Operationalizing Agentic Commerce: Retail Workflows Delivering Measurable ROI Today

Listen to this article

 

From recommendation engines to automated pricing dashboards, AI-powered tools have become common in retail. But agentic commerce is shifting the landscape again. AI agents are now doing tasks for shoppers and retailers, like helping them find products, making purchases, and handling post-purchase tasks. 

A CXO playbook for fixing what’s broken in the digital contact center

A CXO playbook for fixing what’s broken in the digital contact center

Enterprises have invested heavily in modernizing contact centers. Cloud migrations, omnichannel platforms, bots, and analytics were meant to transform customer service. 

Yet for many organizations, the results haven’t matched the investment. 

Costs continue to rise. AI pilots stall. Customer experience remains inconsistent. Leadership teams find themselves reacting to problems instead of staying ahead of them. 

Why 2026 is the breakout year for AI-powered CRM and data platforms in P&C

Listen to this article

 

The insurance industry has spent the last decade digitizing surfaces. For Property & Casualty (P&C) carriers in particular, rising claims severity, catastrophe volatility, and underwriting margin pressure are exposing the limits of surface-level digitization. What is different - heading into 2026 is where transformation is happening. AI is moving inside operational cores: CRM decisioning layers, data platforms, and infrastructure orchestration. 

The rise of AI-native operations: How L&A enterprises are unlocking 30–40% efficiency gains through CloudOps and actuarial modernization

Listen to this article

 

The insurance industry rarely changes overnight. Whether it is regulatory complexity, product proliferation, legacy infrastructure drag, or growing expectations for hyper-personalized experiences, it accumulates pressure quietly.  

For Life & Annuities (L&A) carriers, that pressure has reached a tipping point. Operating models designed for stable actuarial cycles are now expected to support near real-time decisioning, continuous risk recalibration, and always-on digital ecosystems.  

Reimagining IEP with Evidence AI Analyst: From siloed tasks to intelligent orchestration

Reimagining IEP with Evidence AI Analyst: From siloed tasks to intelligent orchestration

Integrated Evidence Planning (IEP) has never lacked rigor. What it has lacked is coherence. 

For years, IEP has been executed through structured templates, static plans, and cross-functional discussions focused on aligning studies, analyses, and publications to an asset milestone. The intent was sound. The execution was disciplined. Yet outcomes often fell short when evidence met real-world decision-making. 

Integrated Evidence Planning reimagined: Orchestrating evidence with intelligent agents

Listen to this article

 

For years, Integrated Evidence Planning (IEP) has carried a paradox at its core. It is one of the most strategic levers in life sciences, yet the way it has been executed often feels operational, fragmented, and reactive. Teams build structured plans, populate spreadsheets, and align across functions with rigor and expertise. And yet, when a pivotal HTA decision challenges comparator choice, or when a payer questions endpoint relevance, the same thought resurfaces - we could have seen this coming.