{"id":134983,"date":"2026-07-02T09:49:07","date_gmt":"2026-07-02T13:49:07","guid":{"rendered":"https:\/\/www.agribusinessglobal.com\/?p=134983"},"modified":"2026-07-02T09:49:43","modified_gmt":"2026-07-02T13:49:43","slug":"why-delivery-will-win-crop-protections-ai-decade","status":"publish","type":"post","link":"https:\/\/www.agribusinessglobal.com\/pt\/agrochemicals\/why-delivery-will-win-crop-protections-ai-decade\/","title":{"rendered":"Por que a entrega vencer\u00e1 a d\u00e9cada da IA na prote\u00e7\u00e3o de cultivos"},"content":{"rendered":"

A prote\u00e7\u00e3o de cultivos est\u00e1 se aproximando de um momento crucial. As decis\u00f5es que as empresas tomarem hoje ajudar\u00e3o a determinar quem liderar\u00e1 o setor na pr\u00f3xima d\u00e9cada.<\/p>\n

A intelig\u00eancia artificial (IA) rapidamente se tornou um dos temas mais discutidos na agricultura. A maior parte da aten\u00e7\u00e3o tem se concentrado no que a IA pode fazer no campo, ajudando os produtores a melhorar a produtividade, otimizar insumos e tomar decis\u00f5es mais acertadas. Essas aplica\u00e7\u00f5es s\u00e3o importantes e continuar\u00e3o a gerar valor. Mas a maior oportunidade pode estar dentro da \u00e1rea de pesquisa e desenvolvimento (P&D), onde a pr\u00f3xima gera\u00e7\u00e3o de produtos fitossanit\u00e1rios \u00e9 descoberta e desenvolvida.<\/p>\n

Hoje em dia, quase todas as empresas t\u00eam uma hist\u00f3ria sobre IA. No entanto, as empresas que se destacarem como l\u00edderes n\u00e3o ser\u00e3o definidas pela efic\u00e1cia com que falam sobre IA. Elas ser\u00e3o definidas pela capacidade de descobrir, desenvolver e entregar produtos melhores com mais efici\u00eancia do que seus concorrentes.<\/p>\n

\u00c9 a\u00ed que reside a verdadeira oportunidade.<\/p>\n

A inova\u00e7\u00e3o significativa n\u00e3o vem apenas da IA. Ela surge da combina\u00e7\u00e3o de IA e aprendizado de m\u00e1quina com design computacional, dados propriet\u00e1rios e cientistas que sabem como questionar pressupostos, fazer as perguntas certas e interpretar resultados. A tecnologia pode gerar possibilidades. Os cientistas determinam quais valem a pena explorar.<\/p>\n

Quando essas pe\u00e7as trabalham juntas, a IA se torna mais do que uma ferramenta. Ela se torna uma forma de tomar melhores decis\u00f5es logo no in\u00edcio do processo de descoberta. E, em \u00faltima an\u00e1lise, s\u00e3o as melhores decis\u00f5es, e n\u00e3o os melhores algoritmos, que impulsionam a inova\u00e7\u00e3o.<\/p>\n

A efici\u00eancia do capital muda a equa\u00e7\u00e3o.<\/strong><\/h2>\n

A descoberta de produtos para prote\u00e7\u00e3o de cultivos sempre foi cara, demorada e incerta. Encontrar novas mol\u00e9culas eficazes exige capital e paci\u00eancia consider\u00e1veis, e muitos candidatos falham somente ap\u00f3s anos de investimento. A oportunidade criada pela IA n\u00e3o se resume a acelerar o processo. Ela permite aprender mais r\u00e1pido, identificar candidatos com baixo potencial mais cedo e concentrar recursos nas oportunidades com maior probabilidade de sucesso.<\/p>\n

O verdadeiro avan\u00e7o n\u00e3o est\u00e1 apenas na velocidade. Est\u00e1 na efici\u00eancia do capital.<\/p>\n

