½ÃÀ庸°í¼­
»óǰÄÚµå
1611943

¼¼°èÀÇ È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå : Á¦°ø Á¦Ç°, ±â¼ú, Àü°³, ¿ëµµ, ÃÖÁ¾ ¿ëµµº° ¿¹Ãø(2025-2030³â)

AI in Chemical & Material Informatics Market by Offering (Services, Software), Technology (Computer Vision, Machine Learning, Predictive Analytics), Deployment, Application, End-Use - Global Forecast 2025-2030

¹ßÇàÀÏ: | ¸®¼­Ä¡»ç: 360iResearch | ÆäÀÌÁö Á¤º¸: ¿µ¹® 185 Pages | ¹è¼Û¾È³» : 1-2ÀÏ (¿µ¾÷ÀÏ ±âÁØ)

    
    
    




¡á º¸°í¼­¿¡ µû¶ó ÃֽŠÁ¤º¸·Î ¾÷µ¥ÀÌÆ®ÇÏ¿© º¸³»µå¸³´Ï´Ù. ¹è¼ÛÀÏÁ¤Àº ¹®ÀÇÇØ Áֽñ⠹ٶø´Ï´Ù.

È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀÇ 2023³â ½ÃÀå ±Ô¸ð´Â 86¾ï 9,000¸¸ ´Þ·¯·Î Æò°¡µÇ¾ú½À´Ï´Ù. 2024³â¿¡´Â 120¾ï 8,000¸¸ ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµÇ°í, º¹ÇÕ ¿¬°£ ¼ºÀå·ü(CAGR) 39.46%·Î ¼ºÀåÇÏ¿© 2030³â¿¡´Â 892¾ï 9,000 ¸¸¹Ì ´Þ·¯¿¡ µµ´ÞÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´ÉÀÇ ´ë»ó ¹üÀ§¿¡´Â Àç·á ¹× È­ÇÐ °øÁ¤ÀÇ ¹ß°ß, ¼³°è ¹× ÃÖÀûÈ­¸¦ °¡¼ÓÈ­Çϱâ À§ÇÑ ÀΰøÁö´ÉÀÇ ÅëÇÕÀÌ Æ÷ÇԵ˴ϴÙ. Ư¼ºÀ» ¿¹ÃøÇϰí, ±â´É¼ºÀ» Á¶Á¤ÇÑ ½Å±Ô Àç·á¸¦ ¼³°èÇÏ´Â AIÀÇ ´É·ÂÀÌ ÇÊ¿äÇÕ´Ï´Ù. Áö¼Ó °¡´É ´É·üÀûÀ̰í È¿À²ÀûÀÎ Á¦Á¶ °øÁ¤¸¦ ½ÇÇöÇϱâ À§ÇØ ³ë·ÂÇϰí ÀÖÀ¸¸ç, ÀÌ¿¡ µû¶ó ¿¬±¸ °³¹ß°ú °ü·ÃµÈ ½Ã°£°ú ºñ¿ëÀ» Å©°Ô ÁÙÀÏ ¼ö ÀÖ½À´Ï´Ù. AI ±â¼úÀÇ ¹ßÀü°ú ÇÔ²² °¡Á× ½Å±ÔÇϰí È¿À²ÀûÀÎ Àç·á ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡¿¡ ¿µÇâÀ» ¹Þ°í ÀÖ½À´Ï´Ù. ƯÈ÷ Á¤È®¼ºÀ» ´õ¿í ³ôÀÌ°í ¹ß°ß±îÁöÀÇ ±â°£À» ´ÜÃàÇÏ´Â AI ¸ðµ¨ÀÇ °³¹ß¿¡´Â ±â¾÷ÀÌ °æÀï·ÂÀ» À¯ÁöÇÒ ¼ö ÀÖµµ·Ï ÇÏ´Â Àý´ë ¼ºÀå ±âȸ°¡ ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ±âȸ¸¦ »ì¸®±â À§ÇÑ Á¦¾ÈÀ¸·Î¼­´Â °í±Þ °è»ê ¾Ë°í¸®Áò¿¡ ´ëÇÑ ÅõÀÚ³ª È­ÇÐ, Àç·á °úÇÐ, AIÀÇ Àü¹® Áö½ÄÀ» Ȱ¿ëÇϱâ À§ÇÑ ºÐ¾ß Ⱦ´ÜÀûÀÎ Çù·Â °ü°èÀÇ Çü¼ºµîÀÌ ÀÖ½À´Ï´Ù. ¹Ý¸é, °íǰÁú ÀÌ·¯ÇÑ µ¥ÀÌÅÍÀÇ ºÎÁ·°ú AI ±â¼ú°ú ±âÁ¸ ½Ã½ºÅÛ °£ÀÇ ÅëÇÕ º¹À⼺°ú °°Àº °úÁ¦µµ ³²¾Æ ÀÖ½À´Ï´Ù.ÀÇ Á¦¾àÀ» ±Øº¹Çϱâ À§ÇØ Àº °ß°íÇÑ µ¥ÀÌÅÍ ¼öÁý ¹× °ËÁõ ÇÁ·¹ÀÓ¿öÅ©, º¹ÀâÇÑ È­ÇÐ µ¥ÀÌÅ͸¦ ´Ù·ê ¼ö ÀÖ´Â È®Àå °¡´ÉÇÑ AI ¸ðµ¨ÀÇ °³¹ß¿¡ Çõ½ÅÀÇ °¡´É¼ºÀÌ ÀÖ½À´Ï´Ù. ¾÷°è Àüü¿¡¼­ÀÇ Ã¤¿ëÀ» ÃËÁøÇϴµ¥µµ ÁÖ·ÂÇÒ ¼ö ÀÖ½À´Ï´Ù. »õ·Î¿î AI ´É·Â¿¡ ´ëÇÑ ÀûÀÀÀ» ¿ì¼±ÇØ¾ß ÇÕ´Ï´Ù.

