By Tiago Ferreira, Founder of Elevida
I work as a fractional Chief AI Officer, mostly with healthcare organizations.
Most AI leadership focuses on the technology. I focus on the people side, because that is where almost every adoption stalls.
Book a 30-minute discovery callWant to baseline your team first? Start with the $997 AI Readiness Snapshot.
Master's in Cyberpsychology and Digital Transformation Leadership. Background across U.S. Government, healthcare startups, and enterprise change work. Practice runs from Tampa Bay, Florida, with clients across the United States.
Most fractional AI executives come out of engineering, product, or CTO backgrounds. Tool selection sits at the top of the scope. Change management lands somewhere around item four or five. The order is upside down.
"The technology rarely fails. What stalls is the people-readiness gap that nobody is leading."
I run the same engagement in the opposite order. The human infrastructure is the strategy. Technology decisions still get made, and they get made well, but they serve the people side rather than the other way around.
The work translates to insurance, financial services, and other regulated industries where adoption is the actual bottleneck. Most of the practice runs in healthcare because that is where the people-side gap is widest right now.
When this fits
Most leaders find their way here at one of these moments.
-
AI tools are deployed and adoption is uneven. Some teams are using what was rolled out, others are not, and the gap is widening rather than closing.
-
Multiple pilots are running with no shared strategy. Different departments are doing their own thing, vendors are talking past each other, and there is no single place where the picture comes together.
-
Leadership feels real pressure to have an AI strategy. The board is asking. Investors are asking. Internally, no one has clear ownership of the answer.
-
Early adopters are starting to burn out. The same handful of people are doing all the experimentation, demos, and explaining, while everyone else is waiting for permission or clarity.
-
Governance has become a board-level question. Policies, vendor risk, ethics, accountability. There is no clear owner and no clear cadence for reporting upward.
Human infrastructure as the strategy
Most CAIOs build a tool stack and then try to retrofit the people around it. I build a people-readiness foundation first and let the tool decisions follow. The four areas to the right are the load-bearing parts of that foundation. They are the work that sits underneath any successful AI rollout, regardless of vendor or model. When they are weak, even the best technology stalls. When they are strong, the technology lands quickly and stays.
Psychological safety
Whether people feel safe to experiment, ask questions, and admit when something is not working.
Workforce readiness
Confidence and identity, not just skills training. Whether people see themselves as the kind of professionals who use AI well.
Adoption design
How AI gets built into daily workflows in ways people sustain past the initial rollout.
Governance with a human lens
Policies that protect people first and data second. Clinical safety, dignity, equity, and accountability built into the framework.
What is included
A 12-month minimum engagement, three to four days a month embedded with your leadership team.
AI readiness assessment
The diagnostic that anchors everything else. Builds on the Snapshot methodology, with deeper team-level signal and pillar scoring you can defend in front of a board.
Strategy and roadmap
An AI vision aligned to the business goals you actually have, with a phased plan that respects how fast your organization can move rather than how fast a vendor wants you to.
Governance framework
AI policies, ethical guidelines, vendor risk framework, and the compliance scaffolding (HIPAA-aware for healthcare) the board will look for. Built once, maintained on a cadence.
Adoption and enablement
Workforce readiness programming, psychological safety infrastructure, and the change-management work that keeps adoption from flat-lining at a fraction of the user base.
Executive and board communication
Reporting cadence, KPI development, and the stakeholder education layer so leadership and the board are aligned on what AI is actually doing for the organization, in language they trust.
Onboarding fee of $15,000 in the first 30 days, capitalized into the governance committee charter, AI inventory, vendor risk framework, and acceptable-use policy.
Investment
A clear ladder. Start at the tier that matches where you actually are.
| AI Readiness Snapshot | AI Strategy Workshop | Fractional CAIO | |
|---|---|---|---|
| Investment | $997 | $5K - $15K | $15K - $20K per month, plus $15K onboarding |
| Length | One week | One to three weeks | 12-month minimum, 3-4 days/month |
| What you get | Confidential team survey, one-page executive briefing, 15-minute walkthrough call. | Board-ready strategy translating diagnostic data into a defensible action plan. | Embedded part-time AI executive leadership across strategy, governance, adoption, and board reporting. |
| Best for | Leaders who need a baseline before doing anything else. | Leaders who have signal and need a plan they can defend. | Leaders who need ongoing executive partnership on the people side of AI. |
| Learn about the Snapshot | Ask on your discovery call | Book a discovery call |
A full-time Chief AI Officer in the U.S. averages $352,000 base salary, often $500,000 loaded with benefits and equity (Glassdoor 2026). The fractional model delivers embedded executive leadership at roughly 40 to 50 percent of that loaded cost, scoped for organizations that need the leadership without the full-time overhead.
About Tiago
Tiago Ferreira is the founder of Elevida. He holds a Master's in Cyberpsychology, the study of how people interact with technology, and a Master's in Digital Transformation Leadership, the study of how organizations actually change. The combination is rare in the fractional CAIO market, where most executives come up through engineering or product.
His background spans U.S. Government, healthcare startups, and enterprise change work, which means he is comfortable in regulated environments, change-resistant cultures, and the operational constraints that make AI adoption harder than the demos suggest.
The practice runs primarily out of Tampa Bay, Florida, with clients across the United States. Capacity is intentionally limited to a small number of active retainers at any given time so each engagement gets the depth it needs.
Common questions
Why a 12-month minimum?
Adoption work is not a sprint. The assessment, governance setup, and rollout cadence each take a quarter to land properly. A shorter engagement risks declaring a win before the people side has actually shifted. The minimum protects you from that.
We already have a CTO. Where does this fit?
The CTO owns the technical architecture. The Fractional CAIO owns the human infrastructure, the governance posture, and the adoption design. The roles run in parallel and tend to make each other more effective, not redundant.
What does three to four days a month actually look like?
Roughly: two days embedded with your leadership team in working sessions, governance committee, and board prep; one day on workforce readiness work with managers; and a half to full day on adoption diagnostics and reporting. The cadence flexes to where the engagement is in its lifecycle.
Do you require we use specific AI tools?
No. Tool selection is part of the work, but it is downstream of the people-readiness foundation. There are no resale relationships, no kickbacks, and no preferred vendor list to push.
Do you only work with healthcare?
Most of the practice is healthcare because that is where the people-readiness gap is widest right now. The work translates to insurance, financial services, and other regulated industries where adoption is the actual bottleneck. If you are in one of those, the discovery call is the right place to talk through fit.
What happens at the end of the engagement?
Your governance, reporting cadence, and adoption infrastructure stay with your team. The goal is for you to not need a Fractional CAIO at the end of twelve months, because you have built the internal muscle to run the work yourselves.
Let's talk.
A 30-minute discovery call. We talk about where your team is, where you want to take it, and whether a Fractional CAIO is the right fit for the next year of work.
Book a discovery call