Um processo mais r\u00e1pido que prioriza as mol\u00e9culas erradas gera pouco valor. Um processo mais inteligente que aprimora a qualidade das decis\u00f5es ao longo da descoberta transforma a economia da inova\u00e7\u00e3o. Ele reduz o risco e aumenta o retorno sobre cada d\u00f3lar investido em pesquisa.<\/p>\n

Essa mudan\u00e7a \u00e9 importante porque as expectativas dos investidores mudaram. Os mercados de capitais recompensam cada vez mais a disciplina, a previsibilidade e a aloca\u00e7\u00e3o eficiente de recursos. Longos ciclos de desenvolvimento com perfis de risco opacos s\u00e3o submetidos a um escrut\u00ednio maior do que antes.<\/p>\n

Como resultado, a discuss\u00e3o em torno da descoberta orientada por IA est\u00e1 evoluindo. A quest\u00e3o n\u00e3o \u00e9 mais simplesmente se essas plataformas podem acelerar a pesquisa. \u00c9 se elas podem ajudar as empresas a inovar de forma mais produtiva e a alocar capital de forma mais eficaz.<\/p>\n

Em \u00faltima an\u00e1lise, por\u00e9m, o placar permanece o mesmo. A ind\u00fastria n\u00e3o \u00e9 recompensada por ideias. Ela \u00e9 recompensada por produtos que funcionam.<\/p>\n

As empresas que se destacar\u00e3o ser\u00e3o aquelas que, de forma consistente, conseguirem levar seus candidatos da fase de descoberta \u00e0 valida\u00e7\u00e3o e, finalmente, \u00e0s m\u00e3os dos produtores. Tr\u00eas perguntas moldam cada vez mais essa discuss\u00e3o: Quanto investimento em P&D \u00e9 necess\u00e1rio para sustentar a inova\u00e7\u00e3o? Como as empresas podem acessar recursos de descoberta de ponta sem arcar com grandes custos fixos? E, talvez o mais importante, como podemos criar qu\u00edmica verdadeiramente inovadora em vez de continuar otimizando mecanismos de a\u00e7\u00e3o j\u00e1 existentes?<\/p>\n

Corrigindo a P&D em est\u00e1gio inicial\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/strong><\/h2>\n

Essas quest\u00f5es apontam diretamente para uma das maiores oportunidades na prote\u00e7\u00e3o de cultivos atualmente: aprimorar a etapa inicial do processo de descoberta.<\/p>\n

Durante d\u00e9cadas, a ind\u00fastria construiu grandes organiza\u00e7\u00f5es internas projetadas em torno da escala e do controle. Esse modelo produziu inova\u00e7\u00f5es importantes, mas as ferramentas computacionais atuais permitem que os pesquisadores avaliem mol\u00e9culas potenciais com uma precis\u00e3o muito maior do que era poss\u00edvel at\u00e9 mesmo alguns anos atr\u00e1s. Em vez de depender fortemente de triagens amplas e abordagens de tentativa e erro, as equipes podem concentrar recursos em candidatos com maior probabilidade de sucesso.<\/p>\n

O resultado \u00e9 uma mudan\u00e7a fundamental em onde o valor \u00e9 criado. Em muitos casos, a decis\u00e3o mais importante n\u00e3o \u00e9 qual mol\u00e9cula priorizar, mas sim qual delas deixar de ser pesquisada.<\/p>\n

Os maiores ganhos geralmente v\u00eam no in\u00edcio.<\/strong><\/h2>\n

Cada mol\u00e9cula eliminada antes de entrar em testes subsequentes dispendiosos preserva recursos para uma oportunidade melhor. Cada via malsucedida identificada precocemente economiza anos de esfor\u00e7o e investimento. Essas decis\u00f5es iniciais muitas vezes determinam a efici\u00eancia de todo o processo de desenvolvimento.<\/p>\n

