... AI-ready data is foundational for a bank’s AI success since it demands clean, accessible, and well-governed data. Bank CIOs should focus on three interconnected pillars for implementing AI applications with AI-ready data: Use case prioritization, legacy modernization with robust data ecosystem and metadata ...
Analyst(s): Sudarshana Bhattacharya | Moutusi Sau
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... as agentic AI, robotics and automation, presents the next significant wave beyond digital business but already demands that executive leaders consider how they will need to recalibrate their AI ambitions and competitive strategies. The five components of autonomous business Here’s what AI-powered autonomy ...
... The rapid progression of AI is transforming the possibilities of robotic process automation. Enterprise application leaders can leverage this research to achieve their process optimization and transformation goals more efficiently and effectively through AI-enabled robotic process automation. More Detail ...
... Heads of I&O often overlook unconventional barriers to AI usage, such as AI fatigue and accountability gaps, when providing AI tools for the broader organization. These barriers stem from disconnects between employees and executives, causing AI initiatives to fail due to a lack of employee adoption. ...
... As AI enters a phase of rapid standardization, organizations should consider the readiness of their data for AI. D&A leaders focused on data management must prepare for standardized, interchangeable AI models and algorithms by prioritizing data readiness, infrastructure orchestration, metadata-driven ...
... Innovation in AI data, engineering and platforms is critical to compete in the AI race. Within this race, only product leaders prepared to enhance domain data with unstructured and synthetic data, embrace AI-driven engineering and operations, and build new AI ecosystems will be positioned to succeed. ...
... Access Insights Already a Gartner client? Developers often lack adequate training or time to identify and resolve security issues in their code. AI code security assistants help cybersecurity leaders address this challenge by providing contextually relevant, developer-friendly guidance to uncover and ...
Analyst(s): Mark Horvath | Manjunath Bhat | Dionisio Zumerle
... Marketing organizations face unanticipated brand risks generated by AI implementation. CMOs can achieve positive AI-based brand outcomes, and avoid potential perils, by strengthening brand governance, especially in content creation, compliance reviews and chatbot experiences. Overview Strategic Planning ...
... insights on emerging trends Google’s Gemini Enterprise’s unified, governed and extensible approach is a direct response to fragmented AI stacks. IT leaders must consolidate AI platforms, prioritize governance, and design for ecosystem integration or risk irrelevance. Overview Gartner Recommended Reading ...
Analyst(s): Chirag Dekate | Joe Mariano | Tom Coshow | Mark O'Neill