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¼¼°èÀÇ AIOps(IT ¿î¿µÀ» À§ÇÑ ÀΰøÁö´É) ½ÃÀå Àü¸Á(-2030³â) : ±¸¼º¿ä¼Òº°, ¹èÆ÷ À¯Çüº°, Á¶Á÷ ±Ô¸ðº°, ¿ëµµº°, ÃÖÁ¾ »ç¿ëÀÚº°, Áö¿ªº° ºÐ¼®

Artificial Intelligence for IT Operations (AIOps) Market Forecasts to 2030 - Global Analysis By Component (Solutions, Services and Other Components), Deployment Type, Organization Size, Application, End User and By Geography

¹ßÇàÀÏ: | ¸®¼­Ä¡»ç: Stratistics Market Research Consulting | ÆäÀÌÁö Á¤º¸: ¿µ¹® 200+ Pages | ¹è¼Û¾È³» : 2-3ÀÏ (¿µ¾÷ÀÏ ±âÁØ)

    
    
    



¡Ø º» »óǰÀº ¿µ¹® ÀÚ·á·Î Çѱ۰ú ¿µ¹® ¸ñÂ÷¿¡ ºÒÀÏÄ¡ÇÏ´Â ³»¿ëÀÌ ÀÖÀ» °æ¿ì ¿µ¹®À» ¿ì¼±ÇÕ´Ï´Ù. Á¤È®ÇÑ °ËÅ並 À§ÇØ ¿µ¹® ¸ñÂ÷¸¦ Âü°íÇØÁֽñ⠹ٶø´Ï´Ù.

Stratistics MRC¿¡ µû¸£¸é, AIOps(IT ¿î¿µÀ» À§ÇÑ ÀΰøÁö´É) ¼¼°è ½ÃÀåÀº 2024³â 49¾ï 9,000¸¸ ´Þ·¯¿¡ À̸£°í, ¿¹Ãø ±â°£ µ¿¾È 29%ÀÇ ¿¬Æò±Õ º¹ÇÕ ¼ºÀå·ü(CAGR)·Î ¼ºÀåÇÏ¿© 2030³â¿¡´Â 230¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

IT ¿î¿µÀ» À§ÇÑ ÀΰøÁö´É(AIOps)Àº ÀΰøÁö´É, ¸Ó½Å·¯´×, ºòµ¥ÀÌÅÍ ºÐ¼®À» ÅëÇØ IT ¿î¿µÀ» °­È­Çϰí ÀÚµ¿È­ÇÏ´Â °ÍÀ¸·Î, AIOps Ç÷§ÆûÀº ½Ç½Ã°£ µ¥ÀÌÅÍ ºÐ¼®, À̺¥Æ® »ó°ü°ü°è, ÀÌ»ó ¡ÈÄ °¨Áö, ÀÚµ¿È­µÈ »ç°í ´ëÀÀÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù. AIOps´Â ¹æ´ëÇÑ ¾çÀÇ IT µ¥ÀÌÅ͸¦ ¼öÁý ¹× ºÐ¼®ÇÏ¿© º¹ÀâÇØÁö´Â IT ȯ°æ¿¡¼­ ¼öÀÛ¾÷ °³ÀÔÀ» ÃÖ¼ÒÈ­Çϸ鼭 ½Ã½ºÅÛ ¼º´ÉÀ» ÃÖÀûÈ­Çϰí, ¹®Á¦¸¦ »çÀü¿¡ ¿¹Ãø ¹× ÇØ°áÇϸç, ´Ù¿îŸÀÓÀ» ÁÙÀÌ°í ¿î¿µ È¿À²¼ºÀ» Çâ»ó½Ãų ¼ö ÀÖ½À´Ï´Ù.

Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ ¹× ÇÏÀ̺긮µå ÀÎÇÁ¶ó µµÀÔ È®´ë

Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ°ú ÇÏÀ̺긮µå ÀÎÇÁ¶óÀÇ Ã¤ÅÃÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ±âÁ¸ÀÇ IT °ü¸® µµ±¸·Î´Â ÀÌ·¯ÇÑ º¹À⼺À» °¨´çÇÒ ¼ö ¾ø±â ¶§¹®¿¡ AIOps°¡ ÇʼöÀûÀÎ ¿ä¼Ò·Î ¶°¿À¸£°í ÀÖ½À´Ï´Ù. Àüü µ¥ÀÌÅ͸¦ ½Ç½Ã°£À¸·Î ó¸® ¹× ºÐ¼®ÇÏ¿© ½ÇÇà °¡´ÉÇÑ ÅëÂû·ÂÀ» Á¦°øÇϰí, ÀÛ¾÷À» ÀÚµ¿È­Çϸç, ÀáÀçÀûÀÎ ¹®Á¦¸¦ ¿¹ÃøÇÕ´Ï´Ù. À̸¦ ÅëÇØ IT ¿î¿µÀÇ ¼º´É, È®À强, È¿À²¼ºÀ» Çâ»ó½ÃÄÑ Á¶Á÷ÀÌ ÇÏÀ̺긮µå ¹× Ŭ¶ó¿ìµå ±â¹Ý ÀÎÇÁ¶ó·Î ÀüȯÇÔ¿¡ µû¶ó AIOps¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡Çϸ鼭 ½ÃÀå ¼ºÀåÀ» °ßÀÎÇϰí ÀÖ½À´Ï´Ù.

AIOpsÀÇ ÀåÁ¡¿¡ ´ëÇÑ ÀÌÇØ¿Í ÀνÄÀÌ ³·½À´Ï´Ù.

AIOpsÀÇ ÀÌÁ¡¿¡ ´ëÇÑ ÀÌÇØ¿Í ÀνÄÀÌ Á¦ÇÑÀû ¸¹Àº Á¶Á÷, ƯÈ÷ Áß¼Ò±â¾÷(SME)Àº AIOps°¡ ¾î¶»°Ô IT ¼º´ÉÀ» Çâ»ó½Ã۰í, ÇÁ·Î¼¼½º¸¦ ÀÚµ¿È­Çϸç, ¿î¿µ ºñ¿ëÀ» Àý°¨ÇÒ ¼ö ÀÖ´ÂÁö¿¡ ´ëÇØ Àß ¾ËÁö ¸øÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Áö½Ä ºÎÁ·Àº AIOps ¼Ö·ç¼Ç ÅõÀÚ¿¡ ´ëÇÑ È¸ÀÇÀûÀÎ ½Ã°¢°ú ¼Ò±ØÀûÀΠŵµ¸¦ ³º´Â´Ù. ¶ÇÇÑ, Àå±âÀûÀÎ ROI¸¦ ¸íÈ®ÇÏ°Ô ÆÄ¾ÇÇÏÁö ¸øÇÏ¸é ±â¾÷Àº AIOps µµÀÔÀ» ÁÖÀúÇÏ°Ô µÇ°í, ÀÚµ¿È­, È¿À²¼º, °æÀï ¿ìÀ§¸¦ È®º¸ÇÒ ¼ö ÀÖ´Â ±âȸ¸¦ ³õÄ¥ ¼ö ÀÖ½À´Ï´Ù. ±× °á°ú, ½ÃÀå ¼ºÀåÀÌ ¾ïÁ¦µÉ ¼ö ¹Û¿¡ ¾ø½À´Ï´Ù.

»çÀ̹ö º¸¾È¿¡ ´ëÇÑ °ü½É Áõ°¡

AI¿É½º´Â AI¿Í ¸Ó½Å·¯´×À» Ȱ¿ëÇÏ¿© ÀÌ»ó ¡Èĸ¦ ŽÁöÇϰí, ÀáÀçÀûÀÎ Ä§ÇØ °¡´É¼ºÀ» ¿¹ÃøÇϰí, ´ëÀÀÀ» ÀÚµ¿È­ÇÏ¿© »çÀ̹ö º¸¾ÈÀ» °­È­Çϰí, »ç°íÀÇ ½Å¼ÓÇÑ ÇØ°áÀ» À§ÇØ AI¿Í ¸Ó½Å·¯´×À» Ȱ¿ëÇÏ¿© »çÀ̹ö º¸¾ÈÀ» °­È­ÇÕ´Ï´Ù. AIOps´Â ¹æ´ëÇÑ ¾çÀÇ º¸¾È µ¥ÀÌÅ͸¦ ½Ç½Ã°£À¸·Î ºÐ¼®ÇÏ¿© ±â¾÷ÀÌ °ø°ÝÀ¸·ÎºÎÅÍ ¼±Á¦ÀûÀ¸·Î ¹æ¾îÇϰí, À§Çù¿¡ ´ëÇÑ °¡½Ã¼ºÀ» ³ôÀ̰í, Àü¹ÝÀûÀÎ º¸¾È ü°è¸¦ °­È­ÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇϸç, AIOps ¼Ö·ç¼ÇÀÇ µµÀÔÀ» °¡¼ÓÈ­ÇÕ´Ï´Ù.

