5 Reasons Why Healthcare Consumer Experience Initiatives Are Impacted by AI (Ungated)
AI is rapidly transforming the healthcare consumer experience, yet many organizations across payer and provider segments struggle to move beyond early-stage pilots to achieve meaningful, enterprise-wide impact. Fragmented ownership, limited data readiness, and workforce resistance often stall progress, driving up costs without delivering sustained value. This webinar organized with Customer Contact Week (CCW) explores five critical ...
The CX Gap in Financial Services: Why Resolving Interactions is Not the Same as Keeping Customers
Financial institutions today face a hidden risk: customers are not leaving loudly—they are quietly redistributing their financial relationships. Traditional CX metrics like NPS, CSAT, and resolution rates fail to capture this shift, creating a dangerous “loyalty illusion.” This whitepaper explores how AI-powered CX must evolve beyond interaction resolution to detect early signals of relationship erosion. ...
B2B AI Customer Support: A Strategic Infrastructure Rather Than an Operational Tool
Key Points AI in B2B customer support is entering a decisive phase. What began as chatbot experimentation is evolving into embedded, enterprise-grade intelligence across service ecosystems. For organizations operating under complex SLAs, distributed infrastructure, and high-value contracts, AI is no longer a marginal cost lever – it is becoming a control layer for operational resilience. ...
From Operations to Autonomy: Building the AI-Native Telco with Agentic AI
Key Points Telecom is approaching an inflection point: the era of incremental automation is giving way to AI-native operations. Thanks to the scale of operational complexity, combined with the intensity of growth pressure. Future leaders will be defined by operating models that can sense, decide, and act across the network and the business. This transition ...
The New Tech Stack for the Modern Chief Underwriting Officer (CUO)
Today’s Chief Underwriting Officers are expected to balance speed, precision, portfolio control, scalability, win rates, and risk appetite in an increasingly complex market. Achieving these goals requires more than isolated tools. It demands an integrated technology stack that connects data, intelligence, automation, and decision-making across the underwriting lifecycle. From data integration and intake enrichment to ...
The AI ROI Mirage in Banking (Ungated)
Banks are investing heavily in AI, but many programs still struggle to show a measurable financial impact. The problem is not always technology. It is the value frame. Most banking AI initiatives are still judged through a narrow productivity lens: hours saved, licenses deployed, headcount reduced. But in financial services, AI value often shows up ...
AI SDLC vs. Agentic SDLC: Why Enterprises Need Orchestrated AI for Software Engineering
Key Points Enterprises are increasingly under pressure to deliver software faster, with better quality, while under multiple increasing regulatory and security constraints. The multitude of AI tools that we have today are rapidly entering software development through coding assistants, AI-driven quality assurance, automated documentation, and intelligent code reviews. However, can simply adding AI tools transform ...
The AI ROI Mirage in Banking
Explore why productivity alone is not enough to measure AI ROI in banking, and how Sutherland’s six-lever framework helps financial institutions prove and scale AI value.
From Months to Days: How AI Is Rewriting the Rules of Provider Credentialing
Key Points In our previous blog, we examined the true financial cost of provider credentialing delays, which runs into hundreds of thousands of dollars per provider, millions per hospital, and billions across the US healthcare system annually. If that analysis landed with the weight it deserved, a natural question follows: is this a problem that ...