... Model Enhancement Data Access and Preparation Business Activity Monitoring Advanced Process Analysis Task Mining Process Orchestration Execution Generative AI Process Discovery Process Comparison, Analysis and Validation Automation Opportunities Digital Transformation Inclusion Criteria Gartner Recommended ...
Analyst(s): David Sugden | Marc Kerremans | Nick Duffy
Get more from Gartner
Interested in receiving proven business and technology insights, analyst guidance, benchmarks, diagnostics and more? Connect with a Gartner representative to learn more about becoming a Gartner client.
... data serves as a privacy-friendly supplement to real data for testing and training machine learning models, contributing to the acceleration of AI and generative AI adoption. Digital leaders should use this research to explore synthetic data, leveraging its advantages to stay ahead of competition. Gartner ...
Analyst(s): Daniel Sun | Gunjita Mundeja | Alys Woodward
... these capabilities integrate into their solutions. Overview Analysis Recommendations Conclusion Gartner Recommended Reading Note 1: Generative AI Versus Discriminative AI Gartner Research ...
... progress by monitoring: AI skills proficiency through both self-assessments and peer reviews Participation in experiential (not just static) AI learning activities Productivity and business outcomes, such as reduced cycle times, increased output and faster time to market Reduction inAI-related compliance ...
... Spatial AI, the connecting tissue of physical AI and digital AI, represents a $46 billion opportunity by 2036. Product and innovation leaders across tech and industry must understand how to start building spatial AI capabilities into their strategic roadmaps or risk falling behind in the AI race. Overview ...
... Retrieval augmented generation is a generative AI deployment approach that allows organizations to supplement LLMs with internal data to enhance response accuracy. RAG workflows are challenging to plan and implement. Technical professionals can use this research to prepare for RAG. More Detail Gartner ...
... Generative AI has increased the pressure on software engineering leaders to deliver software faster, without compromising quality or security. This leadership vision communicates the value of developer experience, engineering intelligence, and choosing the right developer productivity metrics. Overview ...
Analyst(s): Brad Dayley | Mark O'Neill | Akis Sklavounakis
... Enterprises’ explosive use of generative AI (GenAI) impacts network performance, cost and scale and heightens the need for robust security. Product managers can capitalize on these escalating enterprise risks by optimizing reference architectures and building security guardrails. Overview Analysis Gartner ...
Analyst(s): Simon Richard | Charanpal Bhogal | Marissa Schmidt | Evan Zeng | Chirag Dekate
... Generative AI will drastically change how employees expect to find information. To reduce information overload and avoid employee attrition, CCOs should reevaluate their channel mix to incorporate GenAI-driven chatbots and work cross-functionally to mitigate potential risks. Overview Analysis Gartner ...
Analyst(s): Will Grant | Nabeeha Ahmed | Adam Herold | Anthony Mullen