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ºü¸¥ ±â¼ú Çõ½Å°ú »õ·Î¿î ¾Ë°í¸®Áò, µµ±¸ ¹× Ç÷§ÆûÀÇ ºó¹øÇÑ µµÀÔÀ¸·Î ÀÎÇØ ±â¾÷ÀÌ ÃֽŠAIOps ¼Ö·ç¼ÇÀ» À¯ÁöÇÏ´Â °ÍÀº ¾î·Á¿î ÀÏÀÔ´Ï´Ù. °ø±Þ¾÷ü´Â °æÀï·ÂÀ» À¯ÁöÇϱâ À§ÇØ ¿¬±¸°³¹ß¿¡ ¸¹Àº ÅõÀÚ¸¦ ÇØ¾ß Çϴµ¥, ÀÌ´Â ¸®¼Ò½º°¡ ÁýÁßµÉ ¼ö ÀÖ½À´Ï´Ù. ¶ÇÇÑ, ±Þ°ÝÇÑ º¯È­´Â ±âÁ¸ IT ½Ã½ºÅÛ°úÀÇ »óÈ£¿î¿ë¼º ¹®Á¦·Î À̾îÁ® ÅëÇÕ ¹× µµÀÔÀÇ º¹À⼺À» Áõ°¡½Ãų ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ¿ªÇÐÀº ¼Ò±Ô¸ð º¥´õ¸¦ ¾ÐµµÇϰí ÀáÀçÀû ±¸¸ÅÀÚ¿¡°Ô ºÒÈ®½Ç¼ºÀ» ÃÊ·¡ÇÒ ¼ö ÀÖ½À´Ï´Ù.

COVID-19ÀÇ ¿µÇâ

Äڷγª19 ÆÒµ¥¹ÍÀº ¿ø°Ý ±Ù¹«¿Í ¿Â¶óÀΠȰµ¿ Áõ°¡·Î ÀÎÇØ ±â¾÷ÀÌ µðÁöÅÐ ÀÎÇÁ¶ó¿¡ ´ëÇÑ ÀÇÁ¸µµ°¡ ³ô¾ÆÁö¸é¼­ AIOpsÀÇ Ã¤ÅÃÀ» °¡¼ÓÈ­½ÃÄ×½À´Ï´Ù. AIOps´Â Ŭ¶ó¿ìµå ȯ°æ °ü¸®, ½Ã½ºÅÛ ¼º´É ÃÖÀûÈ­, »çÀü ¹®Á¦ ÇØ°á¿¡ ÇʼöÀûÀÎ ¿ä¼Ò·Î ÀÚ¸® Àâ¾Ò½À´Ï´Ù. ±×·¯³ª °æ±â ºÒÅõ¸í¼ºÀ¸·Î ÀÎÇØ ÀϺΠÅõÀÚ, ƯÈ÷ Áß¼Ò±â¾÷ÀÇ ÅõÀÚ°¡ Áö¿¬µÇ¸é¼­ Àüü ½ÃÀåÀÇ ¼ºÀå ±Ëµµ¿¡ ´Ù¾çÇÑ ¿µÇâÀ» ¹ÌÄ¡°í ÀÖ½À´Ï´Ù.

