Plain language for complex systems.

AI designed so access, actions, decisions, and outcomes remain governed, observable, auditable, and ultimately owned by people.

Intelligence that operates within explicit permissions, guardrails, observability, auditability, and human responsibility.

AI that can plan, use tools, and take actions within defined permissions rather than only generating a response.

Operational systems combining models, tools, data, permissions, workflows, guardrails, and human oversight to complete bounded work.

Workflows in which AI agents coordinate steps or tools while operating within explicit controls, escalation paths, and accountability.

The use of data to understand performance, identify patterns, explain outcomes, and support decisions.

A defined interface that allows applications and services to exchange data or request actions from one another.

The ability to reconstruct what happened, which data and tools were used, and who or what was responsible.

The use of software to perform repeatable work with reduced manual effort and more consistent execution.

AI limited by explicit scope, permissions, tools, constraints, and escalation paths.

Technologies and practices that turn operational data into reports, dashboards, and decision-ready information.

Applications and platforms that support essential organizational processes, data, controls, and decisions.

Technology engineered for high availability, capacity, monitoring, recovery, and strict service commitments.

On-demand computing services that provide scalable infrastructure, applications, data, and integration capabilities.

The combination of data, analytics, rules, and context to improve how decisions are made and acted upon.

Information and tools that help people make better-grounded decisions without removing human responsibility.

Automation that follows explicit rules and produces predictable results for the same inputs.

Redesigning operations, services, and decision-making through technology rather than simply replacing old tools.

AI deployed across business operations with integration, security, governance, support, and measurable organizational outcomes.

Software used across an organization to manage important processes, data, and controls.

The structure connecting business goals, processes, data, applications, infrastructure, security, and operating responsibilities.

The connectivity linking an organization’s users, locations, applications, cloud services, and data.

Automation triggered by a business event, such as a hire, transaction, or status change, rather than a manual request.

Setting direction, allocating resources, managing risk, building capable teams, and remaining accountable for organizational outcomes.

Technology implementations delivered across regions while balancing enterprise standards with local requirements and support.

Technology services designed to operate reliably across regions, locations, and time zones.

The roles, policies, controls, and decision rights that determine how technology is selected, used, changed, and reviewed.

Technical and procedural constraints that keep automated or AI-driven actions within approved boundaries.

A deliberate point where a person reviews, approves, overrides, or assumes responsibility for a system’s action.

Human interpretation and accountability applied where context, ambiguity, ethics, or consequence make rules alone insufficient.

The processes and technologies used to establish identity and control what users and systems may access or do.

Automated provisioning, updating, and removal of identities, access, licenses, and related lifecycle tasks.

Applications supporting a specific operational function such as human resources, finance, safety, or field operations.

Microsoft’s cloud identity and access service for managing users, applications, devices, authentication, and permissions.

Microsoft’s unified API for accessing and managing data and services across Microsoft 365.

The ability to understand a system’s behavior through logs, metrics, traces, events, and operational context.

The ability to continue delivering critical services through failures, disruptions, demand changes, and planned transitions.

Coordinating multiple systems, steps, rules, and dependencies as one managed process.

Microsoft’s platform for data modeling, visualization, dashboards, and business intelligence.

Microsoft’s low-code platform for building applications, workflows, analytics, websites, and AI-enabled business solutions.

AI or decision capabilities embedded in live operations with controls, monitoring, support, and accountability.

A measurable commitment defining expected availability, performance, response, or support.

Connecting applications, data, identities, and workflows so they operate as a coordinated system.

A plan aligning technology investments, architecture, risk, talent, and delivery with organizational priorities.

Data whose source, meaning, quality, ownership, and timeliness are understood well enough to support decisions and automation.

Intelligence that understands the operating context, acts within permission, remains observable in execution, and is accountable in outcome.

Voice communications carried over IP networks, allowing voice to share scalable, routable infrastructure with data.

The managed coordination of tasks, systems, decisions, and exceptions across an end-to-end process.