Nvidia Stock Faces Challenges as IBM Survey Reveals Limited AI ROI
PorAinvest
domingo, 11 de mayo de 2025, 6:11 am ET2 min de lectura
IBM--
IBM estimates that by 2028, over 1 billion apps will emerge, putting pressure on businesses to scale their AI capabilities. According to a new IBM CEO study, business leaders expect AI investments to more than double over the next two years, with a significant focus on AI agents. However, only 25% of AI initiatives have achieved the expected ROI, indicating a need for more effective integration and operationalization [1].
IBM's new hybrid technologies, agent capabilities, and support from IBM Consulting aim to address these challenges. The company's watsonx Orchestrate platform provides a comprehensive suite of enterprise-ready agent capabilities, including pre-built domain agents for HR, sales, and procurement, and integration with over 80 leading enterprise applications. The platform also offers agent observability for performance monitoring and governance across the agent lifecycle [2].
To complement these offerings, IBM is introducing webMethods Hybrid Integration, a next-generation solution that replaces rigid workflows with intelligent and agent-driven automation. This tool will help manage the sprawl of integrations across apps, APIs, B2B partners, events, gateways, and file transfers in hybrid cloud environments. An independent Forrester Consulting study found that a composite organization realized a 176% ROI over three years by automating these integrations [3].
IBM is also focusing on unlocking the value of unstructured data for generative AI. The new watsonx.data will bring together an open data lakehouse with data fabric capabilities to unify, govern, and activate data across silos, formats, and clouds. This could lead to more accurate AI models, with internal tests showing up to 40% more accurate AI than conventional RAG [4].
Infrastructure for AI scale is another key focus. IBM's new LinuxONE 5 platform can process up to 450 billion AI inference operations per day, with state-of-the-art AI accelerators and significant cost savings compared to x86 solutions. The platform also offers advanced security features and integration with IBM's quantum-safe encryption technology [5].
These innovations come at a critical time for AI companies like Nvidia, which relies on selling expensive AI accelerators to train and run complex AI models. The future of AI may involve more efficient models running on cheaper hardware, which could negatively impact Nvidia's growth story. However, IBM's focus on hybrid capabilities, agent-based solutions, and unlocking unstructured data could provide a more cost-effective and scalable alternative for enterprises [6].
References:
[1] IBM Launches Enterprise Gen-AI Technologies with Hybrid Capabilities. Inside AI News. https://insideainews.com/2025/05/08/ibm-launches-enterprise-gen-ai-technologies-with-hybrid-capabilities/
[2] IBM watsonx Orchestrate. IBM. https://www.ibm.com/products/watsonx-orchestrate
[3] Forrester Consulting, The Total Economic Impact™ of IBM webMethods. IBM. https://www.ibm.com/products/webmethods
[4] IBM watsonx.data. IBM. https://www.ibm.com/products/watsonx-data
[5] IBM LinuxONE 5. IBM. https://www.ibm.com/products/linuxone
[6] IBM's AI Innovations Aim to Boost Enterprise ROI and Scalability. IBM. https://www.ibm.com/ai/innovations
NVDA--
IBM's survey of 2,000 CEOs found that only 25% reported AI initiatives delivering expected ROI and only 16% scaling enterprise-wide. Businesses are struggling to make AI investments work due to limitations such as creating false information and lack of real reasoning. This is bad news for Nvidia, which relies on selling expensive AI accelerators to train and run complex AI models. The future of AI may involve more efficient models running on cheaper hardware, which could negatively impact Nvidia's growth story.
IBM recently unveiled a suite of enterprise-grade AI technologies at its annual THINK event, aiming to address the challenges faced by businesses in scaling AI investments and achieving expected ROI. The company's new offerings, including hybrid capabilities and agent-based solutions, are designed to help enterprises build AI agents with their own data and integrate them across diverse environments.IBM estimates that by 2028, over 1 billion apps will emerge, putting pressure on businesses to scale their AI capabilities. According to a new IBM CEO study, business leaders expect AI investments to more than double over the next two years, with a significant focus on AI agents. However, only 25% of AI initiatives have achieved the expected ROI, indicating a need for more effective integration and operationalization [1].
IBM's new hybrid technologies, agent capabilities, and support from IBM Consulting aim to address these challenges. The company's watsonx Orchestrate platform provides a comprehensive suite of enterprise-ready agent capabilities, including pre-built domain agents for HR, sales, and procurement, and integration with over 80 leading enterprise applications. The platform also offers agent observability for performance monitoring and governance across the agent lifecycle [2].
To complement these offerings, IBM is introducing webMethods Hybrid Integration, a next-generation solution that replaces rigid workflows with intelligent and agent-driven automation. This tool will help manage the sprawl of integrations across apps, APIs, B2B partners, events, gateways, and file transfers in hybrid cloud environments. An independent Forrester Consulting study found that a composite organization realized a 176% ROI over three years by automating these integrations [3].
IBM is also focusing on unlocking the value of unstructured data for generative AI. The new watsonx.data will bring together an open data lakehouse with data fabric capabilities to unify, govern, and activate data across silos, formats, and clouds. This could lead to more accurate AI models, with internal tests showing up to 40% more accurate AI than conventional RAG [4].
Infrastructure for AI scale is another key focus. IBM's new LinuxONE 5 platform can process up to 450 billion AI inference operations per day, with state-of-the-art AI accelerators and significant cost savings compared to x86 solutions. The platform also offers advanced security features and integration with IBM's quantum-safe encryption technology [5].
These innovations come at a critical time for AI companies like Nvidia, which relies on selling expensive AI accelerators to train and run complex AI models. The future of AI may involve more efficient models running on cheaper hardware, which could negatively impact Nvidia's growth story. However, IBM's focus on hybrid capabilities, agent-based solutions, and unlocking unstructured data could provide a more cost-effective and scalable alternative for enterprises [6].
References:
[1] IBM Launches Enterprise Gen-AI Technologies with Hybrid Capabilities. Inside AI News. https://insideainews.com/2025/05/08/ibm-launches-enterprise-gen-ai-technologies-with-hybrid-capabilities/
[2] IBM watsonx Orchestrate. IBM. https://www.ibm.com/products/watsonx-orchestrate
[3] Forrester Consulting, The Total Economic Impact™ of IBM webMethods. IBM. https://www.ibm.com/products/webmethods
[4] IBM watsonx.data. IBM. https://www.ibm.com/products/watsonx-data
[5] IBM LinuxONE 5. IBM. https://www.ibm.com/products/linuxone
[6] IBM's AI Innovations Aim to Boost Enterprise ROI and Scalability. IBM. https://www.ibm.com/ai/innovations

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