¿¹Ãø ±â°£ µ¿¾È ¼­ºñ½º ºÐ¾ß°¡ °¡Àå Å« ºñÁßÀ» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

¼­ºñ½º ºÎ¹®Àº AIOps ¼Ö·ç¼ÇÀÇ µµÀÔ, ÅëÇÕ ¹× Áö¼ÓÀûÀÎ °ü¸®¿¡ ÇʼöÀûÀÎ Áö¿øÀ» Á¦°øÇÔÀ¸·Î½á À¯¸®ÇÑ ¼ºÀå¼¼¸¦ º¸ÀÏ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ÄÁ¼³ÆÃ ¼­ºñ½º´Â ±â¾÷ÀÌ ¿ä±¸ »çÇ×À» Æò°¡Çϰí Çʿ信 ¸Â´Â AIOps Àü·«À» ¼³°èÇÏ¿© È¿°úÀûÀÎ ¹èÆ÷¸¦ º¸ÀåÇÒ ¼ö ÀÖµµ·Ï µ½½À´Ï´Ù. ¸Å´ÏÁöµå ¼­ºñ½º´Â AIOps Ç÷§ÆûÀÇ Áö¼ÓÀûÀÎ ¸ð´ÏÅ͸µ, À¯Áöº¸¼ö ¹× ÃÖÀûÈ­¸¦ Á¦°øÇÏ¿© ¿î¿µ È¿À²¼ºÀ» ³ôÀÔ´Ï´Ù. Á¶Á÷ÀÌ AIOpsÀÇ ÀÌÁ¡À» ÃÖ´ëÇÑ È°¿ëÇÏ·Á´Â °æÇâÀÌ ³ô¾ÆÁü¿¡ µû¶ó Àü¹® ¼­ºñ½º¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡Çϸ鼭 ½ÃÀåÀÇ ¼ºÀå°ú º¸±ÞÀ» ÃËÁøÇϰí ÀÖ½À´Ï´Ù.

¿¹Ãø ±â°£ µ¿¾È °¡Àå ³ôÀº CAGRÀ» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµÇ´Â ºÎ¹®Àº Á¤ºÎ ±â°ü ºÎ¹®ÀÔ´Ï´Ù.

Á¤ºÎ ºÎ¹®Àº °ø°ø ¼­ºñ½ºÀÇ È¿À²¼º°ú ´ëÀÀ·ÂÀ» ³ôÀ̱â À§ÇØ AI ±â¹Ý ¼Ö·ç¼Ç äÅÃÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ¿¹Ãø ±â°£ µ¿¾È °¡Àå ³ôÀº CAGRÀ» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. Á¤ºÎ´Â AIOps¸¦ Ȱ¿ëÇÏ¿© IT ÀÎÇÁ¶ó¸¦ ¸ð´ÏÅ͸µÇϰí, ÀÚ¿ø ¹èºÐÀ» ÃÖÀûÈ­Çϸç, »çÀ̹ö º¸¾È Á¶Ä¡¸¦ °³¼±ÇÏ´Â µ¥ Ȱ¿ëÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, Á¤ºÎÀÇ ±ÔÁ¦¿Í AI R&D¿¡ ´ëÇÑ ÀÚ±Ý Áö¿øÀº AI¿É½º µµÀÔ¿¡ À¯¸®ÇÑ È¯°æÀ» Á¶¼ºÇϰí, ¹Î°£ º¥´õ¿ÍÀÇ ÅõÀÚ ¹× Çù¾÷ Áõ°¡·Î À̾îÁ® ½ÃÀå ¼ºÀåÀ» °¡¼ÓÇϰí ÀÖ½À´Ï´Ù.

