The Multimodal World of Enterprise AI

Multimodal applications of AI are gaining credence throughout the enterprise at increasingly rapid rates—and for good reason. Firstly, they come close to realizing the full potential of foundation models and large language models (LLMs) which, by default, are multimodal.

AI Across Markets and Industries

With all the noise around generative AI (GenAI) since the advent of ChatGPT, has the signal gotten lost? Are we missing the one "killer app" that will make GenAI indispensable? What is more likely is that multiple killer apps will surface across many markets and industries.

Tackling Explainability and Interpretability in Language Models

The very nature of language models—large language models (LLMs), foundation models, and frontier models—confounds the notions of explainability and transparency.

Moving to Agentic AI

Intelligent agents are not new. In its April 15, 1995, issue, Datamation published my 1-3-year forecast. Agents, I predicted, would automate repetitive tasks, help with email, and coach us on managing time wisely. Sound familiar?

ElevenLabs and IBM Bring Premium Voice Capabilities to Agentic AI

ElevenLabs integration with IBM watsonx Orchestrate will help clients to deliver natural, multilingual conversational experiences at scale.

Datadog and Sakana AI Collaborate to Advance AI Innovation and Observability for Enterprises

Collaboration brings together leading AI research and cloud observability expertise to support next-generation AI applications, starting in Japan.

Kocho Selects Zadara to Enable Efficient Sovereign AI Clouds

The partnership enhances Kocho's agility and security while supporting data sovereignty, AI readiness, and its Microsoft-first cloud strategy.

Building an AI-Ready Enterprise: Governance as the Foundation for Scalable AI

Solving the 95% Blind Spot

Solving the 95% Blind Spot: How to Find the Issues Your Contact Center Doesn't Know It Has Your Contact Center Is Flying Blind on 95% of Customer Data Most teams analyze only 5%—manual tags and sampled data. The rest stays hidden in transcripts, chats, and surveys. What This Costs You: Reacting weeks after problems start Missing emerging issues with outdated taxonomies Never catching the "unknown unknowns" that drain revenue Why AI deflection fails (and what works instead) The Avoidance Imperative—eliminate issues at the source How autonomous taxonomy delivers 100% coverage Get the Ebook

Spiral by UJET - The AI Issue Hub for Decision-Grade Data

What if anyone in your entire company—from an engineer to a marketing leader—could instantly ask a plain language question and get a definitive, quantified answer from 100% of your customer conversations? This datasheet shows you how. Learn how Spiral’s easy-to-use AI agent autonomously analyzes every call, chat, email, and review to find the ultra-specific root cause of every customer issue—transforming 100% of your customer conversations into actionable, predictive insights. Go from 'What if?' to 'Here's how.' Trusted by innovative teams at Turo, Owlet, and Whitepages

Tipping the Scales: AI-led or Human-led CX in 2025 and Beyond

When should AI handle the interaction—and when should humans step in? Watch this on-demand session with CCW Digital and UJET experts to find out. What You'll Learn: 2025–2026 AI predictions and emerging CX capabilities Strategies for seamless AI-to-human escalation Which use cases need AI vs. where humans are essential A framework for balancing AI-led and human-led experiences Featuring Brooke Lynch (CCW Digital), Matthew Clare (UJET), and Dave Michels (TalkingPointz) Watch On Demand Now!