¼¼°èÀÇ ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ½ÃÀå
Artificial Intelligence Orchestration
»óǰÄÚµå : 1737528
¸®¼­Ä¡»ç : Global Industry Analysts, Inc.
¹ßÇàÀÏ : 2025³â 05¿ù
ÆäÀÌÁö Á¤º¸ : ¿µ¹® 208 Pages
 ¶óÀ̼±½º & °¡°Ý (ºÎ°¡¼¼ º°µµ)
US $ 5,850 £Ü 8,163,000
PDF (Single User License) help
PDF º¸°í¼­¸¦ 1¸í¸¸ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. Àμâ´Â °¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.
US $ 17,550 £Ü 24,489,000
PDF (Global License to Company and its Fully-owned Subsidiaries) help
PDF º¸°í¼­¸¦ µ¿ÀÏ ±â¾÷ÀÇ ¸ðµç ºÐÀÌ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. Àμâ´Â °¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.


Çѱ۸ñÂ÷

¼¼°èÀÇ ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ½ÃÀåÀº 2030³â±îÁö 283¾ï ´Þ·¯¿¡ ´ÞÇÒ Àü¸Á

2024³â¿¡ 97¾ï ´Þ·¯·Î ÃßÁ¤µÇ´Â ¼¼°èÀÇ ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ½ÃÀåÀº 2024-2030³â¿¡ CAGR 19.5%·Î ¼ºÀåÇϸç, 2030³â¿¡´Â 283¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÌ ¸®Æ÷Æ®¿¡¼­ ºÐ¼®ÇÑ ºÎ¹®ÀÇ ÇϳªÀÎ AI ¼Ö·ç¼ÇÀº CAGR 17.4%¸¦ ±â·ÏÇϸç, ºÐ¼® ±â°£ Á¾·á±îÁö 172¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. AI ¼­ºñ½º ºÐ¾ßÀÇ ¼ºÀå·üÀº ºÐ¼® ±â°£¿¡ CAGR 23.4%·Î ÃßÁ¤µË´Ï´Ù.

¹Ì±¹ ½ÃÀåÀº 26¾ï ´Þ·¯·Î ÃßÁ¤, Áß±¹Àº CAGR 18.6%·Î ¼ºÀå ¿¹Ãø

¹Ì±¹ÀÇ ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ½ÃÀåÀº 2024³â¿¡ 26¾ï ´Þ·¯·Î ÃßÁ¤µË´Ï´Ù. ¼¼°è 2À§ÀÇ °æÁ¦´ë±¹ÀÎ Áß±¹Àº 2030³â±îÁö 44¾ï ´Þ·¯ÀÇ ½ÃÀå ±Ô¸ð¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµÇ¸ç, ºÐ¼® ±â°£ÀÎ 2024-2030³âÀÇ CAGRÀº 18.6%ÀÔ´Ï´Ù. ±âŸ ÁÖ¸ñÇÒ ¸¸ÇÑ Áö¿ªº° ½ÃÀåÀ¸·Î´Â ÀϺ»°ú ij³ª´Ù°¡ ÀÖÀ¸¸ç, ºÐ¼® ±â°£ Áß CAGRÀº °¢°¢ 17.5%¿Í 17.0%·Î ¿¹ÃøµË´Ï´Ù. À¯·´¿¡¼­´Â µ¶ÀÏÀÌ CAGR ¾à 13.6%·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.

¼¼°è ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ½ÃÀå - ÁÖ¿ä µ¿Çâ ¹× ÃËÁø¿äÀÎ Á¤¸®

ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ÇÀÌ ±â¾÷ ÀÎÅÚ¸®Àü½º ¾ÆÅ°ÅØÃ³ÀÇ Áß¿äÇÑ °èÃþÀ¸·Î ºÎ»óÇϰí ÀÖ´Â ÀÌÀ¯´Â ¹«¾ùÀΰ¡?

ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ÇÀº ºÐ»êµÈ ȯ°æ¿¡¼­ ¿©·¯ AI/ML ¸ðµ¨, µ¥ÀÌÅÍ ÆÄÀÌÇÁ¶óÀÎ, API, ÀÚµ¿È­ ¿öÅ©Ç÷ο츦 Á¶Á¤ÇÏ¿© È®Àå °¡´ÉÇÑ ±â¾÷±Þ AI ¹èÆ÷¸¦ ½ÇÇöÇÏ´Â µ¥ ÀÖÀ¸¸ç, ¸Å¿ì Áß¿äÇÑ ¿ªÇÒÀ» Çϰí ÀÖ½À´Ï´Ù. Á¶Á÷ÀÌ ´Ù¾çÇÑ ¾Ë°í¸®Áò, Ç÷§Æû, Çϵå¿þ¾î ÀÎÇÁ¶ó¸¦ äÅÃÇÏ°í º¹À⼺ÀÌ Áõ°¡ÇÏ´Â ¿À´Ã³¯ÀÇ AI »ýŰ迡¼­ ¿ÀÄɽºÆ®·¹À̼ÇÀº ¼­·Î ´Ù¸¥ AI ÄÄÆ÷³ÍÆ®¸¦ ÅëÇÕÀûÀÎ °¡Ä¡¸¦ âÃâÇÏ´Â ½Ã½ºÅÛÀ¸·Î Á¶È­½ÃŰ´Â ¿¬°á°í¸® ¿ªÇÒÀ» ÇÕ´Ï´Ù. ¿ÀÄɽºÆ®·¹À̼ÇÀº Ŭ¶ó¿ìµå, On-Premise, ¿§Áö ȯ°æ¿¡¼­ ÀûÀýÇÑ ¸ðµ¨ÀÌ ¹èÆ÷, ½ÇÇà, ¸ð´ÏÅ͸µµÇ°í, ÄÁÅØ½ºÆ® ¿ä±¸»çÇ×°ú ºñÁî´Ï½º ±ÔÄ¢¿¡ µû¶ó ¹Ýº¹ÀûÀ¸·Î °³¼±µÉ ¼ö ÀÖµµ·Ï º¸ÀåÇÕ´Ï´Ù.

±â¾÷ÀÌ »çÀÏ·ÎÈ­µÈ AI ½ÇÇè¿¡¼­ ÇÁ·Î´ö¼Ç±Þ AI ¼Ö·ç¼ÇÀ¸·Î ÀüȯÇÔ¿¡ µû¶ó ¿ÀÄɽºÆ®·¹À̼ÇÀº ¹öÀü °ü¸®, ¸ðµ¨ °Å¹ö³Í½º, µ¥ÀÌÅÍ Á¾¼Ó¼º °ü¸®, ÄÄÇöóÀ̾ð½º, ¼º´É ÃÖÀûÈ­¿Í °°Àº ÁÖ¿ä ¿î¿µ °úÁ¦¸¦ ÇØ°áÇÕ´Ï´Ù. ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ÇÀº ¸ðµ¨ ¼ö¸íÁÖ±â°ü¸®(ML Ops), ½Ç½Ã°£ Ãß·Ð, ÀÇ»ç°áÁ¤ ÀÚµ¿È­¸¦ ¿øÈ°ÇÏ°Ô ÅëÇÕÇϰí È®Àå °¡´ÉÇÏ°Ô ±¸ÇöÇÕ´Ï´Ù. À̸¦ ÅëÇØ AIÀÇ °á°ú¹°À» ºñÁî´Ï½º ÇÁ·Î¼¼½º, IT ½Ã½ºÅÛ, °í°´ ¿ëµµ¿¡ Á÷Á¢ ÅëÇÕÇÏ¿© Á¤Àû ÀλçÀÌÆ®¸¦ µ¿Àû ½Ã½ºÅÛ Àü¹ÝÀÇ ÀÎÅÚ¸®Àü½º·Î ÀüȯÇÒ ¼ö ÀÖ½À´Ï´Ù. ¹Îø¼º, Åõ¸í¼º, ½Å·Ú¼ºÀÌ ³ôÀº AI¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡ÇÔ¿¡ µû¶ó ¿ÀÄɽºÆ®·¹À̼ÇÀº Áö´ÉÇü ±â¾÷ ÀÎÇÁ¶óÀÇ ÇÙ½É ¿ä¼Ò·Î ºÎ»óÇϰí ÀÖ½À´Ï´Ù.

ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç Ç÷§ÆûÀº ¿î¿µ°ú ¼ö¸íÁÖ±â°ü¸®¸¦ ¾î¶»°Ô °­È­Çϴ°¡?

ÃֽŠÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç Ç÷§ÆûÀº µ¥ÀÌÅÍ ¼öÁý ¹× Àü󸮺ÎÅÍ ¸ðµ¨ ÈÆ·Ã, ¹èÆ÷, ¸ð´ÏÅ͸µ, ÀçÈÆ·Ã¿¡ À̸£±â±îÁö AI/MLÀÇ Àüü ¼ö¸íÁÖ±âÀ» ÅëÇÕµÈ ÀÚµ¿È­µÈ ÇÁ·¹ÀÓ¿öÅ©¿¡¼­ ó¸®ÇÒ ¼ö ÀÖµµ·Ï ¼³°èµÇ¾ú½À´Ï´Ù. ¼³°èµÇ¾î ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Ç÷§ÆûÀº ÄÁÅ×À̳ÊÈ­µÈ ¸¶ÀÌÅ©·Î¼­ºñ½º, CI/CD ÆÄÀÌÇÁ¶óÀÎ, ¿öÅ©ÇÃ·Î¿ì ¿£ÁøÀ» Ȱ¿ëÇÏ¿© °³¹ß, Å×½ºÆ®, ÇÁ·Î´ö¼Ç ȯ°æ¿¡ °ÉÄ£ ÀÛ¾÷À» ¿ÀÄɽºÆ®·¹À̼ÇÇϸç, Kubeflow, MLflow, Airflow, DataRobot°ú °°Àº AWS SageMaker, Azure ML, Google Vertex AI¿Í °°Àº Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ¼Ö·ç¼Ç°ú AWS SageMaker, Azure ML, Google Vertex AI¿Í °°Àº ÁÖ¿ä ÅøÀ» ÅëÇØ Á¶Á÷Àº ¸ðµ¨ ·Ñ¾Æ¿ôÀ» ÀÚµ¿È­Çϰí, ÄÄÇ»ÆÃ ¸®¼Ò½º¸¦ È®ÀåÇϸç, ¹èÆ÷ ¸¶ÂûÀ» ÁÙÀÏ ¼ö ÀÖ½À´Ï´Ù.

µ¿½Ã¿¡ ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ÇÀº ÅëÇÕ ¸ðµ¨ ¸ð´ÏÅ͸µ, µå¸®ÇÁÆ® °¨Áö, ¹öÀü ÃßÀû, ÄÄÇöóÀ̾𽺠üũÆ÷ÀÎÆ®¸¦ ÅëÇØ ¼³¸í°¡´É¼º, °¨»ç°¡´É¼º, ¸®½ºÅ© °ü¸®¸¦ °­È­ÇÕ´Ï´Ù. ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ÇÁ·¹ÀÓ¿öÅ©¿¡ ³»ÀåµÈ °Å¹ö³Í½º Á¤Ã¥ ¹× ¾×¼¼½º Á¦¾î´Â ¸ðµ¨ÀÌ Ã¥ÀÓ°¨ ÀÖ°Ô ¹èÆ÷µÇ°í GDPR(EU °³ÀÎÁ¤º¸º¸È£±ÔÁ¤), HIPAA, »õ·Î¿î AI À±¸® °¡À̵å¶óÀΰú °°Àº ±ÔÁ¦ ÇÁ·¹ÀÓ¿öÅ©¿Í ÀÏÄ¡Çϵµ·Ï º¸ÀåÇÕ´Ï´Ù. ¶ÇÇÑ ¿ÀÄɽºÆ®·¹À̼ÇÀº ÀÌ¿ë »ç·ÊÀÇ ¸Æ¶ô, »ç¿ëÀÚ ÇÁ·ÎÆÄÀÏ, ½Ç½Ã°£ ¼º´É ÁöÇ¥¸¦ ±â¹ÝÀ¸·Î ÃÖÀûÀÇ ¸ðµ¨À» ¼±ÅÃÇÏ´Â µî AI ÀÛ¾÷À» Áö´ÉÀûÀ¸·Î ¶ó¿ìÆÃÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇÕ´Ï´Ù. ±× °á°ú, º¸´Ù ÀûÀÀ·ÂÀÌ ¶Ù¾î³ª°í ź·ÂÀûÀ̸ç Áö¼ÓÀûÀ¸·Î ÇнÀÇÏ´Â AI ½Ã½ºÅÛÀ» ±¸ÇöÇÏ¿© Àΰ£ÀÇ °³ÀÔ ¾øÀ̵µ ¶óÀ̺ê ȯ°æ¿¡¼­ ÁøÈ­ÇÒ ¼ö ÀÖ½À´Ï´Ù.

ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ǿ¡ ´ëÇÑ ¼ö¿ä´Â ¾îµð¿¡¼­ Áõ°¡Çϰí ÀÖÀ¸¸ç, ¾î¶² ºÐ¾ß¿¡¼­ µµÀÔÀÌ ÁøÇàµÇ°í Àִ°¡?

ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ǿ¡ ´ëÇÑ ¼ö¿ä´Â ±ÝÀ¶ ¼­ºñ½º, ÇコÄɾî, Á¦Á¶, ¼Ò¸Å, Åë½Å, ¹°·ù µî µ¥ÀÌÅÍ Áý¾àÀûÀ̰í ÀÚµ¿È­¸¦ ÃßÁøÇÏ´Â »ê¾÷ Àü¹Ý¿¡¼­ °¡¼ÓÈ­µÇ°í ÀÖ½À´Ï´Ù. ±ÝÀ¶ ¼­ºñ½º¿¡¼­ ¿ÀÄɽºÆ®·¹À̼ÇÀº »ç±â °¨Áö ¸ðµ¨, ½Å¿ë Á¡¼ö ¿£Áø, ¾ö°ÝÇÑ ±ÔÁ¦ °¨µ¶ ÇÏ¿¡ ½Ç½Ã°£À¸·Î ÀÛµ¿ÇØ¾ß ÇÏ´Â ¾Ë°í¸®Áò Æ®·¹À̵ù ½Ã½ºÅÛÀ» °ü¸®ÇÏ´Â µ¥ »ç¿ëµÇ°í ÀÖ½À´Ï´Ù. ÀÇ·á Á¦°øÀÚ¿Í »ý¸í°úÇÐ ±â¾÷Àº Áø´Ü ¸ðµ¨, À¯ÀüüÇÐ ÆÄÀÌÇÁ¶óÀÎ, ÀÓ»ó½ÃÇè ¿¹Ãø, ȯÀÚ Âü¿© ÅøÀÇ Á¶Á¤¿¡ ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ÇÀ» µµÀÔÇϰí ÀÖÀ¸¸ç, °Å¹ö³Í½º, ÃßÀû¼º, Á¤È®¼ºÀ» ÃÖ¿ì¼± °úÁ¦·Î »ï°í ÀÖ½À´Ï´Ù.

Á¦Á¶¾÷¿¡¼­ ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ÇÀº ½ºÆ®¸®¹Ö ¼¾¼­ µ¥ÀÌÅÍ¿Í ¿©·¯ Ãß·Ð ¿£ÁøÀ» Æ÷ÇÔÇÑ ¿¹Ãø À¯Áöº¸¼ö, ǰÁú °Ë»ç, °ø±Þ¸Á ÃÖÀûÈ­ ¿öÅ©Ç÷οìÀÇ Áß½ÉÀÌ µÇ°í ÀÖ½À´Ï´Ù. ¼Ò¸Å¾÷¿¡¼­´Â ¿È´Ïä³Î ȯ°æ¿¡¼­ Ãßõ ¿£Áø, Àç°í ¿¹Ãø, µ¿Àû °¡°Ý Ã¥Á¤ ¸ðµ¨, °í°´ ¼¼ºÐÈ­ Á¶Á¤¿¡ ¿ÀÄɽºÆ®·¹À̼ÇÀÌ È°¿ëµÇ°í ÀÖ½À´Ï´Ù. Åë½Å ¹× ½º¸¶Æ® ÀÎÇÁ¶ó¿¡¼­ ¿ÀÄɽºÆ®·¹À̼ÇÀº AI¸¦ Ȱ¿ëÇÑ ³×Æ®¿öÅ© ÃÖÀûÈ­, °í°´ ¼­ºñ½º º¿, IoT µð¹ÙÀ̽º °ü¸®¸¦ Áö¿øÇÕ´Ï´Ù. ÀÌ·¯ÇÑ ¸ðµç ºÐ¾ß¿¡¼­ Á¶Á÷Àº ½ÇÇè¿ë AI¿¡¼­ ±â¾÷±Þ AI·Î ÀüȯÇϰí ÀÖÀ¸¸ç, ÀÌ¿¡ µû¶ó ±Ô¸ð, ¹Îø¼º, ÄÄÇöóÀ̾𽺸¦ µ¿µîÇÏ°Ô Áö¿øÇÏ´Â ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ±â´É¿¡ ´ëÇÑ ¿ä±¸°¡ Áõ°¡Çϰí ÀÖ½À´Ï´Ù.

ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ½ÃÀåÀÇ ¼¼°è ¼ºÀå µ¿·ÂÀº?

