{"id":22167,"date":"2025-11-17T22:03:00","date_gmt":"2025-11-17T21:03:00","guid":{"rendered":"https:\/\/bstartup.jellibylab.com\/inteligencia-artificial-en-2025-perspectivas-de-inversion-y-las-nuevas-olas-de-innovacion\/"},"modified":"2026-01-19T22:18:48","modified_gmt":"2026-01-19T21:18:48","slug":"inteligencia-artificial-en-2025-perspectivas-de-inversion-y-las-nuevas-olas-de-innovacion","status":"publish","type":"post","link":"https:\/\/bstartup.bancsabadell.com\/ca\/inteligencia-artificial-en-2025-perspectivas-de-inversion-y-las-nuevas-olas-de-innovacion\/","title":{"rendered":"Intel\u00b7lig\u00e8ncia Artificial el 2025: Perspectives d\u2019inversi\u00f3 i les noves onades d\u2019innovaci\u00f3"},"content":{"rendered":"
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Durant les \u00faltimes dues d\u00e8cades, poques tecnologies han tingut un impacte tan transformador i transversal com la intel\u00b7lig\u00e8ncia artificial (IA). Si b\u00e9 la seva hist\u00f2ria comen\u00e7a molt abans, el veritable punt d\u2019inflexi\u00f3 va arribar amb l\u2019auge de l\u2019aprenentatge profund, el creixement exponencial del poder computacional i, m\u00e9s recentment, la irrupci\u00f3 de la IA generativa. Per als fons de venture capital, aix\u00f2 representa una revoluci\u00f3 en temps real, on les oportunitats floreixen, per\u00f2 tamb\u00e9 requereixen una aguda capacitat d\u2019an\u00e0lisi i timing de mercat.<\/em><\/p>\n

 <\/p>\n

L\u2019auge imparable de la inversi\u00f3 en IA<\/strong><\/span><\/p>\n

Les xifres parlen per si soles: segons dades de The Economist, en el 2024 la inversi\u00f3 global en IA va aconseguir 200.000 milions de d\u00f2lars, el doble que en el 2023. Aix\u00f2 inclou tant capital risc com inversi\u00f3 en infraestructura, centres de dades, i el desenvolupament de xips especialitzats per a tasques d\u2019infer\u00e8ncia i entrenament de models. Aquest frenes\u00ed d\u2019inversi\u00f3 ha estat liderat per actors com Nvidia, Amazon, Microsoft i Alphabet, que no sols aposten per models propis, sin\u00f3 tamb\u00e9 per crear el hardware i la infraestructura necessaris per a escalar la IA.<\/p>\n

 <\/p>\n

A Europa, el panorama no es queda enrere. Segons un estudi de IDC citat per Europa Press, la despesa empresarial en intel\u00b7lig\u00e8ncia artificial a la regi\u00f3 EMEA va augmentar un 61% en el 2024 respecte a l\u2019any anterior. Aquest creixement ha estat estimulat per incentius p\u00fablics, l\u2019adopci\u00f3 en sectors tradicionals com la banca i la ind\u00fastria, i una nova generaci\u00f3 de startups enfocades en solucions verticals.<\/p>\n

 <\/p>\n

En qu\u00e8 estan invertint els fons de VC?<\/strong><\/span><\/p>\n

1. Apostes en models fundacionals\u2026 per\u00f2 amb cautela<\/p>\n

Durant la primera onada d\u2019entusiasme generada per models com ChatGPT, Bard o Claude, molts fons van explorar invertir directament en startups centrades en grans models ling\u00fc\u00edstics (LLMs). No obstant aix\u00f2, l\u2019elevada barrera d\u2019entrada t\u00e8cnica i el domini de pocs actors (OpenAI, Google, Anthropic, Mistralenc, Cohere) ha redirigit l\u2019inter\u00e8s cap a aplicacions pr\u00e0ctiques i models m\u00e9s lleugers, que poden adaptar-se a contextos locals o necessitats espec\u00edfiques de negoci.<\/p>\n

