AI without an owner
Staff use AI tools without rules, with sensitive information and no traceability.
On-demand artificial intelligence leadership
CAIO as a Service: AI with strategy, governance and return
An external Chief AI Officer with a clear mandate, a defined monthly capacity and accountability to leadership. We bring order to how your organization adopts artificial intelligence: what to do first, how to do it safely and how to prove it pays off.
Executive outcome- AI strategy aligned with the business
- Use cases prioritized by value and risk
- Responsible and secure use policies
- Adoption and return indicators
Direct answer
What is CAIO as a Service?
It is the Chief AI Officer function engaged with flexible dedication. A senior leader takes ownership of the artificial intelligence program — strategy, governance and delivery — under a mandate agreed with senior management, a fixed monthly time budget and a clear reporting line.
In many mid-sized companies nobody owns AI: each department tries tools on its own and no one is accountable for the outcome. AI is already in your company, even if no one approved it. The question is not whether to adopt it, but whether anyone is leading it.
Clear mandateAuthority and reporting agreed with leadership
Fixed capacityDefined days of dedication every month
AccountabilityOne person owns the AI program
Why hire one
Six reasons to have a CAIO, even on demand
Pilots that never scale
Enthusiastic trials that never reach production or measurable value.
Data and confidentiality risk
Information leakage, intellectual property exposure and vendor lock-in.
Regulatory and reputational pressure
Customers, auditors and regulators are starting to ask how AI is governed.
Scarce talent
Hiring a full-time CAIO is costly and difficult in the region.
Return you must prove
The board needs to know what is invested, what is gained and what risk is taken.
What the CAIO does
Six responsibilities under one mandate
The CAIO does not hand over a report and leave: these functions are carried out continuously and answered for before leadership.
Strategy and roadmap
- AI strategy built on total cost of ownership (TCO), not just license prices
- Use cases prioritized by value, feasibility, risk and data availability
- Regular updates to the roadmap and the budget
Governance and policy
- AI policy, roles and an approval workflow for new uses
- Risk classification of each use case referencing ISO/IEC 42001, NIST AI RMF and, where the organization does business in Europe, the EU AI Act
- Alignment with data protection and information security (ISO/IEC 27001)
Vendors and architecture
- Evaluation of models, tools and vendors against explicit, comparable criteria
- Architecture decisions: integration, data, hosting and usage costs
- Control of lock-in, confidentiality and vendor continuity risks
Delivery leadership
- Coordination of internal teams, partners and external vendors
- Milestones, KPIs and a business case for every initiative
- Regular reporting to management and the board
Capability building
- Training plan by audience: leadership, managers and teams
- A network of internal champions who drive adoption
- AI literacy and rules for responsible use
Market watch
- Assessment of relevant new models and features
- Tracking of vendor pricing and terms
- Regulatory changes translated into concrete company decisions
Methodology
Five phases from curiosity to value
An iterative cycle: every phase produces concrete deliverables and clear decisions.
01
Discover
Data and process maturity, current AI use (including unapproved), objectives and constraints.
→ AI maturity assessment
02
Prioritize
A portfolio of use cases scored by value, feasibility, risk and data availability.
→ Use-case map and roadmap
03
Govern
Acceptable use policy, roles, AI committee, risk, privacy and security controls.
→ AI governance framework
04
Pilot
Bounded pilots with success metrics, evaluated vendors and exit criteria.
→ Measured pilots and scale decision
05
Scale
Operational adoption, training, change management and indicator tracking.
→ Value dashboard and continuous improvement
Engagement models
Dedication that fits where you are
The service runs on a fixed monthly capacity, expressed in days of dedication agreed in the proposal, with scheduled sessions (on site or remote) and availability between sessions for time-sensitive decisions.
Interim
Interim CAIO: build it, then hand it over
For organizations planning to hire their own head of AI. The CAIO builds the function — strategy, governance, team and first initiatives — and hands it over in an orderly way when the internal hire arrives.
- Useful when it is not yet clear what profile to hire
- The program moves forward while recruitment runs
- Documented handover and initial support for the new leader
Illustrative: shows the shape of the engagement, not figures from a real case.
Ongoing
Ongoing CAIO: part-time AI leadership
A permanent part-time role embedded in the leadership team. The right fit when the organization needs senior AI leadership on a sustained basis but cannot yet justify a full-time position.
- A seat on the leadership or AI committee
- Regular review of the portfolio, risks and vendors
- A stable, predictable budget
Illustrative: shows the shape of the engagement, not figures from a real case.
Project-based
Project-based CAIO: one transformation, start to finish
Ownership of a defined transformation initiative — for example, bringing AI into customer service or an operational process — with agreed scope, timeline and deliverables.
- A concrete, measurable objective from day one
- Coordination of vendors and teams throughout the initiative
- Close-out with results, lessons learned and next steps
Illustrative: shows the shape of the engagement, not figures from a real case.
