For the CIO
Sovereign intelligence for the CIO
Build one controlled environment for enterprise AI.
The CIO owns the technology estate, and AI has quietly added a second, unmanaged estate: team-level subscriptions, embedded copilots, homegrown scripts and agents with their own credentials. The job is to turn that sprawl into one environment with consistent identity, data access, spend and audit. This page lists what to worry about and what to ask vendors.
What a CIO worries about
Shadow AI across the business
Teams adopt tools faster than IT can review them. Sensitive documents end up in services nobody inventoried, and there is no single place to see which models and agents are in use. See the AI estate.
Tool sprawl and duplicated spend
Several teams pay for overlapping assistants, vector databases and model APIs. Without shared routing, budgets and usage reporting, cost grows without a view of value.
Integration that breaks permissions
Connecting AI to document stores and business systems is easy. Connecting it so that each answer respects the asker's permissions is the hard part, and the part that fails audits.
Operating AI like any other production service
Models change, providers have outages and prompts drift. Someone must own monitoring, incident response, versioning and rollback for AI the way they do for applications.
Vendor concentration
Standardising on one hosted assistant simplifies today and concentrates risk tomorrow. The CIO needs a plan for substitution before the contract is signed.
What a Sovereign Intelligence Platform gives you
A single control point across the estate
The trust and governance fabric runs through all six layers, so identity, policy, audit and monitoring apply to every model, agent and workflow in the same way.
Deployment where you decide
The infrastructure layer is designed for cloud, private cloud, on-premise and hybrid deployment, with dedicated deployments scoped per engagement.
Model choice with routing and failover
The models layer is built around a gateway so approved models can be routed, swapped and tracked for cost without rewriting applications.
Context that respects existing permissions
The data and context layer is designed so retrieval inherits access controls from the source systems rather than flattening them into a shared index.
A path from pilot to operations
The guide walks through ten steps from requirements to operating and learning, so a pilot has a defined route to production.
Capabilities are described as what the platform is designed to let you do. For what is true today and what is not claimed, see the trust centre.
Questions to ask any vendor
Use this as a checklist in any evaluation, ours included. Each question comes with what a good answer looks like.
01How does the platform inherit our identity provider, groups and provisioning?
A good answer: Single sign-on and group mapping with a documented provisioning and deprovisioning path. If SCIM or SAML are not yet available, the vendor says so and gives a date.
02Does retrieval respect source-system permissions at query time?
A good answer: Yes, demonstrated with two test accounts where one must not see a document the other can. A shared index with post-filtering only is a warning sign.
03Can we deploy in our own cloud account, a private environment or on-premise, and which parts remain with the vendor?
A good answer: A clear matrix of deployment options, what runs where, what telemetry leaves the boundary and what the vendor can access.
04How do we see every model, agent and tool connection in use, including those teams created themselves?
A good answer: An inventory generated from the platform itself, with owners and risk levels, exportable through an API.
05Which models can we use, can we bring our own, and what does switching cost?
A good answer: A list of supported providers and open-weight options, a bring-your-own-model route and routing rules we control.
06What observability do you provide, and does it export in open formats?
A good answer: Traces, tool calls, cost and policy decisions, exportable to our existing monitoring stack. Open conventions are still maturing, so ask which version is used.
07How do spend controls work at team, project and agent level?
A good answer: Budgets, alerts and hard caps per scope, with usage attributed to a named owner.
08How does the platform support our architecture review and change advisory process?
A good answer: Documented architecture, data-flow diagrams and dependency lists, plus change notices and release notes that map to our review cycle, so AI components are reviewed like any other production service.
09What is your change process when a model is updated or retired?
A good answer: Version pinning, advance notice, evaluation against our own test sets and a rollback route.
10Which of your sub-processors and infrastructure providers does our data touch?
A good answer: A current list with locations and purposes, and notice of changes. See also our own sub-processor page as an example of the format to expect.
11What does a migration away from you look like, in time and in formats?
A good answer: Documented export of data, configuration, workflows and logs, plus cooperation obligations. For cloud services in the EU, switching rules under the Data Act (opens in a new tab) set a minimum.
12How do you handle an incident involving an AI agent, and who gets paged?
A good answer: A runbook with a kill switch per agent, an escalation path and access to the full action trace.
Recommended reading
Frequently asked questions
Should the CIO consolidate on one AI vendor?
Consolidate on one controlled environment, not necessarily one model supplier. A gateway and shared governance let you use several models under one set of rules.
Where do we start with shadow AI?
Start by inventorying what exists: models, agents, data flows and owners. Then offer an approved route that is easier to use than the workaround.
Does the CIO need on-premise AI?
Not always. Match the deployment option to data classification and regulatory exposure. Many workloads suit a hosted model with strict policy; some need dedicated or on-premise infrastructure.
Build with control: for the CIO
Start with one entry point. Add intelligence, agents, workflows and infrastructure as you prove value. Or read the step-by-step build guide and take the readiness assessment.