°¡Àå Å« Á¡À¯À²À» Â÷ÁöÇÏ´Â Áö¿ª

¾Æ½Ã¾ÆÅÂÆò¾çÀº ´Ù¾çÇÑ »ê¾÷ ºÐ¾ß¿¡¼­ µðÁöÅÐ Çõ½Å ÀÌ´Ï¼ÅÆ¼ºêÀÇ Ã¤ÅÃÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ¿¹Ãø ±â°£ µ¿¾È °¡Àå Å« ½ÃÀå Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. Áß±¹, Àεµ, ÀϺ» µîÀÇ ±¹°¡¿¡¼­ Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ, ºòµ¥ÀÌÅÍ, AI ±â¼ú¿¡ ´ëÇÑ ´ë±Ô¸ð ÅõÀÚ·Î ITÀÇ È¿À²¼º°ú ¹Îø¼ºÀ» ³ôÀ̰í ÀÖÀ¸¸ç, IT ȯ°æÀÇ º¹À⼺°ú »çÀü ¿¹¹æÀû »ç°í °ü¸®ÀÇ Çʿ伺ÀÌ AI¿É½º ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä¸¦ ´õ¿í ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ´õ¿í ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, AI Çõ½Å°ú ½º¸¶Æ® ½ÃƼ ÀÌ´Ï¼ÅÆ¼ºê¿¡ ´ëÇÑ Á¤ºÎÀÇ Áö¿øÀº ½ÃÀå ¼ºÀåÀ» °¡¼ÓÈ­Çϰí ÀÖÀ¸¸ç, ¾Æ½Ã¾ÆÅÂÆò¾çÀº AI¿É½º Àü¸Á¿¡¼­ ÁÖ¿ä ±â¾÷·Î ÀÚ¸®¸Å±èÇϰí ÀÖ½À´Ï´Ù.

CAGRÀÌ °¡Àå ³ôÀº Áö¿ª :

ºÏ¹Ì´Â ÁÖ¿ä ±â¼ú ±â¾÷ÀÇ Á¸Àç¿Í ±¤¹üÀ§ÇÑ IT ÀÎÇÁ¶ó·Î ÀÎÇØ ¿¹Ãø ±â°£ µ¿¾È °¡Àå ³ôÀº CAGRÀ» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. Ŭ¶ó¿ìµå ÄÄÇ»ÆÃ, ºòµ¥ÀÌÅÍ ºÐ¼®, µðÁöÅÐ Àüȯ ÀÌ´Ï¼ÅÆ¼ºêÀÇ ³ôÀº äÅ÷üÀº ¿î¿µÀ» ÃÖÀûÈ­ÇÏ°í ¼­ºñ½º Á¦°øÀ» °­È­ÇϰíÀÚ ÇÏ´Â ±â¾÷µéÀÇ AIOps ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä¸¦ ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, »çÀ̹ö À§Çù Áõ°¡¿Í ±ÔÁ¦ Áؼö ¿ä±¸ »çÇ×À¸·Î ÀÎÇØ ±â¾÷µéÀº º¸¾È°ú ¿î¿µ È¿À²¼ºÀ» °³¼±Çϱâ À§ÇØ AIOps¿¡ ´ëÇÑ ÅõÀÚ¸¦ ´Ã¸®°í ÀÖ½À´Ï´Ù. ÀÌ Áö¿ªÀº ±â¼ú Çõ½Å°ú ±â¼ú ÅëÇÕ¿¡ ÁßÁ¡À» µÎ°í ÀÖ¾î ¼¼°è AIOps ½ÃÀåÀÇ ÁÖ¿ä ±â¾÷·Î ÀÚ¸®¸Å±èÇϰí ÀÖ½À´Ï´Ù.

¹«·á Ä¿½ºÅ͸¶ÀÌ¡ ¼­ºñ½º

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Á¦5Àå AIOps(IT ¿î¿µÀ» À§ÇÑ ÀΰøÁö´É) ¼¼°è ½ÃÀå : ÄÄÆ÷³ÍÆ®º°

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    • µ¥ÀÌÅÍ ºÐ¼®
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  • AppDynamics
  • DataDog
  • BigPanda
  • New Relic
  • IBM Instana
  • Moogsoft
  • Dynatrace
  • LogicMonitor
  • Splunk
  • BMC
  • PagerDuty
  • ScienceLogic
  • Zabbix
  • Elastic
  • Cisco
  • Sumo Logic
  • Servicenow
  • Freshservice
  • CloudHealth
  • OpsRamp
LSH 24.11.11

According to Stratistics MRC, the Global Artificial Intelligence for IT Operations (AIOPS) Market is accounted for $4.99 billion in 2024 and is expected to reach $23.00 billion by 2030 growing at a CAGR of 29% during the forecast period. Artificial Intelligence for IT Operations (AIOps) refers to the use of artificial intelligence, machine learning, and big data analytics to enhance and automate IT operations. AIOps platforms enable real-time data analysis, event correlation, anomaly detection, and automated incident response. By collecting and analyzing vast amounts of IT data, AIOps helps organizations optimize system performance, predict and resolve issues proactively, reduce downtime, and improve operational efficiency, all while minimizing manual intervention in increasingly complex IT environments.

