... FAQs on AI-Enabled Marketing What is agentic AI, and why does it matter for CMOs? Agentic AI refers to autonomous or semi-autonomous software entities that perceive, decide and act. It shifts AI from a tool to a teammate — and requires new governance, workflows and talent strategies. Why hasn’t AI reduced ...
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... While AI has become the leading topic in the IT industry, its rise underscores the need for a cohesive cloud strategy. The intersection of cloud computing and AI is poised to be one of the most impactful developments in decades, necessitating strategic planning and integration. Join this complimentary ...
... recommended actions to help you achieve your goals. •Target responsibilities to evolve IT roles to support AI learning •Determine what a good relationship with an AI agent looks like •Three types of AI behavior challenges and what to focus on Return to this web page to watch the webinar. Contact us at gartnerwebinars ...
... Organizations often face challenges in moving AI models from pilot to production due to operational and cultural bottlenecks. According to the Gartner 2024 Analytics and AI Engineering Survey, organizations with low AI engineering utilization had, on average, 16% fewer AI models in active use within the past ...
... Explaining AI/ML models to nontechnical stakeholders is challenging and affects their trust and adoption in production. Data scientists must adopt three practices to enhance model explanations, gain trust, and improve the responsible and ethical use of AI/ML. Overview Analysis Recommendations Conclusion ...
... Organizations often experiment with machine learning by manually deploying models to show value. After initial success, data scientists and AI architects must use MLOps practices to scale ML by automating training, deployment, and monitoring. This research provides a roadmap for MLOps maturity. Overview ...
... AI-ready data is not a fixed state. Instead, data must be fit for purpose according to the requirements of AI use cases and take into consideration data availability and access, internal skills and cost constraints. Data scientists must complete the current assessment to determine if their data is AI-ready ...
... Organizations must navigate a complex landscape of platforms and tools when implementing GenAI. This framework offers a structured approach to evaluating and selecting the right implementation method, helping minimize risk and ensuring an effective, efficient strategy tailored to each use case. Overv ...
... The race for national AI sovereignty is in full force, with leading nation-states releasing their competing national AI policies, strategies, funding and other initiatives. Given the timing and magnitude of the U.S. AI Action Plan of July 23, 2025, and the China Global AI Governance Action Plan of July ...
Analyst(s): Lydia Clougherty Jones | Frances Karamouzis