[{"data":1,"prerenderedAt":3318},["ShallowReactive",2],{"article-detail-100193":3,"all-tag-group":2064,"all-tags":3001,"all-tag":3176},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"detail":8,"surround":635,"relateItems":668,"_id":2058,"_type":2059,"title":2060,"_source":2061,"_file":2062,"_stem":2063,"_extension":2059},"/article/100193","article",false,"",{"url":9,"title":10,"publishAt":11,"tags":12,"category":23,"eyeCatchImage":48,"content":59,"text":628,"publishAtDetail":629,"tagsBySlugs":633,"sortedIndex":21,"sysId":634},100193,"AIは「効率化」ではなく「絆」のために。3000時間の声を解像度に変える、Pococha流・AIネイティブなチームの作り方","2026-04-15T00:00",[13,18],{"name":14,"slug":15,"numberOfArticles":16,"sysId":17},"Pococha","pococha",0,"64a7de0a1ca814d3027c",{"name":19,"slug":20,"numberOfArticles":21,"sysId":22},"AI","ai",1,"6f67af86257489b5b116",{"metadata":24,"sys":27,"fields":46},{"tags":25,"concepts":26},[],[],{"space":28,"id":33,"type":34,"createdAt":35,"updatedAt":35,"environment":36,"publishedVersion":40,"revision":21,"contentType":41,"locale":45},{"sys":29},{"type":30,"linkType":31,"id":32},"Link","Space","7mrdlclm9xss","1YUOB3ElOJjJ5QAfDIlATj","Entry","2025-01-10T04:06:09.211Z",{"sys":37},{"id":38,"type":30,"linkType":39},"master","Environment",2,{"sys":42},{"type":30,"linkType":43,"id":44},"ContentType","category","en-US",{"categoryName":47},"事業・サービス",{"file":49,"sysId":58},{"url":50,"details":51,"fileName":56,"contentType":57},"//images.ctfassets.net/7mrdlclm9xss/6Vp2eXSL97BCt9YPEIGsu9/f2e7456a802309ecf60ead9439dfd246/kv_260309_FS_420.jpg",{"size":52,"image":53},853898,{"width":54,"height":55},1260,841,"kv_260309_FS_420.jpg","image/jpeg","6Vp2eXSL97BCt9YPEIGsu9",{"time":60,"blocks":61,"version":627},1776218075945,[62,69,74,79,87,93,98,103,117,122,127,132,145,150,155,160,173,178,183,188,193,198,203,215,220,225,230,235,240,245,250,262,267,272,277,282,287,292,297,302,307,319,324,329,334,339,344,349,354,359,364,369,374,379,384,389,394,407,412,417,422,427,432,437,443,448,453,458,463,476,481,486,491,501,506,511,516,528,533,538,543,548,553,565,570,575,580,585,590,595,607,614,621],{"id":63,"type":64,"data":65,"tunes":68},"gESjBPAB5w","paragraph",{"text":66,"align":67},"ファウンダーの南場による「AIオールイン」宣言から1年。DeNA全社でAIネイティブ化が進む中、LLMの活用によって大きな変化を遂げた組織があります。",null,{},{"id":70,"type":64,"data":71,"tunes":73},"HIhPfH53PH",{"text":72,"align":67},"それは、ライブコミュニケーションアプリ『\u003Ca href=\"https://www.pococha.com/ja-jp\" target=\"_blank\">Pococha\u003C/a>』を運営するPococha事業部。AIを掛け合わせることで何が変わり、どのような価値が生まれているのか。",{},{"id":75,"type":64,"data":76,"tunes":78},"YHSgnCa22j",{"text":77,"align":67},"『Pococha』のPdM、コミュニティマネージャー、データサイエンティストの3人に、その最前線を聞きました。",{},{"id":80,"type":64,"data":81,"tunes":83},"kjPZ_rnqMP",{"text":82,"align":67},"※本文中では、Pococha事業部を「Pococha」、サービス名を「『Pococha』」と表記しています。",{"wrapped":84},{"types":85},[86],"note",{"id":88,"type":89,"data":90,"tunes":92},"nqfz-f6Nq8","header",{"text":91,"level":40},"「職人の修行」をAIで代替。生産性を劇的に変えた「知の共有」",{},{"id":94,"type":64,"data":95,"tunes":97},"_kmEv432BD",{"text":96,"align":67},"\u003Cb>── 「AIオールイン」によって、この1年でどのような変化がありましたか？\u003C/b>",{},{"id":99,"type":64,"data":100,"tunes":102},"r4ZjnY2PkY",{"text":101,"align":67},"\u003Cb>加藤 貴浩（以下、加藤）：\u003C/b> プロダクトに関しては、AI機能の企画から開発・運用までのサイクルを自律的に回せる体制が整った、という段階にあります。",{},{"id":104,"type":105,"data":106,"tunes":116},"0OySkCldJz","ctf-asset-image",{"caption":107,"asset":108},"\u003Cb>▲ライブコミュニティ事業本部Pococha事業部プロダクト部 副部長　加藤 貴浩（かとう たかひろ）\u003Cbr>\u003C/b>2024年にDeNAへ中途入社。プロダクト部副部長としてPdM陣のマネジメントを担当。同時に、大規模アジャイル開発のフレームワーク「SAFe（Scaled Agile Framework）」をベースとした、スケーラブルな強いプロダクト組織づくりと運営に従事。\u003Cb>\u003C/b>",{"id":109,"file":110},"4GUUekGZt3yPai1SKLdGdW",{"url":111,"details":112,"fileName":115},"//images.ctfassets.net/7mrdlclm9xss/4GUUekGZt3yPai1SKLdGdW/739a57fcf5cf7c9d1212337d2b8d4119/01_260309_FS_069.jpg",{"size":113,"image":114},668823,{"width":54,"height":55},"01_260309_FS_069.jpg",{},{"id":118,"type":64,"data":119,"tunes":121},"DFugcT77TE",{"text":120,"align":67},"直近では、2026年1月に、配信中のコメントからAIがリアルタイムに配信タイトルを自動生成する機能をリリースしました。単に開発して終わりではなく、リリース後もAIが想定通りに動いているかを把握し、その結果を受けてプロンプトを改善していく。こうした運用まで含めた一連のサイクルを回せるようになったことは、組織として大きな転換点だと感じています。",{},{"id":123,"type":64,"data":124,"tunes":126},"3-l2dh6csT",{"text":125,"align":67},"\u003Cb>── 金丸さんの担当されているコミュニティ領域ではいかがでしょうか。