ÀΰøÁö´É ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ½ÃÀåÀÇ ¼ºÀåÀº ±â¾÷ AIÀÇ ¼º¼÷, AI µµÀÔÀÇ º¹À⼺ Áõ°¡, ½Å·Ú¼º, °¨»ç¼º, È®À强ÀÌ ³ôÀº AI ¿î¿µÀÇ Çʿ伺 µî ¸î °¡Áö ÁÖ¿ä µ¿Çâ¿¡ ÀÇÇØ ÁÖµµµÇ°í ÀÖ½À´Ï´Ù. Á¶Á÷ÀÌ ¿©·¯ ¿µ¿ª¿¡ °ÉÃÄ AI¿¡ ÅõÀÚÇÔ¿¡ µû¶ó ¿ÀÄɽºÆ®·¹À̼ÇÀº ¸ðµ¨ÀÇ ³­¸³, »çÀÏ·ÎÈ­µÈ ÀλçÀÌÆ®, ¿î¿µÀÇ ºñÈ¿À²¼ºÀ» ÇÇÇϱâ À§ÇØ ÇʼöÀûÀ̶ó´Â ÀνÄÀÌ È®»êµÇ°í ÀÖ½À´Ï´Ù. ÁÖ¿ä ¿øµ¿·ÂÀº AI ÆÄÀÌÇÁ¶óÀÎÀ» ¼ÒÇÁÆ®¿þ¾î Á¦Ç°À¸·Î Ãë±ÞÇϰí ÀÚµ¿È­, °üÂû °¡´É¼º, ¹Ýº¹Àû °³¼±ÀÌ ÇÊ¿äÇÑ ML Ops ¹× DataOps °üÇàÀ¸·Î ÀüȯÇÏ´Â ±â¾÷ÀÇ º¯È­ÀÔ´Ï´Ù.

Ŭ¶ó¿ìµå ³×ÀÌÆ¼ºê ¾ÆÅ°ÅØÃ³, ÄÁÅ×À̳ÊÈ­, ·Î¿ìÄÚµå Ç÷§Æû, ¿ÀǼҽº ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ÅøÀÇ ¹ßÀüÀº AI ¿î¿µÀÇ À庮À» ³·Ãß°í ÀÖ½À´Ï´Ù. ÀÌ¿Í ÇÔ²² AIÀÇ °øÁ¤¼º, Ã¥ÀÓ¼º, Åõ¸í¼º¿¡ ´ëÇÑ ±ÔÁ¦ ´ç±¹ÀÇ °¨½Ã°¡ °­È­µÇ¸é¼­ ±â¾÷ÀÌ ÄÄÇöóÀ̾𽺠¹× ¼ö¸íÁֱ⠸ð´ÏÅ͸µÀ» ÅëÇÕÇÑ ¿ÀÄɽºÆ®·¹ÀÌ¼Ç ¼Ö·ç¼ÇÀ» äÅÃÇϵµ·Ï À¯µµÇϰí ÀÖ½À´Ï´Ù. ¿ÀÄɽºÆ®·¹À̼ÇÀ» ÅÏŰ AI ½ºÅÿ¡ ÅëÇÕÇÏ´Â ¼Ö·ç¼Ç ÅëÇÕ¾÷üµé °£ÀÇ Àü·«Àû ÆÄÆ®³Ê½Êµµ äÅÃÀ» °¡¼ÓÈ­Çϰí ÀÖÀ¸¸ç, AI°¡ °³º°ÀûÀÎ µµÀÔ¿¡¼­ ÅëÇÕµÈ ±â¾÷ ½Ã½ºÅÛÀ¸·Î ÁøÈ­ÇÔ¿¡ µû¶ó Áß¿äÇÑ Áú¹®ÀÌ Á¦±âµÇ°í ÀÖ½À´Ï´Ù. ÀΰøÁö´É ¿ÀÄɽºÆ®·¹À̼ÇÀÌ °íµµ·Î ±ÔÁ¦µÈ ¹Ì¼Ç Å©¸®Æ¼ÄÃÇÑ È¯°æ¿¡¼­ ź·ÂÀûÀ̰í, Ã¥ÀÓ°¨ ÀÖ°í, Áö¼ÓÀûÀ¸·Î ÇнÀÇÏ´Â AI »ýŰ踦 ±¸ÇöÇÒ ¼ö ÀÖÀ» ¸¸Å­ ºü¸£°Ô È®ÀåÇÒ ¼ö Àִ°¡?

