Where the number was produced
The study Christian & Timbers ran between January and June 2026 rests on interviews with more than 250 senior executives across 180 companies, a focused survey of 80 Fortune 500 executives and conversations with more than 300 engineers working in the field. It puts the pool of engineers able to deliver measurable enterprise returns at roughly 2,000 in the United States and projects demand for the role rising 2,100% by the end of 2026. Major consulting firms are described as planning to grow these teams from 20 people to 100.[1]
An executive search firm earns its revenue from placements, and a narrow pool pulls the fee per placement upward. That does not make the estimate wrong; it does mean the party doing the measuring and the party gaining from the demand the measurement creates share an address. The report gives neither the sampling frame behind the 2,000 figure nor the criterion by which it was counted.[1]
Who a 2,000-person definition leaves out
A pool that size is a definition before it is a measurement. Set the criterion at someone an enterprise buyer would accept today and you get 2,000; set it at someone who could do this work after six months of training and you get a far larger number. What separates the two is not talent but who carries the training cost. The competing account is that the study rests on a documented skills rubric the report does not summarise.[1]
The distributional metric to watch
If the scarcity is real rather than definitional, it should show up in pay. Two line items are worth following: the salary bands published in postings for these roles, and the share of positions opened to internal transfer. If the first rises while the second stays low, a narrow group is capturing the scarcity premium; if the second rises, companies have started carrying the cost in house. Firm founder Jeff Christian's remark that enterprises are hiring in the middle of summer points to the pressure sitting with budget holders, and where that pressure is passed on can be measured in posting data.[1]