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#enterpriseai — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #enterpriseai, aggregated by home.social.

  1. AI isn’t magic. In our conversation with Sophie Dionnet (Dataiku), she cuts to the real enterprise AI trap: not models, but change management.

    “Taking a decision is one hour, implementation is two years.”

    That gap is where AI succeeds or stalls.

    Watch on YouTube: youtube.com/shorts/Rh2kZ4P_ib4

    #EnterpriseAI #ChangeManagement #Dataiku #AI

  2. AI isn’t magic. In our conversation with Sophie Dionnet (Dataiku), she cuts to the real enterprise AI trap: not models, but change management.

    “Taking a decision is one hour, implementation is two years.”

    That gap is where AI succeeds or stalls.

    Watch on YouTube: youtube.com/shorts/Rh2kZ4P_ib4

  3. Anthropic Weighs New Model Launch to Counter GPT-6 Astra

    Reuters reports Anthropic may release a new model before its IPO, days after CEO Dario Amodei called for the industry to slow down.

    pulseofnations.lol/anthropic-w

    #Anthropic #Claude #EnterpriseAi #Gpt6 #Ipo #OpenAI

  4. Infinito.Nexus 14.0: Turn Local AI into a Secure Digital Workforce

    In Short Infinito.Nexus 14.0 enables companies to operate AI on their own infrastructure, connect it securely to existing business applications and deploy AI agents such as Hermes and OpenClaw as virtual employees. Sensitive information can be processed by local models, while optional connections to OpenAI, Anthropic and OpenRouter provide access to external frontier models when greater capabilities are needed. Companies decide which data may leave their infrastructure, which tools an agent can use and which actions remain restricted. Infinito.Nexus 14.0 brings models, enterprise applications and autonomous agents together in one controlled infrastructure. Organizations can now combine local AI for sensitive data with external frontier models and deploy agents such as Hermes and OpenClaw as isolated virtual employees. Generative AI has already changed how employees search, write, analyze and develop. But most organizations still face an uncomfortable choice: either send business data to an external AI provider or accept the operational complexity of building a local AI platform from scratch. Infinito.Nexus 14.0 introduces a third option: a hybrid AI architecture in which organizations decide where every workload runs. Sensitive prompts can be processed by local models through Ollama or LM Studio. Tasks that require the capabilities of frontier models can be routed to OpenAI, Anthropic or OpenRouter. Applications and agents use one centrally managed gateway instead of implementing separate provider integrations. The result is not merely another enterprise chatbot. Version 14.0 provides the foundation for a secure digital workforce. […]

    blog.infinito.nexus/blog/2026/

  5. Infinito.Nexus 14.0: Turn Local AI into a Secure Digital Workforce

    In Short Infinito.Nexus 14.0 enables companies to operate AI on their own infrastructure, connect it securely to existing business applications and deploy AI agents such as Hermes and OpenClaw as virtual employees. Sensitive information can be processed by local models, while optional connections to OpenAI, Anthropic and OpenRouter provide access to external frontier models when greater capabilities are needed. Companies decide which data may leave their infrastructure, which tools an agent can use and which actions remain restricted. Infinito.Nexus 14.0 brings models, enterprise applications and autonomous agents together in one controlled infrastructure. Organizations can now combine local AI for sensitive data with external frontier models and deploy agents such as Hermes and OpenClaw as isolated virtual employees. Generative AI has already changed how employees search, write, analyze and develop. But most organizations still face an uncomfortable choice: either send business data to an external AI provider or accept the operational complexity of building a local AI platform from scratch. Infinito.Nexus 14.0 introduces a third option: a hybrid AI architecture in which organizations decide where every workload runs. Sensitive prompts can be processed by local models through Ollama or LM Studio. Tasks that require the capabilities of frontier models can be routed to OpenAI, Anthropic or OpenRouter. Applications and agents use one centrally managed gateway instead of implementing separate provider integrations. The result is not merely another enterprise chatbot. Version 14.0 provides the foundation for a secure digital workforce. […]

    blog.infinito.nexus/blog/2026/

  6. Episode Recap: The Three Ingredients That Turn AI Into Value – we ask what enterprise AI success really looks like. Sophie Dionnet says it’s people, orchestration and governance, not just flash tools. She shares how a Roche patent lawyer built his own agents and why controls accelerate scale. Listen on Spotify 👉 open.spotify.com/episode/5VHvV

  7. Episode Recap: The Three Ingredients That Turn AI Into Value – we ask what enterprise AI success really looks like. Sophie Dionnet says it’s people, orchestration and governance, not just flash tools. She shares how a Roche patent lawyer built his own agents and why controls accelerate scale. Listen on Spotify 👉 open.spotify.com/episode/5VHvV #EnterpriseAI #AnalysePodcast

  8. Kai-Fu Lee forecasts that AI will unleash radical changes inside companies. Lee says CEOs must take personal charge of their technology strategy.

