C suite solutions. Technology, data and AI
AI for Technology, Data and AI
AI runs on six teams. It breaks between them.
Data prepares it, the platform hosts it, engineering builds it, IT runs it, security protects it and the Chief AI Office answers for it. Each team does its part well. Most AI still stalls in the gaps. We look at the whole estate, find where AI gets stuck between offices, and put agents exactly there.
The short answer
It takes on the volume work across the technology estate. Agents resolve service desk tickets, fix data quality issues, write tests and review code, triage security alerts, track licence and cloud use and keep a live register of every AI agent in the company.
The bigger gain shows up between teams. When data, platform, engineering, IT and security work from one registry and one set of controls, AI moves from pilot to production faster and stays safe once it’s there. Leadership gets one view of the estate instead of six.
The tension
Everyone in this group wants technology to move the business forward. But each office is measured on a different number, and AI touches all of them at once.
CIO Office
Uptime and IT cost
Does everything run, at the right cost?
Chief AI Office
AI value in production
Is AI paying back, safely?
Data Office
Data quality and access
Can people and agents trust the data?
Digital Office
Digital adoption and revenue
Do customers use and buy online?
CTO Office
Delivery speed
How fast do we ship, and how safely?
CISO Office
Risk and incidents
Are we protected, and ready if not?
Engineering wants speed and security wants control. IT wants one platform and the business wants every new tool. Each number can look healthy while AI still sits stuck between teams.
The AI delivery relay
This is how AI really moves from idea to value in a company. Watch the handoffs. That’s where pilots stall, costs creep and risk slips through.
Leg 1
Data
Data Office
Leg 2
Platform
CIO and Chief AI Offices
Leg 3
Build
CTO and Digital Offices
Leg 4
Deploy
Chief AI and CTO Offices
Leg 5
Run
CIO Office
Leg 6
Secure
CISO Office
Handoff 1
Data that isn’t ready
The use case is approved. The data is incomplete, unlabelled or locked away.
Agent. Profiles, fixes and documents data and extracts what sits in documents.
Handoff 2
Every team builds its own stack
Agent. Discovers every model, agent and AI tool in use and adds it to one registry.
Handoff 3
Pilots that never ship
The demo works. Security, cost and controls get checked at the very end.
Agent. Checks data, security, cost and controls from the first sprint.
Handoff 4
Agents nobody watches
In production, quality drifts and cost grows quietly.
Agent. Monitors quality, cost and drift for every agent and routes tasks to the right model.
Handoff 5
A new attack surface
Agents with broad access, prompt injection and deepfake fraud.
Agent. Sets permissions per agent, tests for attacks and triages alerts.
The loop nobody closes. Value nobody measures.
Once an agent is live, nobody tracks what it’s worth to the business, so the next budget round starts from opinion. Agent. Value tracking agents link every agent’s use to the business KPI it was meant to move and report it to the CFO and the board.
Inside each office
Each office has its own canvas. Here’s the short version of each, with the three value leaks we’d look at first. The full canvas covers what the office runs and governs, its processes and its control tower.
Chief Information Officer
CIO Office
Run reliable, cost efficient technology and one platform the company builds AI on.
Office page live
Explore the CIO Office →
Where value leaks
Agent sprawl
One registry, platform and set of controls for every agent
Licence and cloud waste
Use tracked against entitlement and commitment
Service desk volume
Routine tickets resolved end to end by agents
Measured on
Availability, IT cost as a share of revenue, projects on time and AI adoption.
Control tower
Availability
Run against change spend
Agents in production
Ticket deflection
Chief AI Officer
Chief AI Office
Turn data and AI into enterprise value, safely, on one platform.
Office page live
Explore the Chief AI Office →
Where value leaks
Pilots that never scale
Validation First pilots on one governed platform
Unmanaged model cost
A decision layer routes each task to the right size of model
Value not measured
Value tracking tied to finance from day one
Measured on
EBIT impact from AI, use cases in production, governance coverage and cost per task.
Control tower
Use cases by stage
Value realised
Cost per AI task
Agents by risk tier
Chief Data Officer
Data Office
Make data trusted, findable and ready for people and agents.
Office page live
Explore the Data Office →
Where value leaks
Data not ready for AI
Quality agents profile, fix and document data
Knowledge locked in documents
Unstructured data extracted and linked
Nobody can find the data
Catalogue agents describe and tag every data set
Measured on
Data quality, time to data, data product adoption and data incidents.
Control tower
Data quality score
Time to data
Data products in use
Chief Digital Officer
Digital Office
Grow digital channels, digital revenue and how customers use them.
Office page live
Explore the Digital Office →
Where value leaks
Journeys that drop customers
Journey agents find and fix where people give up
Digital conversion that stalls
Agents test and personalise every step
One experience for everyone
Personalisation at scale across web and app
Measured on
Digital revenue share, conversion, active users and digital cost to serve.
Control tower
Digital conversion
Active users
Journey drop off
Chief Technology Officer
CTO Office
Build the products and platforms customers use, fast and safely.
Office page live
Explore the CTO Office →
Where value leaks
Slow delivery from handoffs
Requirement, coding, test and review agents beside engineers
Testing bottleneck
Test generation and regression agents
Growing technical debt
Code analysis and modernisation agents
Measured on
Deployment frequency, lead time, change failure rate and time to restore.
Control tower
DORA metrics
AI assisted delivery
Escaped defects
Chief Information Security Officer
CISO Office
Protect people, systems and agents, and keep the business running if an attack lands.
Office page live
Explore the CISO Office →
Where value leaks
Alert fatigue
Triage agents enrich, group and rank alerts first
Deepfake and impersonation fraud
Detection on calls, video and media
Over privileged agents
Permissions and run time policy for every agent
Measured on
Time to detect and respond, critical vulnerabilities and NIS2, DORA and ISO 27001 compliance.
