Prosecution Insights
Last updated: May 29, 2026
Application No. 18/760,572

OPERATION MODIFICATION TO ADDRESS INCOMPATIBILITY VIA MACHINE LEARNING

Non-Final OA §101§103
Filed
Jul 01, 2024
Priority
Jul 12, 2023 — provisional 63/513,292 +1 more
Examiner
SPAR, ILANA L
Art Unit
3622
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Adp Inc.
OA Round
2 (Non-Final)
45%
Grant Probability
Moderate
2-3
OA Rounds
1y 8m
Est. Remaining
74%
With Interview

Examiner Intelligence

Grants 45% of resolved cases
45%
Career Allowance Rate
160 granted / 353 resolved
-6.7% vs TC avg
Strong +28% interview lift
Without
With
+28.4%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
21 currently pending
Career history
386
Total Applications
across all art units

Statute-Specific Performance

§101
4.0%
-36.0% vs TC avg
§103
84.6%
+44.6% vs TC avg
§102
8.7%
-31.3% vs TC avg
§112
1.5%
-38.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 353 resolved cases

Office Action

§101 §103
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Amendment The following Office Action is responsive to the amendments and remarks received on October 29, 2025. Response to Arguments Applicant's arguments filed October 29, 2025 have been fully considered but they are not persuasive. With regards to the arguments against the 101 rejection, the applicant initially argues (see page 9) that the claimed invention is not directed to an abstract idea. Examiner respectfully disagrees. The claims are directed to maintaining compliance with policies, which falls under both commercial or legal interactions (legal obligations/business relations) and further managing personal behavior or relationships or interactions between people (following rules or instructions). The claims are not directed to addressing technical challenges involved in performing electronic transactions as argued, because the claims do not discuss any technical challenges or technical solutions. Rather, the claims discuss making determinations about operational constraints, and carrying out steps to align with operational constraints. This process is not inherently technical. Applicant further argues that Ex Parte Tovi Grossman et al. provides an analogous example that was determined to be eligible. Examiner respectfully disagrees. Ex Parte Tovi Grossman et al. is not a precedential decision, and therefore any conclusions made in that case are not relevant to the instant application. Further, the conclusion that preventing excessive error, delays, or latency while providing more accurate analysis makes the claims eligible is not correct. Improving decision making and results is an improvement to the abstract idea, and does not encompass an improvement to the technology. Applicant further argues (see page 14) that the technology recited in the claim is not post-solution activity. Examiner has not alleged any insignificant extra-solution activity in the 101 rejection, and therefore the argument is moot. Applicant has argued that the prior art fails to teach the amended claim limitations. This argument is moot in view of the updated 103 rejections below. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. At step 1, claim 1 is directed to a system (article of manufacture), claim 10 is directed to a method, and claim 19 is directed to a computer program product (article of manufacture). The claims are directed to a statutory category. At step 2A prong I, the claims recite an abstract idea. Claims 1, 10, and 19 recite: detecting an update to an operational constraint established in an electronic document; receiving data corresponding to operations executed by an entity; determining, via a model trained with machine learning on historical operational data for the entity, an incompatibility between an operation of the entity and the update to the operational constraint; selecting, responsive to the determination of the incompatibility made via the model, an action to address the incompatibility; transmitting, to the entity, an alert indicating a time limit to receive an override to the action, wherein the time limit is set based on a severity of non-compliance with the update and the action is to be automatically executed responsive to the override not being received from the entity within the time limit; determining, based on monitoring for the override in accordance with the time limit, to automatically execute the action; and transmitting, responsive to the determination to automatically execute the acting, to the electronic processing system, data to cause the electronic processing system to execute the action to modify the operation of the entity to satisfy the update to the operational constraint. These limitations fall within the group of Certain Methods of Organizing Human Activity (i.e., fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). Here, the limitations describe the business practice of monitoring updates to policy requirements and implementing business practices in compliance with those policies. Accordingly, the claims are directed to an abstract idea. At step 2A prong II, the