Generative AI is moving beyond simply answering questions. Increasingly, AI assistants and agents need to interact with the business applications where work actually happens.   That is where Model Context Protocol, or MCP, comes in.   For SAS Customer Intelligence 360, MCP provides a standardized way for an AI application to discover and use selected SAS Customer Intelligence 360 capabilities. Instead of requiring someone to navigate through a user interface screen by screen, an MCP-enabled AI client can translate a natural-language request into calls to SAS Customer Intelligence 360 tools to do things such as configuring journeys or audiences.   Intro to MCP MCP represents an important shift in how people may interact with enterprise applications. The easiest way to think about MCP is as a standard connection between AI applications and external systems.   Model Context Protocol is an open-source standard that lets AI applications connect to external data, tools, and workflows. It uses a client-server architecture: an AI application acts as an MCP host, establishes a client connection to an MCP server, and discovers the capabilities that server exposes.   Instead of requiring AI applications to understand every product's proprietary integration model, MCP provides a common protocol for discovering and invoking capabilities.   Today, those objects are typically managed through application workflows and APIs. With MCP, they become tools that an AI application can discover and orchestrate through natural language.   That doesn't eliminate the marketer from the process. It changes the marketer's level of interaction.   What Does MCP Bring to SAS Customer Intelligence 360? Instead of spending as much time telling the software how to perform every individual step, marketers can increasingly spend their time describing what customer experience they want to create, while AI assists with translating that intent into SAS Customer Intelligence 360 operations.   And that may ultimately be MCP's most important contribution to SAS Customer Intelligence 360. It’s not simply another integration interface, but a foundation for a more conversational and agent-driven way of working with marketing technology.   Here are some of the things you can do with MCP and SAS Customer Intelligence 360:   Build and Manage Journeys Through MCP an AI client can: create and update scheduled journeys including schedules, audience nodes, task nodes, goals, personalization, and other schedule information. retrieve scheduled journeys, search for them, review them, activate them, examine occurrence history, and delete them. For example, rather than starting with individual screens, a marketer working through an MCP-enabled assistant could express an objective such as: “Create a journey for our credit card retention audience that sends an SMS reminder and uses account renewal as the goal.” The AI client can use the SAS Customer Intelligence 360 tools exposed through MCP to help construct the necessary SAS Customer Intelligence 360 objects. The exact requests still need to satisfy the schemas and lifecycle rules exposed by SAS Customer Intelligence 360.   Create Marketing Tasks The MCP server also exposes task capabilities within the context of the scheduled journey. Supported task types currently include bulk email, SMS, custom bulk, Facebook advertising, Google Ads, Google Display & Video 360, LinkedIn advertising, Snapchat advertising, and mobile push. Tasks can be created, retrieved, searched, updated, copied, deleted, and moved to a ready state.   Work with SAS 360 Audiences The current SAS Customer Intelligence 360 MCP supports searching and retrieving audiences, getting audience counts, copying audiences, creating API- and database-sourced audiences, uploading CSV audience data, running or refreshing audiences, and deleting audiences.   To see all the capabilities exposed by MCP, please read the Customer Intelligence 360 user guide.   Example Use Cases: With MCP, here are some examples of things you can do once you have Customer Intelligence 360’s MCP integrated into your client (Claude, VSCode, etc): Build a Journey: "Create a journey for customers whose credit cards expire in the next 60 days. Send an SMS reminder, wait 7 days, and use account renewal as the conversion goal." "Add an SMS task to my Welcome Journey that sends the customer a reminder 24 hours after enrollment." “Create an SMS creative for our loyalty renewal reminder and use it in the Renewal Journey.” "Use my 'High Value At-Risk Customers' audience to create a re-engagement journey with an email followed by an SMS three days later for anyone who doesn't respond." "We're launching a new premium checking product. Target high-value checking customers who don't already own it, create a three-touch journey using email, SMS, and mobile push, and use account opening as the goal." Create an Audience: “Create an audience of customers in Cary that have spent more than $100 this year” “Find the audience we used for last month's premium-card campaign, copy it, and modify the new version to include only customers with a balance over $25,000” "Add Last Name, First Name and Email Address to the High Value Audience" Operations “List all of the journeys that are running this week” “How many customers are in my High Value At-Risk Audience?” "Show me the recent occurrences of the Credit Card Retention journey and tell me whether it ran as expected."   ... View more

