{"id":1246,"date":"2026-04-02T07:45:23","date_gmt":"2026-04-02T07:45:23","guid":{"rendered":"https:\/\/bbotech.vn\/artificial-ai-trends-2026\/"},"modified":"2026-04-02T08:15:17","modified_gmt":"2026-04-02T08:15:17","slug":"artificial-ai-trends-2026","status":"publish","type":"post","link":"https:\/\/bbotech.vn\/vi\/artificial-ai-trends-2026\/","title":{"rendered":"T\u1eeb 5% L\u00ean 40% Trong M\u1ed9t N\u0103m: Agentic AI \u0110ang T\u0103ng T\u1ed1c Nhanh H\u01a1n B\u1ea5t K\u1ef3 Xu H\u01b0\u1edbng C\u00f4ng Ngh\u1ec7 N\u00e0o Tr\u01b0\u1edbc \u0110\u00f3"},"content":{"rendered":"

Th\u00e1ng 8\/2025, Gartner c\u00f4ng b\u1ed1 m\u1ed9t con s\u1ed1 khi\u1ebfn nhi\u1ec1u CTO ph\u1ea3i d\u1eebng l\u1ea1i \u0111\u1ecdc l\u1ea1i: cu\u1ed1i n\u0103m 2026, 40% \u1ee9ng d\u1ee5ng enterprise s\u1ebd t\u00edch h\u1ee3p AI agent<\/strong> th\u1ef1c hi\u1ec7n nhi\u1ec7m v\u1ee5 c\u1ee5 th\u1ec3 \u2014 t\u0103ng t\u1eeb ch\u01b0a \u0111\u1ebfn 5% v\u00e0o \u0111\u1ea7u n\u0103m 2025. Kh\u00f4ng c\u00f3 c\u00f4ng ngh\u1ec7 n\u00e0o trong 10 n\u0103m qua c\u00f3 t\u1ed1c \u0111\u1ed9 adoption curve d\u1ed1c \u0111\u1ebfn v\u1eady, k\u1ec3 c\u1ea3 cloud hay mobile.<\/p>\n

Nh\u01b0ng con s\u1ed1 n\u00e0y c\u0169ng \u0111i k\u00e8m m\u1ed9t c\u1ea3nh b\u00e1o: h\u01a1n 40% d\u1ef1 \u00e1n agentic AI s\u1ebd b\u1ecb h\u1ee7y tr\u01b0\u1edbc cu\u1ed1i 2027<\/strong> v\u00ec chi ph\u00ed leo thang, gi\u00e1 tr\u1ecb kinh doanh kh\u00f4ng r\u00f5 r\u00e0ng, ho\u1eb7c thi\u1ebfu ki\u1ec3m so\u00e1t r\u1ee7i ro. \u0110\u00e2y kh\u00f4ng ph\u1ea3i xu h\u01b0\u1edbng b\u1ea1n c\u00f3 th\u1ec3 “ch\u1edd xem” \u2014 nh\u01b0ng c\u0169ng kh\u00f4ng ph\u1ea3i th\u1ee9 n\u00ean tri\u1ec3n khai v\u1ed9i v\u00e0ng.<\/p>\n

B\u00e0i vi\u1ebft n\u00e0y ph\u00e2n t\u00edch c\u1ee5 th\u1ec3 agentic AI l\u00e0 g\u00ec, t\u1ea1i sao n\u00f3 kh\u00e1c v\u1edbi GenAI tr\u01b0\u1edbc \u0111\u00e2y, v\u00e0 \u0111\u00e2u l\u00e0 nh\u1eefng t\u00edn hi\u1ec7u th\u1ef1c s\u1ef1 \u0111\u00e1ng theo d\u00f5i cho c\u00e1c engineering team t\u1ea1i Vi\u1ec7t Nam.<\/p>\n

 <\/p>\n

\"Agentic<\/p>\n

 <\/p>\n

Agentic AI L\u00e0 G\u00ec \u2014 V\u00e0 T\u1ea1i Sao N\u00f3 Kh\u00e1c V\u1edbi ChatGPT B\u1ea1n \u0110ang D\u00f9ng<\/h2>\n