\u003C/b>",{},{"id":128,"type":64,"data":129,"tunes":131},"sOw2xMKzNO",{"text":130,"align":67},"\u003Cb>金丸 裕佑（以下、金丸）：\u003C/b> 組織としての一番大きな変化は、特定のメンバーに知識が偏る「知の偏在」が解消され、組織全体で知見を共有できるようになったことです。私が管掌しているのはコミュニティ領域、つまりアプリ内でのユーザーさん同士のつながりや、それと連動したオフラインのイベントなど、デジタルと非デジタルの両面で「絆」を守っていく役割を担っています。",{},{"id":133,"type":105,"data":134,"tunes":144},"sEhE1wl99M",{"caption":135,"asset":136},"\u003Cb>▲ライブコミュニティ事業本部Pococha事業部プラットフォームマネジメント部 部長　金丸 裕佑（かねまる ゆうすけ）\u003Cbr>\u003C/b>新卒でメガバンク傘下の金融事業会社に入社。その後、MBA、コンサルティングファームでの経営コンサルタント職、MIXIでの事業開発部長を経て、2022年にDeNAへ中途入社。DeNAと並行して、会社経営・大学教員等にも取り組む。\u003Cb>\u003C/b>",{"id":137,"file":138},"2souqbHO5IjsCrwcBQaE3w",{"url":139,"details":140,"fileName":143},"//images.ctfassets.net/7mrdlclm9xss/2souqbHO5IjsCrwcBQaE3w/269a9ad472bd03889b07d668ccb7ce00/02_260309_FS_002.jpg",{"size":141,"image":142},621223,{"width":54,"height":55},"02_260309_FS_002.jpg",{},{"id":146,"type":64,"data":147,"tunes":149},"JSm63lXWM4",{"text":148,"align":67},"コミュニティマネジメントは、あらゆる産業に於いて不可欠であるものの、まだ知識としても技術としても未確立な部分が多い領域です。「コミュニティをどうつくり、どう成長させ、どう運用していくのか」といった拠り所となる知見が世の中にもまだ少ないため、これまではメンバー個々人が持つ知識や経験、スキルが偏在し、散らばっている状態でした。",{},{"id":151,"type":64,"data":152,"tunes":154},"bAylYhQPoM",{"text":153,"align":67},"しかしAIを活用するようになってから、あらゆるシーンでこの分散されていた知識が統合されるようになり、アウトプットやアウトカムの質が、以前とは比較にならないほど抜本的に向上しました。以前であればOJTやOFFJT、実務経験など、一定の水準に達するために必要だった時間や経験の蓄積、いわば「職人の修行時間」が大幅にカットされ、本来届けるべき価値の追求に時間を割けるようになりました。結果として、生産性が飛躍的に伸びたと実感しています。",{},{"id":156,"type":64,"data":157,"tunes":159},"TPURwHV8vv",{"text":158,"align":67},"\u003Cb>── AI活用を推進する安達さんの視点ではどうでしょうか。\u003C/b>",{},{"id":161,"type":105,"data":162,"tunes":172},"JsVBps6RLB",{"caption":163,"asset":164},"\u003Cb>▲IT本部AI・データ戦略統括部AI技術開発部　安達 涼（あだち りょう）\u003Cbr>\u003C/b>神経経済学分野で博士号を取得 (カリフォルニア工科大学)後、2018年にDeNAへ中途入社。人間の経済・社会的意思決定の数理的、脳科学的メカニズムに興味をもつ。現在はソーシャルデータサイエンスチームを立ち上げ、ライブコミュニティ事業において、AIを駆使した社会的つながりの解明と事業活用に従事。\u003Cb>\u003C/b>",{"id":165,"file":166},"5Re3tpyyIjG7za4y8hbB1p",{"url":167,"details":168,"fileName":171},"//images.ctfassets.net/7mrdlclm9xss/5Re3tpyyIjG7za4y8hbB1p/9a9497ce4a37a2f38ee2b9ce579cb2b5/03_260309_FS_194.jpg",{"size":169,"image":170},596691,{"width":54,"height":55},"03_260309_FS_194.jpg",{},{"id":174,"type":64,"data":175,"tunes":177},"oLbhWeMRFN",{"text":176,"align":67},"\u003Cb>安達 涼（以下、安達）：\u003C/b> AIチームの視点から補足すると、この1年で大きく3つの変化がありました。",{},{"id":179,"type":64,"data":180,"tunes":182},"YQ4DrdldGI",{"text":181,"align":67},"1つ目は「テキスト分析」の進化です。『Pococha』には発話やコメントなどの膨大なテキストデータがありますが、くだけた表現も多く、これまでは機械学習で分析するハードルが高くなっていました。それが、コンテキストを理解して「よしなに」分析してくれるLLMの登場で一変しました。リッチなコミュニケーションデータを活用した分析や機能の実装など、この1年でできること・やりたいことが一気に広がりました。",{},{"id":184,"type":64,"data":185,"tunes":187},"H35Iu1fQUi",{"text":186,"align":67},"2つ目は「ダッシュボード実装」のスピードです。これまで事業部向けダッシュボードをデプロイする際には、エンジニアに相談した上で、優先度の兼ね合いや他部署との調整などに数ヶ月を要していました。それが、Claude CodeやCursor、DevinといったAI駆動開発ツールを活用することで、データサイエンティストが一人でReactを用いた複雑なアプリケーションの開発・実装からデプロイまで完結させ、短期間で現場にデリバリーできるようになりました。",{},{"id":189,"type":64,"data":190,"tunes":192},"gywA4dlq7S",{"text":191,"align":67},"そして3つ目が、こうした効率化によって「中長期的な技術スタックの蓄積」に時間を割けるようになったことです。既存業務に関わる分析・開発の工数が削減されたことで、半年・一年先の実装を見据えた技術検証を、より早期に実行できるようになりました。",{},{"id":194,"type":89,"data":195,"tunes":197},"GZ3OM9Cryr",{"text":196,"level":40},"全社導入Geminiが転換点。試行錯誤を加速させる「アンラーニング」の文化",{},{"id":199,"type":64,"data":200,"tunes":202},"v4_V7pA1k7",{"text":201,"align":67},"\u003Cb>──南場さんの「AIオールイン」宣言以降、具体的にはどのような動きから始まったのでしょうか。\u003C/b>",{},{"id":204,"type":105,"data":205,"tunes":214},"zr55Ycy6iI",{"caption":7,"asset":206},{"id":207,"file":208},"53vdiGw77wYqOGa5KyqLv7",{"url":209,"details":210,"fileName":213},"//images.ctfassets.net/7mrdlclm9xss/53vdiGw77wYqOGa5KyqLv7/fbdf46b78ddf63e3e8dac0df9d729a1a/04_260309_FS_228.jpg",{"size":211,"image":212},591565,{"width":54,"height":55},"04_260309_FS_228.jpg",{},{"id":216,"type":64,"data":217,"tunes":219},"cCtzacqFAa",{"text":218,"align":67},"\u003Cb>加藤： \u003C/b>最初は安達さんのAIチームと短期的なプロジェクトを立ち上げ、「AIを活用した機能を『Pococha』に実装する」という目標から始まりました。ただ、当初はAIをどのようにUXに落とし込むのか、具体的なイメージを描ききれていない部分もありました。",{},{"id":221,"type":64,"data":222,"tunes":224},"iqS3FRPNdc",{"text":223,"align":67},"転換点は、Geminiが全社導入され、メンバーが直接AIに触れる機会が増えたことです。「こういう情報を渡せば、こう返ってくる」という実感を個々人が得たことで、企画の解像度が一気に上がりました。『Pococha』はライブコミュニケーションアプリなので、ユーザーさんのテキストデータが大量にあります。「LLMとの親和性が極めて高い」と気づいてからは、AIを活用する機能の企画がどんどん形になっていきました。",{},{"id":226,"type":64,"data":227,"tunes":229},"EThqkmHGf7",{"text":228,"align":67},"\u003Cb>金丸： \u003C/b>Pocochaにはもともと「新しいものに挑戦する」カルチャーがあり、南場さんの号令は強い「追い風」でした。