In SAS Viya, when running code in SAS Studio, the automatic macro variable _SASPROGRAMFILE contains the full path (or URI) of the program file. However, when running the same program using the VS Code SAS extension, _SASPROGRAMFILE resolves to the filename only, without the directory path. Is there a way to determine the full path of the program file when running from VS Code? Does SAS Viya expose this information through any existing environment variable, or other macro variable? Any hints or recommended approaches? ... View more

Team Name Team CLMers Track Public Sector Use Case *Our team, CLMers, proposes an AI-powered wildfire prevention platform that helps public authorities anticipate and mitigate wildfires before they occur. The solution combines weather forecasts, satellite imagery, vegetation indicators, historical wildfire records, and open data to generate dynamic wildfire risk assessments.  Using predictive analytics and geospatial intelligence, the platform estimates ignition risk, fire spread potential, and expected impact. It also provides decision support recommendations to help optimize prevention measures and resource allocation.  By shifting wildfire management from reaction to prevention, the project helps protect ecosystems, rural communities, and critical infrastructure while improving climate resilience and public-sector efficiency.  Built on scalable cloud technologies and open data, the solution can be replicated in any wildfire-prone region worldwide.  Vision: From firefighting to fire prevention. Technology SAS Viya Region Spain Team lead Cobas López, Christian Team members 18 Team members Social media handles *all team members' social media links here* Is your team interested in participating in an interview? Y Optional: Expand on your technology expertise     The Team     Pitch Jury ... View more

Team Name Ludlowe Legacy Track  Track: Health care & Life Sciences Use Case GreenSeer is an auto-ML-inspired environmental intelligence platform designed to help policymakers and organizations more efficiently evaluate the effectiveness of environmental policies and pollution-control interventions. By combining decades of EPA pollution data, policy documents, and external factors such as weather, GreenSeer uses intelligent model selection, statistical analysis, and explainable AI to identify meaningful patterns and assess environmental changes. The results are presented through an interactive SAS-powered dashboard that translates complex analyses into clear, actionable insights for better environmental decision-making. Technology SAS Viya, Python, Forecasting Models, Causal Inference; EPA air-quality and emissions data, NOAA weather and smoke data, transportation and energy datasets, and more. Region Raleigh, NC, Fairfield, CT Team lead Andrew Kutsch Team members @andyk08   Andrew Kutsch, Adil Syed, Gamid Muratbekov Social media handles *all team members' social media links here* Is your team interested in participating in an interview? Y Optional: Expand on your technology expertise     ... View more

Part of our #SASVoice | Learning from Our Customers series, sharing practical lessons from real customer situations.   The Challenge A global organization was introducing new technologies, modernizing business processes and driving transformation across multiple areas of the business.   This raised an important question: Did employees have the skills needed to turn these investments into business value?   The challenge was not simply providing more training. It was understanding where capability gaps existed and connecting workforce development with the organization's broader business priorities.   Without this connection, learning risked becoming a separate activity rather than a practical part of the transformation strategy.   The Approach The organization took a more structured approach to understanding and developing workforce capabilities.   Skills assessments helped identify capability gaps. Development planning and role-based learning opportunities then helped connect those needs with relevant development pathways.   Learning priorities were aligned more closely with business and transformation priorities, moving the conversation beyond course completion and towards longer-term capability building.   The Outcomes The approach created a clearer connection between workforce development and broader transformation priorities.   It was designed to support: Better alignment between learning investments and business goals Improved workforce preparedness Stronger support for transformation initiatives Greater focus on long-term capability development     Lessons Learned Learning creates the greatest value when there is a clear reason for it. Before asking: “Which course should people take?” organizations may benefit from first asking: “Which capabilities do we need, where are the gaps and what business objective are we trying to support?” Starting with the need rather than the course can help create learning pathways that are more relevant to employees and more closely connected with business priorities.   Learn More Not sure where the most important skills gaps are in your organization? A Learning Needs Assessment can help identify priorities before defining the right learning approach. SAS Premium Learning Subscription can then support ongoing, role-based skills development across teams and learning needs. ➡️ Learn more about SAS Premium Learning Subscription: https://www.sas.com/gms/redirect.jsp?detail=PLN69124_1174760520   Editor's Note: This article is based on real customer experiences. Specific customer details have been anonymized to focus on the business challenge, approach and lessons learned.      ... View more