Vimos isso em primeira m\u00e3o em Enko<\/a>, onde m\u00faltiplos programas avan\u00e7aram da fase de descoberta para a valida\u00e7\u00e3o em campo em uma fra\u00e7\u00e3o do tempo tradicionalmente associado \u00e0 pesquisa em prote\u00e7\u00e3o de cultivos. O valor n\u00e3o reside simplesmente na maior rapidez dos programas. Melhores ferramentas ajudam os cientistas a tomar decis\u00f5es mais confi\u00e1veis no in\u00edcio do processo. Quando os pesquisadores conseguem identificar oportunidades promissoras mais cedo e eliminar candidatos menos promissores antes que recursos significativos sejam alocados, eles podem concentrar seu tempo, talento e capital onde realmente importa.<\/p>\n

\u00c9 isso que, em \u00faltima an\u00e1lise, impulsiona a produtividade em P&D.<\/p>\n

O Elemento Humano<\/strong><\/h2>\n

O julgamento cient\u00edfico continua sendo essencial. A IA pode analisar enormes quantidades de dados e identificar padr\u00f5es em uma escala que nenhum ser humano consegue igualar, mas n\u00e3o pode substituir a experi\u00eancia, o contexto, a intui\u00e7\u00e3o ou a capacidade de ponderar prioridades conflitantes.<\/p>\n

Os cientistas ainda decidem quais perguntas valem a pena fazer, quais hip\u00f3teses merecem ser testadas e quais oportunidades justificam o investimento. As organiza\u00e7\u00f5es de pesquisa mais eficazes n\u00e3o est\u00e3o substituindo cientistas por algoritmos. Elas est\u00e3o equipando os cientistas com melhores ferramentas para que tomem melhores decis\u00f5es.<\/p>\n

Apesar de todo o potencial da IA, \u00e9 importante reconhecer suas limita\u00e7\u00f5es. A IA pode transformar as descobertas, mas n\u00e3o pode eliminar a necessidade de valida\u00e7\u00e3o em campo, revis\u00e3o regulat\u00f3ria ou os extensos testes necess\u00e1rios para levar produtos seguros e eficazes ao mercado. Os produtores ainda precisam de produtos que tenham desempenho consistente em condi\u00e7\u00f5es reais, e os mercados ainda recompensam os resultados.<\/p>\n

A entrega \u00e9 a medida<\/strong><\/h2>\n

A prote\u00e7\u00e3o de cultivos nunca sofreu com a falta de ideias. O maior desafio sempre foi transformar essas ideias em produtos de sucesso.<\/p>\n

A promessa da IA n\u00e3o \u00e9 mudar essa realidade. A promessa \u00e9 nos ajudar a identificar as oportunidades certas mais cedo, aprender mais r\u00e1pido e evitar investir anos em oportunidades erradas.<\/p>\n

Para um setor constru\u00eddo sobre longos prazos, altos custos e riscos t\u00e9cnicos significativos, essa \u00e9 uma mudan\u00e7a importante.<\/p>\n

Os vencedores da pr\u00f3xima d\u00e9cada n\u00e3o ser\u00e3o as empresas com a narrativa de IA mais ambiciosa. Ser\u00e3o as empresas que consistentemente tomarem decis\u00f5es melhores, alocarem capital de forma mais eficaz e traduzirem a inova\u00e7\u00e3o em solu\u00e7\u00f5es pr\u00e1ticas para os produtores.<\/p>","protected":false},"excerpt":{"rendered":"

Tony Klemm, CEO da Enko, explica por que decis\u00f5es mais inteligentes em P&D, efici\u00eancia de capital e entrega de produtos definir\u00e3o o futuro da prote\u00e7\u00e3o de cultivos.<\/p>","protected":false},"author":110,"featured_media":67580,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1917,4,1604,1848],"tags":[],"class_list":["post-134983","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-abg-update-feature","category-agrochemicals","category-agtech","category-executive-outlook"],"yoast_head":"\nWhy Delivery Will Win Crop Protection's AI 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