The Missing Workforce for the AI Age:
Integrating Data & AI Expertise into Business Operations
16 pages | Laurel Consulting White Paper | October 2026
Why do growing data & AI investments still struggle to deliver business value? One reason is a missing workforce that bridges operations and technology. This white paper introduces a new workforce
—Domain Data & AI Experts (DDAIEs)—combining operational knowledge
with data & AI expertise and taking on a distinct mission: Trailblaze, Consult, and Coach.
Executive Summary
As Artificial Intelligence (AI) advances rapidly, organizations have access to increasingly powerful data & AI capabilities. Yet translating those capabilities into meaningful business value remains challenging. Business teams continue to need more data, insights, and AI to improve operations, while technical teams face growing project queues and expanding data & AI product inventories to maintain. At the same time, valuable functionality already built into application systems may remain underutilized.
These challenges are often interpreted as technology or resource problems. Organizations respond by purchasing more tools, expanding technical teams, or changing where data & AI professionals are placed. But a more fundamental problem lies in the conventional separation between business operations and technical expertise. Business professionals understand the operational context but often lack sufficient data & AI expertise; data & AI professionals possess deep technical expertise but may work at a distance from business operations. Centralized, distributed, and hub-spoke staffing models organize these professionals differently, but structure alone does not create the integrated capability that the AI age increasingly requires.
This white paper proposes a workforce capability designed to fill that gap: Domain Data & AI Experts (DDAIEs). DDAIEs possess the combination of knowledge of a business domain, data & AI functionality built into the domain's application systems, and data & AI technology. More importantly, they are charged with a distinct three-fold mission: Trailblaze, Consult, and Coach.
Trailblaze means actively exploring what rapidly advancing technology makes possible and identifying how data & AI capabilities can be used to improve operations. Consult means helping business and technical teams determine the most effective way to address an operational need, including choosing between built-in data or AI functionality in the application systems and custom-built solution. Coach means helping business users build their own knowledge, capability, and confidence with data & AI rather than becoming increasingly dependent on technical specialists.
With DDAIEs operating within business domains, organizations can move from a transaction-based data & AI delivery model toward an integrated model. Operational needs can be examined within their business context before becoming technical requests by default. Existing capabilities can be leveraged where appropriate, custom development can be pursued when justified, and specialized technical teams can focus their expertise on work that truly requires it.
Organizations do not need to create this workforce from scratch. Technical professionals can develop deeper domain expertise; domain professionals can develop stronger data & AI expertise; and cross-functional initiatives can serve as incubators where people develop the ability to operate across both worlds. Wherever the starting point, establishing an integrated capability is the ultimate goal.
DDAIEs should be operationally embedded but professionally connected. The CDAIO office can help grow and sustain this workforce through professional development, common standards, community building, cross-domain learning, and connection to organizational data & AI leadership structure.
The workforce challenge for the AI age is therefore not simply how to deliver more data & AI products. It is how to make the organization itself increasingly capable of leveraging data & AI. DDAIEs provide a workforce mechanism for building that capability.