Market Dynamics:

Driver:

Growing adoption of cloud computing and hybrid infrastructures

The growing adoption of cloud computing and hybrid infrastructures is because traditional IT management tools struggle to handle this complexity, making AIOps essential. AIOps platforms leverage AI and machine learning to process and analyze data across cloud and on-premises systems in real-time, providing actionable insights, automating tasks, and predicting potential issues. This enhances the performance, scalability, and efficiency of IT operations, driving the demand for AIOps as organizations transition to hybrid and cloud-based infrastructures, fuelling the growth of the market.

Restraint:

Limited understanding and awareness of AIOps benefits

Limited understanding and awareness of AIOps benefits many organizations, particularly small and medium-sized enterprises (SMEs), may not fully grasp how AIOps can enhance IT performance, automate processes, and reduce operational costs. This lack of knowledge creates scepticism and reluctance to invest in AIOps solutions. Additionally, without clear visibility into the long-term ROI, businesses may hesitate to adopt AIOps, leading to missed opportunities for automation, efficiency gains, and competitive advantage. Consequently, market growth is constrained.

Opportunity:

Increased focus on cybersecurity

The cybersecurity threats grow in complexity, traditional security measures struggle to keep pace. AIOps enhances cybersecurity by leveraging AI and machine learning to detect anomalies, predict potential breaches, and automate responses, ensuring faster incident resolution. By analyzing vast amounts of security data in real-time, AIOps helps organizations proactively defend against attacks, improve threat visibility, and strengthen their overall security posture, accelerating the adoption of AIOps solutions.

Threat:

Rapid technological change

Rapid technological change and new algorithms, tools, and platforms are frequently introduced, making it difficult for companies to maintain up-to-date AIOps solutions. Vendors need to invest heavily in R&D to stay competitive, which can be resource-intensive. Additionally, rapid changes may lead to interoperability issues with existing IT systems, increasing the complexity of integration and adoption. These dynamics can also overwhelm smaller vendors and create uncertainty for potential buyers.

Covid-19 Impact

The COVID-19 pandemic accelerated the adoption of AIOps as businesses increasingly relied on digital infrastructures due to remote work and heightened online activity. The surge in IT workloads and complexity drove demand for automated solutions to ensure operational continuity and efficiency. AIOps became essential for managing cloud environments, optimizing system performance, and resolving issues proactively. However, economic uncertainty delayed some investments, particularly in small to mid-sized businesses, creating mixed effects on the market's overall growth trajectory.

The services segment is expected to be the largest during the forecast period

The services segment is estimated to have a lucrative growth, by providing essential support for implementation, integration, and ongoing management of AIOps solutions. Consulting services help organizations assess their needs and design tailored AIOps strategies, ensuring effective deployment. Managed services enhance operational efficiency by offering continuous monitoring, maintenance, and optimization of AIOps platforms. As organizations increasingly seek to maximize the benefits of AIOps, the demand for specialized services drives market growth and adoption.

The government segment is expected to have the highest CAGR during the forecast period

The government segment is anticipated to witness the highest CAGR growth during the forecast period, due to increased adoption AI-driven solutions to enhance efficiency and responsiveness in public services. Governments utilize AIOps for monitoring IT infrastructure, optimizing resource allocation, and improving cybersecurity measures. Additionally, government regulations and funding for AI research and development create a favourable environment for AIOps adoption, leading to increased investments and collaboration with private sector vendors, thereby driving market growth.

Region with largest share:

Asia Pacific is projected to hold the largest market share during the forecast period driven by the increasing adoption of digital transformation initiatives across various industries. Countries like China, India, and Japan are witnessing significant investments in cloud computing, big data, and AI technologies, which enhance IT efficiency and agility. The rising complexity of IT environments and the need for proactive incident management further fuel demand for AIOps solutions. Additionally, government support for AI innovation and smart city initiatives is accelerating market growth, positioning Asia Pacific as a key player in the AIOps landscape.

