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 .
Status of Claims
This is a non-final office action in response to the application filed 19 March 2024. Claims 1-14 are pending and have been examined.
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 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claim 1 recites a process for improving total customer experience in IT incident management, and is directed to the abstract idea of monitoring and managing the assignment and resolution of IT service incidents.
Claim 1 recites at least the following limitations:
detecting, by the AI-enabled utility plug-in, that an IT incident has been reassigned to a different team more than a predetermined number of times;
temporarily preventing, by the AI-enabled utility plug-in, further reassignment of the IT incident;
identifying, by the AI-enabled utility plug-in, the earliest available common time slot for a meeting among the respective stakeholders based on their availability mapped in the IT incident management tool;
automatically scheduling, by the AI-enabled utility plug-in, a meeting with the respective stakeholders to determine incident ownership and resolution steps; and
updating, by the AI-enabled utility plug-in, the IT incident management tool with the determined incident ownership and resolution steps.
Under Step 1, independent claim 1 recites at least one step or act, including detecting that an IT incident has bee reassigned to a different team more than a predetermined number of times. Thus the claims fall within one of the statutory categories of invention.
Under Step 2A Prong One, the limitations of claim 1 for detecting that an IT incident has been reassigned to a different team more than a predetermined number of times; preventing further reassignment of the IT incident; identifying the earliest available common time slot for a meeting among the respective stakeholders; scheduling a meeting with the respective stakeholders; and updating the IT incident management tool with the determined incident ownership and resolution steps, as drafted, illustrates a process that under its broadest reasonable interpretation falls with certain methods of organizing human activity category of abstract ideas because the limitations are directed to monitoring and managing the assignment and resolution of IT service incidents by human agents (see at least Specification at [para. 0007, 0031-0032] and applying predetermined business rules upon the occurrence of an event. (See Specification at [para. 0011]: “The plug-in defines escalation rules based on the severity and impact of the incident and automatically triggers escalations to ensure prompt attention and resolution of critical incidents.). See MPEP 2106.04(a)(2)(II). Additionally, the claims are reasonably construed to fall with the mental processes grouping of abstract concepts because the claims are directed to the abstract concept of IT incident resolution data collection, analysis, and recommendation output. The claimed steps could be performed by a human mentally or manually using a pen and paper to detect the number if resignments, prevent further reassignment, identify a common time to schedule a meeting, scheduling the meeting, and updated the IT incident management tool with incident ownership and resolution steps. See MPEP 2106.04(a)(2)(III). Therefore the claims are directed to an abstract idea.
Under Step 2A Prong Two the judicial exception of claim 1 is not integrated into a practical application. In particular, the claims only recite a plug-in and IT management tool for performing the recited steps. These elements are recited at a high level of generality (i.e., as a generic computing components performing a generic computing function) and amount to no more than mere instructions to apply the exception using generic computer components. See MPEP 2106.05(f). For example, Applicant’s specification at paragraph [0011] states: “The AI-enabled utility plug-in integrates with communication platforms to facilitate collaboration and information sharing among stakeholders. It provides a user interface for inputting and updating information related to the IT incident and automatically synchronizes this information with the IT incident management tool.” Adding generic computer components to perform generic functions, such as data gathering, performing calculations, and outputting a result would not transform the claim into eligible subject matter. See MPEP 2106.05(h). Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The “AI-enable utility plug-in” is broadly and generically claimed as a data analysis tool that is programmed to perform a function upon the occurrence of an event. Applying the broadest reasonable interpretation of “AI”, because it is generically and broadly claimed, it is reasonable to construe the claimed “AI” as a computing device or generic processing device used to process data input and generate output. The claim does not include technical details that amount to an improvement to plugin technology, but to more efficient data collection, analysis, and recommendation output for improved IT incident resolution (customer support). The recited steps could be performed by a human to analyze performance data, schedule a decision making meeting, and update incident resolution assignments and procedures to comply with service level agreement contract terms. Performance by computer of operations that previously were performed manually, albeit less efficiently, does not convert an abstract idea into eligible subject matter. Here, the additional limitations do not integrate the judicial exception into a practical application. More particularly, the claims do not recite (i) an improvement to the functionality of a computer or other technology or technical field; (ii) a “particular machine” to apply or use the judicial exception; (iii) a particular transformation of an article to a different thing or state; or (iv) any other meaningful limitation beyond generally linking the use of the abstract idea to a particular technological environment or field of use. See MPEP 2106.05(e); 84 Fed. Reg. at 55. As a result, the AI-enabled utility plug-in does not integrate the recited abstract idea into a practical application.
