
 
 Ezi nqaku yesibini kwi-series ye-5-part ye-agentic AI kwi-enterprise. Kwi-Part I, sincoma yintoni i-agentic AI kunye neendlela ezahlukileyo kunye ne-generative AI, ekukhuthaza ukuchithwa kwimeko ye-hype kwi-reality ye-pragmatic. Kwi-Part II, sinxibelelanisa njani iinkonzo ezisuka kwi-autonomy ngokusebenzisa iindidi ezahlukileyo ezahlukileyo ezahlukileyo, yaye ngoko kuxhomekeke ukuchithwa kwe-step-by-step. Ezi nqaku yesibini kwi-series ye-5-part ye-agentic AI kwi-enterprise. Kwi-Part I, sincoma yintoni i-agentic AI kunye neendlela ezahlukileyo kunye ne-generative AI, ekukhuthaza ukuchithwa kwimeko ye-hype kwi-reality ye-pragmatic. Kwi-Part II, sinxibelelanisa njani iinkonzo ezisuka kwi-autonomy ngokusebenzisa iindidi ezahlukileyo ezahlukileyo ezahlukileyo, yaye ngoko kuxhomekeke ukuchithwa kwe-step-by-step. Le nqaku yesibini kwi-series ye-5-part ye-agentic AI kwi-enterprise. Ukusetyenziswa kwe-Agent ye-autonomous ayikho yokuphumelela kwelanga. Yinto yokuhamba wokunyusa amandla kunye nokuthembeka. Kwixesha elandelayo, ukusetyenziswa kwe-AI ye-Agent ye-Enterprise kunokwenzeka njenge-spectrum ye-mature kunye neengxaki ezimbini ezininzi, ezisuka kwiiyunithi ezincinci ze-assistant ukuya kwiinkqubo ezininzi ze-autonomous ngokupheleleyo. Qinisekisa ukuba i-crawl-walk-run-fly kwiinkqubo ze-AI. Ukuphumelela kwindawo yakho kwi-curve inokunceda ukufikelela imibuzo emangalisayo kunye nezinyathelo ezilandelayo kwiiprojekthi zakho ze-AI. Iinkampani ezininzi kwimeko ezidlulileyo, z Kwimeko esekelweyo, iinkqubo ze-automation kunye ne-analytics ziyafumaneka kwiminyaka emininzi. Yenza iinkqubo ezisekelweyo, i-chatbots ezincinci, i-robot process automation (RPA) bot, okanye iimodeli ze-machine learning ezivela kwiimodeli ezihambelana. Ezi iinkqubo zokusebenza iinkqubo ezihambelanayo ezihambelanayo ezihambelanayo ezihambelanayo (isib. Ukuhlaziywa kwe-transaction ezihambelanayo okanye ukuvelisa i-report ukusuka kwimveliso) kunye nokunceda abantu nge-grunt work. Nangona kunjalo, ayikho izicwangciso ezihambelanayo okanye i-autonomy efanelekileyo - zibonise iinkqubo ezihamb Phase 1 - Assisted Intelligence (Crawl): Iinyanga ezidlulileyo babona i-explosion ye-generative AI-powered assistants ezisebenza kunye nokuninzi kakhulu. Oku kwiminyaka yobugcisa efana ne-Microsoft's Copilot kwi-Office apps, i-Google's Duet AI for Workspace, okanye i-chatbots ezisekelwe kwi-GPT ezinokufuneka iilwimi yemvelo kunye neengxaki ezininzi ezininzi zokusebenza. Ezi assistants zihlanganisa iingcebiso ezininzi zokusebenza - umzekelo, zixhomekeke i-imeyile, ukufumana imibuzo ye-free-form - ukunika ukunyusa kwimveliso ezininzi zophando. Nangona kunjalo, le assistants ezininzi ziquka i-reactive. Zisebenza isicwang Phase 2 - Generative AI Assistants (Walk): Ngiya kufikelela i-agent ye-AI efanelekileyo. Iinkqubo kwi-Phase 3 zinokufumaneka izinga eliphezulu kwaye ziya kubonakala kunye nokuthumela i-plan ye-multi-step ukufumana. Zifumaneka izixhobo efana