特に、僕らが大切にしてきた「仮説検証を繰り返して学びを体系化する」というコミュニティマネジメントの手法が、AIを試行錯誤するプロセスと綺麗にフィットしました。全社的なGemini導入という流れも相まって、まさに「点と線がつながり」、組織として一気に加速しました。",{},{"id":231,"type":64,"data":232,"tunes":234},"6bUYvtf4kj",{"text":233,"align":67},"コミュニティで交わされる内容は定量化しにくい定性的なものも多く、これまでは、個別の声をつぶさに聞いていったり、イベント後にユーザーインタビューを行ったりしてきました。それでもすべてのデータが把握できるわけではなく、推測に頼らざるを得ない部分もありましたし、かなり意識はしていても情報の鮮度という意味では、真にリアルタイムではない課題もあったんです。それが安達さんがつくってくれたツールによって、広範囲でモニタリングできるようになりました。",{},{"id":236,"type":64,"data":237,"tunes":239},"1GPnXcqPgr",{"text":238,"align":67},"AIを業務にネイティブに使えるチームになったことで、知の偏在がなくなり、スピードも上がりました。リアルタイムでモニタリングできることで、「こうしたらユーザーさんにもっと喜んでもらえるんじゃないか」を試して、次の施策にスピーディーに反映していく。打席に立つ数が増え、結果としてヒットも生まれやすくなる。そんな良い循環が生まれています。",{},{"id":241,"type":89,"data":242,"tunes":244},"YOYY4DivGT",{"text":243,"level":40},"専門用語の壁を打破。AIがエンジニアと事業部を繋ぐ「共通言語」に",{},{"id":246,"type":64,"data":247,"tunes":249},"CeUSGw56k6",{"text":248,"align":67},"\u003Cb>──『Pococha』とLLMの相性が良かった。それだけで、これほど大きな変化が生まれるものなのでしょうか？\u003C/b>",{},{"id":251,"type":105,"data":252,"tunes":261},"w8rW5KuMqW",{"caption":7,"asset":253},{"id":254,"file":255},"kJMzsgwjIxbC9BnIeVcsU",{"url":256,"details":257,"fileName":260},"//images.ctfassets.net/7mrdlclm9xss/kJMzsgwjIxbC9BnIeVcsU/e342de5e8e63f1566bb433ac981b4cc1/05_260309_FS_255.jpg",{"size":258,"image":259},613564,{"width":54,"height":55},"05_260309_FS_255.jpg",{},{"id":263,"type":64,"data":264,"tunes":266},"zrcklvZgCa",{"text":265,"align":67},"\u003Cb>安達：\u003C/b> AI技術への大きな期待感が生まれたことは過去にもありましたが、AIが事業部のあらゆる部分にまで浸透したことはありませんでした。今回のLLMの台頭によって初めて、AI活用が事業部のどのメンバーにとっても「自分ごと」になりました。",{},{"id":268,"type":64,"data":269,"tunes":271},"MZToO_G85K",{"text":270,"align":67},"これまでは、事業部メンバーからみれば、機械学習モデルが何をしているのか分からない部分が多かったと思います。しかしGeminiなどのAIツールが導入された今、たとえば「CSV形式のデータをアップロードして分析する」といった、かつてはアナリストや機械学習エンジニアが担っていた作業も、事業部メンバーが自らAIとチャット形式で完結できるようになりました。",{},{"id":273,"type":64,"data":274,"tunes":276},"zi-ryH3Nj0",{"text":275,"align":67},"これによってデータサイエンティスト・エンジニアと事業部メンバー間のコミュニケーションが劇的に活発化し、専門用語の壁が取り払われて「共通言語」が生まれた。これこそが、最大のブレイクスルーだと感じています。",{},{"id":278,"type":64,"data":279,"tunes":281},"lEkmeM5Lau",{"text":280,"align":67},"\u003Cb>──共通言語ができたことで、職種間の連携の質も変わりそうです。\u003C/b>",{},{"id":283,"type":64,"data":284,"tunes":286},"92rzJ_KoLW",{"text":285,"align":67},"\u003Cb>加藤：\u003C/b>確かに、以前はエンジニアからの技術的な説明を「難しいな」と感じながら聞いているような場面もありました。それが、AIへの解像度が上がったことで、プロダクト側から「LLMを使って○○なことはできないか」と具体的なアイデアを提案できるレベルになり、職種間の目線が合うようになりました。互いの専門性を理解しつつ、共通のツールと言語を持つことで、意思疎通の速度と深さが段違いに向上したと感じています。",{},{"id":288,"type":64,"data":289,"tunes":291},"WN4cVhmFXF",{"text":290,"align":67},"また、新機能の開発やローンチにおいて、コミュニティマネジメントチームとの密な連携は欠かせません。AIによる深いユーザー理解は、新機能に対してコミュニティがどう反応するかを予測したり、最適なユーザーコミュニケーションを設計したりするうえで、『Pococha』の強力な武器となっています。",{},{"id":293,"type":64,"data":294,"tunes":296},"ODCIPY_dw1",{"text":295,"align":67},"\u003Cb>金丸：\u003C/b> 実務の現場で特に顕著に感じているのは、プロフェッショナルが陥りがちな「ガラスの天井」が打破されたことです。経験豊富なメンバーほど、企画や施策、イベントを立案するアプローチにおいて、「こうすればこうなる」という規定路線や固定観念、あるいは予算や工数の制約といった見えない「キャップ」を知らず知らずの内に思考にかけてしまいがちです。",{},{"id":298,"type":64,"data":299,"tunes":301},"k2mZQJCbe2",{"text":300,"align":67},"ですが、AIを「壁打ち相手」として活用し、対話しながら企画を練ることで、個人の想像力を超えた斬新なアイデアが次々と創出されるようになりました。この「思考の拡張と深化」こそが重要です。結果として、ネガティブな制約から解放され、「どうすれば実現できるか」という前向きな発想へと転換されました。最終的に、ユーザーさんに届けるべき本質的な価値の追求に集中できるようになったと実感しています。",{},{"id":303,"type":64,"data":304,"tunes":306},"SniTYXmOZN",{"text":305,"align":67},"\u003Cb>──なぜPocochaチームは、そこまでスムーズにAIを使いこなせるようになったのでしょうか。\u003C/b>",{},{"id":308,"type":105,"data":309,"tunes":318},"KtBCCIn9N0",{"caption":7,"asset":310},{"id":311,"file":312},"18Uf2RswU8YXcjwOmnjc45",{"url":313,"details":314,"fileName":317},"//images.ctfassets.net/7mrdlclm9xss/18Uf2RswU8YXcjwOmnjc45/dc850f56c9cf62f08b8dbeeef66079b0/06_260309_FS_106.jpg",{"size":315,"image":316},615808,{"width":54,"height":55},"06_260309_FS_106.jpg",{},{"id":320,"type":64,"data":321,"tunes":323},"KeyZAHtKGZ",{"text":322,"align":67},"\u003Cb>金丸：\u003C/b> 変化に対する強い弾力性と、「新しいもの好き」が集まるカルチャーが土壌にあったからだと思います。",{},{"id":325,"type":64,"data":326,"tunes":328},"9tN6pq-lJ-",{"text":327,"align":67},"特に効果的だったのは、「教え合い、ノウハウを即座に共有する」仕組みです。誰かがプロンプトのコツを掴めば、その知見が組織全体に一気に伝播し、各プロジェクトでさらに進化していく。この「スパイラル的な進化」が組織全体の底上げ、言わば「高次元での金太郎飴化」を可能にしました。