... Gartner client? Investing in an effective AI portfolio of solutions and services will be critical to success in this very competitive and fragmented industry. Winning tech services leaders will grow and defend market share by delivering a curated retail-specific AI application portfolio designed to effectively ...
Analyst(s): Arindam Das | Tom Coshow | David Ackerman
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... client? Building AI solutions with ROI is competitive and requires experimentation and customer buy-in. Technology service leaders can boost AI sales by developing AI data agents to build AI-ready data quality, governance and semantic layers, while lowering the cost of delivering these AI-ready data foundations ...
... Persistent AI risks, including agent terrorism, rogue AI, insider threats, and skills atrophy, threaten enterprise security, governance, and workforce readiness. Heads of EA should embed robust AI governance and continuous risk mitigation into enterprise architecture to maximize their AI investments. ...
... Leading physical AI startups are creating innovative physical AI architecture, hardware for industry-specific solutions, and preparing for unstructured autonomy. Product leaders must reimagine AI systems and infrastructure and invest in physical intelligence innovation to scale physical AI adoption. Overview ...
... Access Insights Already a Gartner client? AI slop is lowering the quality of information, and changing laws are making the AI product market trickier. Product leaders can stand out by labeling premium assets as “AI-free,” thus mitigating potential risks of faulty AI products and content that may be misleading ...
... Access Insights Already a Gartner client? Expansion of AI adoption is creating urgent demands for AI-ready data. AI-ready data is defined in the context of the AI use case and technique, necessitating the evolution of data management practices. D&A leaders must continuously prove data readiness and adapt ...
Analyst(s): Ehtisham Zaidi | Svetlana Sicular | Roxane Edjlali | Mark Beyer
... Vendors are rapidly integrating AI into email security for detections and features, but not all uses of AI improve outcomes. This research identifies the strengths, weaknesses, and differentiation points of AI-enabled email security features. Insights at a Glance Issue Impact Implications Gartner Recommended ...
... core risk to AI adoption is that models don’t just fail, they “fail convincingly” and lead to the loss of stakeholder trust. This research helps data scientists and AI architects translate performance signals into actionable reliability narratives that build confidence in predictive AI models. Overview ...
... engineering leader AI tools and complex tokenomics disrupt software delivery. For the software engineering leader, the mission demands modernizing practices to deliver maximum value without inflating budgets. Yet, slashing innovation funding guarantees irrelevance and unchecked AI adoption generates ...