... 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
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... disruption, this scenario-based guide maps the enterprise applications market from 2026 into the 2040s. Download it to compare four scenarios, spot genuine AI-native vendors, and get buy-versus-build, cost, agent and contract negotiation moves you can act on now. High-Level Overview Contributors Gartner Recommended ...
... Access Insights Already a Gartner client? AI leaders must balance AI ambition with the mitigation of increasing technology, talent and business risks to maximize enterprise value from AI. Gartner’s seven themes help AI leaders focus on the decisions and actions that matter most through 2027. Analysis ...
... Despite the breathtaking pace of AI innovation, focusing on what never changes in the ever-changing AI world allows leaders responsible for AI to build future-proof strategies that transcend the hype and deliver sustainable business value. Leaders should adopt these seven principles to deliver lasting ...
Analyst(s): Ben Yan | Pieter den Hamer | Leinar Ramos
... Financial services leaders have a vision for the role of AI at their firms, but many banks lack the maturity to translate that vision into action. To boost AI value realization, leaders must improve maturity across seven dimensions of AI, including strategy, governance, engineering and data readiness ...
... Access Insights Already a Gartner client? Balance AI roadmap strategy by aligning the art of the possible with the art of the plausible. Learn how Heads of Enterprise Architecture can classify AI investments as “defend,” “extend,” and “upend” to connect AI demand to business value, governance, and execution ...
... AI governance programs require standardized performance metrics, such as model degradation rates and incident detection times, to objectively quantify risk mitigation and enforce enterprisewide accountability. This research introduces 10 foundational metrics leaders responsible for AI need to benchmark ...
Analyst(s): Antonia Roesler | Joel Backaler | Claire Song
... AI adoption in program and portfolio management is accelerating as PPM leaders seek to enhance efficiency, improve decision-making accuracy, and focus on higher-value initiatives. This research curates a comprehensive set of PPM AI use cases and outlines best practices from across industries. Overview ...
Analyst(s): James Boyle | Shivica Mathur | Peter Clegg
... Access Insights Already a Gartner client? Enterprise AI adoption threatens legacy managed-services revenue as AI agents and automation shift value from labor-driven, transactional models to software-intensive, outcome-based services requiring MSPs and CSPs to evolve their business and delivery strategies ...