Molts VCs han pres nota que els guanyadors no sempre seran els qui cre\u00efn els models m\u00e9s potents, sin\u00f3 els qui aconsegueixin integrar-los de manera efica\u00e7 en fluxos de treball del m\u00f3n real.<\/p>\n

 <\/p>\n

2. IA vertical: menys hype, m\u00e9s especialitzaci\u00f3<\/p>\n

La gran promesa est\u00e0 en les solucions verticals. Startups que apliquen IA generativa o predictiva a sectors com legaltech, insurtech, salut, log\u00edstica, energia o agroalimentaci\u00f3 s\u00f3n cada vegada m\u00e9s atractives per als inversors. Aquestes empreses no competeixen per crear el pr\u00f2xim ChatGPT, sin\u00f3 per resoldre un problema espec\u00edfic amb avantatges competitius reals: dades propiet\u00e0ries, know-how sectorial, integraci\u00f3 amb sistemes legacy, etc.<\/p>\n

Alguns exemples:
\n\u00b7 IA per a an\u00e0lisi de contractes legals amb models entrenats espec\u00edficament en legislaci\u00f3 local.
\n\u00b7 Eines de suport cl\u00ednic per a diagn\u00f2stic o documentaci\u00f3 m\u00e8dica en temps real.
\n\u00b7 Plataformes de gesti\u00f3 energ\u00e8tica que optimitzen el consum en temps real combinant IA i sensors IoT.<\/p>\n

 <\/p>\n

3. Infraestructura: el \u201cpic i pala\u201d de l\u2019era de la IA<\/p>\n

Igual que en la febre de l\u2019or, no sempre guanyen els qui busquen l\u2019or, sin\u00f3 els qui venen les pales. Aix\u00ed ho han ent\u00e8s molts fons que estan apostant per la infraestructura necess\u00e0ria per a escalar la IA: xips, emmagatzematge, xarxes de distribuci\u00f3, i plataformes middleware per a orquestrar models en producci\u00f3.<\/p>\n

Empreses com Modular, Weights & Biases, Hugging Face o Lambda Labs estan capitalitzant aquesta necessitat d\u2019infraestructura que no dep\u00e8n d\u2019un cas d\u2019\u00fas concret, sin\u00f3 de l\u2019aven\u00e7 general de l\u2019ecosistema.<\/p>\n

 <\/p>\n

4. Eines per a l\u2019adopci\u00f3 empresarial<\/p>\n

Un dels colls d\u2019ampolla actuals \u00e9s la implementaci\u00f3 efectiva de IA en empreses tradicionals. Aqu\u00ed estan emergint startups que ofereixen plataformes low-code per a construir fluxos de treball amb IA, solucions de governan\u00e7a de dades, avaluaci\u00f3 de biaixos, explainability, i compliment regulador (AI Governance). Aquest ser\u00e0 un dels segments clau especialment a Europa, amb l\u2019entrada en vigor del Reglament de IA de la Uni\u00f3 Europea.<\/p>\n

 <\/p>\n

Qu\u00e8 busquen els inversors en una startup de IA?<\/strong><\/span><\/p>\n

Encara que les m\u00e8triques cl\u00e0ssiques com el TAM (mercat total direccionable), la tracci\u00f3 i l\u2019equip continuen sent fonamentals, els VCs hem afegit alguns criteris espec\u00edfics per a avaluar startups de IA:<\/p>\n

