01Users & channels
AI activity
Employees reach approved and unapproved AI through several technical routes.
- Web and desktop AI tools
- Enterprise AI workspaces
- Embedded productivity AI
- Internal apps using model APIs
Independent professional portfolio
AI workbench.
Practical demonstrations of how I connect AI opportunity, governance, enablement and operational control. Every scenario and data point is fictional.
← Return to professional profileCASE / 01
AI Tooling Control Centre
A management concept for seeing where licences, adoption, cost and governance need attention—without reducing AI value to a usage count.
286Allocated licences
72%Monthly active
£18.4kQuarterly cost
14Actions open
AI tool portfolio
Licence, adoption, cost and action signalsTool / workflowUsageAdoptionSignalAction
Knowledge assistant118 / 14084%£6.2kHealthy
Meeting intelligence64 / 8278%£4.9kWatch cost
Writing copilot31 / 4865%£3.1kEnable
Research workspace12 / 1675%£2.4kReview risk
Automation studio0 / 0Pilot£1.8kControlled
Healthy / on trackAttention / enableDecision / risk
Colour is always paired with a written status.
Corporate deployment reference
How the Control Centre gets its evidence.
A practical, vendor-neutral architecture for connecting network, identity, SaaS administration, finance and business evidence to a governed dashboard. It starts read-only and complements the company's existing platforms.
Company-managed network and cloud boundaryEncrypted transportRead-only collectionLeast-privilege identities
02Evidence sources
Corporate telemetry
Different systems contribute different parts of the usage and ownership picture.
- SWG, firewall, DNS or CASB logs
- Vendor admin reports & APIs
- Identity, SSO and SCIM groups
- AI gateway, ITSM and finance data
03Collection plane
Secure ingestion
A small integration service collects approved fields without changing source systems.
- REST or Graph API collectors
- Syslog, Logpush or SIEM query
- Scheduled CSV or database extract
- Service accounts and secrets vault
04Data & rules
Analytics backend
A governed data layer joins evidence and turns it into traceable metrics.
- Raw landing area and history
- Curated SQL or warehouse model
- Tool, user and owner mappings
- Threshold, cost and control rules
05Decision layer
Control Centre
Role-based views surface signals, exceptions and accountable actions.
- Portfolio, adoption and cost views
- Alerts and decision queue
- Scheduled management reports
- Monitoring and improvement backlog
Security and operational guardrailsRole-based accessData minimisationAudit trailRetentionHuman reviewChange control
Signal-to-answer contract
What can tell us “who used what—and for which task?”
No single technical source answers the full question. The Control Centre joins several evidence types and preserves their limitations instead of presenting assumptions as facts.
Evidence source
Can establish
Cannot establish alone
Network / SWG / CASB
Tool or domain, user or device, time, requests and data volume
The exact business task or prompt meaning
Vendor admin analytics
Seats, active users, feature activity and platform-provided usage measures
Cross-tool activity that the vendor cannot see
Enterprise AI / API gateway
Calling application, model, tokens, cost, policy and declared use case
AI activity that bypasses the governed gateway
Identity / SSO / SCIM
User, group, department mapping, access and sign-in evidence
Whether access produced useful business value
Use-case registry & feedback
Approved task, owner, purpose, risk class, outcome and value evidence
Complete coverage without accountable user participation
Task insight without surveillance
Prefer vendor-supplied aggregate task categories, declared use-case tags in governed applications, workflow metadata, approved surveys and outcome evidence. Network traffic identifies the service—not the meaning of an employee's work—and prompt content should not be collected by default.
Hands-on contribution
What I can handle behind the dashboard.
Start with the management decisions, inventory the available evidence, design a minimum data model, configure safe connections, test the calculations and establish an operational support model. The exact products would follow the organisation's approved technology landscape.
- Map network and SaaS evidence
- Configure read-only API collectors
- Design the SQL data model
- Build and test metric rules
- Secure identities, secrets and access
- Monitor refreshes and exceptions
- Reconcile licences, usage and cost
- Document support and runbooks
Cross-functional delivery
A system assembled with the right owners—not around them.