ÁÖ¿ä ½ÃÀå Åë°è
±âÁسâ(2023) 86¾ï 9,000¸¸ ´Þ·¯
ÃßÁ¤³â(2024) 120¾ï 8,000¸¸ ´Þ·¯
¿¹Ãø³â(2030) 892¾ï 9,000¸¸ ´Þ·¯
º¹ÇÕ ¿¬°£ ¼ºÀå·ü(CAGR)(%) 39.46%

½ÃÀå ¿ªÇÐ : ±Þ¼ÓÈ÷ ÁøÈ­ÇÏ´Â È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀÇ ÁÖ¿ä ½ÃÀå ÀλçÀÌÆ® °ø°³

È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀº ¼ö¿ä ¹× °ø±ÞÀÇ ¿ªµ¿ÀûÀÎ »óÈ£ÀÛ¿ë¿¡ ÀÇÇØ º¯¸ð¸¦ ÀÌ·ç°í ÀÖ½À´Ï´Ù. °áÁ¤ÀÇ Á¤±³È­¿Í »õ·Î¿î ºñÁî´Ï½º ±âȸ ȹµæ¿¡ ´ëºñ ÀÌ·¯ÇÑ µ¿ÇâÀ» Á¾ÇÕÀûÀ¸·Î ÆÄ¾ÇÇÔÀ¸·Î½á ±â¾÷Àº Á¤Ä¡Àû, Áö¸®Àû, ±â¼úÀû, »çȸÀû, °æÁ¦ÀûÀÎ ¿µ¿ª¿¡ °ÉÄ£ ´Ù¾çÇÑ ¸®½ºÅ©¸¦ °æ°¨ÇÒ ¼ö ÀÖÀ½°ú µ¿½Ã¿¡ ¼ÒºñÀÚ Çൿ ±×¸®°í ±×°ÍÀÌ Á¦Á¶ ºñ¿ë°ú ±¸¸Å µ¿Çâ¿¡ ¹ÌÄ¡´Â ¿µÇâÀ»º¸´Ù ¸íÈ®ÇÏ°Ô ÀÌÇØÇÒ ¼ö ÀÖ½À´Ï´Ù.

  • ½ÃÀå ¼ºÀå ÃËÁø¿äÀÎ
    • È­Çлê¾÷¿¡ À־ÀÇ Àç·áÀÇ ¹ß°ß°ú ½ÇÇèÀÇ °¡¼Ó¿¡ ¼ö¹ÝÇÏ´Â µ¥ÀÌÅÍ »ý¼º Áõ°¡
    • Àç·áƯ¼º°ú È­ÇйÝÀÀ ¿¹Ãø ¸ðµ¨¸µ¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡
  • ½ÃÀå ¼ºÀå ¾ïÁ¦¿äÀÎ
    • È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ¼Ö·ç¼ÇÀÇ µµÀÔ ºñ¿ëÀÇ ³ôÀÌ
  • ½ÃÀå ±âȸ
    • È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ¼Ö·ç¼ÇÀÇ Áö¼ÓÀûÀÎ ±â¼ú Áøº¸
    • ȯ°æ ģȭÀû ÀÎ Àç·á ¹× °øÁ¤ ¼³°è¿¡ ´ëÇÑ »õ·Î¿î ÀÀ¿ë
  • ½ÃÀåÀÇ °úÁ¦
    • È­ÇÐ, Àç·á Á¤º¸Çп¡¼­ AI »ç¿ë¿¡ µû¸¥ µ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã¿Í º¸¾È ¿ì·Á

Porter's Five Forces : È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀ» Ž»öÇÏ´Â Àü·« µµ±¸