Under Step 2B the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The Specification does not provide additional details about the AI-enabled utility plug-in, IT incident management tool, or communication platform that would distinguish these additional elements from any generic computing components that communicate with one another in a network environment. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using generic computer components which cannot provide an inventive concept. See MPEP 2106.05.
Dependent claims 2-14 include the abstract ideas of independent claim 1. The limitations of the dependent claims merely narrow the method of organizing human activity/mental process by describing the type of data collected, analyzed, and specific business rules that are applied to assign a incident resolution task or perform a function upon the occurrence of an event or trigger. The limitations of the dependent claims are not integrated into a practical application because none of the additional elements set forth any limitations that meaningfully limit the abstract idea implementation. There are no additional elements that transform the claim into a patent eligible idea by amounting to significantly more. The analysis above applies to all statutory categories of invention. Accordingly claims 1-14 are rejected as ineligible for patenting under 35 U.S.C. 101.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1-2, 4-14 are rejected under 35 U.S.C. 103 as being unpatentable over Adrian et al. (US 2014/0278646) in view of Beshears et al. (US 2010/0076898), and in further view of Zhang et al. (US 2023/0009268).
Regarding Claim 1, Adrian et al. discloses a method for improving total customer experience (TCE) in IT incident management using an AI-enabled utility for an IT incident management tool, the method comprising: (… a method for work assignment queue elimination. Adrian et al. [para. 0007-0008]. … The ticket assignment queue management module 1015 may be stored on the at least one memory 1010. For example, the ticket assignment queue management module 1015 may be a plugin software stored on the at least one memory 1010. The ticket assignment queue management module 1015 may store data and/or code that when executed by the at least one processing unit 1005 performs the functions associated with the ticket assignment queue management module 1015. … The ticket assignment queue management module 1015 may include various modules configured to perform the methods described herein. Adrian et al. [para. 0105-0107; Fig. 3, 9-10]);
While Adrian et al. discloses use of ticket assignment rules and business logic server functions to perform ticket queue reassignment (Adrian et al. [para. 0007, 0033-0037 (number of re-assignments; ticket assignment based on a set of rules),0064-0065, 0073 (user reassignment (to a ticket) may be necessitated by not reaching organization goals based on the collected metrics), 0090-0094 (accept or decline reassignment)], Adrian et al. fails to explicitly disclose detecting, by the AI-enabled utility plug-in, that an IT incident has been reassigned to a different team more than a predetermined number of times; temporarily preventing further reassignment of the IT incident. Beshears et al. discloses these limitations. ( A single plug-in may be configured into a number of different work or equity rules depending upon the schedule profile used. … a rule plug-in is configured to understand the context of the schedule assignment or schedule creation. Beshears et al. [0054-0056]. … Each rule plug-in will return a result that helps the assignment algorithm or the preference based scheduling algorithm used by the schedule processor 36 determine what schedule to assign or create, respectively. The rule plug-in will return the current state of the rule, i.e. whether or not the rule is true. Beshears et al. [para. 0141, 0147-0149]). It would have been obvious to one of ordinary skill in the art of data management and plugin configuration before the effective filing date of the claimed invention to modify the steps of Adrian et al. to include the application assignment business logic rules and conditions disclosed by Beshears et al. for providing a rule plug in (Beshears et al. [para. 0008], in a manner that would have yielded predictable results.
