Rowan Curran

Wie jede Blase wird auch der aktuelle Glanz der KI in 2026 vergehen, da Unternehmen die Funktionalität der KI gegenüber ihrem Flair priorisieren werden. Die diesjährigen KI-Prognosen betonen, wie wichtig es ist, in Bereiche wie Schulung und Governance zu investieren und gleichzeitig den ROI der KI genauer zu bewerten.

In 2026, AI will trade its tiara for a hard hat as enterprises prioritize AI function over flair. This year’s AI predictions emphasize the importance of investing in areas such as training and governance while evaluating the ROI of AI more closely.

As autonomous agents evolve from novelty to necessity, the protocols that govern their behavior become critical infrastructure. This blog explores the foundational tools we need to build a trustworthy agentic future.

Snowflake Summit 2025 highlighted advancements in AI, data integration, and platform capabilities, emphasizing innovation and strategic growth initiatives.

The ServiceNow Knowledge 2025 event unveiled ambitious advancements in AI-driven enterprise technology, with a focus on autonomous workflows, unified data platforms, and human-machine collaboration. Key announcements included the launch of the AI Control Tower for managing AI agents, the expansion of Workflow Data Fabric to unify disparate data sources, and the intent to acquire data.world […]

Moveworks’ global event in San Jose marked a major inflection point in enterprise AI with the announcement of Agent Studio, Plugin Workspace, and an AI Agent Marketplace — all part of its strategy to become the go-to platform for building business-ready AI agents. Analysts Julie Mohr and Rowan Curran provide their insights on the announcements. […]

Loads of news came out of a hot Google Cloud Next 2025 in Las Vegas. The most notable announcements? Sovereign AI solutions on-prem, developer innovations that meet timely needs, very applicable multimodality for content and CX, and new elements for building the enterprise agentic AI stack.

San Jose was abuzz with excitement as AI enthusiasts gathered for the 2025 NVIDIA GTC AI conference. Find out what the key announcements were and what they could mean for your technology roadmap in this review.

To achieve seamless cross-platform functionality, AI agents need standardized frameworks addressing not just technical compatibility but also security, governance, adaptability, and intent. Read this post to learn the nine dimensions of agentic AI interoperability. 

As vendors come out of the woodwork announcing their “agentic AI” innovations, we explore what the term truly encompasses and what is hype.

In the ever-evolving landscape of artificial intelligence, businesses are moving beyond traditional AI agents toward something far more transformative: agentic AI.

For more than a decade, Forrester has been committed to researching AI and ML technologies and platforms. During my 13-year tenure at Forrester, I had the privilege of working alongside our talented AI analysts. Together, we have continuously refined our market definitions and research focus to stay aligned with emerging tech trends and business needs. […]

AWS may have been caught off guard by the sudden rise of generative AI, but now it’s coming for the competition from every possible angle. Get our key takeaways from AWS re:Invent 2024.

Sophisticated enterprise knowledge applications require advanced RAG architectures. Use these three concepts to build smarter RAG apps.

Enterprises experimenting with generative AI (genAI) are prioritizing use cases that enable internal and external users to better retrieve information they need, be it data, how-to pages, corporate policies, or return policies. Retrieval-augmented generation (RAG) is now the most common underlying approach for building this type of large language model (LLM)-based enterprise knowledge-retrieval application. What […]

In our inaugural evaluation, The Forrester Wave™: AI Foundation Models For Language, Q2 2024, we break down large language model (LLM) model offering, strategy, and market presence across 21 criteria for 10 providers. Get a preview of the report including four things you should be looking for in a model here.

It’s easy to trust generative AI implementations because of how human they feel. But when it comes to security, there are still some fundamental challenges to overcome with genAI. Learn more about those challenges in this post.

The market for AI foundation models is still in its infancy. While enterprises still rely mostly on pretrained large language models for AI needs, the market is evolving and changing quickly. Tech leaders must understand how to navigate it.

Google recently held its Google Cloud Next conference four months early to unveil new AI offerings and upstage its rivals. Get a detailed review of all of the announcements at the event in this post.