... This use-case assessment outlines 19 of the most prominent use cases for agentic AI in banking, measuring them against value and feasibility. Banking CIOs can use this comparison to inform their investments in agentic AI to improve operations and customer experience and reduce risk exposure. Overview ...
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... As organizations deploy AI agents, compliance guidance designed for human judgment becomes ineffective. Agents require explicit rules, decision logic, escalation triggers, and approval thresholds. Compliance leaders must help developers encode compliance requirements into AI systems from the start. ...
... Agentic AI can increasingly participate in and perform parts of PPM processes, moving beyond generating content to taking action within defined boundaries. PPM leaders must enable their people, processes and data readiness if they wish to capitalize on the benefits of agentic AI embedded in adaptive ...
Analyst(s): Zainab Ali | Woojin Choi | Jennifer Jackson | Peter Clegg
... Heads of I&O rely on AI capacity that community opposition now delays. AI data centers are not inherently bad; their impact depends on the terms they are built on. Use this research to weigh strains and gains, reduce delivery risk and engage stakeholders before those terms are set. Insights at a Glance ...
Analyst(s): Mark Jaggers | Henrique Cecci | Paul Wang | Autumn Stanish
... A successful AI agent architecture depends on effective agent integrations with components such as AI models, MCP servers and other agents. Software architects should mediate these interactions through AI gateways to enforce consistent, centrally governed policies and enable observability. Overview ...
... Marketing is becoming one of the enterprise’s largest AI spenders outside of IT, yet it rarely has full control over cost and governance. The innovations highlighted here give CMOs an independent FinOps layer through which to control marketing AI spend, prove its value, and maintain flexibility. Insights ...
... Access Insights Already a Gartner client? The generative AI model providers market is maturing fast as enterprises adopt commercial foundational models. Competition spans hyperscalers to niche AI labs, driven by frontier-model innovation, cost-performance trade-offs, and openness debates. The market ...
Analyst(s): Radu Miclaus | Leinar Ramos | Birgi Tamersoy | Chirag Dekate | Mike Fang
... Organizations struggle to control AI spending because visibility alone does not change behavior when accountability is unclear or unenforced. Software engineering leaders must establish clear decision rights, cost ownership, and governance authority, so those driving AI consumption are accountable for ...
... Access Insights Already a Gartner client? Individual and functional AI adoption can improve productivity without transforming marketing performance. CMOs should direct the redesign of consequential, cross-functional workflows by sponsoring workshops using our guidance to resolve unclear ownership, informal ...