While Adrian et al. and Beshears et al. combined disclose determining and managing scheduling conflicts, (Beshears et al. 0158]), the combined references fail to explicitly disclose identifying, by the AI-enabled utility plug-in, the earliest available common time slot for a meeting among the respective stakeholders based on their availability mapped in the IT incident management tool; automatically scheduling, by the AI-enabled utility plug-in, a meeting with the respective stakeholders to determine incident ownership and resolution steps. Zhang et al. discloses this limitation. (… an intelligent scheduling assistant that executes on a client device, for example as part of a meeting management application, and an intelligent scheduling server that executes on a backend server. Zhang et al. [para. 0021]. … the system comprises a client device 120 on which a meeting management application 130 executes. In some examples, … The meeting management application 130 includes an intelligent scheduling assistant 160, which may be installed, for example, as an add-in or plug-in component of the application 130. Zhang et al. [para. 0027-0029, 0040; Fig. 1]. …The meeting server 190 is configured to conduct the meeting 195 at the scheduled time and allow the organizer and the invitees (e.g., on other client devices 180) to interact in an online fashion. Zhang et al. [para. 0032]). It would have been obvious to one of ordinary skill in the art of plug-in configuration and meeting scheduling before the effective filing date of the claimed invention to modify the plug-in configuration steps of Adrian et al. and Beshears et al. combined to include identifying, by the AI-enabled utility plug-in, the earliest available common time slot for a meeting among the respective stakeholders based on their availability mapped in the IT incident management tool; automatically scheduling, by the AI-enabled utility plug-in, a meeting with the respective stakeholders to determine incident ownership and resolution steps as disclosed by Zhang et al. to overcome the problems faced by a meeting organizer when trying to schedule a meeting for a large number of potential invitees that have diverse individual time constraints (Zhang et al. [para. 0025]), in a manner that would have yielded predictable results.
and updating, by the AI-enabled utility plug-in, the IT incident management tool with the determined incident ownership and resolution steps. (The business logic server 510 may include functions to perform ticket queue assignment, ticket queue ordering, and group assignment. The business logic server 510 may include functions to update data stored on the data storage 515. Adrian et al. [para. 0065-0068; Fig. 5]).
Regarding Claim 2, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising: determining, by the AI-enabled utility plug-in, that no resolution has been reached after the scheduled meeting; and automatically triggering, by the AI-enabled utility plug-in, a notification to a higher-level authority for prioritization and resolution of the IT incident. (The metrics may include the time to resolve a specific type of ticket, the kick back rate of the ticket, and the like. The information may include status of a currently assigned ticket (e.g., metrics as to whether the agent is working at or above capacity). Adrian et al. [0035]. … the escalation module 1030 may be configured to notify a manager of active tickets with expired estimated start dates. In order to monitor the ticket assignment queue status, an escalation may be developed to look for any potential breaching tickets. Adrian et al. [para. 0109]).
Regarding Claim 4, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, wherein the predetermined number of times for reassignment is configurable based on the specific requirements of the IT incident management process. (Example embodiments may, based on objectives of the organization, allow managers to tailor ticket assignment based on a set of rules. Adrian et al. [para. 0037]. … the ticket assignment queue management module 1015 may store data and/or code that when executed by the at least one processing unit 1005 performs the functions associated with the ticket assignment queue management module 1015. … The ticket assignment queue management module 1015 may include various modules configured to perform the methods described herein. Adrian et al. [para. 0105-0107; Fig. 3, 9-10]).
Regarding Claim 5, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising providing, by the AI-enabled utility plug-in, an option for a leader to schedule a second meeting with an adjustable duration and participant list if no resolution is reached during the first scheduled meeting. (Users of the system can include both the meeting organizer and the invitees to the meeting. UI controls are provided which allow the organizer to make a meeting request 140 and receive time recommendations 145. Additionally, the user 110 (organizer or invitee) can enter their own preference settings 150. Zhang et al. [para. 0029]). It would have been obvious to one of ordinary skill in the art of plug-in configuration and meeting scheduling before the effective filing date of the claimed invention to modify the plug-in configuration steps of Adrian et al. and Beshears et al. combined to include providing, by the AI-enabled utility plug-in, an option for a leader to schedule a second meeting with an adjustable duration and participant list if no resolution is reached during the first scheduled meeting as disclosed by Zhang et al. to overcome the problems faced by a meeting organizer when trying to schedule a meeting for a large number of potential invitees that have diverse individual time constraints (Zhang et al. [para. 0025]), in a manner that would have yielded predictable results.