Network & security
Expose SWG, firewall, DNS, CASB or SIEM data and agree safe logging boundaries.
Identity & workplace
Provide SSO, SCIM, licence and organisational mappings using least-privilege access.
Data & platform
Host collectors, storage, orchestration, data quality and the supported analytics model.
Procurement & FinOps
Reconcile contracts, seats, invoices, unit rates, renewals and accountable cost owners.
Risk, privacy & legal
Approve purpose, minimisation, retention, access, classification and monitoring controls.
Business & AI owners
Define the task taxonomy, validate meaning, own actions and measure realised value.
Practical starting point
- Define decisions.Agree the questions, owners, privacy boundary and minimum measures.
- Pilot evidence.Connect one AI workspace, identity groups, network discovery and cost data.
- Build the backend.Run scheduled collectors into a governed SQL database or warehouse.
- Prove the signals.Reconcile samples with vendors, users, licences and finance before reporting.
- Operationalise.Add monitoring, access reviews, exception handling, runbooks and a review cadence.
Reference design only. The sources, integrations, processing logic and controls shown here are fictional and illustrate a configurable approach—not a deployed employer solution. Actual monitoring would require security, privacy, legal and workforce approvals.
Design principles
Visibility that drives decisions.
The dashboard deliberately combines quantitative and qualitative signals. A red or amber state is not a verdict; it is a prompt for accountable review.
Decision first
Every metric should lead to an accountable question, action or owner.
Signals in context
Licence data means little without adoption, cost, risk and business-demand context.
Colour plus language
Traffic lights accelerate scanning, but written statuses preserve meaning and accessibility.
Drill with purpose
Move from portfolio to function or workflow only when a decision requires deeper evidence.
Demonstration boundary
This is an independently created portfolio model using invented tools, figures and thresholds. It does not reproduce any employer dashboard, internal reporting logic, cost data or confidential control.
CASE / 02
Use-case Decision Gate
A lightweight way to stop exciting ideas from bypassing value, risk and operational questions. Scores create structure; accountable judgement still makes the decision.
Use case
Value
Feasible
Data fit
Oversight
Ready
Gate
Knowledge search assistant
5/5
4/5
4/5
3/5
4/5
Pilot
Automated people decisions
4/5
2/5
1/5
1/5
2/5
Stop
Meeting action capture
3/5
5/5
4/5
4/5
4/5
Approve
Public research synthesis
3/5
4/5
3/5
3/5
3/5
Assess
How I would use it
Facilitate a cross-functional conversation, record assumptions and conditions, identify missing owners, and decide whether to approve, assess further, redesign or stop. The score never replaces governance.
CASE / 03
Pilot-to-BAU Readiness
A pilot proves that something can work. Operational readiness determines whether it can become a dependable, accountable and supportable part of normal business activity.
01CHECKPOINT
Ownership & support
A named business owner, service owner and route for user help.
- Accountable owner
- Support boundary
- Escalation path
02CHECKPOINT
Risk & control
Approved use, data boundaries, human oversight and exception handling.
- Risk decision
- Control evidence
- Incident route
03CHECKPOINT
People & adoption
Role-based guidance, enablement, communications and feedback.
- User guidance
- Training plan
- Adoption measure
04CHECKPOINT
Performance & value
A baseline, target, cost view and review cadence that can drive action.
- Success measure
- Cost owner
- Review rhythm
05CHECKPOINT
Technology & supplier
Dependencies, resilience, change, service levels and exit considerations.
- Supplier owner
- Continuity plan
- Exit route
06CHECKPOINT
Knowledge & transition
Runbooks, handover evidence, known limitations and lessons learned.
- BAU handover
- Known issues
- Improvement backlog
MODEL / 04
One connected operating rhythm
Discover → Assess → Approve → Pilot → Enable → Transition → Monitor → Improve. The value lies in the handoffs and feedback loops—not the labels alone.
Discover
Frame the opportunity
Assess
Test value, feasibility and risk
Approve
Create accountable permission
Pilot
Learn inside a safe boundary
Enable
Build capability and confidence
Transition
Establish the operational landing
Monitor
Keep value and risk visible
Improve
Convert evidence into action
Continue the conversation