既存の成功モデルに固執せず、新しいものを否定しない「アンラーニング」の姿勢が、AIネイティブ化を加速させる大きな推進力になったと感じています。",{},{"id":330,"type":64,"data":331,"tunes":333},"CDHH63bIrN",{"text":332,"align":67},"\u003Cb>──AIが組織にどんどん浸透していく中で、安達さん側、つまりAIチームとして何か取り組まれたことはありましたか。\u003C/b>",{},{"id":335,"type":64,"data":336,"tunes":338},"IFICe_QCT1",{"text":337,"align":67},"\u003Cb>安達：\u003C/b>実は、私たち側の変化というよりは、事業部側の変化が大きかったと感じています。Geminiなどでの壁打ちを通じて、事業部メンバーから「UX向上のためにこんなことをやりたいが、AIで○○なことをやるのは可能か」といった具体的なアイデアが自発的に出てくるようになりました。これはAIが浸透する前にはあまり見られなかった現象です。",{},{"id":340,"type":64,"data":341,"tunes":343},"uSxQM0YGG5",{"text":342,"align":67},"開発プロセスも大きく変わりました。以前なら、データを使って検証し、フィードバックをもらって……というやり取りを繰り返し、一定のクオリティに達するまでに2〜3ヶ月を要していました。その間に事業状況が変わってしまい、せっかくの分析を施策に活かし切れないことも少なくありませんでした。しかし現在は、AI駆動開発により、フィードバックを受ければ即座に変更点をダッシュボード内に実装できます。",{},{"id":345,"type":64,"data":346,"tunes":348},"0kdb-JOlPr",{"text":347,"align":67},"さらに、検証に使えるデータの範囲も広がりました。以前は限られたデータセットでの実験に留まっていましたが、今は広範囲のユーザーデータを用いて、事業部のメンバーが自らダッシュボード上でインタラクティブに検証を行えます。これによって検証サイクルが大幅に短縮され、開発工数も大幅に削減されました。",{},{"id":350,"type":64,"data":351,"tunes":353},"83y1OGzQnh",{"text":352,"align":67},"\u003Cb>──プロジェクトのスパンが短くなり、回数も増えたことで、安達さん側の「質」も向上したということでしょうか。\u003C/b>",{},{"id":355,"type":64,"data":356,"tunes":358},"Q2QI0KeZxj",{"text":357,"align":67},"\u003Cb>安達：\u003C/b>質に関しては、1つの正解を探すのではなく、複数のシナリオや施策のパターンを同時に提示できるようになったことが大きいです。同じ時間で、今までは一つしかできなかったものが、今は複数提示できる。施策の「厚み」が増したと感じています。",{},{"id":360,"type":89,"data":361,"tunes":363},"7bR61KfaPb",{"text":362,"level":40},"数百万人の声をリアルタイムに構造化。新手法「ブロードリスニング」の真価",{},{"id":365,"type":64,"data":366,"tunes":368},"hLI0oDlgDd",{"text":367,"align":67},"\u003Cb>── これまでPocochaでは多くの方へのユーザーインタビューを通じて、ユーザーさん一人ひとりと向き合ってきたと聞いています。その「個の理解」はAIによってどう変わったのでしょうか。\u003C/b>",{},{"id":370,"type":64,"data":371,"tunes":373},"WXdxcCpJhI",{"text":372,"align":67},"\u003Cb>金丸：\u003C/b>インタビューは、ユーザーさんを深く知るために不可欠なものです。これまで実施したインタビューは3000時間以上に及びます。コミュニティ運営を考える上で、「ユーザーさんが何を言い、何を考えているのか」を最優先にインタビューを続けてきましたが、やはりそこには物理的な限界がありました。",{},{"id":375,"type":64,"data":376,"tunes":378},"81NNnF8rS0",{"text":377,"align":67},"また、どうしても「バックミラーを見ながら運転している」ような、少し前の情報の分析になりがちで、分析から施策に適用するまでに一定のリードタイムがかかってしまう現実もありました。そこで導入したのが、LLMを活用した「ブロードリスニング」です。",{},{"id":380,"type":64,"data":381,"tunes":383},"6zE6QEn0PO",{"text":382,"align":67},"これは言わば、「数百万人のユーザーさんに対して同時にインタビューを行っている」ような状態です。これまで多くの時間をかけて抽出していた深いインサイトを、コミュニティ全体の膨大な発話データからリアルタイムに構造化し、捉えられるようになりました。ユーザーさんのホットでリアルな声を瞬時に確認できるため、今日この瞬間の声を、明日あるいは今日の施策に速やかに転用することが可能になっています。",{},{"id":385,"type":64,"data":386,"tunes":388},"urruxEKfZK",{"text":387,"align":67},"\u003Cb>安達：\u003C/b>これまでPocochaチームが積み重ねてきた3000時間を超える定性データは、まさに「宝」です。それをAIに学習・活用させることで、主観に頼らない客観的なデータとして「コミュニティの熱量」を可視化できるようになりました。",{},{"id":390,"type":64,"data":391,"tunes":393},"KW1bG5yxoL",{"text":392,"align":67},"膨大なデータをAIで網羅的に収集・要約することで、特定の施策に対しても「どのようなタイプのユーザーさんが、どのような文脈で喜んでくださっているか」を即座に判定できます。また、少数のユーザーさんしか発信していないような、マイナーだけれども重要なご意見や、不具合・不正の火種を早期に検知して対処できるようにもなりました。この情報の「鮮度」が、今の『Pococha』の強みに繋がっていると思います。",{},{"id":395,"type":105,"data":396,"tunes":406},"OnH3i0Dn3s",{"caption":7,"asset":397},{"id":398,"file":399},"6G6VtJyB5Whs9lGtDTiQJh",{"url":400,"details":401,"fileName":405},"//images.ctfassets.net/7mrdlclm9xss/6G6VtJyB5Whs9lGtDTiQJh/d35d399f9a4d8d3a2f16745d77d5e065/07_Broad_Listening02.png",{"size":402,"image":403},687894,{"width":54,"height":404},713,"07_Broad Listening02.png",{},{"id":408,"type":64,"data":409,"tunes":411},"z6Mlmo7bYC",{"text":410,"align":67},"\u003Cb>金丸： \u003C/b>また、これによってコミュニティ運営に置けるオンライン（アプリ内）とオフライン（イベントなど）の領域が地続きになり、熱量の高い「オンライン⇔オフラインのループ」が生まれています。",{},{"id":413,"type":64,"data":414,"tunes":416},"wWNBQDti6-",{"text":415,"align":67},"オフライン特有の「熱量の高さ」と、オンラインの持つ「拡散性」。AIによってそれぞれの弱点が補完され、相互の強みがより引き立てられるようになりました。その結果、「消費者」としての楽しみ方が中心だったユーザーさんが、自ら場をつくる「当事者」となり、その熱量がサービス全体に波及していくサイクルをこの1年で実現できています。",{},{"id":418,"type":64,"data":419,"tunes":421},"LJNjD7usXX",{"text":420,"align":67},"\u003Cb>安達：\u003C/b> さらに今後は、「パーソナライゼーション」を極めていきたいと考えています。サービス内で各々のユーザーさんがどのような状態にあって、その状態のときはどのような行動をおすすめすればもっと『Pococha』を楽しめるのか。行動データだけでなく、LLMを用いたテキスト分析を掛け合わせることで、ユーザーさんの心理的な解像度を高めています。",{},{"id":423,"type":64,"data":424,"tunes":426},"2PNQW7Jj3O",{"text":425,"align":67},"たとえば、リスナーさんがライバーさんとどのように打ち解け、ファンになっていくのかという「ユーザージャーニー」の変化も、コメントや会話の内容から追えるようになりました。",{},{"id":428,"type":64,"data":429,"tunes":431},"tgBxTI7_CW",{"text":430,"align":67},"\u003Cb>──反応を追うだけでなく、その裏側にある「心理」もAIで捉えようとしている、ということでしょうか？