JAMES' BLOG

Post quantum cryptography has a deadline, and it is closer than most boards think. Gartner expects most conventional public key encryption to be unsafe by 2029, and NIST has proposed retiring it after 2030. Data stolen today can be decrypted later, so the exposure starts now. Here is what leaders should own before the migration becomes an emergency.

NIST's 2024 update to the Cybersecurity Framework added a sixth function, Govern, positioned above Identify, Protect, Detect, Respond, and Recover rather than alongside them. Most boards still ask their security teams to report on the other five and skip the one function that was actually written to be the board's job to own, not the CISO's.

For thirty years the IT service desk ran on the ticket. AI agents now resolve requests instead of routing them, and McKinsey documents one service desk automating up to 80 percent of requests. The organizations getting results treat this as an identity, governance, and knowledge management decision first and a technology purchase second.

Growing companies often assume scale is a number to cross. This article reframes scale as a deliberate strategy built on stability paired with speed, decisions kept close to the customer, protected employee experience, and continuous reinvention, not a milestone measured in headcount.

Every headcount conversation eventually asks how many fewer people AI will require. Wrong question. This article shows why the organizations pulling ahead are the ones orchestrating small teams to direct much larger AI-driven output, and what boards should require to get there.

Nearly every pitch deck now claims an AI advantage. This article gives private equity and venture investors a four-question diligence framework, proprietary data, operability, governance, and economics, to separate genuine AI-enabled operators from a polished demo before signing.

For a decade, infrastructure meant compute, storage, and network. Now the real constraint on scaling AI is trust. This article defines AI trust infrastructure as four layers, observability, enforcement, accountability, and transparency, and explains what boards should require before scaling any AI system further.

For thirty years the IT service desk ran on the ticket. That model is being replaced by agentic AI that resolves requests end to end instead of routing them. This article explains what makes a service desk genuinely AI-native, why it is rising now, and what executives should require before scaling it.

Most AI initiatives fail before they ever reach production, and the cause is rarely the model. This article introduces minimum operable data, the scoped, governed data foundation every AI initiative needs to run reliably, and shows executives exactly what to require of their teams before funding moves from pilot to full production scale.

As agentic AI scales across the enterprise, every autonomous agent becomes a new non-human identity with credentials someone must secure and govern. This article explains why agentic AI cybersecurity risk grows more urgent, not less, as agents gain decision authority, and what boards should ask before scaling agent deployments further across the business.

Most boards can describe their AI ambitions but cannot document their AI controls. This 2026 governance and control checklist walks directors and executives through the eight areas where oversight most often breaks down, from data readiness to human oversight, and shows what a board should be able to produce as evidence, not just discuss as policy, before the next AI decision reaches the table.

Service level agreements were built to measure uptime, not business outcomes, and that gap is now a board-level liability in the AI era. This article explains why managed services must shift from SLA compliance to business assurance: a model built on outcomes, resilience, governance, and accountability, and what CIOs and boards should demand from every managed services partner.