judicial exception is not integrated into a practical application. The additional elements are a data processing system comprising one or more processors, coupled with memory (claim 1), natural language processing (claim 1, 19), a model trained with machine learning (claim 1, 10, 19), an electronic processing system (claim1, 10), a non-transitory computer readable storage medium (claim 19). Each of these elements is a generic computer component performing generic computing functions, and therefore does not integrate the abstract idea into a practical application when considered either singly or as a whole. The steps of transmitting data can be considered insignificant extra-solution activity, identified by the MPEP at 2106.05(g). At step 2B the additional elements are reconsidered as to whether they amount to significantly more than the abstract idea. Because each of the elements listed above is merely a generic computer component performing generic computing functions, the additional elements do not amount to significantly more than the abstract idea. The additional steps of transmitting data, identified as insignificant extra-solution activity above, are further recognized by the MPEP as being well-understood, routine, and conventional activity that does not amount to significantly more than the abstract idea. Therefore, independent claims 1, 10, and 19 are ineligible. The dependent claims are further considered. Claims 2-5, 8, 9, 11-13, 17, 18, and 20 further limit the abstract idea, and do not contain additional elements. Claims 6 and 15 further teach generating a deeplink, which is a generic computing function and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. Claims 7 and 16 further teach a push notification to a user device, which is a generic computing function and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. Claim 14 teaches a machine learning model, which is a generic computing function and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. Therefore, all claims are directed to ineligible subject matter. Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (US 2021/0312360) in view of Milden et al. (US 2012/0331131), further in view of Backof et al. (US 2008/0155249). With reference to claim 1, 10, 19, Kim et al. teaches a system to control operation compatibility via machine learning, comprising: a data processing system comprising one or more processors, coupled with memory (see Figure 1B), to: detect, via natural language processing, an update to an operational constraint established in an electronic document (see paragraph 41 – change to legal framework, paragraph 52 – analyze the textual format to detect the change, and paragraph 72 – natural language processing); receive, from an electronic processing system, data corresponding to operations executed by an entity (see paragraph 58 – a task that may be impacted by the change); determine, via a model trained with machine learning on historical operational data for the entity, an incompatibility between an operation of the entity and the update to the operational constraint (see paragraph 66 – compare the at least one task parameter with the change to determine whether the task is impacted by the change, and paragraph 68 – may train a machine learning model); select, responsive to the determination of the incompatibility made via model, an action to address the incompatibility (see paragraph 79 – upon a determination that the task is impacted by the change, recommend, via the network, one or more actions associated with the task); transmit, to the entity, an alert (see paragraphs 37-38); and transmit, to the electronic processing system, data to cause the electronic processing system to execute the action to modify the operation of the entity to satisfy the update to the operational constraint (see paragraph 86 – modify the at least one term of the contract to comply with the change to the legal framework). Kim et al. fails to teach indicating a time limit to receive an override to the action, wherein the time limit is set based on a severity of non-compliance with the update and the action is to be automatically executed responsive to the override not being received from the entity within the time limit; determine, based on monitoring for the override in accordance with the time limit, to automatically execute the action. Milden et al. teaches: indicating a time limit to receive an override to the action (see paragraph 50 – should not be introduced until later in the year); and wherein the time limit is set and the action is to be automatically executed responsive to the override not being received from the entity within the time limit (see paragraph 50 – a preferred time may be selected for implementing the update to suit the company’s needs). It would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the time limits as taught by Milden to the policy update protocol of Kim to allow a company to implement changes “to accommodate the work created by implementing a large number of changes” (see paragraph 50), thus smoothing the