This is an AAO appeal decision — a case denied once and appealed. It shows how the framework is applied; it is not the filing population.
The Petitioner, a research scientist working on artificial intelligence, proposed to develop AI technologies for user interest modeling, user-generated content understanding, and economic production iteration services for companies globally.
Field: artificial intelligence / electrical and computer engineering · Read the decision (uscis.gov)
EB-2 threshold — addressed
SCOPS and AAO found the Petitioner qualifies as an advanced degree professional based on his PhD.
Prong 1 — national importancenot established · dispositive
“The proposed endeavor, as described, and the evidence in the record do not support the Petitioner's assertions that the potential impact of his endeavor extends beyond his employer to have a broader impact to his field or implications rising to a level of national importance.”
“The Petitioner, however, makes broad claims, without corroborating evidence, that his research would impact national government policies and advance the field of artificial intelligence.”
“Much of the evidence in the record and the Petitioner's arguments focus on the importance of the field of artificial intelligence.”
“This evidence, however, does not mention the Petitioner's specific proposed projects and their potential impact on the field or on such national initiatives.”
“his overall significance does not establish the national importance of the Petitioner's proposed endeavor in particular.”
“he has not sufficiently established that his proposed endeavor in the United States will have national importance under the first Dhanasar prong.”
AAO decision text
How the evidence was treated
- other · discounted
“The Petitioner mainly relies on his statements, without corroborating evidence, to characterize his research work as valuable for advancing the field of artificial intelligence.”
AAO decision text - publications · discounted
“such previous work mainly relates to whether he is well-positioned to advance his endeavor under Dhanasar's second prong.”
AAO decision text - other · discounted
“the documentation will not be considered since it is dated after the date of filing the petition for the benefit sought.”
AAO decision text - degree · credited
Where this case turned
- Economic claims unsupported · p1 — job/revenue projections with no corroborating basis
- Employer-specific benefit · p1 — "work furthers my company's product" — value accrues to one firm
- Endeavor too vague · p1 — described as a job role, not a defined undertaking
- Field importance conflated with endeavor · p1 — argues the field matters, not the specific endeavor
- Local, not national scope · p1 — impact confined to clients / a region
Notable
AAO declined to consider post-filing evidence (a research paper's conference acceptance dated after the petition filing date) under Matter of Katigbak, treating it as impermissible speculation of future eligibility. The decision also notes that SCOPS/AAO found the well-positioned (p2) prong satisfied but declined to reach p2/p3 since p1 failure was dispositive.
Authorities this decision leans on
From the doctrinal survivor set — 187 authority tests across 47 distinct authorities cleared the differential-lift gates. Only those appear here.
- 8 C.F.R. 103.2(b)(1)
- 8 C.F.R. 103.3
- Flores v. Garland
- Matter of E-M-
- Matter of Katigbak
- Matter of L-A-C-
- USCIS Policy Manual F.5(D)(2)
Cases in adjacent profiles
- The Petitioner, a senior principal biostatistician, proposes to develop innovative statistical and machine-learning meth
- The Petitioner proposed to use advanced deep learning and machine learning models to create efficient, safe, and well-pe
- The Petitioner proposes to advance machine learning methods for the design and optimization of advanced metamaterials an
- The Petitioner, a postdoctoral chemist, proposed to continue developing high-performance materials and novel synthetic m
- The Petitioner proposes to design novel sensor data processing methods and machine learning algorithms for smart wearabl