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IBM’s agentic strategy brings generative AI down to earth and into production
- IBM is focusing on a strategy called 'agentic strategy' to scale generative AI ambitions effectively, emphasizing execution oversight and governance.
- This strategy aims to balance creative momentum with practical operational discipline, bridging the gap between content creation and production-related challenges.
- Bruno Aziza, IBM's group vice president for data, emphasizes the importance of managing costs and governance alongside content engineering and engagement.
- IBM's agentic strategy is about agents working across apps, clouds, and workflows to drive actual value and focuses on both better engagement and efficient production management.
- IBM is promoting a federated framework for integration, enabling data, agents, and business logic to move seamlessly across various silos, clouds, and tools.
- The company offers prebuilt agents connected to numerous applications, allowing organizations to start fast, customize as needed, and scale confidently in hybrid and multi-cloud environments.
- IBM is aiming to avoid hard-coded processes and rigid workflows by enabling dynamic agent behavior through its watsonx Orchestrate product for flexible and adaptive strategies.
- The focus of IBM's approach goes beyond the excitement of generative AI to address operational challenges like scale, accountability, cost, and governance.
- IBM emphasizes the importance of transformation, automation where needed, elimination of unnecessary processes, and a modular mindset to optimize use cases.
- IBM's open approach to operationalizing agents at scale emphasizes its collaboration with companies like Box, Oracle, and Salesforce in production environments.
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