ºÎ¹®

ÄÄÆ÷³ÍÆ®(¼Ö·ç¼Ç, ¼­ºñ½º), ¹èÆ÷(¿ÂÇÁ·¹¹Ì½º, Ŭ¶ó¿ìµå), ¾ÖÇø®ÄÉÀ̼Ç(°í°´ ¼­ºñ½º ¿ÀÄɽºÆ®·¹À̼Ç, ÀÎÇÁ¶ó ¿ÀÄɽºÆ®·¹À̼Ç, Á¦Á¶ ¿ÀÄɽºÆ®·¹À̼Ç, ±âŸ ¾ÖÇø®ÄÉÀ̼Ç), ¾÷°è(IT¡¤Åë½Å, Á¦Á¶, ÇコÄɾî, BFSI, ¼ÒºñÀ硤¼Ò¸Å, Á¤ºÎ¡¤¹æÀ§, ¿¡³ÊÁö¡¤À¯Æ¿¸®Æ¼, ±âŸ ¾÷Á¾)

Á¶»ç ´ë»ó ±â¾÷ÀÇ ¿¹(ÁÖ¸ñ 36»ç)

°ü¼¼ ¿µÇâ °è¼ö

Global Industry Analysts´Â º»»ç ¼ÒÀçÁö, Á¦Á¶ °ÅÁ¡, ¼öÃâÀÔ(¿ÏÁ¦Ç° ¹× OEM)À» ±â¹ÝÀ¸·Î ±â¾÷ÀÇ °æÀï·Â º¯È­¸¦ ¿¹ÃøÇß½À´Ï´Ù. ÀÌ·¯ÇÑ º¹ÀâÇÏ°í ´Ù¸éÀûÀÎ ½ÃÀå ¿ªÇÐÀº ÀÎÀ§ÀûÀÎ ¼öÀÔ¿ø°¡ Áõ°¡, ¼öÀͼº °¨¼Ò, °ø±Þ¸Á ÀçÆí µî ¹Ì½ÃÀû ¹× °Å½ÃÀû ½ÃÀå ¿ªÇÐ Áß¿¡¼­µµ ƯÈ÷ °æÀï»ç¿¡ ¿µÇâÀ» ¹ÌÄ¥ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.

Global Industry Analysts´Â ¼¼°è ÁÖ¿ä ¼ö¼® ÀÌÄÚ³ë¹Ì½ºÆ®(1,4,949¸í), ½ÌÅ©ÅÊÅ©(62°³ ±â°ü), ¹«¿ª ¹× »ê¾÷ ´Üü(171°³ ±â°ü)ÀÇ Àü¹®°¡µéÀÇ ÀǰßÀ» ¸é¹ÐÈ÷ °ËÅäÇÏ¿© »ýŰ迡 ¹ÌÄ¡´Â ¿µÇâÀ» Æò°¡ÇÏ°í »õ·Î¿î ½ÃÀå Çö½Ç¿¡ ´ëÀÀÇϰí ÀÖ½À´Ï´Ù. ¸ðµç ÁÖ¿ä ±¹°¡ÀÇ Àü¹®°¡¿Í °æÁ¦ÇÐÀÚµéÀÌ °ü¼¼¿Í ±×°ÍÀÌ ÀÚ±¹¿¡ ¹ÌÄ¡´Â ¿µÇâ¿¡ ´ëÇÑ ÀǰßÀ» ÃßÀû Á¶»çÇß½À´Ï´Ù.

Global Industry Analysts´Â ÀÌ·¯ÇÑ È¥¶õÀÌ ÇâÈÄ 2-3°³¿ù ³»¿¡ ¸¶¹«¸®µÇ°í »õ·Î¿î ¼¼°è Áú¼­°¡ º¸´Ù ¸íÈ®ÇÏ°Ô È®¸³µÉ °ÍÀ¸·Î ¿¹»óÇϰí ÀÖÀ¸¸ç, Global Industry Analysts´Â ÀÌ·¯ÇÑ »óȲÀ» ½Ç½Ã°£À¸·Î ÃßÀûÇϰí ÀÖ½À´Ï´Ù.

2025³â 4¿ù: Çù»ó ´Ü°è

À̹ø 4¿ù º¸°í¼­¿¡¼­´Â °ü¼¼°¡ ¼¼°è ½ÃÀå Àüü¿¡ ¹ÌÄ¡´Â ¿µÇâ°ú Áö¿ªº° ½ÃÀå Á¶Á¤¿¡ ´ëÇØ ¼Ò°³ÇÕ´Ï´Ù. ´ç»çÀÇ ¿¹ÃøÀº °ú°Å µ¥ÀÌÅÍ¿Í ÁøÈ­ÇÏ´Â ½ÃÀå ¿µÇâ¿äÀÎÀ» ±â¹ÝÀ¸·Î ÇÕ´Ï´Ù.