    Source: Semafor Africa
    semafor.com/article/09/18/2026

    #EnterpriseAI

  9. Kai-Fu Lee forecasts that AI will unleash radical changes inside companies. Lee says CEOs must take personal charge of their technology strategy.

    Source: Semafor Africa
    semafor.com/article/09/18/2026

    #EnterpriseAI

  10. Sophie Dionnet of Dataiku had a great point on today’s episode: the real AI problem isn’t the model — it’s the change. It's easier to chase the new toy than to do the hard work. The Harsh Truth About the Enterprise AI "Gold Rush" is out now. Watch on YouTube and share your thoughts below.

    youtube.com/shorts/-Zg9XEgq2bQ
    #AnalysePodcast #AIDiscussion #EnterpriseAI

  11. Sophie Dionnet of Dataiku had a great point on today’s episode: the real AI problem isn’t the model — it’s the change. It's easier to chase the new toy than to do the hard work. The Harsh Truth About the Enterprise AI "Gold Rush" is out now. Watch on YouTube and share your thoughts below.

    youtube.com/shorts/-Zg9XEgq2bQ

  12. Measuring "useful intelligence per dollar" is a far better metric for AI than tracking raw cost per token, but it still carries a critical flaw: you don't control the pricing.

    If your AI ROI relies on today's API rates, you are betting on someone else's infrastructure costs and margins remaining favorable. That leaves many business cases vulnerable to sudden market re-pricing.

    Read the full analysis on TechFinitive:
    techfinitive.com/opinions/your

    #AI #EnterpriseAI #ROI

  13. Measuring "useful intelligence per dollar" is a far better metric for AI than tracking raw cost per token, but it still carries a critical flaw: you don't control the pricing.

    If your AI ROI relies on today's API rates, you are betting on someone else's infrastructure costs and margins remaining favorable. That leaves many business cases vulnerable to sudden market re-pricing.

    Read the full analysis on TechFinitive:
    techfinitive.com/opinions/your

    #AI #EnterpriseAI #ROI

  14. Measuring "useful intelligence per dollar" is a far better metric for AI than tracking raw cost per token, but it still carries a critical flaw: you don't control the pricing.

    If your AI ROI relies on today's API rates, you are betting on someone else's infrastructure costs and margins remaining favorable. That leaves many business cases vulnerable to sudden market re-pricing.

    Read the full analysis on TechFinitive:
    techfinitive.com/opinions/your

    #AI #EnterpriseAI #ROI

  15. Measuring "useful intelligence per dollar" is a far better metric for AI than tracking raw cost per token, but it still carries a critical flaw: you don't control the pricing.

    If your AI ROI relies on today's API rates, you are betting on someone else's infrastructure costs and margins remaining favorable. That leaves many business cases vulnerable to sudden market re-pricing.

    Read the full analysis on TechFinitive:
    techfinitive.com/opinions/your

    #AI #EnterpriseAI #ROI

  16. Measuring "useful intelligence per dollar" is a far better metric for AI than tracking raw cost per token, but it still carries a critical flaw: you don't control the pricing.

    If your AI ROI relies on today's API rates, you are betting on someone else's infrastructure costs and margins remaining favorable. That leaves many business cases vulnerable to sudden market re-pricing.

    Read the full analysis on TechFinitive:
    techfinitive.com/opinions/your

    #AI #EnterpriseAI #ROI

  17. Ever wondered why some companies can't scale their AI efforts? In this episode, Sophie Dionnet explains that tight, centralized AI governance often hinders growth. Trust and the right controls are key to scaling. Watch on YouTube to learn how organizations can foster the right governance environment. youtube.com/shorts/tnZRW8u5vDQ #dataiku #aigovernance #ai #enterpriseai #llmsecurity

  18. Ever wondered why some companies can't scale their AI efforts? In this episode, Sophie Dionnet explains that tight, centralized AI governance often hinders growth. Trust and the right controls are key to scaling. Watch on YouTube to learn how organizations can foster the right governance environment. youtube.com/shorts/tnZRW8u5vDQ

  19. Organisations already possess most of the answers employees need. The problem is finding them.

    Could one trustworthy corporate AI assistant connect scattered systems, documents and expertise—without compromising security or governance?

    hackernoon.com/the-enterprise-

    #EnterpriseAI #KnowledgeManagement #TTMO

  20. Databricks plans to invest more than US$350 million in Singapore over the next three years. The company will double its local workforce and open a new regional headquarters.