Porter's Five Forces Framework´Â È­ÇÐ ¹× Àç·á ÀÎÆ÷¸Åƽ½º¿¡¼­ AI ½ÃÀå °æÀï ±¸µµ¸¦ ÀÌÇØÇÏ´Â Áß¿äÇÑ µµ±¸ÀÔ´Ï´Ù. Porter's Five Forces Framework´Â ±â¾÷ÀÇ °æÀï·ÂÀ» Æò°¡Çϰí Àü·«Àû ±âȸ¸¦ ޱ¸ÇÏ´Â ¸íÈ®ÇÑ ±â¼úÀ» Á¦°øÇÕ´Ï´Ù. ÀÌ ÇÁ·¹ÀÓ¿öÅ©´Â ±â¾÷ÀÌ ½ÃÀå ³» ¼¼·Âµµ¸¦ Æò°¡ÇÏ°í ½Å±Ô »ç¾÷ÀÇ ¼öÀͼºÀ» ÆÇ´ÜÇÏ´Â µ¥ µµ¿òÀÌ µË´Ï´Ù. ÀÌ·¯ÇÑ ÀλçÀÌÆ®À» ÅëÇØ ±â¾÷Àº ÀÚ»çÀÇ °­Á¡À» Ȱ¿ëÇÏ°í ¾àÁ¡À» ÇØ°áÇϰí ÀáÀçÀûÀÎ °úÁ¦¸¦ ÇÇÇÔÀ¸·Î½á º¸´Ù °­ÀÎÇÑ ½ÃÀå¿¡¼­ÀÇ Æ÷Áö¼Å´×À» È®º¸ÇÒ ¼ö ÀÖ½À´Ï´Ù.

PESTLE ºÐ¼® : È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀÇ ¿ÜºÎ ¿µÇâÀ» ÆÄ¾Ç

¿ÜºÎ °Å½Ã ȯ°æ ¿äÀÎÀº È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀÇ ¼º°ú ¿ªÇÐÀ» Çü¼ºÇÏ´Â µ¥ Áß¿äÇÑ ¿ªÇÒÀ» ÇÕ´Ï´Ù. Á¤Ä¡Àû, °æÁ¦Àû, »çȸÀû, ±â¼úÀû, ¹ýÀû ¹× ȯ°æÀû ¿äÀÎ ºÐ¼® ÀÌ·¯ÇÑ ¿µÇâÀ» Ž»öÇÏ´Â µ¥ ÇÊ¿äÇÑ Á¤º¸¸¦ Á¦°øÇÕ´Ï´Ù.PESTLE ¿äÀÎÀ» Á¶»çÇÔÀ¸·Î½á ±â¾÷Àº ÀáÀçÀûÀÎ À§Çè°ú ±âȸ¸¦ ´õ Àß ÀÌÇØÇÒ ¼ö ÀÖ½À´Ï´Ù. ¿¹ÃøÇÏ°í ¾ÕÀ¸·Î ¿¹»óÇÏ´Â Àû±ØÀûÀÎ ÀÇ»ç °áÁ¤À» ÇÒ Áغñ°¡ µË´Ï´Ù.

½ÃÀå Á¡À¯À² ºÐ¼® È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå °æÀï ±¸µµ ÆÄ¾Ç

È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀÇ »ó¼¼ÇÑ ½ÃÀå Á¡À¯À² ºÐ¼®À» ÅëÇØ °ø±Þ¾÷üÀÇ ¼º°ú¸¦ Á¾ÇÕÀûÀ¸·Î Æò°¡ÇÒ ¼ö ÀÖ½À´Ï´Ù. ±â¾÷Àº ¼öÀÍ, °í°´ ±â¹Ý, ¼ºÀå·ü µî ÁÖ¿ä ÁöÇ¥¸¦ ºñ±³ÇÏ¿© °æÀï Æ÷Áö¼Å´×À» ¹àÈú ¼ö ÀÖ½À´Ï´Ù. ÀÌ ºÐ¼®À» ÅëÇØ ½ÃÀå ÁýÁß, ´ÜÆíÈ­, ÅëÇÕ µ¿ÇâÀ» ¹àÇô³»°í º¥´õµéÀº °æÀïÀÌ Ä¡¿­ÇØÁö´Â °¡¿îµ¥ ÀÚ»çÀÇ ÁöÀ§¸¦ ³ôÀÌ´Â Àü·«Àû ÀÇ»ç °áÁ¤À» ³»¸®´Â µ¥ ÇÊ¿äÇÑ Áö½ÄÀ» ¾òÀ» ¼ö ÀÖ½À´Ï´Ù.

FPNV Æ÷Áö¼Å´×, ¸ÅÆ®¸¯½º È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå¿¡¼­ °ø±Þ¾÷üÀÇ ¼º´É Æò°¡

FPNV Æ÷Áö¼Å´× ¸ÅÆ®¸¯½º´Â È­ÇÐ ¹× Àç·á ÀÎÆ÷¸Åƽ½º¿¡¼­ AI ½ÃÀå¿¡¼­ º¥´õ¸¦ Æò°¡ÇÏ´Â Áß¿äÇÑ µµ±¸ÀÔ´Ï´Ù. ÀÌ Çà·ÄÀ» ÅëÇØ ºñÁî´Ï½º Á¶Á÷Àº °ø±Þ¾÷üÀÇ ºñÁî´Ï½º Àü·«°ú Á¦Ç° ¸¸Á·µµ¸¦ ±âÁØÀ¸·Î Æò°¡ÇÏ¿© ¸ñÇ¥¿¡ ¸Â´Â ÃæºÐÇÑ Á¤º¸¸¦ ¹ÙÅÁÀ¸·Î ÀÇ»ç °áÁ¤À» ³»¸± ¼ö ÀÖ½À´Ï´Ù. ³× °¡Áö »çºÐ¸éÀ» ÅëÇØ °ø±Þ¾÷ü¸¦ ¸íÈ®Çϰí Á¤È®ÇÏ°Ô ¼¼ºÐÈ­ÇÏ¿© Àü·« ¸ñÇ¥¿¡ °¡Àå ÀûÇÕÇÑ ÆÄÆ®³Ê ¹× ¼Ö·ç¼ÇÀ» ÆÄ¾ÇÇÒ ¼ö ÀÖ½À´Ï´Ù.