    \n
  • Dades propiet\u00e0ries: els models sense dades diferencials tenen cada vegada menys avantatge competitiu. Els fons busquen acc\u00e9s exclusiu a datasets \u00fanics o formes innovadores de recol\u00b7lectar-los (per exemple, mitjan\u00e7ant aplicacions m\u00f2bils o aliances industrials).<\/li>\n
  • Capacitat de finetuning: no es tracta nom\u00e9s d\u2019usar GPT-4, sin\u00f3 de com s\u2019adapta el model a un domini o necessitat concreta.<\/li>\n
  • Mecanismes defensius: Qu\u00e8 evita que un competidor amb acc\u00e9s als mateixos models p\u00fablics cre\u00ef una c\u00f2pia en setmanes?<\/li>\n
  • Unit economics clars: el cost computacional de la IA pot reduir marges si no s\u2019optimitza b\u00e9. Aquelles startups amb arquitectures eficients tindran avantatges.<\/li>\n<\/ul>\n

     <\/p>\n

    I cap a on anirem en el futur?<\/strong><\/span><\/p>\n

    1. Cap a models m\u00e9s petits, m\u00e9s privats i m\u00e9s locals<\/p>\n

    Contrari al que sembla, el futur de la IA no \u00e9s nom\u00e9s \u201cm\u00e9s gran\u201d. Ja s\u2019est\u00e0 observant una tend\u00e8ncia cap a models petits (com Phi-3 de Microsoft o Gemma de Google) que poden c\u00f3rrer en dispositius edge o ser finetunejats amb menys dades. Aix\u00f2 obrir\u00e0 la porta a aplicacions en sectors on la privacitat, lat\u00e8ncia o connectivitat s\u00f3n factors cr\u00edtics.<\/p>\n

     <\/p>\n

    2. IA multimodal<\/p>\n

    La combinaci\u00f3 de text, imatge, v\u00eddeo, \u00e0udio i dades estructurades en un mateix sistema (com GPT-4V o Gemini 1.5) transformar\u00e0 sectors com l\u2019atenci\u00f3 al client, el disseny de producte, la medicina o l\u2019entreteniment. Els inversors estem atents a startups que s\u00e0piguen traduir aquesta multimodalitat en avantatges competitius tangibles.<\/p>\n

     <\/p>\n

    3. Agents aut\u00f2noms<\/p>\n

    Ja no parlem nom\u00e9s de IA que respon, sin\u00f3 de IA que actua: sistemes que poden prendre decisions, executar accions en plataformes externes, interactuar amb APIs i optimitzar processos de manera cont\u00ednua. Encara que en fase experimental, els \u201cAI agents\u201d seran clau en \u00e0rees com operacions, m\u00e0rqueting automatitzat o log\u00edstica.<\/p>\n

     <\/p>\n

    4. IA responsable<\/p>\n

    Amb la pressi\u00f3 regulat\u00f2ria en augment, les startups que integrin des de l\u2019inici bones pr\u00e0ctiques de seguretat, \u00e8tica i explicabilitat tindran millors oportunitats per a escalar. La IA responsable no ser\u00e0 un extra, sin\u00f3 un requisit comercial i legal, especialment per a captar clients corporatius o institucionals.<\/p>\n

     <\/p>\n

    Conclusi\u00f3<\/strong><\/span><\/p>\n

    La intel\u00b7lig\u00e8ncia artificial est\u00e0 marcant el pas d\u2019una nova revoluci\u00f3 industrial. Per als fons de venture capital, la clau no \u00e9s nom\u00e9s anticipar quina tecnologia dominar\u00e0, sin\u00f3 entendre com i on s\u2019implementar\u00e0 de manera eficient i \u00e8tica. En aquesta nova era, la diferenciaci\u00f3 no vindr\u00e0 \u00fanicament de tenir el model m\u00e9s potent, sin\u00f3 de la capacitat d\u2019integrar-lo amb prop\u00f2sit, resoldre problemes reals i escalar de manera sostenible.<\/p>\n

     <\/p>\n

    En resum, la pr\u00f2xima generaci\u00f3 d\u2019unicorns de la IA no ser\u00e0 necess\u00e0riament la m\u00e9s cridanera, sin\u00f3 la m\u00e9s \u00fatil.<\/p>\n

     <\/p>\n

    Laurent Arens
    \n<\/strong>Director BStartup10<\/p>\n

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