process of implementing these changes and improving the company’s operations. Kim et al. and Milden et al. fail to teach the time limit is set based on a severity of non-compliance with the update. Backof et al. teaches wherein the time limit is determined based on the severity of a penalty associated with not complying with the detected update (see paragraph 72 and Figure 12 – time to implement the policy on the X axis, penalty on the axis). It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the combination of Kim and Milden with the teachings of Backof to ensure that the time frame selected for implementing policy changes both suits the needs of the company (Milden) and avoids severe penalties (Backof). This allows for the competent adaptation to new situations (see Backof, paragraph 4) with minimal consequences. With reference to claim 2, 11, 20, Kim et al., Milden et al., and Backof et al. teach the system of claim 1, 10, 19 and Kim et al. further teaches comprising the data processing system to: detect the update to the operational constraint using natural language processing (see paragraph 37 and paragraph 72). Milden et al. further teaches determine the time limit based on the detected update to the operational constraint (see paragraph 50 – should not be introduced until later in the year). These teachings are further combined using the same rationale as above. With reference to claim 3, 12 Kim et al., Milden et al., and Backof et al. teach the system of claim 2, 11, and Backof et al. further teaches wherein the time limit is determined based on the severity of a penalty associated with not complying with the detected update (see paragraph 72 and Figure 12 – time to implement the policy on the X axis, penalty on the axis). These teachings are further combined using the same rationale as above. With reference to claim 4, 13 Kim et al., Milden et al., and Backof et al. teach the system of claim 2, 11 and Milden et al. further teaches wherein the time limit is associated with a fiscal year (see paragraph 50). The combination is made using the same rationale as above. With reference to claim 5, 14 Kim et al., Milden et al., and Backof et al. teach the system of claim 1, 11, and Kim et al. further teaches comprising: the data processing system to determine the incompatibility between the updated operational constraint and the operation of the entity using the model (see paragraph 68). With reference to claim 6, 15, Kim et al., Milden et al., and Backof et al. teach the system of claim 2, 11, and Kim et al. further teaches comprising: the data processing system to provide the alert based on generation of a deeplink which directs a site providing details regarding the one or more legislative documents (see paragraph 85). With reference to claim 7, 16, Kim et al., Milden et al., and Backof et al. teach the system of claim 2, 11, and Kim et al. further teaches comprising: the data processing system to provide the alert notification indicating the action comprises sending a push notification to a user device (see paragraph 81 – notifications to the security team would involve notifications on a user device). With reference to claim 8, 17 Kim et al., Milden et al., and Backof et al. teach the system of claim 2, 11, and Milden et al. further teaches wherein the action comprises at least one of automatically updating a payroll policy, automatically updating a leave policy, and automatically updating a tax policy (see paragraph 45 – leave policy). The combination is made using the same rationale as above. With reference to claim 9, 18 Kim et al., Milden et al., and Backof et al. teach the system of claim 2, 11, and Kim et al. further teaches wherein the alert is a point of entry notification (see paragraph 81 – generate alert notifications, and send the alert notifications to a legal team that manages contract review. Applicant’s specification at paragraph 53 – “The point of entry notification can summarize the legal conflict…”). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ILANA L SPAR whose telephone number is (571)270-7537. The examiner can normally be reached 8-4 M-F. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tariq Hafiz can be reached at 571-272-7537. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ILANA L SPAR/Supervisory Patent Examiner, Art Unit 3622
Read full office action

Prosecution Timeline

Show 3 earlier events
Oct 14, 2025
Applicant Interview (Telephonic)
Oct 29, 2025
Response Filed
Jan 13, 2026
Final Rejection mailed — §101, §103
Mar 04, 2026
Applicant Interview (Telephonic)
Mar 04, 2026
Examiner Interview Summary
Mar 10, 2026
Response after Non-Final Action
Apr 13, 2026
Request for Continued Examination
Apr 23, 2026
Response after Non-Final Action

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

2-3
Expected OA Rounds
45%
Grant Probability
74%
With Interview (+28.4%)
3y 7m (~1y 8m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 353 resolved cases by this examiner. Grant probability derived from career allowance rate.

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