Àü·« ºÐ¼® ¹× ±ÇÀå È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀåÀÇ ¼º°ø¿¡ ´ëÇÑ ±æÀ» ±×¸³´Ï´Ù.

È­ÇÐ, Àç·á Á¤º¸Çп¡¼­ AI ½ÃÀåÀÇ Àü·« ºÐ¼®Àº ½ÃÀå¿¡¼­ÀÇ ÇÁ·¹Á𽺠°­È­¸¦ ¸ñÇ¥·Î ÇÏ´Â ±â¾÷¿¡ ÇʼöÀûÀÔ´Ï´Ù. ÀÌ Á¢±Ù¹ýÀ» ÅëÇØ °æÀï ±¸µµ¿¡¼­ °úÁ¦¸¦ ±Øº¹ÇÏ°í »õ·Î¿î ºñÁî´Ï½º ±âȸ¸¦ Ȱ¿ëÇÏ¿© Àå±âÀûÀÎ ¼º°øÀ» ÀÌ·ç±âÀ§ÇÑ ½Ã½ºÅÛÀ» ±¸Ãà ÇÒ ¼ö ÀÖ½À´Ï´Ù.

ÀÌ º¸°í¼­´Â ÁÖ¿ä °ü½É ºÐ¾ß¸¦ Æ÷°ýÇÏ´Â ½ÃÀåÀÇ Á¾ÇÕÀûÀÎ ºÐ¼®À» Á¦°øÇÕ´Ï´Ù.

1. ½ÃÀå ħÅõ : ÇöÀç ½ÃÀå ȯ°æÀÇ »ó¼¼ÇÑ °ËÅä, ÁÖ¿ä ±â¾÷ÀÇ ±¤¹üÀ§ÇÑ µ¥ÀÌÅÍ, ½ÃÀå µµ´Þ¹üÀ§ ¹× Àü¹ÝÀûÀÎ ¿µÇâ·Â Æò°¡.

2. ½ÃÀå °³Ã´µµ : ½ÅÈï ½ÃÀåÀÇ ¼ºÀå ±âȸ¸¦ ÆÄ¾ÇÇÏ°í ±âÁ¸ ºÐ¾ßÀÇ È®Àå °¡´É¼ºÀ» Æò°¡ÇÏ¸ç ¹Ì·¡ ¼ºÀåÀ» À§ÇÑ Àü·«Àû ·Îµå¸ÊÀ» Á¦°øÇÕ´Ï´Ù.

3. ½ÃÀå ´Ù¾çÈ­ : ÃÖ±Ù Á¦Ç° Ãâ½Ã, ¹Ì°³Ã´ Áö¿ª, ¾÷°èÀÇ ÁÖ¿ä Áøº¸, ½ÃÀåÀ» Çü¼ºÇÏ´Â Àü·«Àû ÅõÀÚ¸¦ ºÐ¼®ÇÕ´Ï´Ù.

4. °æÀï Æò°¡ ¹× Á¤º¸ : °æÀï ±¸µµ¸¦ öÀúÈ÷ ºÐ¼®ÇÏ¿© ½ÃÀå Á¡À¯À², »ç¾÷ Àü·«, Á¦Ç° Æ÷Æ®Æú¸®¿À, ÀÎÁõ, ±ÔÁ¦ ´ç±¹ ½ÂÀÎ, ƯÇã µ¿Çâ, ÁÖ¿ä ±â¾÷ÀÇ ±â¼ú Áøº¸ µîÀ» °ËÁõÇÕ´Ï´Ù.

5. Á¦Ç° °³¹ß ¹× Çõ½Å : ¹Ì·¡ ½ÃÀå ¼ºÀåÀ» °¡¼ÓÇÒ °ÍÀ¸·Î ¿¹»óµÇ´Â ÃÖ÷´Ü ±â¼ú, R&D Ȱµ¿, Á¦Ç° Çõ½ÅÀ» °­Á¶ÇÕ´Ï´Ù.

¶ÇÇÑ ÀÌÇØ°ü°èÀÚ°¡ ÃæºÐÇÑ Á¤º¸¸¦ ¾ò°í ÀÇ»ç°áÁ¤À» ÇÒ ¼ö ÀÖµµ·Ï Áß¿äÇÑ Áú¹®¿¡ ´ë´äÇϰí ÀÖ½À´Ï´Ù.