Region with highest CAGR:

North America is projected to have the highest CAGR over the forecast period, owing to the presence of leading technology companies and extensive IT infrastructure. High adoption rates of cloud computing, big data analytics, and digital transformation initiatives fuel demand for AIOps solutions among enterprises seeking to optimize operations and enhance service delivery. Additionally, increasing cyber threats and regulatory compliance requirements prompt organizations to invest in AIOps for improved security and operational efficiency. The region's focus on innovation and technology integration positions it as a key player in the global AIOps market.

Key players in the market

Some of the key players profiled in the Artificial Intelligence for IT Operations (AIOps) Market include AppDynamics , DataDog, BigPanda, New Relic, IBM Instana, Moogsoft, Dynatrace, LogicMonitor, Splunk, BMC, PagerDuty, ScienceLogic, Zabbix, Elastic, Cisco, Sumo Logic, Servicenow, Freshservice, CloudHealth and OpsRamp.

Key Developments:

In August 2024, Dynatrace partnered with Google Cloud to enhance observability solutions for customers, leveraging Google Cloud's infrastructure and AI capabilities to improve application performance and user experiences.

In June 2023, DataDog announced a partnership with Snowflake to enhance observability and security for cloud applications. This integration enables users to analyze DataDog data alongside their Snowflake data, providing deeper insights into performance and security.

In March 2023, DataDog introduced Security Monitoring, a new product designed to enhance threat detection and incident response capabilities within its observability platform, enabling organizations to monitor and respond to security threats in real-time.

Components Covered:

  • Solutions
  • Services
  • Other Components

Deployment Types Covered:

  • On-Premises
  • Cloud-Based
  • Other Deployment Types

Organization Sizes Covered:

  • Small and Medium-Sized Enterprises (SMEs)
  • Large Enterprises
  • Other Organization Sizes

Applications Covered:

  • Incident Management
  • Performance Monitoring
  • Root Cause Analysis
  • Change Management
  • Predictive Analytics
  • Other Applications

End Users Covered:

  • IT and Telecommunications
  • Banking, Financial Services, and Insurance
  • Healthcare
  • Retail
  • Manufacturing
  • Government
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence for IT Operations (AIOps) Market, By Component

  • 5.1 Introduction
  • 5.2 Solutions
    • 5.2.1 Machine Learning
    • 5.2.2 Natural Language Processing (NLP)
    • 5.2.3 Data Analytics
  • 5.3 Services
    • 5.3.1 Consulting
    • 5.3.2 Implementation
    • 5.3.3 Support and Maintenance
  • 5.4 Other Components

6 Global Artificial Intelligence for IT Operations (AIOps) Market, By Deployment Type

  • 6.1 Introduction
  • 6.2 On-Premises
  • 6.3 Cloud-Based
  • 6.4 Other Deployment Types

7 Global Artificial Intelligence for IT Operations (AIOps) Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Small and Medium-Sized Enterprises (SMEs)
  • 7.3 Large Enterprises
  • 7.4 Other Organization Sizes

8 Global Artificial Intelligence for IT Operations (AIOps) Market, By Application

  • 8.1 Introduction
  • 8.2 Incident Management
  • 8.3 Performance Monitoring
  • 8.4 Root Cause Analysis
  • 8.5 Change Management
  • 8.6 Predictive Analytics
  • 8.7 Other Applications

9 Global Artificial Intelligence for IT Operations (AIOps) Market, By End User

  • 9.1 Introduction
  • 9.2 IT and Telecommunications
  • 9.3 Banking, Financial Services, and Insurance
  • 9.4 Healthcare
  • 9.5 Retail
  • 9.6 Manufacturing
  • 9.7 Government
  • 9.8 Other End Users

10 Global Artificial Intelligence for IT Operations (AIOps) Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 AppDynamics
  • 12.2 DataDog
  • 12.3 BigPanda
  • 12.4 New Relic
  • 12.5 IBM Instana
  • 12.6 Moogsoft
  • 12.7 Dynatrace
  • 12.8 LogicMonitor
  • 12.9 Splunk
  • 12.10 BMC
  • 12.11 PagerDuty
  • 12.12 ScienceLogic
  • 12.13 Zabbix
  • 12.14 Elastic
  • 12.15 Cisco
  • 12.16 Sumo Logic
  • 12.17 Servicenow
  • 12.18 Freshservice
  • 12.19 CloudHealth
  • 12.20 OpsRamp
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