key Trends & Drivers Summarized

Why Is the Convergence of AI and IoT Unlocking Next-Generation Intelligence Across Devices and Systems?

The Artificial Intelligence of Things (AIoT)-the fusion of Artificial Intelligence (AI) and the Internet of Things (IoT)-is redefining the way devices, machines, and systems interact by enabling real-time, autonomous decision-making at the edge and in the cloud. IoT provides the sensing and connectivity infrastructure, while AI brings the cognitive ability to analyze data, recognize patterns, predict outcomes, and optimize operations without human intervention. This convergence allows for a shift from reactive automation to proactive intelligence, where devices can learn, adapt, and self-optimize based on contextual insights.

AIoT is fueling a new generation of applications across industries such as manufacturing (predictive maintenance, process automation), healthcare (remote diagnostics, smart wearables), smart cities (traffic control, energy optimization), and agriculture (climate monitoring, autonomous irrigation). By embedding AI models directly into edge devices-such as cameras, sensors, and robots-systems can execute decisions faster, reduce data transmission requirements, and maintain performance even with limited or intermittent connectivity. As digital transformation intensifies globally, AIoT is becoming a foundational layer in building smart, scalable, and resilient cyber-physical systems.

How Are Edge AI and Cloud Intelligence Powering the Evolution of AIoT Architectures?

The advancement of edge computing, low-power AI chips, and distributed machine learning is significantly shaping AIoT deployment models. Edge AI enables data to be processed locally, reducing latency, bandwidth consumption, and cloud dependency-essential for time-sensitive applications like autonomous vehicles, industrial robots, and smart surveillance. Purpose-built AI processors, such as Nvidia Jetson, Intel Movidius, and Google Coral, are allowing real-time inferencing at the edge with minimal energy consumption, enabling scalable AIoT implementations in constrained environments.

At the same time, cloud-based AI provides the computational heft for model training, historical analytics, and system-wide orchestration. Hybrid AIoT architectures leverage both edge and cloud capabilities to balance performance and scalability: the edge handles immediate decision-making, while the cloud oversees system learning, long-term optimization, and model retraining. Software platforms from AWS, Azure, and Google Cloud are enabling seamless device-to-cloud integration with support for edge analytics, digital twins, containerized applications, and federated learning. This architectural flexibility is allowing enterprises to deploy AIoT in diverse environments while ensuring cost-efficiency, security, and continuous improvement of AI models.

Where Is AIoT Adoption Accelerating and Which Use Cases Are Leading Market Growth?

AIoT adoption is accelerating globally, with high uptake across North America, Western Europe, and rapidly growing investment in Asia-Pacific. In the U.S., AIoT is central to industrial automation, smart home ecosystems, and logistics optimization. Europe is leveraging AIoT for smart city development, energy grid intelligence, and environmental monitoring, supported by the EU’s digital strategy and sustainability goals. Asia-Pacific-particularly China, Japan, South Korea, and India-is witnessing rapid deployment in smart manufacturing, public safety, and precision agriculture, driven by large-scale infrastructure investments and government-backed digital initiatives.

Leading use cases include predictive maintenance in manufacturing, where AIoT systems analyze sensor data to forecast equipment failure and schedule proactive maintenance, thereby reducing downtime. In retail, AIoT enables real-time inventory management, shopper analytics, and personalized promotions using in-store sensors and edge computing. In smart homes, voice assistants and connected appliances are integrating AI for adaptive control and user behavior learning. Logistics companies use AIoT for route optimization, fleet management, and cold chain monitoring. Meanwhile, in healthcare, AIoT is enabling continuous patient monitoring, early anomaly detection, and intelligent hospital resource allocation-making it a vital component of remote and preventive care models.

What Is Fueling the Global Growth of the Artificial Intelligence of Things (AIoT) Market?

The growth in the AIoT market is driven by a confluence of accelerating digital transformation, increasing sensor proliferation, and the need for autonomous, intelligent systems that operate in real-time. A critical driver is the exponential growth of IoT data, which requires AI capabilities to derive actionable insights and automate responses. Businesses are investing in AIoT to enhance operational efficiency, reduce human error, cut costs, and gain competitive differentiation through data-driven innovation. Edge AI advancements, lower hardware costs, and the maturation of 5G and LPWAN connectivity are further enabling scalable AIoT deployments in both consumer and industrial domains.

Government funding, smart infrastructure mandates, and industry-specific standards (such as Industry 4.0, ISO/IEC IoT security frameworks) are supporting the adoption of AIoT across regions. Additionally, open-source AI frameworks, interoperable platforms, and digital twin technologies are simplifying development and integration processes. As AIoT ecosystems expand, with more devices becoming intelligent and interconnected, a pivotal question arises: Can the global AIoT ecosystem deliver truly autonomous, secure, and adaptive intelligence at scale-across industries, geographies, and mission-critical environments?

SCOPE OF STUDY:

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

Segments:

Component (Software / Platforms, Services, Professional, Managed); End-Use (BFSI, Retail, Automotive, Transportation & Logistics, Healthcare, Energy & Utilities, Manufacturing, 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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