C\u00e2u tr\u1ea3 l\u1eddi ng\u1eafn: AI th\u00f4ng th\u01b0\u1eddng (generative AI) tr\u1ea3 l\u1eddi c\u00e2u h\u1ecfi<\/em>. Agentic AI t\u1ef1 \u0111\u1eb7t m\u1ee5c ti\u00eau, l\u00ean k\u1ebf ho\u1ea1ch, h\u00e0nh \u0111\u1ed9ng, v\u00e0 \u0111i\u1ec1u ch\u1ec9nh<\/em> \u2014 kh\u00f4ng c\u1ea7n con ng\u01b0\u1eddi can thi\u1ec7p t\u1eebng b\u01b0\u1edbc.<\/p>\n

V\u00ed d\u1ee5 th\u1ef1c t\u1ebf: B\u1ea1n h\u1ecfi ChatGPT “vi\u1ebft test case cho t\u00ednh n\u0103ng login” \u2192 n\u00f3 tr\u1ea3 v\u1ec1 m\u1ed9t \u0111o\u1ea1n text. M\u1ed9t agentic AI testing tool nh\u1eadn m\u1ee5c ti\u00eau “\u0111\u1ea3m b\u1ea3o t\u00ednh n\u0103ng login ho\u1ea1t \u0111\u1ed9ng \u0111\u00fang” \u2192 n\u00f3 t\u1ef1 ph\u00e2n t\u00edch code, vi\u1ebft test, ch\u1ea1y test, ph\u00e1t hi\u1ec7n regression, t\u1ea1o bug report, v\u00e0 c\u1eadp nh\u1eadt test suite khi UI thay \u0111\u1ed5i \u2014 t\u1ea5t c\u1ea3 t\u1ef1 \u0111\u1ed9ng, li\u00ean t\u1ee5c.<\/p>\n

Agentic AI l\u00e0 h\u1ec7 th\u1ed1ng AI c\u00f3 kh\u1ea3 n\u0103ng t\u1ef1 x\u00e1c \u0111\u1ecbnh m\u1ee5c ti\u00eau, l\u1eadp k\u1ebf ho\u1ea1ch h\u00e0nh \u0111\u1ed9ng, th\u1ef1c thi nhi\u1ec1u b\u01b0\u1edbc, h\u1ecdc t\u1eeb k\u1ebft qu\u1ea3, v\u00e0 th\u00edch nghi v\u1edbi m\u00f4i tr\u01b0\u1eddng thay \u0111\u1ed5i \u2014 m\u00e0 kh\u00f4ng c\u1ea7n human prompt t\u1eebng b\u01b0\u1edbc.<\/p><\/blockquote>\n

\u0110i\u1ec3m kh\u00e1c bi\u1ec7t k\u1ef9 thu\u1eadt c\u1ed1t l\u00f5i n\u1eb1m \u1edf v\u00f2ng l\u1eb7p reasoning-action-observation<\/strong>: agent li\u00ean t\u1ee5c \u0111\u00e1nh gi\u00e1 k\u1ebft qu\u1ea3 h\u00e0nh \u0111\u1ed9ng c\u1ee7a m\u00ecnh v\u00e0 \u0111i\u1ec1u ch\u1ec9nh chi\u1ebfn l\u01b0\u1ee3c. \u0110\u00e2y l\u00e0 \u0111i\u1ec1u generative AI \u0111\u01a1n thu\u1ea7n kh\u00f4ng l\u00e0m \u0111\u01b0\u1ee3c.<\/p>\n

3 T\u00edn Hi\u1ec7u Cho Th\u1ea5y Agentic AI \u0110ang Th\u1eadt \u2014 Kh\u00f4ng Ph\u1ea3i Hype N\u1eefa<\/h2>\n

..<\/p>\n

T\u00edn hi\u1ec7u 1: Adoption t\u0103ng nhanh nh\u01b0ng production gap c\u00f2n l\u1edbn<\/h2>\n

D\u1eef li\u1ec7u t\u1eeb nhi\u1ec1u kh\u1ea3o s\u00e1t enterprise n\u0103m 2025: g\u1ea7n 80% enterprise \u0111\u00e3 adopt AI agent theo m\u1ed9t h\u00ecnh th\u1ee9c n\u00e0o \u0111\u00f3<\/strong>, nh\u01b0ng ch\u1ec9 1 trong 9<\/strong> th\u1ef1c s\u1ef1 ch\u1ea1y agent trong production. (Ngu\u1ed3n: Accelirate Agentic AI Statistics 2026)<\/em><\/p>\n