Regarding Claim 6, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: enabling, by the AI-enabled utility plug-in, a justification field in the IT incident management tool for reassigning the IT incident after the predetermined number of times; and allowing, by the AI-enabled utility plug-in, the reassignment of the IT incident only if a valid justification is provided and accepted by the new assignee. ( A single plug-in may be configured into a number of different work or equity rules depending upon the schedule profile used. … a rule plug-in is configured to understand the context of the schedule assignment or schedule creation. Beshears et al. [0054-0056]. … Each rule plug-in will return a result that helps the assignment algorithm or the preference based scheduling algorithm used by the schedule processor 36 determine what schedule to assign or create, respectively. The rule plug-in will return the current state of the rule, i.e. whether or not the rule is true. Beshears et al. [para. 0141, 0147-0149]). It would have been obvious to one of ordinary skill in the art of data management and plugin configuration before the effective filing date of the claimed invention to modify the steps of Adrian et al. to include the application assignment business logic rules and conditions disclosed by Beshears et al. for providing a rule plug in (Beshears et al. [para. 0008], in a manner that would have yielded predictable results.
Regarding Claim 7, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: analyzing, by the AI-enabled utility plug-in, the complexity of the IT incident based on predefined criteria, including the number of teams involved, the technical domains affected, and the impact on business operations; (e processor assigns the ticket based on ticket assignment rules, the system problem and assignment metrics. For example, a ticket may be assigned based on dates (e.g., due dates), location, priority, and the like. For example, a ticket may be assigned based on an agent's capacity (availability or skill set) to resolve the problem. … The metrics may include the time to resolve a specific type of ticket, the kick back rate of the ticket, and the like. Adrian et al. [para. 0024-0027]. … some of the inputs may be skills of the assignee, type of ticket being assigned to them (problem to be solved, work to be done, urgency of the ticket etc.), how long it has taken to do this type of ticket in the past, what the common criteria for completing this type of ticket is, user availability data, user location data, amount of other work that is assigned to them, and gets inputs (e.g., metrics) based on how long things may be taking to help dynamically build out how long different types of work should take. Adrian et al. [para. 0030-0031, 0065, 0068 (create and update data related to the incident)]);
and dynamically adjusting, by the AI-enabled utility plug-in, the predetermined number of times for reassignment based on the analyzed complexity of the IT incident. ( A single plug-in may be configured into a number of different work or equity rules depending upon the schedule profile used. … a rule plug-in is configured to understand the context of the schedule assignment or schedule creation. Beshears et al. [0054-0056]. … Each rule plug-in will return a result that helps the assignment algorithm or the preference based scheduling algorithm used by the schedule processor 36 determine what schedule to assign or create, respectively. The rule plug-in will return the current state of the rule, i.e. whether or not the rule is true. Beshears et al. [para. 0141, 0147-0149]). It would have been obvious to one of ordinary skill in the art of data management and plugin configuration before the effective filing date of the claimed invention to modify the steps of Adrian et al. to include the application assignment business logic rules and conditions disclosed by Beshears et al. for providing a rule plug in (Beshears et al. [para. 0008], in a manner that would have yielded predictable results.
Regarding Claim 8, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: monitoring, by the AI-enabled utility plug-in, the status and progress of the IT incident resolution after the meeting; and providing, by the AI-enabled utility plug-in, real-time notifications to the respective stakeholders and higher-level authorities regarding any delays or deviations from the determined resolution steps. (In block 525 the business logic server 510 creates and updates data related to the incident. Adrian et al. [para. 0068]. … a manager of a group may initiate user reassignment based on receiving a message indicating a match exception (e.g., see FIG. 3 above) due to no users matching a primary ticket assignment rule(s) for a new ticket. The user reassignment may initiate a new process (e.g., described in FIG. 7 below). Alternatively, ticket reassignment may return processing to block 555. Ticket reassignment may be based on data stored in data storage 515. Adrian et al. [para. 0073]. … continuous monitoring of the system may alert the manager to a potential breaching situation (e.g., an assignment that is a condition that does not meet organizational goals). Adrian et al. [para. 0090-0094]).