1. ÇöÀç ½ÃÀå ±Ô¸ð¿Í ÇâÈÄ ¼ºÀå ¿¹ÃøÀº?

2. ÃÖ°íÀÇ ÅõÀÚ ±âȸ¸¦ Á¦°øÇÏ´Â Á¦Ç°, ºÎ¹® ¹× Áö¿ªÀº ¾îµðÀԴϱî?

3. ½ÃÀåÀ» Çü¼ºÇÏ´Â ÁÖ¿ä ±â¼ú µ¿Çâ°ú ±ÔÁ¦ÀÇ ¿µÇâÀº?

4. ÁÖ¿ä º¥´õÀÇ ½ÃÀå Á¡À¯À²°ú °æÀï Æ÷Áö¼ÇÀº?

5. º¥´õ ½ÃÀå ÁøÀÔ, ö¼ö Àü·«ÀÇ ¿øµ¿·ÂÀÌ µÇ´Â ¼öÀÍ¿ø°ú Àü·«Àû ±âȸ´Â ¹«¾ùÀΰ¡?

¸ñÂ÷

Á¦1Àå ¼­¹®

Á¦2Àå Á¶»ç ¹æ¹ý

Á¦3Àå ÁÖ¿ä ¿ä¾à

Á¦4Àå ½ÃÀå °³¿ä

Á¦5Àå ½ÃÀå ÀλçÀÌÆ®

  • ½ÃÀå ¿ªÇÐ
    • ¼ºÀå ÃËÁø¿äÀÎ
      • È­Çлê¾÷¿¡ À־ÀÇ Àç·á ¹ß°ß°ú ½ÇÇèÀÇ °¡¼Ó¿¡ ÀÇÇÑ µ¥ÀÌÅÍ »ý¼º Áõ°¡
      • Àç·á Ư¼º°ú È­ÇÐ ¹ÝÀÀÀÇ ¿¹Ãø ¸ðµ¨¸µ ¼ö¿ä Áõ°¡
    • ¾ïÁ¦¿äÀÎ
      • È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ¼Ö·ç¼ÇÀÇ µµÀÔ ºñ¿ëÀÌ ³ô´Ù
    • ±âȸ
      • È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ¼Ö·ç¼Ç¿¡ À־ÀÇ Áö¼ÓÀûÀÎ ±â¼ú Áøº¸
      • ȯ°æ ģȭÀû ÀÎ Àç·á ¹× °øÁ¤ ¼³°è¸¦À§ÇÑ »õ·Î¿î ÀÀ¿ë
    • °úÁ¦
      • È­ÇÐ, Àç·á Á¤º¸Çп¡¼­ AI »ç¿ë°ú °ü·ÃµÈ µ¥ÀÌÅÍÀÇ ÇÁ¶óÀ̹ö½Ã¿Í º¸¾È¿¡ ´ëÇÑ ¿ì·Á
  • ½ÃÀå ¼¼ºÐÈ­ ºÐ¼®
    • Á¦°ø ³»¿ë : ¿¹Ãø ´É·Â¿¡ ÀÇÇØ È­ÇÐ, Àç·á Á¤º¸Çп¡ À־ÀÇ AI ¼ÒÇÁÆ®¿þ¾îÀÇ ÀÌ¿ëÀ» È®´ë
    • ±â¼ú : °ú°ÅÀÇ ÆÐÅÏÀ» ÇнÀÇÏ¿© ½Å¼ÓÇÑ ÀÇ»ç °áÁ¤ ÇÁ·Î¼¼½º¸¦ ½ÇÇöÇÏ´Â ¸Ó½Å·¯´×ÀÇ ÀÀ¿ëÀÌ È®´ë
    • µµÀÔ : ½ºÅ¸Æ®¾÷ ±â¾÷ºÎÅÍ Áß±Ô¸ð ±â¾÷±îÁö Ŭ¶ó¿ìµå AI ½Ã½ºÅÛÀÇ ³ôÀº °¡´É¼º
    • ¿ëµµ : ½ÃÇèÀ̳ª Å×½ºÆ®¿¡ À־ÀÇ ÀÚ¿øÀ» Àý¾àÇÒ ¼ö Àֱ⠶§¹®¿¡ Àç·áÀÇ ¹ß°ßÀ̳ª ½ÇÇèÀ» À§ÇÑ AI ¼ö¿ä°¡ ³ô¾ÆÁö°í ÀÖ½À´Ï´Ù.
    • ÃÖÁ¾ ¿ëµµ : È­ÇÐ ¾÷°è Àüü¿¡¼­ È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´ÉÀÇ »ç¿ëÀ» È®´ëÇØ, »õ·Î¿î È­Çй°ÁúÀÇ ¹ß°ßÀ» °¡¼ÓÇÑ´Ù
  • Porter's Five Forces ºÐ¼®
  • PESTEL ºÐ¼®
    • Á¤Ä¡Àû
    • °æÁ¦
    • »ç±³
    • ±â¼úÀû
    • ¹ý·ü»ó
    • ȯ°æ

