Generative AI has quietly collapsed the seventy-year separation between instruction and data. The companies that recognize this, and build the engineering discipline to match, will own the decade. A few months ago, the chief information officer of a health insurer with more than $20 billion in annual revenue made a remark that has stayed with…
Banks and credit unions are sitting on an underleveraged growth asset. For years, the banking contact center has been measured almost entirely on efficiency with key metrics including handle time, first-call resolution, and cost per interaction. The primary goal was to manage a high volume of inbound service requests, and the technology available in past years did not offer much beyond that. Now AI is handling…
Should you build or buy a knowledge management system? For most organizations, buying a commercial knowledge management platform is more cost-effective than building one in-house. Hidden costs, including security, AI development, scalability, integration, and ongoing maintenance, cause in-house builds to exceed original budgets. Commercial platforms spread these costs across many customers and continuously invest in…
How to get budget for Knowledge Management by aligning to priorities leadership already owns. If you can’t get budget for Knowledge Management, the fastest path forward is to reframe your initiative as a direct enabler of a business priority leadership already owns. This five-step playbook shows you how to make that case, find an executive…
Insurers face growing pressure to deliver accurate, compliant answers faster across increasingly complex product lines. AI knowledge management is how leading carriers are rising to that challenge. Every customer interaction in insurance depends on an agent being able to find the right answer quickly, accurately, and in a form they can communicate with confidence. Getting…
And Why Trusted Knowledge Is the Real Foundation for AI Success Most AI reliability problems aren’t model problems. They’re knowledge problems. Consider Millennium Tower, the “Leaning Tower of San Francisco.” When it opened in 2009, it looked flawless from the outside, but homeowners began noticing signs that something wasn’t right. Balls rolled across kitchen floors…
Executive Summary Private equity firms face a distinctive and high-stakes challenge when operating portfolio companies with established brands and loyal customer bases: how to transform legacy, labor-intensive cost structures through AI-powered automation without disrupting the customer experience that underpins the entire value proposition. To illustrate the financial stakes: a 500-agent contact center with fully-loaded agent…
Jensen Huang knows how to simplify complexity. At GTC 2026, he described the AI stack as a five-layer cake: Energy, Chips, Infrastructure, Models, and Applications. Clean. Memorable. Useful. But there’s a layer missing. Look at where the gap sits: between Models and Applications. That’s exactly where enterprise AI breaks down in practice. You have extraordinary…
Week #1 Developer Series “Don’t tell me how to use your product — show me how to build with it.” — SVP of IT, $5B+ US Credit Union That single sentence opened one of the most memorable customer conversations I’ve had at eGain. The technology executive leading IT at one of America’s largest credit unions…
The promise of AI in customer experience automation has captivated enterprises worldwide. Yet for every success story, there are countless organizations struggling to extract meaningful returns from their AI investments. The gap between AI’s potential and its practical delivery isn’t a technology problem—it’s a fundamental mismatch between how AI solutions are architected and what real-world…