\u003C/b>",{},{"id":433,"type":64,"data":434,"tunes":436},"9oHe5pGkqu",{"text":435,"align":67},"\u003Cb>安達：\u003C/b>はい。それが新たに開発したリスナーのタイプ分析「PocoTI（Poco Type Indicator）」（以下、「PocoTI」）です。これは、ランクや応援レベルといった「行動の達成度」でユーザーさんを分類するのではなく、どんな心理的モチベーションで『Pococha』を楽しんでいるのかをLLMで推定し、分類するものです。MBTIという性格診断をご存知の方も多いと思いますが、これを参考に、これまで収集してきた約8万人のユーザーアンケートを活用して開発しました。",{},{"id":438,"type":89,"data":439,"tunes":442},"rt5IMf6cL9",{"text":440,"level":441},"■「PocoTI」の仕組み",3,{},{"id":444,"type":64,"data":445,"tunes":447},"hXrVtP7n5J",{"text":446,"align":67},"過去のユーザーアンケートとMBTIを参考に、以下3つの軸を定義しました。それぞれの軸を特徴づけるコメントや行動データを収集し、視聴時間などの定量データと、コメントのテキストデータを掛け合わることで、ユーザーさんを分類します。",{},{"id":449,"type":64,"data":450,"tunes":452},"jjd_8-vlyB",{"text":451,"align":67},"\u003Cb>1. 根本動機：つながりたいのか、応援したいのか（C/S）\u003Cbr>2. \u003C/b>\u003Cb>関係スタイル：グループが好きか、1対1（個人）を重視するか（G/I）\u003Cbr>3. \u003C/b>\u003Cb>行動スタンス：自ら発信（表現）したいか、受け取り（見守り）たいか（E/R）\u003C/b>",{},{"id":454,"type":64,"data":455,"tunes":457},"_edereT5cE",{"text":456,"align":67},"たとえば、以下の図にある「CGE（盛り上げ役のコミュニケーター）」と「SIR（影から支える支援者）」では、心地よいと感じるコミュニケーションが全く異なります。",{},{"id":459,"type":64,"data":460,"tunes":462},"4Ejvx7hHaf",{"text":461,"align":67},"かつては膨大な時間をかけてユーザー理解を深め、辿り着いていた「個別のニーズ」を、今はAIを活用してすべてのユーザーさんに対して自動的に把握することが可能になりました。",{},{"id":464,"type":105,"data":465,"tunes":475},"Qrpyf7oRJR",{"caption":7,"asset":466},{"id":467,"file":468},"3zc99xG18IfmkGhClCyKQ0",{"url":469,"details":470,"fileName":474},"//images.ctfassets.net/7mrdlclm9xss/3zc99xG18IfmkGhClCyKQ0/146a9591ed5a405d293654a9d353a7b0/08_PocoTI__type.png",{"size":471,"image":472},663023,{"width":54,"height":473},714,"08_PocoTI _type.png",{},{"id":477,"type":64,"data":478,"tunes":480},"PffvWku_yM",{"text":479,"align":67},"\u003Cb>──この圧倒的な解像度の向上を、今後プロダクトへどのように活かしていくのでしょうか。\u003C/b>",{},{"id":482,"type":64,"data":483,"tunes":485},"5fUH3qiWmO",{"text":484,"align":67},"\u003Cb>加藤：\u003C/b>これまで私たちが培ってきた「ユーザーさんに寄り添うマインド」を、システムとして実装できるようになりました。たとえば、つながりを求めるタイプ（C）の方には新しいコミュニティとの出会いを、応援したい気持ちが強いタイプ（S）の方にはライバーさんとの絆が深まる仕組みを提案する、といった具合です。",{},{"id":487,"type":64,"data":488,"tunes":490},"muOXsm0ycY",{"text":489,"align":67},"AIがユーザーさん一人ひとりの心理状態を瞬時に理解し、可視化してくれるからこそ、私たちは「一律の施策」から脱却できます。こうしたユーザーさんの特徴量を活用することで、それぞれの状態に応じた最適な体験をリアルタイムで届けることが可能となります。",{},{"id":492,"type":493,"data":494,"tunes":500},"bjbI0K-WZ5","embed",{"service":495,"source":496,"embed":497,"width":498,"height":499,"caption":7},"youtube","https://youtu.be/ARBw3IgVEUM?si=BTPnw9oqKt8FxfyN","https://www.youtube.com/embed/ARBw3IgVEUM?",580,320,{},{"id":502,"type":89,"data":503,"tunes":505},"z2oKUNEcx7",{"text":504,"level":40},"AIで感性を研ぎ澄まし、世界一「ユーザー解像度」が高いチームへ",{},{"id":507,"type":64,"data":508,"tunes":510},"KsPfMwtrkV",{"text":509,"align":67},"\u003Cb>──これまでのお話から、Pococha独自の取り組みによって、チームが驚異的なスピード、質、量で変化してきたことがわかりました。これから皆さんが実現したいこと、目指すビジョンについて教えてください。\u003C/b>",{},{"id":512,"type":64,"data":513,"tunes":515},"8EK_YaAYT1",{"text":514,"align":67},"\u003Cb>加藤： \u003C/b>今日のお話を通して「Pocochaらしさ」を感じていただけたのだとしたら、それは『Pococha』がどこまでもコミュニティを大切にするプロダクトだからだと思います。『Pococha』には日々、熱いやり取りが行われる小さなコミュニティが多数存在しています。その一つひとつをしっかりと理解していくためには、そこで交わされているコミュニケーションの内容を深く読み解くことが不可欠です。",{},{"id":517,"type":105,"data":518,"tunes":527},"L9tWpqKzkR",{"caption":7,"asset":519},{"id":520,"file":521},"6OyOXf20oUPVCIendjCHHv",{"url":522,"details":523,"fileName":526},"//images.ctfassets.net/7mrdlclm9xss/6OyOXf20oUPVCIendjCHHv/d24785852cd7e5f4e09cf562afd8abd1/09_260309_FS_158.jpg",{"size":524,"image":525},595954,{"width":54,"height":55},"09_260309_FS_158.jpg",{},{"id":529,"type":64,"data":530,"tunes":532},"ANl_OMC9iF",{"text":531,"align":67},"LLMの登場によって、これまで人が膨大な時間をかけて行っていた会話内容の分析が、瞬時に可能になりました。これによって、ユーザー解像度を今までとは違う次元に持っていくことができるようになったと考えています。",{},{"id":534,"type":64,"data":535,"tunes":537},"5n63CdliPj",{"text":536,"align":67},"その深いユーザー理解を基盤とした上で、今後のPdMに問われるのは、AIという新しい技術を単に転用するのではなく、「AIがあるからこそつくれる新しいユーザー体験や価値」を生み出せるかどうかではないでしょうか。日本発の世界規模のtoCサービスを目指すと同時に、新しい価値を形にできるPdMを輩出していきたいと思っています。",{},{"id":539,"type":64,"data":540,"tunes":542},"nj9RlyBG0k",{"text":541,"align":67},"\u003Cb>金丸：\u003C/b>目標は、『Pococha』をライブ配信という領域で世界一のサービスにすることです。これは、「世界一ユーザーの解像度が高いチーム」であることと同義だと思っています。AIの進化によって、これまでは人を介すことで損なわれがちだったユーザーさんの「声の質感」や「さまざまな感情」といった情報も、純度の高い状態でプロダクト開発に繋げられるようになりました。",{},{"id":544,"type":64,"data":545,"tunes":547},"DmJ7xkweVM",{"text":546,"align":67},"また、人では叶わなかったことをAIに代替させる発想も大切です。