    Source: Fintech News Singapore
    fintechnews.sg/137356/ai/datab

    #EnterpriseAI

  21. Databricks plans to invest more than US$350 million in Singapore over the next three years. The company will double its local workforce and open a new regional headquarters.

    Source: Fintech News Singapore
    fintechnews.sg/137356/ai/datab

    #EnterpriseAI

  22. TotalEnergies partners with AI firm Mistral to speed up exploration by building AI models that analyze geological data and generate exploration scenarios.

    Source: Ecofin Agency
    ecofinagency.com/news-digital/

    #EnterpriseAI #Mistral

  23. TotalEnergies partners with AI firm Mistral to speed up exploration by building AI models that analyze geological data and generate exploration scenarios.

    Source: Ecofin Agency
    ecofinagency.com/news-digital/

    #EnterpriseAI #Mistral

  24. Sumsub has launched a workforce verification solution that adds identity document checks, biometric liveness detection and background screening to existing IAM and HR platforms.

    Source: Fintech News Singapore
    fintechnews.sg/137348/security

    #EnterpriseAI

  25. Sumsub has launched a workforce verification solution that adds identity document checks, biometric liveness detection and background screening to existing IAM and HR platforms.

    Source: Fintech News Singapore
    fintechnews.sg/137348/security

    #EnterpriseAI

  26. "The real challenge isn't the latest model, but the change management. It’s easier to get excited by the new toy than to actually use it." – Sophie Dionnet of @Dataiku.

    Spot-on thoughts on the enterprise #AI 'gold rush' and doing the hard work. Where do you think this is heading?

    Watch our full chat on YouTube: youtube.com/shorts/-Zg9XEgq2bQ
    #EnterpriseAI #ChangeManagement #AnalysePodcast

  27. "The real challenge isn't the latest model, but the change management. It’s easier to get excited by the new toy than to actually use it." – Sophie Dionnet of @Dataiku.

    Spot-on thoughts on the enterprise 'gold rush' and doing the hard work. Where do you think this is heading?

    Watch our full chat on YouTube: youtube.com/shorts/-Zg9XEgq2bQ

  28. Consistency is the floor. Accountability goes further.

    Building AI for high-stakes, regulated environments?

    Prompt logs & model versions aren’t enough. True auditability requires explaining why an input produced an output - and tracing it directly to policy.

    🎬 Watch Alex Porcelli’s full talk on #InfoQ - infoq.com/presentations/decisi

    #AI #AgenticAI #EnterpriseAI #SoftwareArchitecture

  29. Consistency is the floor. Accountability goes further.

    Building AI for high-stakes, regulated environments?

    Prompt logs & model versions aren’t enough. True auditability requires explaining why an input produced an output - and tracing it directly to policy.

    🎬 Watch Alex Porcelli’s full talk on #InfoQ - infoq.com/presentations/decisi

    #AI #AgenticAI #EnterpriseAI #SoftwareArchitecture

  30. Consistency is the floor. Accountability goes further.

    Building AI for high-stakes, regulated environments?

    Prompt logs & model versions aren’t enough. True auditability requires explaining why an input produced an output - and tracing it directly to policy.

    🎬 Watch Alex Porcelli’s full talk on #InfoQ - infoq.com/presentations/decisi

    #AI #AgenticAI #EnterpriseAI #SoftwareArchitecture

  31. Consistency is the floor. Accountability goes further.

    Building AI for high-stakes, regulated environments?

    Prompt logs & model versions aren’t enough. True auditability requires explaining why an input produced an output - and tracing it directly to policy.

    🎬 Watch Alex Porcelli’s full talk on #InfoQ - infoq.com/presentations/decisi

    #AI #AgenticAI #EnterpriseAI #SoftwareArchitecture

  32. Consistency is the floor. Accountability goes further.

    Building AI for high-stakes, regulated environments?

    Prompt logs & model versions aren’t enough. True auditability requires explaining why an input produced an output - and tracing it directly to policy.

    🎬 Watch Alex Porcelli’s full talk on - infoq.com/presentations/decisi

  33. The real problem with enterprise data? Not multiple definitions - pretending there’s only one.

    If Marketing and Finance can’t agree on what an “active customer” is, how can an AI agent?

