... As AI commoditizes expertise and takes over routine tasks and data-driven decisions, CIOs must engage in human-AI alchemy, reshaping technology and people into a unified workforce. This alchemy starts with three key ingredients: trust, coaching, and risk ownership. Insights at a Glance Issue Impact ...
Analyst(s): Rob O'Donohue | Brook Selassie
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... Model Hardware Standard (MHS) as a signal that enterprise AI vendors are shifting to physical operations, enabling agents to connect and safely run machinery through a universal interface, and potentially streamlining integration across physical-AI ecosystems. Analysis Gartner Recommended Reading Evolving ...
Analyst(s): Reuben Harwood | Jan-Martin Lowendahl | Michael Shanler
... Already a Gartner client? AI is reshaping enterprise applications, bringing new risks and mandates. This guide defines seven critical themes for application leaders, providing an urgency framework to help you prioritize investments, manage agentic risks and drive sustainable AI value through 2027. Analysis ...
... Access Insights Already a Gartner client? Market expectations for AI agents exceed their current capabilities. This research helps AI leaders better understand the current state of the technology, as well as its risks and limitations, in order to manage expectations and avoid project failure. Insights ...
Analyst(s): Pieter den Hamer | Tom Coshow | Arun Chandrasekaran | Tong Zhang | Haritha Khandabattu | Leinar Ramos | Gabriele Rigon | Anthony Mullen | Erick Brethenoux | Ben Yan
... AI supercomputing is redefining IT in life science organizations, transforming technology from a cost center into the engine room for discovery. By compressing project timelines, early adopters can attain formidable competitive advantage as industry leaders pivot toward compute-driven research. Insights ...
... depend on is ready. Enterprise application leaders must harden execution, governance, and accountability across CRM automation before scaling agentic AI. Insights at a Glance Issue Impact More Detail Gartner Recommended Reading Gartner Insights Abstract ...
Analyst(s): Adam Briggs | Arthur Villa | Ilona Hansen | Mike Levisay
... Treating manual governance as a downstream checkpoint in an AI-native SDLC is an existential threat to business value. Software engineering leaders must immediately transition to automated guardrails and adaptive controls to proactively mitigate security risks, protect IP and prevent eroding long-term ...
... CISOs are reacting to the dual impacts of frontier LLM vulnerability discovery and internal organizational AI ambitions. These forces are making managing technical debt and data debt critical, creating a new alignment in incentives and forcing a shift of cybersecurity priorities. Insights at a Glance ...
Analyst(s): Alex Michaels | Charlie Winckless | Niyati Daftary
... offers embedded conversational tools and standalone agentic automation. This guide helps heads of enterprise applications navigate Mistral’s enterprise AI assistant by providing an overview of its key capabilities and shortcomings, as well as recommendations for its use. Insights at a Glance Strategic Planning ...
Analyst(s): Tushar Srivastava | Irina Guseva | Stephen Emmott