Liquid World: The Living Operating System

Welcome to the era where business is designed in both atoms and algorithms. In the Liquid World, AI doesn’t just assist—it anticipates, simulates, and acts, turning insight into execution at speed. This global report spotlights five macrotrends redefining how enterprises build, decide, test, and evolve—so you can move from digital ambition to measurable impact, with learning embedded in every process.

Agentic AI: from Copilots to Autopilot

Agentic AI moves beyond copilots into an autonomous layer of agents that plan, coordinate, and execute full chains of work. Connected to enterprise systems, agents prioritize leads, generate proposals, reconfigure supply chains, and resolve incidents end to end—within explicit objectives, constraints, and supervision. The payoff is operational elasticity: siloed functions behave like one system, learning from every executed cycle.

AI-First by Design: systems that learn

AI-First by Design rewrites software’s grammar: systems are built to learn from every interaction. Work becomes a live loop of intent, decision, action, verification, and learning, where models and rules recombine in real time. Products stop being static releases and become living systems that adapt and evolve—while people focus on designing learning cycles, supervising performance, and setting ethical boundaries.

Decisioning 2.0: Next Best Action, everywhere

Decisioning 2.0 replaces report-driven governance with a real-time “brain.” A centralized decision platform listens to streaming events, assembles context, generates options, and selects the Next Best Action based on propensity, risk, and cost—then executes and learns from outcomes. Governance upgrades too: policies become versioned code, decisions leave auditable traces, and safe rollbacks keep autonomy under control across every touchpoint.

Synthetic Users: the truth before production

Synthetic Users are “cognitive twins” of customers—generative agents that navigate journeys, hesitate, abandon, and react like real people. Powered by synthetic data and GenAI intent modeling, they let teams rehearse interfaces, pricing, and policies at scale before touching production. The result is truth before launch: faster learning, fewer failures, and innovation that accelerates without turning customers into test subjects.

ExperimentOS: when the Roadmap becomes a Lab

ExperimentOS turns experimentation from pilots into the operating system. Strategy, operations, and technology share a common language of hypotheses, tests, metrics, and decisions. Every change—pricing, journeys, models, supply chains—runs in bounded segments with success criteria and rollback capability, powered by feature flags and telemetry. AI prioritizes what to test, designs variants, and interprets results—so learning becomes continuous.