    Enterprise AI agents don’t fail because models are dumb. They fail because enterprise semantics are messy!

    🔗 Watch Fabiane Nardon’s full #QConAI Boston talk: infoq.com/presentations/enterp

    #AI #DataEngineering #EnterpriseAI #AIAgents #InfoQ

  34. The real problem with enterprise data? Not multiple definitions - pretending there’s only one.

    If Marketing and Finance can’t agree on what an “active customer” is, how can an AI agent?

    Enterprise AI agents don’t fail because models are dumb. They fail because enterprise semantics are messy!

    🔗 Watch Fabiane Nardon’s full #QConAI Boston talk: infoq.com/presentations/enterp

    #AI #DataEngineering #EnterpriseAI #AIAgents #InfoQ

  35. The real problem with enterprise data? Not multiple definitions - pretending there’s only one.

    If Marketing and Finance can’t agree on what an “active customer” is, how can an AI agent?

    Enterprise AI agents don’t fail because models are dumb. They fail because enterprise semantics are messy!

    🔗 Watch Fabiane Nardon’s full #QConAI Boston talk: infoq.com/presentations/enterp

    #AI #DataEngineering #EnterpriseAI #AIAgents #InfoQ

  36. The real problem with enterprise data? Not multiple definitions - pretending there’s only one.

    If Marketing and Finance can’t agree on what an “active customer” is, how can an AI agent?

    Enterprise AI agents don’t fail because models are dumb. They fail because enterprise semantics are messy!

    🔗 Watch Fabiane Nardon’s full #QConAI Boston talk: infoq.com/presentations/enterp

    #AI #DataEngineering #EnterpriseAI #AIAgents #InfoQ

  37. The real problem with enterprise data? Not multiple definitions - pretending there’s only one.

    If Marketing and Finance can’t agree on what an “active customer” is, how can an AI agent?

    Enterprise AI agents don’t fail because models are dumb. They fail because enterprise semantics are messy!

    🔗 Watch Fabiane Nardon’s full Boston talk: infoq.com/presentations/enterp

  38. AI is getting cheaper, but enterprise spending keeps rising. An AI PM's take on tokenomics, model routing, and why the cheapest token isn't the safest choice. hackernoon.com/why-regulated-e #enterpriseai

  39. AI is getting cheaper, but enterprise spending keeps rising. An AI PM's take on tokenomics, model routing, and why the cheapest token isn't the safest choice. hackernoon.com/why-regulated-e #enterpriseai

  40. AI is getting cheaper, but enterprise spending keeps rising. An AI PM's take on tokenomics, model routing, and why the cheapest token isn't the safest choice. hackernoon.com/why-regulated-e #enterpriseai

  41. AI is getting cheaper, but enterprise spending keeps rising. An AI PM's take on tokenomics, model routing, and why the cheapest token isn't the safest choice. hackernoon.com/why-regulated-e

  42. AI is getting cheaper, but enterprise spending keeps rising. An AI PM's take on tokenomics, model routing, and why the cheapest token isn't the safest choice. hackernoon.com/why-regulated-e #enterpriseai

  43. Most orgs chasing the latest AI model are missing the point entirely.

    Sophie Dionnet from Dataiku puts it plainly: the transformation you need today doesn't require the newest model. It requires the hard, unglamorous work of change management.

    The real trap? Preferring the new toy over actually putting it to use.

    Watch on YouTube: youtube.com/shorts/1iSO634q-Lw

    #EnterpriseAI #Dataiku #ChangeManagement

  44. Most orgs chasing the latest AI model are missing the point entirely.

    Sophie Dionnet from Dataiku puts it plainly: the transformation you need today doesn't require the newest model. It requires the hard, unglamorous work of change management.

    The real trap? Preferring the new toy over actually putting it to use.

    Watch on YouTube: youtube.com/shorts/1iSO634q-Lw

  45. Salesforce unveiled an enterprise architecture called the Enterprise AI Harness to give companies centralized control over artificial intelligence agents, models, data access, workflows, and security policies.

    Source: Newsbytes Philippines
    newsbytes.ph/2026/09/14/salesf

    #EnterpriseAI #Salesforce

  46. Salesforce unveiled an enterprise architecture called the Enterprise AI Harness to give companies centralized control over artificial intelligence agents, models, data access, workflows, and security policies.

    Source: Newsbytes Philippines
    newsbytes.ph/2026/09/14/salesf

    #EnterpriseAI #Salesforce