Cloud SAP® automation now has a standards-based path to AI
Key Takeaways Connecting AI assistants to SAP requires custom integration work that must be rebuilt for every new AI platform the organization adopts. The Precisely Automate MCP Server exposes existing Automate Studio scripts and Automate Evolve workflows to any MCP-compatible AI tool through one standards-based connection. Native OData support in Automate Studio ensures cloud SAP […]
5 takeaways from Precisely Now: Trusted AI starts with trusted data
Key Takeaways AI moved from planning to production faster than data readiness did, and agents now act on untrusted data at machine speed, before anyone can intervene. Precisely announced the Precisely Platform for unified data management and Precisely AI Studio for building on it. AI Studio is available today. Customers at Lake Michigan Credit Union […]
What does it take to build AI-ready data products?
Key Takeaways Building trust into a data product from the start is what separates a data product from a dataset, and what determines whether it can support AI systems at scale. AI-ready data products require machine-readable semantics, standardized reference data, and governance that extends to the agents and models consuming them, not just the humans. […]
Here’s what Big Data London confirmed about the state of AI-ready data
Key Takeaways Enterprise trust in AI runs directly through the quality and governance of the data feeding it, and that realisation is now widespread. Most organisations sense a context gap: data that exists but lacks the meaning, enrichment, and consistency that AI systems need to act reliably on it. Location intelligence remains a meaningful, underused […]
Something big is coming on October 8 — and I want you to be there
Key Takeaways Precisely Now is October 8, featuring major product announcements, an exclusive IDC research conversation, and customer stories from data leaders doing this work at scale. IDC Research VP Stewart Bond will discuss why data intelligence has become a first-order AI infrastructure decision Two enterprise data leaders from Lake Michigan Credit Union and Charter […]
What 20 UK data leaders told me about scaling AI — and what they wouldn’t admit at first
Key Takeaways: Most organizations are still between piloting and selective production on AI — and the blocker is almost never the model. It’s the data underneath it. Agentic AI changes the stakes: when AI acts instead of recommends, bad data no longer produces a bad report — it produces a compounding chain of bad decisions […]
Most Enterprises Aren’t AI-Ready. Data is the Barrier.
Key Takeaways AI is already running in most enterprises, but the data feeding it isn’t ready. Fragmented, ungoverned data compounds errors at machine speed before anyone can intervene. The real AI readiness gap isn’t a technology problem, but a data architecture problem: integration doesn’t inform governance, governance doesn’t connect to quality, and enrichment is bolted […]
How New AI Agents for Customer Communications Help You Move Faster with Confidence
Key Takeaways: Regulated communications teams face compounding pressure across the board, including challenging change management cycles, manual compliance review, data exposure concern, and time-consuming archive retrieval. EngageOne™ RapidCX now embeds four additional AI capabilities across the communication lifecycle: template creation, compliance review, data masking, and archive search. Each capability is designed around human oversight. AI […]
A Look at the 2026 AI Software Engineering Intern Program at Precisely
Authors: Joshua Ofori Otchere, Director, Software Development, Precisely Yvon Leclerc, Vice President, R&D, Precisely Key Takeaways Precisely Engineering welcomed 12 interns this term; six share their experiences here, including four who joined through a hackathon-inspired hiring approach. In an AI-driven engineering environment, curiosity, collaboration, and the ability to ask the right questions matter as much […]
Data Governance for AI Is Under Pressure: What the Data — and Experts — Are Telling Us
Key Takeaways Without a formal data governance program, trust in organizational data is essentially a coin toss. That gap has real consequences as AI systems scale decisions at speed. A data governance program and a data strategy must work together; governance built in isolation from business objectives stalls quickly, and organizations that align both see […]
Agentic AI Engineering: How Precisely Builds Teams That Are Ready
Key Takeaways For responsible Agentic AI engineering, teams need structured training in multi-agent system design, human-in-the-loop principles, and the limits of AI autonomy. Clean coding architecture is what separates teams that use AI tools effectively from those that use them to build technical debt faster. The AI Cohort Program at Precisely demonstrates that engineering culture […]
Why AI Needs a Semantic Layer
Key Takeaways A semantic layer sits between raw data and the AI systems that query it, translating physical data structures into governed business definitions — so every tool, team, and agent draws from the same source of truth. Without a semantic layer, AI returns confident, well-structured answers that can look correct while relying on the […]