2025³â 7¿ù: ÃÖÁ¾ °ü¼¼ Àç¼³Á¤

°í°´´Ôµé²²´Â °¢ ±¹°¡º° ÃÖÁ¾ ¸®¼ÂÀÌ ¹ßÇ¥µÈ ÈÄ 7¿ù¿¡ ¹«·á ¾÷µ¥ÀÌÆ® ¹öÀüÀ» Á¦°øÇØ µå¸³´Ï´Ù. ÃÖÁ¾ ¾÷µ¥ÀÌÆ® ¹öÀü¿¡´Â ¸íÈ®ÇÏ°Ô Á¤ÀÇµÈ °ü¼¼ ¿µÇ⠺м®ÀÌ Æ÷ÇԵǾî ÀÖ½À´Ï´Ù.

»óÈ£ ¹× ¾çÀÚ °£ ¹«¿ª°ú °ü¼¼ÀÇ ¿µÇ⠺м® :

¹Ì±¹ <>Áß±¹ <>¸ß½ÃÄÚ <>ij³ª´Ù <>EU <>ÀϺ» <>Àεµ <>±âŸ 176°³±¹

¾÷°è ÃÖ°íÀÇ ÀÌÄÚ³ë¹Ì½ºÆ®: Global Industry AnalystsÀÇ Áö½Ä ±â¹ÝÀº ±¹°¡, ½ÌÅ©ÅÊÅ©, ¹«¿ª ¹× »ê¾÷ ´Üü, ´ë±â¾÷, ±×¸®°í ¼¼°è °è·® °æÁ¦ »óȲÀÇ Àü·Ê ¾ø´Â ÆÐ·¯´ÙÀÓ ÀüȯÀÇ ¿µÇâÀ» °øÀ¯ÇÏ´Â ºÐ¾ßº° Àü¹®°¡ µî °¡Àå ¿µÇâ·Â ÀÖ´Â ¼ö¼® ÀÌÄÚ³ë¹Ì½ºÆ® ±×·ìÀ» Æ÷ÇÔÇÑ 14,949¸íÀÇ ÀÌÄÚ³ë¹Ì½ºÆ®¸¦ ÃßÀûÇϰí ÀÖ½À´Ï´Ù. 16,491°³ ÀÌ»óÀÇ º¸°í¼­ ´ëºÎºÐ¿¡ ¸¶ÀϽºÅæ¿¡ ±â¹ÝÇÑ 2´Ü°è Ãâ½Ã ÀÏÁ¤À» Àû¿ëÇϰí ÀÖ½À´Ï´Ù.

¸ñÂ÷

Á¦1Àå Á¶»ç ¹æ¹ý

Á¦2Àå °³¿ä

Á¦3Àå ½ÃÀå ºÐ¼®

Á¦4Àå °æÀï

KSA
¿µ¹® ¸ñÂ÷

¿µ¹®¸ñÂ÷

Global Artificial Intelligence Orchestration Market to Reach US$28.3 Billion by 2030

The global market for Artificial Intelligence Orchestration estimated at US$9.7 Billion in the year 2024, is expected to reach US$28.3 Billion by 2030, growing at a CAGR of 19.5% over the analysis period 2024-2030. AI Solutions, one of the segments analyzed in the report, is expected to record a 17.4% CAGR and reach US$17.2 Billion by the end of the analysis period. Growth in the AI Services segment is estimated at 23.4% CAGR over the analysis period.

The U.S. Market is Estimated at US$2.6 Billion While China is Forecast to Grow at 18.6% CAGR

The Artificial Intelligence Orchestration market in the U.S. is estimated at US$2.6 Billion in the year 2024. China, the world's second largest economy, is forecast to reach a projected market size of US$4.4 Billion by the year 2030 trailing a CAGR of 18.6% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 17.5% and 17.0% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 13.6% CAGR.

Global Artificial Intelligence Orchestration Market - Key Trends & Drivers Summarized

Why Is AI Orchestration Emerging as a Critical Layer in Enterprise Intelligence Architectures?

Artificial Intelligence Orchestration is fast becoming a pivotal enabler of scalable, enterprise-wide AI deployment by coordinating multiple AI/ML models, data pipelines, APIs, and automation workflows across distributed environments. In today’s increasingly complex AI ecosystems, where organizations employ diverse algorithms, platforms, and hardware infrastructures, orchestration acts as the connective tissue that harmonizes disparate AI components into cohesive, value-generating systems. It ensures that the right model is deployed, executed, monitored, and iteratively improved based on contextual needs and business rules-across cloud, on-premises, and edge environments.

