Thomas Godwin

Data quality is emerging as the critical gating factor separating enterprise AI projects that produce results from those that fizzle out.

Enterprises are locked in a long-term standoff with legacy infrastructure, with growing demand for virtualization modernization that doesn't require a full rebuild.

Enterprises are investing heavily in AI customer experience, but many experiments are stalling out before ever going live.

Without trusted data as the foundation, even the most sophisticated models will produce outcomes that enterprises can't act on with confidence.

The modern data stack might already be the new legacy. In response, Google Cloud is rebuilding for a world where AI agents — not humans — are the

Enterprise AI transformation has cleared the POC stage. Slalom explains how the C-suite became the fastest-moving force in the building.

The Tax Court advised a taxpayer that if he filed a second petition, he probably would not have a chance for another review of the IRS’s collection action.

The Fifth Circuit, overruling the Tax Court, held that for purposes of Sec. 1402(a)(13), “limited partner” means a partner in a limited partnership that has limited liability.

The enthusiasm for enterprise AI is outpacing strategic thinking — and process automation, not more AI tools, is the fix most organizations might be missing.

Becoming an AI-native company is no longer the competitive advantage it was five minutes ago. Now, it's an empirical obligation, and Dell Technologies Inc. made that case to customers at its annual flagship event.