『Pococha』では、AIを「ポコ助」と名付けて擬人化し、イベントのパブリックビューイングで司会を任せるなど、「1メンバー」として扱うエンタメ的なカルチャーもあります。人では出来ない膨大な情報量を瞬時にキャッチアップして体験を飛躍的に向上させてくれるAIは、私たちにとって「良きパートナー」であり、世界一のサービスをつくる上でも不可欠な存在です。",{},{"id":549,"type":64,"data":550,"tunes":552},"UJ1sn0C8DF",{"text":551,"align":67},"\u003Cb>安達：\u003C/b>3月のイベントで南場さんが発した「中途半端な専門性は淘汰される」という視点に立てば、我々がなすべきは、コミュニティ理解という圧倒的な専門性を、AIをフル活用して世界一のレベルまで高めることです。",{},{"id":554,"type":105,"data":555,"tunes":564},"177S7ka-CD",{"caption":7,"asset":556},{"id":557,"file":558},"5LGS5AX2lDNeJ5SXS6C4Ok",{"url":559,"details":560,"fileName":563},"//images.ctfassets.net/7mrdlclm9xss/5LGS5AX2lDNeJ5SXS6C4Ok/df8ace6d6b86ab518a63704956638c45/10_260309_FS_197.jpg",{"size":561,"image":562},588967,{"width":54,"height":55},"10_260309_FS_197.jpg",{},{"id":566,"type":64,"data":567,"tunes":569},"5gRy9qwoXs",{"text":568,"align":67},"データサイエンティストとしては、事業を理解し、AIを駆使して分析し、ダッシュボードの作成から運用までを一貫して行う。そんな、他社ではまだ確立されていない０→1まですべてを1人でカバーできる「新しい働き方」のロールモデルを、このPocochaから発信していきたいと思っています。",{},{"id":571,"type":64,"data":572,"tunes":574},"HvnxISvn8z",{"text":573,"align":67},"\u003Cb>── 最後に教えてください。皆さんにとってAIとは、どのような存在ですか？\u003C/b>",{},{"id":576,"type":64,"data":577,"tunes":579},"9dxe1gu5PW",{"text":578,"align":67},"\u003Cb>金丸： \u003C/b>今や「水」や「ペン」と同じくらい当たり前の、日常的な道具です。同時に、手元に置く「ナイフ」のようでもあります。ないと困るけれど、切れ味が鋭いからこそ、扱い方を間違えるとケガをしてしまう。使用する人自身や目的によって大きく変化するものです。とはいえ、我々にとっては、もはやそれなしでは考えられない、不可欠な存在です。",{},{"id":581,"type":64,"data":582,"tunes":584},"kisdAwUD-D",{"text":583,"align":67},"\u003Cb>加藤：\u003C/b>私も同じく「ツール」だと捉えています。日々の仕事において、この強力なツールをいかに使いこなしていくかが重要である、という考えです。 ",{},{"id":586,"type":64,"data":587,"tunes":589},"LGHi8ibC9I",{"text":588,"align":67},"\u003Cb>安達：\u003C/b> 私も同じです。あと、今後はAIシミュレーションとフィジカルAIの進化を楽しみにしています。",{},{"id":591,"type":64,"data":592,"tunes":594},"a0yCaU_IQV",{"text":593,"align":67},"\u003Cb>── AIを特別なものではなく、自分たちの分身や道具として手懐けている姿が印象的でした。本日はありがとうございました。\u003C/b>",{},{"id":596,"type":105,"data":597,"tunes":606},"iczOE8aapj",{"caption":7,"asset":598},{"id":599,"file":600},"7xLXB1AXrfBsbsZ3QVnWTi",{"url":601,"details":602,"fileName":605},"//images.ctfassets.net/7mrdlclm9xss/7xLXB1AXrfBsbsZ3QVnWTi/0f72a913ba6134da1cd46692c5940f5d/11_260309_FS_474.jpg",{"size":603,"image":604},897906,{"width":54,"height":55},"11_260309_FS_474.jpg",{},{"id":608,"type":64,"data":609,"tunes":611},"cDmP_e-9Mw",{"text":610,"align":67},"※本記事掲載の情報は、公開日時点のものです。",{"wrapped":612},{"types":613},[86],{"id":615,"type":64,"data":616,"tunes":618},"afa4LnVh0s",{"text":617,"align":67},"※株式会社ディー・エヌ・エーおよびすべての子会社（以下「DeNAグループ」）は、\u003Ca href=\"https://csr.dena.com/jp/technology/aipolicy/ai-policy/\" target=\"_blank\">DeNAグループAIポリシー\u003C/a>に基づき、情報セキュリティ管理および個人情報管理に関する基本方針に則った取り組みを遂行しています。",{"wrapped":619},{"types":620},[86],{"id":622,"type":64,"data":623,"tunes":626},"NPZnZmJxZ4",{"text":624,"align":625},"執筆・編集：川越 ゆき　撮影：内田 麻美\u003Cbr>撮影場所：WeWork 渋谷スクランブルスクエア 共用エリア/会議室","RIGHT",{},"2.26.4","ファウンダーの南場による「AIオールイン」宣言から1年。DeNA全社でAIネイティブ化が進む中、LLMの活用によって大きな変化を遂げた組織があります。\n\nそれは、ライブコミュニケーションアプリ『Pococha』を運営するPococha事業部。AIを掛け合わせることで何が変わり、どのような価値が生まれているのか。\n\n『Pococha』のPdM、コミュニティマネージャー、データサイエンティストの3人に、その最前線を聞きました。\n\n※本文中では、Pococha事業部を「Pococha」、サービス名を「『Pococha』」と表記しています。\n\n「職人の修行」をAIで代替。生産性を劇的に変えた「知の共有」\n\n── 「AIオールイン」によって、この1年でどのような変化がありましたか？\n\n加藤 貴浩（以下、加藤）： プロダクトに関しては、AI機能の企画から開発・運用までのサイクルを自律的に回せる体制が整った、という段階にあります。\n\n▲ライブコミュニティ事業本部Pococha事業部プロダクト部 副部長　加藤 貴浩（かとう たかひろ）2024年にDeNAへ中途入社。プロダクト部副部長としてPdM陣のマネジメントを担当。同時に、大規模アジャイル開発のフレームワーク「SAFe（Scaled Agile Framework）」をベースとした、スケーラブルな強いプロダクト組織づくりと運営に従事。\n\n直近では、2026年1月に、配信中のコメントからAIがリアルタイムに配信タイトルを自動生成する機能をリリースしました。単に開発して終わりではなく、リリース後もAIが想定通りに動いているかを把握し、その結果を受けてプロンプトを改善していく。こうした運用まで含めた一連のサイクルを回せるようになったことは、組織として大きな転換点だと感じています。\n\n── 金丸さんの担当されているコミュニティ領域ではいかがでしょうか。\n\n金丸 裕佑（以下、金丸）： 組織としての一番大きな変化は、特定のメンバーに知識が偏る「知の偏在」が解消され、組織全体で知見を共有できるようになったことです。私が管掌しているのはコミュニティ領域、つまりアプリ内でのユーザーさん同士のつながりや、それと連動したオフラインのイベントなど、デジタルと非デジタルの両面で「絆」を守っていく役割を担っています。\n\n▲ライブコミュニティ事業本部Pococha事業部プラットフォームマネジメント部 部長　金丸 裕佑（かねまる ゆうすけ）新卒でメガバンク傘下の金融事業会社に入社。その後、MBA、コンサルティングファームでの経営コンサルタント職、MIXIでの事業開発部長を経て、2022年にDeNAへ中途入社。DeNAと並行して、会社経営・大学教員等にも取り組む。\n\nコミュニティマネジメントは、あらゆる産業に於いて不可欠であるものの、まだ知識としても技術としても未確立な部分が多い領域です。「コミュニティをどうつくり、どう成長させ、どう運用していくのか」といった拠り所となる知見が世の中にもまだ少ないため、これまではメンバー個々人が持つ知識や経験、スキルが偏在し、散らばっている状態でした。\n\nしかしAIを活用するようになってから、あらゆるシーンでこの分散されていた知識が統合されるようになり、アウトプットやアウトカムの質が、以前とは比較にならないほど抜本的に向上しました。