Á¦6Àå È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå : Á¦°øº°

  • ¼­ºñ½º
  • ¼ÒÇÁÆ®¿þ¾î

Á¦7Àå È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå : ±â¼úº°

  • ÄÄÇ»ÅÍ ºñÀü
  • ¸Ó½Å·¯´×
  • ¿¹Ãø ºÐ¼®

Á¦8Àå È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå : Àü°³º°

  • Ŭ¶ó¿ìµå
  • ¿ÂÇÁ·¹¹Ì½º

Á¦9Àå È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå : ¿ëµµº°

  • Àç·áÀÇ ¹ß°ß°ú ½ÇÇè
  • Àç·á Á¦Á¶
  • ǰÁú °ü¸® ¹× º¸Áõ

Á¦10Àå È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå : ÃÖÁ¾ ¿ëµµº°

  • ¹èÅ͸®¿Í ¿¡³ÊÁö ÀúÀå
  • È­Çоàǰ
  • ±Ý¼Ó ¹× ±¤¾÷
  • ÀǾàǰ
  • Æú¸®¸Ó¿Í ÇÃ¶ó½ºÆ½
  • ¹ÝµµÃ¼

Á¦11Àå ¾Æ¸Þ¸®Ä«ÀÇ È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå

  • ¾Æ¸£ÇîÆ¼³ª
  • ºê¶óÁú
  • ij³ª´Ù
  • ¸ß½ÃÄÚ
  • ¹Ì±¹

Á¦12Àå ¾Æ½Ã¾ÆÅÂÆò¾çÀÇ È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå

  • È£ÁÖ
  • Áß±¹
  • Àεµ
  • Àεµ³×½Ã¾Æ
  • ÀϺ»
  • ¸»·¹À̽þÆ
  • Çʸ®ÇÉ
  • ½Ì°¡Æ÷¸£
  • Çѱ¹
  • ´ë¸¸
  • ű¹
  • º£Æ®³²

Á¦13Àå À¯·´, Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«ÀÇ È­ÇÐ ¹× Àç·á Á¤º¸ÇÐ ºÐ¾ß ÀΰøÁö´É ½ÃÀå

  • µ§¸¶Å©
  • ÀÌÁýÆ®
  • Çɶõµå
  • ÇÁ¶û½º
  • µ¶ÀÏ
  • À̽º¶ó¿¤
  • ÀÌÅ»¸®¾Æ
  • ³×´ú¶õµå
  • ³ªÀÌÁö¸®¾Æ
  • ³ë¸£¿þÀÌ
  • Æú¶õµå
  • īŸ¸£
  • ·¯½Ã¾Æ
  • »ç¿ìµð¾Æ¶óºñ¾Æ
  • ³²¾ÆÇÁ¸®Ä«
  • ½ºÆäÀÎ
  • ½º¿þµ§
  • ½ºÀ§½º
  • ÅÍŰ
  • ¾Æ¶ø¿¡¹Ì¸®Æ®(UAE)
  • ¿µ±¹

Á¦14Àå °æÀï ±¸µµ

  • ½ÃÀå Á¡À¯À² ºÐ¼®(2023³â)
  • FPNV Æ÷Áö¼Å´× ¸ÅÆ®¸¯½º(2023³â)
  • °æÀï ½Ã³ª¸®¿À ºÐ¼®
    • NobleAI°¡ Microsoft Azure ¸¶ÄÏÇ÷¹À̽º¿¡¼­ AI ÅøÀ» Ãâ½ÃÇÏ¿© È­ÇÐ ¹× Àç·á °³¹ß¿¡ Çõ¸íÀ» ÀÏÀ¸Å²´Ù
    • TDK Corporation, ¸ÓƼ¸®¾ó ÀÎÆ÷¸Åƽ½º¸¦ °­È­ÇÏ´Â »õ·Î¿î AI µ¥ÀÌÅÍ ºÐ¼® Ç÷§Æû ¡¸Aim¡¹À» ¹ßÇ¥
    • Toray, ¼öÁö ¼±Á¤ °­È­¿Í Á¦Ç° °³¹ß ¼Óµµ Çâ»ó¿¡ AI¸¦ Ȱ¿ëÇÑ ¼­ºñ½º¸¦ µµÀÔ
  • Àü·« ºÐ¼®°ú Á¦¾È

±â¾÷ ¸ñ·Ï

  • AI Materia
  • Ansatz AI
  • Bytelab Solutions SL. All
  • Chemical.AI
  • Citrine Informatics
  • Dassault Systemes SE
  • ENEOS Corporation
  • Enthought, Inc.
  • Fujitsu Limited
  • Hitachi High-Tech Corporation
  • International Business Machines Corporation
  • Kebotix, Inc.
  • Mat3ra
  • Materials.Zone Ltd.
  • Mitsubishi Chemical Holdings Corporation
  • Noble Artificial Intelligence, Inc.
  • PerkinElmer Inc
  • Phaseshift Technologies Inc.
  • Polymerize Private Limited
  • Schrodinger, Inc.
  • Sumitomo Chemical Co. Ltd.
  • TDK Corporation
  • Tilde Materials Informatics
  • Toray Industries, Inc.
  • Uncountable Inc
BJH 24.12.24

The AI in Chemical & Material Informatics Market was valued at USD 8.69 billion in 2023, expected to reach USD 12.08 billion in 2024, and is projected to grow at a CAGR of 39.46%, to USD 89.29 billion by 2030.

