A quick scan of executive job boards and recent AI headlines tells you something important. Companies are no longer experimenting with AI on the side. They are building leadership roles dedicated to it.
Take the recent Vice President, Enterprise AI Strategy & Value Capture role at Ulta Beauty that is now created and open as of Feb 2026. This is not a technical manager buried in IT. It is a business leader responsible for identifying use cases, prioritizing investments, aligning functions, and proving financial return. In other words, AI is now a board-level topic.
This trend is accelerating across retail, financial services, healthcare, and technology. Organizations want someone accountable for turning AI from hype into safe, measurable business impact. They are hiring leaders who can connect customer experience, operations, data, governance, and value realization. Or they are bringing in large consulting firms who have a history of handing over a pricey slide deck that could be generated via AI, with the right prompts.
The question is not whether AI needs executive oversight and strategic partnerships. It does.
The real questions are about role clarity, timing and structure. Finding those who can show and do, versus tell. AI educated or experienced practitioners and leaders who arrive to teach & align it all strategically. Not via a project. A transformation.
A full-time VP of AI Strategy is a significant commitment. Compensation can easily exceed several hundred thousand dollars annually before bonuses and benefits. Add a team, tooling, pilots, and integration costs, and the investment climbs quickly.
For large enterprises with mature data environments and clear AI roadmaps, that may make sense.
For many organizations, it does not.
Common scenarios we see:
That is where an AI workshop & fractional leadership can help change the equation.
Consulting does not have to begin with a large retainer. Many organizations start with structured AI education and executive alignment sessions, to build a shared foundation. Or to go backward and start over to do it all correctly.
For example, structured AI training programs help leadership teams and operational groups understand practical use cases, governance implications, and ROI frameworks before moving into broader transformation work. These programs are designed to meet organizations where they are, whether that means executive briefings, department-level enablement, or cross-functional workshops focused on measurable business outcomes.
Training-first engagements allow companies to:
From there, organizations can transition into full consulting, roadmap development, or deeper execution support as needed. This staged model keeps investment proportional to readiness and maturity.
Before you hire a full-time AI VP.
Before you sign a Big Four consulting agreement.
Before you commit significant capital to AI tooling.
Consider starting with structured AI training and fractional advisory support through QX Now, Scoreboard Group, or Efficiencies.AI. These firms offer scalable programs and engagement models designed to build clarity, prove value, and prepare your organization to invest in AI and your future with confidence.
Smart companies do not rush into AI. They architect it deliberately, with the right level of expertise at the right stage.