ne-algorithms, ukusetyenziswa kwizixhobo (isib. i-API ye-calling), i-memory ye-context, kunye ne-learning dynamic ukusuka kwi-feedback. Kwimeko, i-"colleagues ye-digital" ziya kukufumana kunye ne-end-to-end izixhobo ezifanelekileyo. Umzekelo, i-agent ye-IT ye-support kwi-phase leyo ingathola ngokufanelekileyo isicelo yomsebenzisi ukusuka kwi-start ukuya ku-end: Phase 3 - Goal-Driven AI Agents (Run): I-Aspirational End-State yi-system ( okanye i-ecosystem of systems) ye-AI agents ezisebenza nge-inventory engaphansi kwe-human involvement - ezisebenza ngempumelelo njenge-workforce ye-digital kwiinkqubo okanye iinkqubo ezithile. I-Phase 4 i-scenario ingaba, ngoko ke, i-organized order-fulfilling agent ( okanye iqela le-agents) enokufumana imiyalelo yeenkcukacha kubathengi, kwaye isebenze yonke into ukusuka ukulawula i-inventory kunye nokupakisha i-customer, ukuxhaswa kwimeko emzimbeni, yonke into ngaphandle kwe-step-holding. Kwi-step-step, ungayifumana inkqubo epheleleyo yebhizinisi kwi-AI Phase 4 - Fully Autonomous Agentic Systems (Fly): Ngaba iinkampani ziyafumaneka namhlanje? Ngokuba kwimvavanyo yam (i-echoed yi-industrial surveys), iinkampani ezininzi ngoku zihlanganisa kwi-Phase 2-3 - zisebenzisa i-AI assistants generative ukwandisa abasebenzi, kwaye ndingathanda i-pilot ye-agent ye-autonomous kakhulu kwimeko yokusetyenziswa kwimeko yeenkcukacha. Akukho ngokubanzi ukuqala ukusetyenziswa kwe-GenAI assistant ukunceda abasebenzi (i-Phase 2), ke i-agent ye-purpose-driven ye-process ye-high-value (i-Phase 3). Kwiimeko ezininzi ukufikelela kwi-maturity curve akufuneka kuphela ubuchwepheshe ezininzi, kodwa iinkqubo ezininzi kunye Ngokutsho, ukufumana i-phase yakho yokusebenza ukulawula imibuzo. Umzekelo, ukuba ibhizinisi yakho ibhizinisi "kufundisa ukuqhuba" kunye ne-RPA bots eziphambili, ukufikelela ngqo kwi-agent epheleleyo yokulawula iingxaki ezininzi kubangela iingxaki. Ingaba kunokwenzeka ukuba kuqala ukuqhuba i-assistent ye-generative, ukufumana ngokufanelekileyo kunye ne-AI outputs, ngoko ngokushesha ukunika i-AI i-autonomy engaphezulu kwindawo ebonakalayo. Ngokuqhelekileyo, ukuba ungenza i-Phase 2 iipilot ezisetyenziswayo, ungenza ukufundisa kunye ne-Agent ye-Phase 3 - kodwa kufuneka uxhaswe kwi-architecture Kule nqaku elandelayo yesiqingatha, siya kuqhagamshelane kwi-conceptual roadmap ukuya kwi-architecture efunekayo yokuphumelela. Yintoni kuthatha phantsi kwe-cap to turn a nifty prototype agent into a production-grade solution? Njengoko kubonakala, iinkqubo ze-agent AI ezifanelekileyo zihlanganisa i-DNA epheleleyo. Kwi-Part 3, siya kubandakanya iiyunithi ezisiqingatha eziphambili ze-architecture ye-agent ye-AI ye-enterprise, ukusuka indlela yokufumana iingcebiso ukuya kwindlela yokulawulwa, kwaye ibandakanya iingcebiso ze-design ngamnye.

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Crawl, Walk, Run, Fly - Iiyure ezine ze-AI Agents Maturity

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