Kho\u1ea3ng c\u00e1ch n\u00e0y kh\u00f4ng ph\u1ea3i d\u1ea5u hi\u1ec7u x\u1ea5u \u2014 n\u00f3 cho th\u1ea5y th\u1ecb tr\u01b0\u1eddng \u0111ang trong giai \u0111o\u1ea1n h\u1ecdc h\u1ecfi, kh\u00f4ng ph\u1ea3i th\u1ea5t v\u1ecdng. \u0110\u00e2y l\u00e0 pattern t\u01b0\u01a1ng t\u1ef1 giai \u0111o\u1ea1n cloud adoption n\u0103m 2012\u20132015.<\/p>\n

T\u00edn hi\u1ec7u 2: Multi-agent systems tr\u1edf th\u00e0nh mainstream trong enterprise<\/h2>\n

Gartner v\u00e0 Forrester \u0111\u1ec1u x\u00e1c \u0111\u1ecbnh 2026 l\u00e0 n\u0103m b\u00f9ng ph\u00e1t c\u1ee7a multi-agent systems<\/strong> \u2014 ki\u1ebfn tr\u00fac nhi\u1ec1u agent chuy\u00ean bi\u1ec7t ph\u1ed1i h\u1ee3p v\u1edbi nhau d\u01b0\u1edbi m\u1ed9t central coordinator.<\/p>\n

Forrester d\u1ef1 b\u00e1o 30% enterprise app vendors<\/strong> s\u1ebd tri\u1ec3n khai Model Context Protocol (MCP) server \u0111\u1ec3 h\u1ed7 tr\u1ee3 cross-platform agent collaboration v\u00e0o cu\u1ed1i 2026. (Ngu\u1ed3n: Forrester AI Agent Forecast 2026)<\/em><\/p>\n

T\u00edn hi\u1ec7u 3: Ng\u00e0nh testing\/QA l\u00e0 vertical d\u1eabn \u0111\u1ea7u adoption<\/h2>\n
    \n
  • 72% QA team<\/strong> \u0111ang kh\u00e1m ph\u00e1 ho\u1eb7c l\u00ean k\u1ebf ho\u1ea1ch adopt AI-driven testing workflows. (Ngu\u1ed3n: CloudQA 2026 Software Testing Trends)<\/em><\/li>\n
  • 45% QA team<\/strong> \u0111ang d\u00f9ng AI trong testing (World Quality Report 2024), t\u0103ng t\u1eeb 22% n\u0103m 2022.<\/li>\n
  • C\u00e1c h\u1ec7 th\u1ed1ng autonomous testing agent r\u00fat ng\u1eafn testing cycle t\u1eeb nhi\u1ec1u ng\u00e0y xu\u1ed1ng c\u00f2n kho\u1ea3ng 2 gi\u1edd<\/strong>. (Ngu\u1ed3n: QualiZeal, 2025)<\/em><\/li>\n<\/ul>\n

    T\u1ea1i Sao Xu H\u01b0\u1edbng N\u00e0y T\u0103ng T\u1ed1c \u2014 Hai Y\u1ebfu T\u1ed1 Th\u00fac \u0110\u1ea9y<\/h2>\n

    Y\u1ebfu t\u1ed1 c\u00f4ng ngh\u1ec7: LLM \u0111\u1ee7 m\u1ea1nh \u0111\u1ec3 reasoning, kh\u00f4ng ch\u1ec9 generate<\/h2>\n

    Agentic AI tr\u1edf n\u00ean kh\u1ea3 thi v\u00e0o 2025\u20132026 v\u00ec c\u00e1c LLM th\u1ebf h\u1ec7 m\u1edbi (Claude 3.5+, GPT-4o, Gemini 2.0) l\u1ea7n \u0111\u1ea7u ti\u00ean \u0111\u1ee7 n\u0103ng l\u1ef1c \u0111\u1ec3 th\u1ef1c hi\u1ec7n multi-step reasoning \u0111\u00e1ng tin c\u1eady. K\u1ebft h\u1ee3p v\u1edbi tool use (API calls, code execution), LLM c\u00f3 th\u1ec3 t\u01b0\u01a1ng t\u00e1c v\u1edbi h\u1ec7 th\u1ed1ng th\u1ef1c t\u1ebf.<\/p>\n

    Y\u1ebfu t\u1ed1 kinh t\u1ebf: \u00c1p l\u1ef1c t\u0103ng n\u0103ng su\u1ea5t kh\u00f4ng th\u1ec3 tr\u00ec ho\u00e3n<\/h2>\n

    88% executives<\/strong> \u0111ang t\u0103ng ng\u00e2n s\u00e1ch AI v\u00ec agentic AI. 78% executives<\/strong> cho bi\u1ebft h\u1ecd s\u1ebd ph\u1ea3i t\u00e1i c\u01a1 c\u1ea5u operating model \u0111\u1ec3 t\u1eadn d\u1ee5ng agentic AI. (Ngu\u1ed3n: Accelirate Agentic AI Statistics 2026)<\/em><\/p>\n