Control tower
Time to respond
Critical vulnerabilities
Privileged access
Agents that work across offices
The biggest wins in this group come from shared foundations that every office uses, so AI moves from idea to production on one path.
CIO
Chief AI
CISO
One agent registry
Every model and agent with owner, purpose, data, risk tier and controls, kept live as things change.
Data
Chief AI
Digital
One governed data layer
Trusted, documented data that people and agents can find and use within the rules.
Chief AI
CIO
CTO
Model cost routing
Each task sent to the right size of model, with cost and quality tracked per agent.
All six
A technology and AI control tower
One set of numbers for the whole estate, with alerts at the handoffs before they turn into incidents.
All of this runs on one enterprise AI platform, Cortex, which plugs into your cloud, data platforms, core systems and security tools. Every office builds on the same foundation and the same controls.
What leadership would open on Monday
Illustrative
Technology and AI control tower
Sample data to show the view. Not client results.
Agents live
42
▲ 9 this quarter
CIO and Chief AI
Value from AI
€6.8m
of €12m plan
Chief AI Office
Cost per AI task
€0.03
▼ 38%
Chief AI Office
Data quality
87%
▲ 6 pts
Data Office
Availability
99.94%
No P1 this month
CIO Office
Critical vulns
23
▲ 5 this week
CISO Office
Idea
23
Pilot
11
Production
6
Scaled
3
Handoff alerts this week
Two approved use cases blocked on missing customer data fields
Handoff 1. Data to platform
Seven AI tools found in use outside the registry
Handoff 2. Platform to build
Claims agent accuracy down 4 points since the last model update
Handoff 4. Deploy to run
Three agents with write access they haven’t used in 60 days
Handoff 5. Run to secure
Illustrative example. Figures are invented to show how the view works. In discovery we build it on your own data and KPIs.
Your industry changes the estate
The relay is the same everywhere. Where AI gets stuck is not. Here’s where the estate is hardest in the industries we work in, and the handoff we’d look at first.
CPG
Retailer, distributor and market data in many formats
Data to platform
Data quality and extraction agents for partner data
FMCG
Many ERPs across markets after acquisitions
Platform to build
An agent layer over core systems through APIs
Retail
Store, online and supply systems that don’t talk
Data to platform
One governed product and customer data layer
D2C
A fast growing stack of SaaS tools
Platform to build
Licence use tracking and tool consolidation
Automotive
Vehicle software, plants and dealer systems
Build to deploy
Test generation and release readiness agents
Healthcare
Sensitive data and strict validation rules
Deploy to run
Agent monitoring with full audit trails
Energy
Operational technology next to IT
Run to secure
Alert triage across IT and OT
Manufacturing
Legacy plant systems and machine data
Data to platform
Machine data extraction and legacy code analysis
Logistics
Partner integrations and documents at volume
Data to platform
Document and EDI extraction agents
BFSI
Core systems, DORA and model risk rules
Build to deploy
AI registry and model risk controls
B2B technology
Engineering speed against growing technical debt
Build to deploy
Agentic delivery and code modernisation
The rules are changing
EU AI Act
High risk obligations for Annex III systems apply, under the Digital Omnibus
Regulation 2026/1744, in force since 27 July 2026
EU AI Act
Obligations for high risk AI in products covered by Annex I apply
Regulation 2026/1744
Already in force
Operational resilience, third party and incident reporting rules that now cover AI suppliers too
Financial services and critical sectors
Your intervention map
Bring your technology leaders and the AI use case that has been stuck the longest. We bring the canvases. In one session we map your relay and mark where agents and shared foundations would pay back first.
01
Your office canvases
The offices in your technology estate, mapped to how your teams really work.
02
Your value chain
Your relay placed on your industry and company, with the platforms and systems behind each leg.
03
Your intervention points
Each handoff leak with an agent design, its controls and the KPI it moves. Delivered as a mind map, an architecture view or an interactive dashboard.
AI for technology, data and AI, answered
What can AI do for technology, data and AI teams?
Agentic AI takes on the volume work across the technology estate. Agents resolve service desk tickets, fix data quality issues, write tests and review code, triage security alerts, track licence and cloud use and keep a live register of every AI agent in the company. Technology leaders get one view of the estate instead of six separate reports.
How do you stop agent sprawl and shadow AI?
With one registry, one platform and one set of controls. Discovery agents find the models, agents and AI tools already in use, record owner, purpose, data and risk tier for each, and flag anything running outside the rules. New agents are built on the shared platform from day one.
Why do so many AI pilots fail to reach production?
MIT’s NANDA study found that 95% of generative AI pilots showed no measurable impact on profit and loss. The usual causes sit between teams. Data that isn’t ready, no shared platform, security reviews at the end and no owner for the value. Fixing those handoffs matters more than picking a better model.
How do you control the cost of running AI models?
By routing each task to the right size of model and watching cost per task. A decision layer sends simple work to small, cheap models and keeps large models for the tasks that need them. Monitoring agents track cost, quality and drift for every agent in production.
What does the EU AI Act mean for technology leaders?
It means knowing every AI system you run, its risk tier and its controls. Under the Digital Omnibus, obligations for high risk systems in Annex III apply from 2 December 2027 and for Annex I from 2 August 2028. A live AI register and logged agent actions make compliance a by product of how you work.
Does this work with our cloud and data stack?
Yes. Agents work across Microsoft Azure, AWS, Google Cloud, Databricks, Snowflake, ServiceNow, your ERP and core systems, connecting through APIs and the Model Context Protocol. Nothing needs replacing to start.
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