以前であればOJTやOFFJT、実務経験など、一定の水準に達するために必要だった時間や経験の蓄積、いわば「職人の修行時間」が大幅にカットされ、本来届けるべき価値の追求に時間を割けるようになりました。結果として、生産性が飛躍的に伸びたと実感しています。\n\n── AI活用を推進する安達さんの視点ではどうでしょうか。\n\n▲IT本部AI・データ戦略統括部AI技術開発部　安達 涼（あだち りょう）神経経済学分野で博士号を取得 (カリフォルニア工科大学)後、2018年にDeNAへ中途入社。人間の経済・社会的意思決定の数理的、脳科学的メカニズムに興味をもつ。現在はソーシャルデータサイエンスチームを立ち上げ、ライブコミュニティ事業において、AIを駆使した社会的つながりの解明と事業活用に従事。\n\n安達 涼（以下、安達）： AIチームの視点から補足すると、この1年で大きく3つの変化がありました。\n\n1つ目は「テキスト分析」の進化です。『Pococha』には発話やコメントなどの膨大なテキストデータがありますが、くだけた表現も多く、これまでは機械学習で分析するハードルが高くなっていました。それが、コンテキストを理解して「よしなに」分析してくれるLLMの登場で一変しました。リッチなコミュニケーションデータを活用した分析や機能の実装など、この1年でできること・やりたいことが一気に広がりました。\n\n2つ目は「ダッシュボード実装」のスピードです。これまで事業部向けダッシュボードをデプロイする際には、エンジニアに相談した上で、優先度の兼ね合いや他部署との調整などに数ヶ月を要していました。それが、Claude CodeやCursor、DevinといったAI駆動開発ツールを活用することで、データサイエンティストが一人でReactを用いた複雑なアプリケーションの開発・実装からデプロイまで完結させ、短期間で現場にデリバリーできるようになりました。\n\nそして3つ目が、こうした効率化によって「中長期的な技術スタックの蓄積」に時間を割けるようになったことです。既存業務に関わる分析・開発の工数が削減されたことで、半年・一年先の実装を見据えた技術検証を、より早期に実行できるようになりました。\n\n全社導入Geminiが転換点。試行錯誤を加速させる「アンラーニング」の文化\n\n──南場さんの「AIオールイン」宣言以降、具体的にはどのような動きから始まったのでしょうか。\n\n加藤： 最初は安達さんのAIチームと短期的なプロジェクトを立ち上げ、「AIを活用した機能を『Pococha』に実装する」という目標から始まりました。ただ、当初はAIをどのようにUXに落とし込むのか、具体的なイメージを描ききれていない部分もありました。\n\n転換点は、Geminiが全社導入され、メンバーが直接AIに触れる機会が増えたことです。「こういう情報を渡せば、こう返ってくる」という実感を個々人が得たことで、企画の解像度が一気に上がりました。『Pococha』はライブコミュニケーションアプリなので、ユーザーさんのテキストデータが大量にあります。「LLMとの親和性が極めて高い」と気づいてからは、AIを活用する機能の企画がどんどん形になっていきました。\n\n金丸： Pocochaにはもともと「新しいものに挑戦する」カルチャーがあり、南場さんの号令は強い「追い風」でした。特に、僕らが大切にしてきた「仮説検証を繰り返して学びを体系化する」というコミュニティマネジメントの手法が、AIを試行錯誤するプロセスと綺麗にフィットしました。全社的なGemini導入という流れも相まって、まさに「点と線がつながり」、組織として一気に加速しました。\n\nコミュニティで交わされる内容は定量化しにくい定性的なものも多く、これまでは、個別の声をつぶさに聞いていったり、イベント後にユーザーインタビューを行ったりしてきました。それでもすべてのデータが把握できるわけではなく、推測に頼らざるを得ない部分もありましたし、かなり意識はしていても情報の鮮度という意味では、真にリアルタイムではない課題もあったんです。それが安達さんがつくってくれたツールによって、広範囲でモニタリングできるようになりました。\n\nAIを業務にネイティブに使えるチームになったことで、知の偏在がなくなり、スピードも上がりました。リアルタイムでモニタリングできることで、「こうしたらユーザーさんにもっと喜んでもらえるんじゃないか」を試して、次の施策にスピーディーに反映していく。打席に立つ数が増え、結果としてヒットも生まれやすくなる。そんな良い循環が生まれています。\n\n専門用語の壁を打破。AIがエンジニアと事業部を繋ぐ「共通言語」に\n\n──『Pococha』とLLMの相性が良かった。それだけで、これほど大きな変化が生まれるものなのでしょうか？\n\n安達： AI技術への大きな期待感が生まれたことは過去にもありましたが、AIが事業部のあらゆる部分にまで浸透したことはありませんでした。今回のLLMの台頭によって初めて、AI活用が事業部のどのメンバーにとっても「自分ごと」になりました。\n\nこれまでは、事業部メンバーからみれば、機械学習モデルが何をしているのか分からない部分が多かったと思います。しかしGeminiなどのAIツールが導入された今、たとえば「CSV形式のデータをアップロードして分析する」といった、かつてはアナリストや機械学習エンジニアが担っていた作業も、事業部メンバーが自らAIとチャット形式で完結できるようになりました。\n\nこれによってデータサイエンティスト・エンジニアと事業部メンバー間のコミュニケーションが劇的に活発化し、専門用語の壁が取り払われて「共通言語」が生まれた。これこそが、最大のブレイクスルーだと感じています。\n\n──共通言語ができたことで、職種間の連携の質も変わりそうです。\n\n加藤：確かに、以前はエンジニアからの技術的な説明を「難しいな」と感じながら聞いているような場面もありました。それが、AIへの解像度が上がったことで、プロダクト側から「LLMを使って○○なことはできないか」と具体的なアイデアを提案できるレベルになり、職種間の目線が合うようになりました。互いの専門性を理解しつつ、共通のツールと言語を持つことで、意思疎通の速度と深さが段違いに向上したと感じています。\n\nまた、新機能の開発やローンチにおいて、コミュニティマネジメントチームとの密な連携は欠かせません。AIによる深いユーザー理解は、新機能に対してコミュニティがどう反応するかを予測したり、最適なユーザーコミュニケーションを設計したりするうえで、『Pococha』の強力な武器となっています。\n\n金丸： 実務の現場で特に顕著に感じているのは、プロフェッショナルが陥りがちな「ガラスの天井」が打破されたことです。経験豊富なメンバーほど、企画や施策、イベントを立案するアプローチにおいて、「こうすればこうなる」という規定路線や固定観念、あるいは予算や工数の制約といった見えない「キャップ」を知らず知らずの内に思考にかけてしまいがちです。\n\nですが、AIを「壁打ち相手」として活用し、対話しながら企画を練ることで、個人の想像力を超えた斬新なアイデアが次々と創出されるようになりました。この「思考の拡張と深化」こそが重要です。結果として、ネガティブな制約から解放され、「どうすれば実現できるか」という前向きな発想へと転換されました。最終的に、ユーザーさんに届けるべき本質的な価値の追求に集中できるようになったと実感しています。\n\n──なぜPocochaチームは、そこまでスムーズにAIを使いこなせるようになったのでしょうか。\n\n金丸： 変化に対する強い弾力性と、「新しいもの好き」が集まるカルチャーが土壌にあったからだと思います。\n\n特に効果的だったのは、「教え合い、ノウハウを即座に共有する」仕組みです。誰かがプロンプトのコツを掴めば、その知見が組織全体に一気に伝播し、各プロジェクトでさらに進化していく。この「スパイラル的な進化」が組織全体の底上げ、言わば「高次元での金太郎飴化」を可能にしました。既存の成功モデルに固執せず、新しいものを否定しない「アンラーニング」の姿勢が、AIネイティブ化を加速させる大きな推進力になったと感じています。\n\n──AIが組織にどんどん浸透していく中で、安達さん側、つまりAIチームとして何か取り組まれたことはありましたか。\n\n安達：実は、私たち側の変化というよりは、事業部側の変化が大きかったと感じています。Geminiなどでの壁打ちを通じて、事業部メンバーから「UX向上のためにこんなことをやりたいが、AIで○○なことをやるのは可能か」といった具体的なアイデアが自発的に出てくるようになりました。これはAIが浸透する前にはあまり見られなかった現象です。\n\n開発プロセスも大きく変わりました。以前なら、データを使って検証し、フィードバックをもらって……というやり取りを繰り返し、一定のクオリティに達するまでに2〜3ヶ月を要していました。その間に事業状況が変わってしまい、せっかくの分析を施策に活かし切れないことも少なくありませんでした。しかし現在は、AI駆動開発により、フィードバックを受ければ即座に変更点をダッシュボード内に実装できます。\n\nさらに、検証に使えるデータの範囲も広がりました。以前は限られたデータセットでの実験に留まっていましたが、今は広範囲のユーザーデータを用いて、事業部のメンバーが自らダッシュボード上でインタラクティブに検証を行えます。これによって検証サイクルが大幅に短縮され、開発工数も大幅に削減されました。\n\n──プロジェクトのスパンが短くなり、回数も増えたことで、安達さん側の「質」も向上したということでしょうか。\n\n安達：質に関しては、1つの正解を探すのではなく、複数のシナリオや施策のパターンを同時に提示できるようになったことが大きいです。同じ時間で、今までは一つしかできなかったものが、今は複数提示できる。施策の「厚み」が増したと感じています。\n\n数百万人の声をリアルタイムに構造化。