The scope of AI in Chemical & Material Informatics encompasses the integration of artificial intelligence to accelerate the discovery, design, and optimization of materials and chemical processes. This field necessitates AI's capability to analyze vast datasets, predict molecular properties, and design novel materials with tailored functionalities. Its applications extend across numerous industries including pharmaceuticals, energy, electronics, and environmental solutions. In terms of end-use, industries gear towards achieving sustainable and efficient manufacturing processes, thereby significantly reducing time and cost associated with R&D. Market growth is primarily influenced by the increasing demand for innovative and efficient material solutions, coupled with advancements in AI technologies that make data processing and analysis more efficient. There are immense opportunities for growth, notably in developing AI models that further enhance precision and reduce discovering timelines, thus enabling companies to stay competitive. Recommendations to capitalize on these opportunities include investing in advanced computational algorithms and forming cross-disciplinary collaborations to leverage expert knowledge from chemistry, materials science, and AI. Despite these opportunities, challenges remain, such as the scarcity of high-quality data and the complexity of integrating AI technologies with existing systems. These issues can hinder the speed and efficacy of AI-driven solutions. To overcome these limitations, there is potential for innovation in developing robust data collection and validation frameworks as well as scalable AI models capable of handling complex chemical data. Efforts can also focus on enhancing transparency and interpretability of AI models to build trust and facilitate adoption across industries. The market exhibits dynamic nature with rapid technological advancements, and stakeholders within the sector should prioritize continuous learning and adaptation to emerging AI capabilities to maintain a strategic edge.

KEY MARKET STATISTICS
Base Year [2023] USD 8.69 billion
Estimated Year [2024] USD 12.08 billion
Forecast Year [2030] USD 89.29 billion
CAGR (%) 39.46%

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving AI in Chemical & Material Informatics Market

The AI in Chemical & Material Informatics Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

  • Market Drivers
    • Increasing data generation with accelerating material discovery & experimentation in chemical industries
    • Rising demand for predictive modeling of material properties and chemical reactions
  • Market Restraints
    • High cost of deployment of AI in chemical & material informatics solutions
  • Market Opportunities
    • Continuous technological advancements in AI in chemical & material informatics solutions
    • Emerging applications for designing environmentally friendly materials and process
  • Market Challenges
    • Data privacy and security concerns associated with the usage of AI in chemical & material informatics

Porter's Five Forces: A Strategic Tool for Navigating the AI in Chemical & Material Informatics Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the AI in Chemical & Material Informatics Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the AI in Chemical & Material Informatics Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the AI in Chemical & Material Informatics Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the AI in Chemical & Material Informatics Market

A detailed market share analysis in the AI in Chemical & Material Informatics Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the AI in Chemical & Material Informatics Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the AI in Chemical & Material Informatics Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the AI in Chemical & Material Informatics Market

A strategic analysis of the AI in Chemical & Material Informatics Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the AI in Chemical & Material Informatics Market, highlighting leading vendors and their innovative profiles. These include AI Materia, Ansatz AI, Bytelab Solutions SL. All, Chemical.AI, Citrine Informatics, Dassault Systemes SE, ENEOS Corporation, Enthought, Inc., Fujitsu Limited, Hitachi High-Tech Corporation, International Business Machines Corporation, Kebotix, Inc., Mat3ra, Materials.Zone Ltd., Mitsubishi Chemical Holdings Corporation, Noble Artificial Intelligence, Inc., PerkinElmer Inc, Phaseshift Technologies Inc., Polymerize Private Limited, Schrodinger, Inc., Sumitomo Chemical Co., Ltd., TDK Corporation, Tilde Materials Informatics, Toray Industries, Inc., and Uncountable Inc.

Market Segmentation & Coverage

This research report categorizes the AI in Chemical & Material Informatics Market to forecast the revenues and analyze trends in each of the following sub-markets:

  • Based on Offering, market is studied across Services and Software.
  • Based on Technology, market is studied across Computer Vision, Machine Learning, and Predictive Analytics.
  • Based on Deployment, market is studied across Cloud and On-premise.
  • Based on Application, market is studied across Material Discovery & Experimentation, Material Manufacturing, and Quality Control & Assurance.
  • Based on End-Use, market is studied across Battery & Energy Storage, Chemicals, Metals & Mining, Pharmaceuticals, Polymer & Plastics, and Semiconductor.
  • Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Increasing data generation with accelerating material discovery & experimentation in chemical industries
      • 5.1.1.2. Rising demand for predictive modeling of material properties and chemical reactions
    • 5.1.2. Restraints
      • 5.1.2.1. High cost of deployment of AI in chemical & material informatics solutions
    • 5.1.3. Opportunities
      • 5.1.3.1. Continuous technological advancements in AI in chemical & material informatics solutions
      • 5.1.3.2. Emerging applications for designing environmentally friendly materials and process
    • 5.1.4. Challenges
      • 5.1.4.1. Data privacy and security concerns associated with the usage of AI in chemical & material informatics
  • 5.2. Market Segmentation Analysis
    • 5.2.1. Offering: Expanding usage of AI software in chemical & material informatics due to its predictive ability
    • 5.2.2. Technology: Growing applications of machine learning to learn from past patterns for quick decision-making processes
    • 5.2.3. Deployment: High potential for cloud AI systems across start-ups and mid-sized enterprises
    • 5.2.4. Application: Significant demand for AI for material discovery & experimentation due to its ability to save resources in trial & testing
    • 5.2.5. End-Use: Expanding usage of AI in chemical & material informatics across the chemical industry to fasten the discovery of new chemicals
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. AI in Chemical & Material Informatics Market, by Offering

