Matt Meyer breaks down the 3 types of input prompts that are required to build and use RAG models.
ai agent
ALM within the Microsoft AI stack introduces versioning and governance for better visibility, clear ownership, and disciplined development processes.
Armanino’s Gina Montgomery details the levels of AI maturity that many organizations face today.
Mico reacts visually and conversationally in Copilot’s new release, elevating user engagement with adaptive tone and personality.
WalMart’s embrace of AI chatbot purchases, along with similar moves to Etsy and Shopify, suggest major changes in retailer and consumer shopping practices are on the horizon.
AI-powered automation tools provide a better handle on the performance of sales and service teams, as well as the AI platforms that are being injected into these core business processes.
Orchestration manages flow of context, error recovery, and handoffs between agents; Microsoft offers services and apps tailored to diverse requirements.
AIS’s Brent Wodicka notes why it’s clear that not all AI works the same way through use case examples.
An AI retrieval agent can help a medical provide to quickly access a patient’s vaccination history or a finance manager to delve into monthly variances. Both examples highlight their transformative power.
With Agent Mode, users can simply ask Excel to create a project portfolio tracker with specific formatting and data relationships. It’s a valuable digital teammate.
ArcherPoint by Cherry Bekaert’s Greg Kaupp discusses the importnace of AI literacy before applying agents, and how the technologies can drive organizational transformation.
BouMatic CIO Michael Fisher describes how the company is using, deploying, and facing challenges related to AI.
HSO’s Kelly Holwagner shares insights on how AI has enabled rapid transformations across various industries and highlights Summit NA sessions.
Ludia Consulting’s Lucas Diaz defines three categories of agents, noting that agent type can determine the outcome.
Michael Simms of Columbus shares how the organization applied AI to combat business challenges while working with Mad Engine.
Prashant G. Bhoyar compares the increasing rate of AI innovation to the slower rate of AI adoption across organizations.
Microsoft announces the world’s most powerful AI data center in Wisconsin as Oracle, OpenAI, and SoftBank reveal plans for $400B+ AI infrastructure under the Stargate project.
National Power CIO S. David Brown explores what the AI transformation journey looks like and how to get started.
Continuing a push to provide access to the best AI for a given function, Microsoft offers Claude models in Copilot Studio, GitHub Copilot, and Researcher Agent.
Microsoft VP of AI Agents, Ray Smith, defines the three levels of AI transformation.