     <\/p>\n

    \"Agentic<\/p>\n

     <\/p>\n

    R\u1ee7i Ro Th\u1ef1c T\u1ebf \u2014 T\u1ea1i Sao 40% D\u1ef1 \u00c1n S\u1ebd Th\u1ea5t B\u1ea1i<\/h2>\n

    Gartner c\u1ea3nh b\u00e1o: h\u01a1n 40% d\u1ef1 \u00e1n agentic AI s\u1ebd b\u1ecb h\u1ee7y tr\u01b0\u1edbc cu\u1ed1i 2027<\/strong>. Ba nguy\u00ean nh\u00e2n ch\u00ednh:<\/p>\n

      \n
    • Chi ph\u00ed v\u1eadn h\u00e0nh kh\u00f4ng \u0111\u01b0\u1ee3c t\u00ednh \u0111\u00fang:<\/strong> Agent ch\u1ea1y li\u00ean t\u1ee5c ti\u00eau t\u1ed1n compute \u0111\u00e1ng k\u1ec3.<\/li>\n
    • Thi\u1ebfu guardrails:<\/strong> Kh\u00f4ng c\u00f3 monitoring \u0111\u00fang ngh\u0129a, m\u1ed9t agent hallucinate c\u00f3 th\u1ec3 trigger cascade failure.<\/li>\n
    • Business value m\u01a1 h\u1ed3:<\/strong> C\u00e1c d\u1ef1 \u00e1n th\u00e0nh c\u00f4ng \u0111\u1ec1u b\u1eaft \u0111\u1ea7u t\u1eeb m\u1ed9t pain point c\u1ee5 th\u1ec3, c\u00f3 th\u1ec3 \u0111o \u0111\u01b0\u1ee3c.<\/li>\n<\/ul>\n

      Agentic AI kh\u00f4ng ph\u1ea3i plug-and-play. N\u00f3 l\u00e0 infrastructure \u0111\u00f2i h\u1ecfi governance, monitoring, v\u00e0 rollback strategy.<\/p><\/blockquote>\n

      \u1ea2nh H\u01b0\u1edfng V\u1edbi QA v\u00e0 Engineering Team T\u1ea1i Vi\u1ec7t Nam<\/h2>\n

      Vi\u1ec7t Nam \u0111ang \u1edf v\u1ecb tr\u00ed thu\u1eadn l\u1ee3i: 81% ng\u01b0\u1eddi d\u00f9ng Vi\u1ec7t Nam t\u01b0\u01a1ng t\u00e1c v\u1edbi AI tool h\u00e0ng ng\u00e0y<\/strong>, v\u00e0 t\u1ef7 l\u1ec7 s\u1eb5n s\u00e0ng chia s\u1ebb data v\u1edbi AI agent \u0111\u1ea1t 96%<\/strong>. (Ngu\u1ed3n: Vietnam News)<\/em><\/p>\n

      Th\u00e1ng 12\/2025, Qu\u1ed1c h\u1ed9i Vi\u1ec7t Nam th\u00f4ng qua Lu\u1eadt Tr\u00ed tu\u1ec7 Nh\u00e2n t\u1ea1o \u0111\u1ea7u ti\u00ean, hi\u1ec7u l\u1ef1c th\u00e1ng 3\/2026 \u2014 t\u1ea1o khung ph\u00e1p l\u00fd cho AI deployment trong fintech, healthcare.<\/p>\n

      Tuy nhi\u00ean, th\u1ecb tr\u01b0\u1eddng \u0111ang \u1edf giai \u0111o\u1ea1n “kh\u00f4ng c\u00f2n th\u1eed nghi\u1ec7m, ch\u01b0a \u0111\u1ebfn mature” (ICSC Corporation, 3\/2026)<\/em>. Ngh\u0129a l\u00e0:<\/p>\n

        \n
      • Window of opportunity c\u00f2n m\u1edf \u2014 early adopter v\u1eabn c\u00f3 l\u1ee3i th\u1ebf<\/li>\n
      • Talent v\u1ec1 AI engineering v\u00e0 MLOps c\u00f2n khan hi\u1ebfm \u2014 \u0111\u00e2y l\u00e0 bottleneck th\u1ef1c s\u1ef1<\/li>\n
      • Nhi\u1ec1u client enterprise Vi\u1ec7t Nam v\u1eabn c\u1ea7n \u0111\u01b0\u1ee3c educate v\u1ec1 ROI c\u1ee5 th\u1ec3<\/li>\n<\/ul>\n

