BEIJING, Jan. 1, 2026 /PRNewswire/ -- As enterprise AI shifts from experimentation to execution, ORIGINAL GALAXY (OG Tech) is tackling the "last mile" of integration. The global AI integrator today hosted the inaugural OG War Room (WR#01), an elite roundtable focused on moving AI from isolated pilots into core enterprise decision-making systems.

Rejecting traditional conference fluff, OG Tech framed the War Room as a signal-discovery exercise for frontline operators. The session prioritized "execution-grade" insights, identifying where AI breaks when facing real-world constraints like data readiness, governance, and organizational accountability.

The Shift: From Tools to Systems A key takeaway from the session: AI adoption stalls when treated as a standalone product. To drive value, AI must evolve into a system-level "brain" capable of autonomous participation in workflows. OG Tech argues that the next phase of the market will be defined by three pillars:

Actionability: Decisions must be executable within real operational loops.

Traceability: Audit trails must exist across long decision chains.

Accountability: Systems must remain governed at an organizational scale.

Product Roadmap: Global AI Decision & Action Center OG Tech also reaffirmed its roadmap to launch a Global AI Decision & Action Center in Q1 2026.

Designed as an "Enterprise Second Brain," the platform moves beyond advisory chatbots. It is architected as a closed-loop execution layer—embedded within core workflows and constrained by enterprise-grade controls—to connect insight directly to action.

About OG Tech ORIGINAL GALAXY (OG Tech) is a leading integrated AI services provider. From strategic advisory to technical implementation, OG Tech builds system-level AI architecture for retail, logistics, and automotive leaders, guiding them through full-scale intelligent transformation.

About OG War Room The OG War Room is an ongoing, operator-focused forum dedicated to a single mission: making AI executable within real enterprise workflows. It cuts through industry noise to elevate the signals that matter for scaling AI systems.