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Report details
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25
Figures
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Tables
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Executive Summary
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Report Conclusions
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Research Objectives
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Research Findings
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Robust Responsible AI Practices Are Still a Goal for Many
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Organizations Target Investments to Ensure Ethical AI Practices and Operational…
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Business Stakes Are High as Organizations Balance Innovation With Responsible…
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Bias and Fairness Challenges Underscore the Need for Enhanced Governance, Transp…
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Stakeholders Grow Engagement in AI Decision-making as AI Integration and Accessi…
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Conclusion
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Research Methodology
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Respondent Demographics
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Research Report: Evaluating the Pillars of Responsible AI
Research Report
Aug 16, 2024
by
Mike Leone, Mark Beccue, Emily Marsh, Enterprise Strategy Group Research
Amid the breakneck pace of AI integration into nearly every facet of today’s businesses, organizations increasingly face the difficult challenge of ensuring responsible AI use across their entire ecosystems. Creating robust, comprehensive policies that ensure AI technologies are developed and used ethically and responsibly is now a top priority, even for organizations still in the early stages of AI deployments. Effective policies and strategies ultimately comprise a host of crucial considerations with data used in AI models and technologies, including accountability, transparency, accuracy, security, reliability, explainability, bias, fairness, privacy, and others.
Without effective responsible AI strategies, organizations risk numerous impacts to their businesses and processes, ranging from reputational damage and legal consequences to increased costs and slower time to market. While the need for responsible AI is clear, execution is a challenging endeavor for most organizations as they work to keep pace with a fast-moving market, as well as stay ahead of evolving regulations that increasingly define the overall use of AI. To gain further insight into these trends and challenges, TechTarget’s Enterprise Strategy Group surveyed 374 professionals at organizations in North America (US and Canada) involved in the strategy, decision-making, selection, deployment, and management of artificial intelligence initiatives and projects.
Page Count: 26
Table of Contents
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Executive Summary
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Report Conclusions
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Research Objectives
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Research Findings
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Robust Responsible AI Practices Are Still a Goal for Many
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Organizations Target Investments to Ensure Ethical AI Practices and Operational Integrity
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Business Stakes Are High as Organizations Balance Innovation With Responsible AI Best Practices
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Bias and Fairness Challenges Underscore the Need for Enhanced Governance, Transparency, and Explainability
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Stakeholders Grow Engagement in AI Decision-making as AI Integration and Accessibility Escalate
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Conclusion
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Research Methodology
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Respondent Demographics
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