  • 6.1. Introduction
  • 6.2. Services
  • 6.3. Software

7. AI in Chemical & Material Informatics Market, by Technology

  • 7.1. Introduction
  • 7.2. Computer Vision
  • 7.3. Machine Learning
  • 7.4. Predictive Analytics

8. AI in Chemical & Material Informatics Market, by Deployment

  • 8.1. Introduction
  • 8.2. Cloud
  • 8.3. On-premise

9. AI in Chemical & Material Informatics Market, by Application

  • 9.1. Introduction
  • 9.2. Material Discovery & Experimentation
  • 9.3. Material Manufacturing
  • 9.4. Quality Control & Assurance

10. AI in Chemical & Material Informatics Market, by End-Use

  • 10.1. Introduction
  • 10.2. Battery & Energy Storage
  • 10.3. Chemicals
  • 10.4. Metals & Mining
  • 10.5. Pharmaceuticals
  • 10.6. Polymer & Plastics
  • 10.7. Semiconductor

11. Americas AI in Chemical & Material Informatics Market

  • 11.1. Introduction
  • 11.2. Argentina
  • 11.3. Brazil
  • 11.4. Canada
  • 11.5. Mexico
  • 11.6. United States

12. Asia-Pacific AI in Chemical & Material Informatics Market

  • 12.1. Introduction
  • 12.2. Australia
  • 12.3. China
  • 12.4. India
  • 12.5. Indonesia
  • 12.6. Japan
  • 12.7. Malaysia
  • 12.8. Philippines
  • 12.9. Singapore
  • 12.10. South Korea
  • 12.11. Taiwan
  • 12.12. Thailand
  • 12.13. Vietnam

13. Europe, Middle East & Africa AI in Chemical & Material Informatics Market

  • 13.1. Introduction
  • 13.2. Denmark
  • 13.3. Egypt
  • 13.4. Finland
  • 13.5. France
  • 13.6. Germany
  • 13.7. Israel
  • 13.8. Italy
  • 13.9. Netherlands
  • 13.10. Nigeria
  • 13.11. Norway
  • 13.12. Poland
  • 13.13. Qatar
  • 13.14. Russia
  • 13.15. Saudi Arabia
  • 13.16. South Africa
  • 13.17. Spain
  • 13.18. Sweden
  • 13.19. Switzerland
  • 13.20. Turkey
  • 13.21. United Arab Emirates
  • 13.22. United Kingdom

14. Competitive Landscape

  • 14.1. Market Share Analysis, 2023
  • 14.2. FPNV Positioning Matrix, 2023
  • 14.3. Competitive Scenario Analysis
    • 14.3.1. NobleAI Launches AI Tools on Microsoft Azure Marketplace to RevolutionizdeChemical and Material Development
    • 14.3.2. TDK Corporation Introduces 'Aim' a New AI Data Analysis Platform to Enhance Materials Informatics
    • 14.3.3. Toray Industries Introduces AI-Powered Service to Enhance Resin Selection and Speed Up Product Development
  • 14.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. AI Materia
  • 2. Ansatz AI
  • 3. Bytelab Solutions SL. All
  • 4. Chemical.AI
  • 5. Citrine Informatics
  • 6. Dassault Systemes SE
  • 7. ENEOS Corporation
  • 8. Enthought, Inc.
  • 9. Fujitsu Limited
  • 10. Hitachi High-Tech Corporation
  • 11. International Business Machines Corporation
  • 12. Kebotix, Inc.
  • 13. Mat3ra
  • 14. Materials.Zone Ltd.
  • 15. Mitsubishi Chemical Holdings Corporation
  • 16. Noble Artificial Intelligence, Inc.
  • 17. PerkinElmer Inc
  • 18. Phaseshift Technologies Inc.
  • 19. Polymerize Private Limited
  • 20. Schrodinger, Inc.
  • 21. Sumitomo Chemical Co., Ltd.
  • 22. TDK Corporation
  • 23. Tilde Materials Informatics
  • 24. Toray Industries, Inc.
  • 25. Uncountable Inc
ºñ±³¸®½ºÆ®
0 °ÇÀÇ »óǰÀ» ¼±Åà Áß
»óǰ ºñ±³Çϱâ
Àüü»èÁ¦