Autonomous AI In The Enterprise
A Fictional Case Study
The guidance paper delves into critical aspects of enterprise AI adoption, including balancing innovation and stability, managing AI-related technical debt, and the importance of cross-functional collaboration. It highlights key concerns such as shadow AI, data security, and the potential pitfalls of rapid, uncoordinated AI implementation. Readers will learn about best practices for establishing AI governance, designing scalable infrastructure, and fostering a culture of responsible AI use.
- Format PDF
- Pages 23
- Publication Date
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Description
The guidance paper delves into critical aspects of enterprise AI adoption, including balancing innovation and stability, managing AI-related technical debt, and the importance of cross-functional collaboration. It highlights key concerns such as shadow AI, data security, and the potential pitfalls of rapid, uncoordinated AI implementation. Readers will learn about best practices for establishing AI governance, designing scalable infrastructure, and fostering a culture of responsible AI use.
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Details
- Format PDF
- Pages 23
- Publication Date
Features
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Strategic Balance:
Balancing the need for rapid AI adoption with long-term system stability and security is crucial for successful implementation.
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Technical Debt
Proactively managing AI-related technical debt through centralized governance, standardized practices, and regular assessments is essential for sustainable AI integration.
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Cross-Functional Collaboration
Fostering partnerships between IT, security, and business units is key to navigating the complexities of enterprise-wide AI adoption.
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Security First
Prioritizing security and compliance throughout the AI implementation process helps mitigate novel vulnerabilities and ensures responsible use of the technology.
About the Resource
This compelling narrative, included in the Fall 2024 Enterprise Technology Leadership Journal, follows Data Unlimited, a cutting-edge tech company, as it navigates the complex landscape of implementing autonomous artificial intelligence (AI) across its organization. Through vivid storytelling and expert insights, readers will gain a valuable understanding of the strategic decisions, technical challenges, and cultural shifts required to successfully adopt AI at scale.
The guidance paper delves into critical aspects of enterprise AI adoption, including balancing innovation and stability, managing AI-related technical debt, and the importance of cross-functional collaboration. It highlights key concerns such as shadow AI, data security, and the potential pitfalls of rapid, uncoordinated AI implementation. Readers will learn about best practices for establishing AI governance, designing scalable infrastructure, and fostering a culture of responsible AI use.
Written by a team of industry experts, this guidance paper offers actionable insights for C-suite executives, IT leaders, and technology professionals looking to harness the power of autonomous AI. Whether you’re just beginning your AI journey or seeking to optimize your existing AI initiatives, this case study provides a road map for navigating the complexities of enterprise AI adoption. Discover how to unlock the full potential of AI while mitigating risks and ensuring long-term success in the rapidly evolving world of enterprise technology.
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