As enterprises move beyond siloed AI experiments into production-grade AI solutions, orchestration addresses key operational challenges such as version control, model governance, data dependency management, compliance, and performance optimization. AI orchestration enables seamless integration of model lifecycle management (ML Ops), real-time inference, and decision automation at scale. It allows AI outputs to be embedded directly into business processes, IT systems, and customer-facing applications, transforming static insights into dynamic, system-wide intelligence. With demand growing for agile, transparent, and reliable AI, orchestration is emerging as a critical pillar of intelligent enterprise infrastructure.

How Are AI Orchestration Platforms Enhancing Operationalization and Lifecycle Management?

Modern AI orchestration platforms are designed to handle the full AI/ML lifecycle-from data ingestion and preprocessing to model training, deployment, monitoring, and retraining-within a unified and automated framework. These platforms leverage containerized microservices, CI/CD pipelines, and workflow engines to orchestrate tasks across development, testing, and production environments. Leading tools such as Kubeflow, MLflow, Airflow, and DataRobot, along with cloud-native orchestration solutions from AWS SageMaker, Azure ML, and Google Vertex AI, are enabling organizations to automate model rollout, scale compute resources, and reduce deployment friction.

In parallel, AI orchestration enhances explainability, auditability, and risk control through integrated model monitoring, drift detection, version tracking, and compliance checkpoints. Governance policies and access controls embedded into orchestration frameworks ensure that models are deployed responsibly and align with regulatory frameworks such as GDPR, HIPAA, and emerging AI ethics guidelines. Moreover, orchestration allows for intelligent routing of AI tasks-such as selecting the most suitable model based on use-case context, user profile, or real-time performance metrics. This results in more adaptive, resilient, and continuously learning AI systems that can evolve in live environments without human intervention.

Where Is Demand for AI Orchestration Growing and Which Sectors Are Leading Deployment?

Demand for AI orchestration is accelerating across data-intensive and automation-driven industries including financial services, healthcare, manufacturing, retail, telecom, and logistics. In financial services, orchestration is being used to manage fraud detection models, credit scoring engines, and algorithmic trading systems that must operate in real-time under strict regulatory oversight. Healthcare providers and life sciences firms are deploying AI orchestration to coordinate diagnostic models, genomics pipelines, clinical trial predictions, and patient engagement tools-where governance, traceability, and accuracy are paramount.

In manufacturing, AI orchestration is central to predictive maintenance, quality inspection, and supply chain optimization workflows that involve streaming sensor data and multiple inference engines. Retailers are using orchestration to align recommendation engines, inventory forecasts, dynamic pricing models, and customer segmentation in omnichannel environments. In telecom and smart infrastructure, orchestration supports AI-enabled network optimization, customer service bots, and IoT device management. Across these sectors, organizations are transitioning from experimentation to enterprise-grade AI, creating demand for orchestration capabilities that support scale, agility, and compliance in equal measure.

What Is Driving the Global Growth of the AI Orchestration Market?

The growth in the artificial intelligence orchestration market is driven by several converging trends, including the maturation of enterprise AI, the rising complexity of AI deployments, and the need for reliable, auditable, and scalable AI operations. As organizations invest in AI across multiple domains, orchestration is increasingly viewed as essential for avoiding model sprawl, siloed insights, and operational inefficiencies. A key driver is the enterprise shift toward ML Ops and DataOps practices that treat AI pipelines as software products-requiring automation, observability, and iterative improvement.

Advances in cloud-native architecture, containerization, low-code platforms, and open-source orchestration tools are lowering the barriers to AI operationalization. In parallel, regulatory scrutiny over AI fairness, accountability, and transparency is pushing organizations to adopt orchestration solutions with built-in compliance and lifecycle oversight. Strategic partnerships between AI platform vendors, cloud providers, and industry-specific solution integrators are also accelerating adoption by embedding orchestration into turnkey AI stacks. As AI evolves from discrete deployments into integrated enterprise systems, a critical question arises: Can AI orchestration scale fast enough to enable resilient, accountable, and continuously learning AI ecosystems across highly regulated and mission-critical environments?

SCOPE OF STUDY:

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

Segments:

Component (Solutions, Services); Deployment (On-Premise, Cloud); Application (Customer Service Orchestration, Infrastructure Orchestration, Manufacturing Orchestration, Other Applications); Vertical (IT & Telecommunications, Manufacturing, Healthcare, BFSI, Consumer Goods & Retail, Government & Defense, Energy & Utilities, Other Verticals)

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 36 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

(ÁÖ)±Û·Î¹úÀÎÆ÷¸ÞÀÌ¼Ç 02-2025-2992 kr-info@giikorea.co.kr
¨Ï Copyright Global Information, Inc. All rights reserved.
PC¹öÀü º¸±â