Accountability, not just advice
How it differs from traditional consulting
Consulting delivers recommendations. CAIO as a Service takes responsibility for getting them done.
Mandate
Authority and reporting line defined in writing and agreed with senior management and any internal bodies that need to be involved.
KPIs
Progress is measured against each use case's KPIs and business case, not hours or activity.
Handover
Structures, documentation and policies stay with the company. If an internal role is created, the handover is planned from the start.
| Aspect | Traditional consulting | CAIO as a Service |
|---|---|---|
| Role | Advises and recommends | Leads and is accountable for the outcome |
| Horizon | A project with an end date | Ongoing, interim or project-based function, with handover |
| Measurement | Deliverables and hours | Business KPIs per use case |
| Vendors | May be tied to one technology | Independent evaluation based on your needs |
| Knowledge | Stays in the report | Stays in your policies, processes and people |
| Cost | Varies project by project | Fixed, predictable monthly capacity |
Getting started
Four steps to set up the function
Before entering the working cycle, we agree on the mandate and the baseline.
01
Conversation and scope
Objectives, scope, reporting line and monthly capacity are agreed with leadership.
→ Agreed mandate
02
Initial inventory
Review of current AI use, use-case discovery and a readiness assessment across data, processes and people.
→ AI baseline
03
Strategy and governance
The AI strategy, roadmap and policy are defined and approved.
→ Approved strategy and policy
04
Regular operation
Delivery leadership, reviews, reporting to leadership and, where applicable, handover to an internal leader.
→ Regular reporting and handover
What your organization gains
Senior AI leadership without paying for the learning curve
Applied experience
Our leadership's 30+ years in IT governance, technology risk and cybersecurity, applied to AI adoption.
Vendor independence
Models and tools are compared against explicit criteria, based on your needs rather than a brand.
One accountable owner
One person answers to leadership for the AI program.
Predictable costs
A fixed monthly capacity, with no open-ended hours or invoice surprises.
No hiring commitment
Senior leadership today, without creating a full-time position yet.
Structured handover
If you later hire an internal CAIO, they inherit a function that is already organized.
CISO + CAIO: AI secure by design
When cybersecurity leadership and AI leadership work together, innovation moves forward without opening gaps. LandoHOUSE can combine both services under a single governance model.
Clear boundaries
What the service does, and what it does not promise
Included
- Strategic leadership and governance of the AI program under an agreed mandate
- Assessment of use cases, vendors, architecture and risks
- Design of policies, committees, approval workflows and indicators
- Leadership of pilots, delivery and adoption
- Regular reporting to management and the board
Outside base scope
- Replacing leadership: business model and investment decisions remain with senior management
- Acting as a development team: building is done by your teams, partners or vendors under the CAIO's direction
- Legal advice: legal matters are handled by your lawyers
- Guarantee of specific financial results
- ISO/IEC 42001 certification (granted by an accredited body)
FAQ
Before hiring a CAIO
What does a Chief AI Officer do?
Leads the organization's artificial intelligence strategy: prioritizes initiatives, sets governance and controls, coordinates departments and vendors, and measures the value obtained.
How is it different from an AI consultant or a technology vendor?
A vendor sells or implements a tool; a consultant solves a project. CAIO as a Service leads the entire program, under an agreed mandate, independent from vendors and accountable to leadership.
What engagement models do you offer?
Three: interim (builds the function and hands it over to an internal leader), ongoing (a permanent part-time role) and project-based (ownership of a defined transformation). All three run on a fixed monthly capacity.
Does the CAIO build the AI solutions?
No. The CAIO leads, prioritizes and oversees. Building is done by your teams, specialized partners or external vendors under the CAIO's coordination.
What happens if we later hire an internal CAIO?
It is planned from the start: policies, documentation, indicators and decisions stay with the company, and the handover is supported so the function does not start from zero.
Is my company too small for this?
Not necessarily. If your teams already use AI or you plan to invest in it, on-demand leadership prevents scattered risk and spending with proportional dedication.
Which frameworks do you use?
Mainly ISO/IEC 42001 (AI management systems) and the NIST AI Risk Management Framework, complemented by ISO/IEC 27001 for information security, the EU AI Act where the organization does business in Europe, and applicable legal requirements.
How long until we see results?
The first deliverables (assessment, use policy and prioritized cases) arrive in the early stages; pilot value depends on each case and is measured with agreed indicators.
How is our information protected?
Through confidentiality agreements, least-privilege access and the rule of not entering sensitive information into unapproved tools. AI vendor assessment is part of the service.
How much does it cost?
It depends on the monthly capacity, maturity and scope. Because the capacity is fixed, the cost is predictable. We quote after a free diagnostic conversation.
Contact
Let's talk about your artificial intelligence strategy
Tell us what you want to achieve with AI, what you already use and what concerns you. We will reply with a proposal for first steps.
Emaillando@landohouse.com
WhatsApp+502 4211 3673
Online bookingcalendly.com/landohouse
CoverageGuatemala and Central America · remote, hybrid or on-site