新手法「ブロードリスニング」の真価\n\n── これまでPocochaでは多くの方へのユーザーインタビューを通じて、ユーザーさん一人ひとりと向き合ってきたと聞いています。その「個の理解」はAIによってどう変わったのでしょうか。\n\n金丸：インタビューは、ユーザーさんを深く知るために不可欠なものです。これまで実施したインタビューは3000時間以上に及びます。コミュニティ運営を考える上で、「ユーザーさんが何を言い、何を考えているのか」を最優先にインタビューを続けてきましたが、やはりそこには物理的な限界がありました。\n\nまた、どうしても「バックミラーを見ながら運転している」ような、少し前の情報の分析になりがちで、分析から施策に適用するまでに一定のリードタイムがかかってしまう現実もありました。そこで導入したのが、LLMを活用した「ブロードリスニング」です。\n\nこれは言わば、「数百万人のユーザーさんに対して同時にインタビューを行っている」ような状態です。これまで多くの時間をかけて抽出していた深いインサイトを、コミュニティ全体の膨大な発話データからリアルタイムに構造化し、捉えられるようになりました。ユーザーさんのホットでリアルな声を瞬時に確認できるため、今日この瞬間の声を、明日あるいは今日の施策に速やかに転用することが可能になっています。\n\n安達：これまでPocochaチームが積み重ねてきた3000時間を超える定性データは、まさに「宝」です。それをAIに学習・活用させることで、主観に頼らない客観的なデータとして「コミュニティの熱量」を可視化できるようになりました。\n\n膨大なデータをAIで網羅的に収集・要約することで、特定の施策に対しても「どのようなタイプのユーザーさんが、どのような文脈で喜んでくださっているか」を即座に判定できます。また、少数のユーザーさんしか発信していないような、マイナーだけれども重要なご意見や、不具合・不正の火種を早期に検知して対処できるようにもなりました。この情報の「鮮度」が、今の『Pococha』の強みに繋がっていると思います。\n\n金丸： また、これによってコミュニティ運営に置けるオンライン（アプリ内）とオフライン（イベントなど）の領域が地続きになり、熱量の高い「オンライン⇔オフラインのループ」が生まれています。\n\nオフライン特有の「熱量の高さ」と、オンラインの持つ「拡散性」。AIによってそれぞれの弱点が補完され、相互の強みがより引き立てられるようになりました。その結果、「消費者」としての楽しみ方が中心だったユーザーさんが、自ら場をつくる「当事者」となり、その熱量がサービス全体に波及していくサイクルをこの1年で実現できています。\n\n安達： さらに今後は、「パーソナライゼーション」を極めていきたいと考えています。サービス内で各々のユーザーさんがどのような状態にあって、その状態のときはどのような行動をおすすめすればもっと『Pococha』を楽しめるのか。行動データだけでなく、LLMを用いたテキスト分析を掛け合わせることで、ユーザーさんの心理的な解像度を高めています。\n\nたとえば、リスナーさんがライバーさんとどのように打ち解け、ファンになっていくのかという「ユーザージャーニー」の変化も、コメントや会話の内容から追えるようになりました。\n\n──反応を追うだけでなく、その裏側にある「心理」もAIで捉えようとしている、ということでしょうか？\n\n安達：はい。それが新たに開発したリスナーのタイプ分析「PocoTI（Poco Type Indicator）」（以下、「PocoTI」）です。これは、ランクや応援レベルといった「行動の達成度」でユーザーさんを分類するのではなく、どんな心理的モチベーションで『Pococha』を楽しんでいるのかをLLMで推定し、分類するものです。MBTIという性格診断をご存知の方も多いと思いますが、これを参考に、これまで収集してきた約8万人のユーザーアンケートを活用して開発しました。\n\n■「PocoTI」の仕組み\n\n過去のユーザーアンケートとMBTIを参考に、以下3つの軸を定義しました。それぞれの軸を特徴づけるコメントや行動データを収集し、視聴時間などの定量データと、コメントのテキストデータを掛け合わることで、ユーザーさんを分類します。\n\n1. 根本動機：つながりたいのか、応援したいのか（C/S）2. 関係スタイル：グループが好きか、1対1（個人）を重視するか（G/I）3. 行動スタンス：自ら発信（表現）したいか、受け取り（見守り）たいか（E/R）\n\nたとえば、以下の図にある「CGE（盛り上げ役のコミュニケーター）」と「SIR（影から支える支援者）」では、心地よいと感じるコミュニケーションが全く異なります。\n\nかつては膨大な時間をかけてユーザー理解を深め、辿り着いていた「個別のニーズ」を、今はAIを活用してすべてのユーザーさんに対して自動的に把握することが可能になりました。\n\n──この圧倒的な解像度の向上を、今後プロダクトへどのように活かしていくのでしょうか。\n\n加藤：これまで私たちが培ってきた「ユーザーさんに寄り添うマインド」を、システムとして実装できるようになりました。たとえば、つながりを求めるタイプ（C）の方には新しいコミュニティとの出会いを、応援したい気持ちが強いタイプ（S）の方にはライバーさんとの絆が深まる仕組みを提案する、といった具合です。\n\nAIがユーザーさん一人ひとりの心理状態を瞬時に理解し、可視化してくれるからこそ、私たちは「一律の施策」から脱却できます。こうしたユーザーさんの特徴量を活用することで、それぞれの状態に応じた最適な体験をリアルタイムで届けることが可能となります。\n\nAIで感性を研ぎ澄まし、世界一「ユーザー解像度」が高いチームへ\n\n──これまでのお話から、Pococha独自の取り組みによって、チームが驚異的なスピード、質、量で変化してきたことがわかりました。これから皆さんが実現したいこと、目指すビジョンについて教えてください。\n\n加藤： 今日のお話を通して「Pocochaらしさ」を感じていただけたのだとしたら、それは『Pococha』がどこまでもコミュニティを大切にするプロダクトだからだと思います。『Pococha』には日々、熱いやり取りが行われる小さなコミュニティが多数存在しています。その一つひとつをしっかりと理解していくためには、そこで交わされているコミュニケーションの内容を深く読み解くことが不可欠です。\n\nLLMの登場によって、これまで人が膨大な時間をかけて行っていた会話内容の分析が、瞬時に可能になりました。これによって、ユーザー解像度を今までとは違う次元に持っていくことができるようになったと考えています。\n\nその深いユーザー理解を基盤とした上で、今後のPdMに問われるのは、AIという新しい技術を単に転用するのではなく、「AIがあるからこそつくれる新しいユーザー体験や価値」を生み出せるかどうかではないでしょうか。日本発の世界規模のtoCサービスを目指すと同時に、新しい価値を形にできるPdMを輩出していきたいと思っています。\n\n金丸：目標は、『Pococha』をライブ配信という領域で世界一のサービスにすることです。これは、「世界一ユーザーの解像度が高いチーム」であることと同義だと思っています。AIの進化によって、これまでは人を介すことで損なわれがちだったユーザーさんの「声の質感」や「さまざまな感情」といった情報も、純度の高い状態でプロダクト開発に繋げられるようになりました。\n\nまた、人では叶わなかったことをAIに代替させる発想も大切です。『Pococha』では、AIを「ポコ助」と名付けて擬人化し、イベントのパブリックビューイングで司会を任せるなど、「1メンバー」として扱うエンタメ的なカルチャーもあります。人では出来ない膨大な情報量を瞬時にキャッチアップして体験を飛躍的に向上させてくれるAIは、私たちにとって「良きパートナー」であり、世界一のサービスをつくる上でも不可欠な存在です。\n\n安達：3月のイベントで南場さんが発した「中途半端な専門性は淘汰される」という視点に立てば、我々がなすべきは、コミュニティ理解という圧倒的な専門性を、AIをフル活用して世界一のレベルまで高めることです。\n\nデータサイエンティストとしては、事業を理解し、AIを駆使して分析し、ダッシュボードの作成から運用までを一貫して行う。そんな、他社ではまだ確立されていない０→1まですべてを1人でカバーできる「新しい働き方」のロールモデルを、このPocochaから発信していきたいと思っています。\n\n── 最後に教えてください。皆さんにとってAIとは、どのような存在ですか？\n\n金丸： 今や「水」や「ペン」と同じくらい当たり前の、日常的な道具です。同時に、手元に置く「ナイフ」のようでもあります。ないと困るけれど、切れ味が鋭いからこそ、扱い方を間違えるとケガをしてしまう。使用する人自身や目的によって大きく変化するものです。とはいえ、我々にとっては、もはやそれなしでは考えられない、不可欠な存在です。\n\n加藤：私も同じく「ツール」だと捉えています。日々の仕事において、この強力なツールをいかに使いこなしていくかが重要である、という考えです。 \n\n安達： 私も同じです。あと、今後はAIシミュレーションとフィジカルAIの進化を楽しみにしています。\n\n── AIを特別なものではなく、自分たちの分身や道具として手懐けている姿が印象的でした。本日はありがとうございました。\n\n※本記事掲載の情報は、公開日時点のものです。\n\n※株式会社ディー・エヌ・エーおよびすべての子会社（以下「DeNAグループ」）は、DeNAグループAIポリシーに基づき、情報セキュリティ管理および個人情報管理に関する基本方針に則った取り組みを遂行しています。\n\n執筆・編集：川越 ゆき　撮影：内田 麻美撮影場所：WeWork 渋谷スクランブルスクエア 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