        Khuy\u1ebfn Ngh\u1ecb Th\u1ef1c T\u1ebf \u2014 L\u00e0m G\u00ec V\u1edbi Th\u00f4ng Tin N\u00e0y<\/h2>\n

        N\u1ebfu team \u0111ang manual testing l\u00e0 ch\u00ednh:<\/strong> Pilot m\u1ed9t agentic testing tool cho m\u1ed9t module trong 6 th\u00e1ng t\u1edbi (Mabl, Blinq.io, Applitools). Ch\u1ec9 s\u1ed1 \u0111\u00fang h\u01b0\u1edbng: regression test time gi\u1ea3m \u226550% trong 3 sprint \u0111\u1ea7u.<\/p>\n

        N\u1ebfu \u0111\u00e3 c\u00f3 automation testing c\u01a1 b\u1ea3n:<\/strong> Th\u00eam AI-powered self-healing v\u00e0o test suite hi\u1ec7n t\u1ea1i \u2014 agentic AI layer c\u00f3 th\u1ec3 ch\u1ea1y tr\u00ean Playwright\/Selenium hi\u1ec7n c\u00f3.<\/p>\n

        N\u1ebfu l\u00e0 QA Lead \u0111\u00e1nh gi\u00e1 business case:<\/strong> Pitch b\u1eb1ng metric cost per defect detected. M\u1ed9t defect ph\u00e1t hi\u1ec7n trong CI\/CD r\u1ebb h\u01a1n 10\u2013100x so v\u1edbi defect \u0111\u1ebfn tay kh\u00e1ch h\u00e0ng.<\/p>\n

        T\u00f3m T\u1eaft \u2014 3 \u0110i\u1ec3m C\u1ea7n Nh\u1edb<\/h2>\n
          \n
        • Agentic AI kh\u00f4ng ph\u1ea3i ChatGPT m\u1edbi h\u01a1n<\/strong> \u2014 ki\u1ebfn tr\u00fac kh\u00e1c, \u0111\u00f2i h\u1ecfi governance v\u00e0 infrastructure kh\u00e1c.<\/li>\n
        • Testing\/QA l\u00e0 use case ROI r\u00f5 nh\u1ea5t hi\u1ec7n t\u1ea1i<\/strong> \u2014 72% QA team \u0111ang explore, adoption t\u0103ng g\u1ea5p \u0111\u00f4i m\u1ed7i 2 n\u0103m.<\/li>\n
        • Th\u1ea5t b\u1ea1i th\u01b0\u1eddng \u0111\u1ebfn t\u1eeb thi\u1ebfu clarity v\u1ec1 business value<\/strong> \u2014 b\u1eaft \u0111\u1ea7u t\u1eeb pain point \u0111o \u0111\u01b0\u1ee3c.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"

          Th\u00e1ng 8\/2025, Gartner c\u00f4ng b\u1ed1 m\u1ed9t con s\u1ed1 khi\u1ebfn nhi\u1ec1u CTO ph\u1ea3i d\u1eebng l\u1ea1i \u0111\u1ecdc l\u1ea1i: cu\u1ed1i n\u0103m 2026, 40% \u1ee9ng d\u1ee5ng enterprise s\u1ebd t\u00edch h\u1ee3p AI agent th\u1ef1c hi\u1ec7n nhi\u1ec7m v\u1ee5 c\u1ee5 th\u1ec3 \u2014 t\u0103ng t\u1eeb ch\u01b0a \u0111\u1ebfn 5% v\u00e0o \u0111\u1ea7u n\u0103m 2025. Kh\u00f4ng c\u00f3 c\u00f4ng ngh\u1ec7 n\u00e0o trong 10 n\u0103m qua c\u00f3 t\u1ed1c […]<\/p>\n","protected":false},"author":3,"featured_media":1244,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[25],"tags":[35,36],"class_list":["post-1246","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tin-cong-nghe","tag-agentic-ai","tag-what-is-agentic-ai"],"acf":[],"_links":{"self":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1246","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/comments?post=1246"}],"version-history":[{"count":4,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1246\/revisions"}],"predecessor-version":[{"id":1284,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1246\/revisions\/1284"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/media\/1244"}],"wp:attachment":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/media?parent=1246"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/categories?post=1246"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/tags?post=1246"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}