Regarding Claim 9, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: monitoring, by the AI-enabled utility plug-in, the status and progress of the IT incident resolution after the meeting; and providing, by the AI-enabled utility plug-in, real-time notifications to the respective stakeholders and higher-level authorities regarding any delays or deviations from the determined resolution steps. (… continuous monitoring of the system may alert the manager to a potential breaching situation (e.g., an assignment that is a condition that does not meet organizational goals). Adrian et al. [para. 0090-0094]).
Regarding Claim 10, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: continuously updating, by the AI-enabled utility plug-in, the knowledge base with new IT incident data; (… continuous monitoring of the system may alert the manager to a potential breaching situation (e.g., an assignment that is a condition that does not meet organizational goals). Adrian et al. [para. 0090-0094]);
and employing machine learning algorithms, by the AI-enabled utility plug-in, to improve the accuracy and relevance of the suggested root causes and resolution steps over time. ( example embodiments may help improve trouble ticket work assignment by collecting metrics that may provide a self learning mechanism to track how well an agent (e.g., a service desk agent) may perform (or has performed) a specific job based on how well the agent resolved past incidents. Adrian et al. [para. 0026]).
Regarding Claim 11, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: tracking, by the AI-enabled utility plug-in, the time spent by each team on the IT incident resolution; and generating, by the AI-enabled utility plug-in, reports on the efficiency and effectiveness of the IT incident management process, including metrics such as average resolution time, number of reassignments, and customer satisfaction scores. (… the processor collects metrics based on the ticket assignment. For example, example embodiments may help improve trouble ticket work assignment by collecting metrics that may provide a self learning mechanism to track how well an agent (e.g., a service desk agent) may perform (or has performed) a specific job based on how well the agent resolved past incidents. The metrics may include the time to resolve a specific type of ticket, the kick back rate of the ticket, and the like. With this information being fed back to the system, example embodiments may help refine assignments and improve the assignment results over time. Adrian et al. [para. 0026-0030]. … Metrics may include time to complete different types of tickets (e.g., by type, by group, by individual (this may be a driver into the skills component to determine the level of skill an agent has to resolve a problem)), quality of the work (e.g., kickbacks, number of tickets created about the same issue after the first issue has been resolved, or failed changes to resolve an issue. This should also drive information into the skills and capabilities of an agent or group), and number of re-assignments.).
Regarding Claim 12, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising integrating, by the AI-enabled utility plug-in, with communication platforms, such as email and chat applications, to facilitate seamless collaboration and information sharing among the respective stakeholders during the IT incident resolution process. ( The incident creation user interface 505, the business logic server 510 and the data storage 515 may be communicatively coupled via, for example, the internet and/or an intranet. The incident creation user interface 505 may be a user interface operating on a client (e.g., personal) computer. Adrian et al. [para. 0063; Fig. 5]. … ticket assignment queue management module 1015 may be a plugin software stored on the at least one memory 1010. The ticket assignment queue management module 1015 may store data and/or code that when executed by the at least one processing unit 1005 performs the functions associated with the ticket assignment queue management module 1015. Alternatively, or in addition to, the ticket assignment queue management module 1015 may be an application-specific integrated circuit, or ASIC. For example, the ASIC may be configured as one or more of the module, or elements of the modules, of the ticket assignment queue management module 1015. The ticket assignment queue management module 1015 may be a standalone hardware module including a processor (not shown) configured to perform the associated functions. Adrian et al. [para. 0101-0107; Fig. 10]).
Regarding Claim 13, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: providing, by the AI-enabled utility plug-in, a user interface for the respective stakeholders to input and update information related to the IT incident, including root cause analysis, impact assessment, and resolution progress; and automatically synchronizing, by the AI-enabled utility plug-in, the information entered through the user interface with the IT incident management tool. (.. collecting metrics that may provide a self learning mechanism to track how well an agent (e.g., a service desk agent) may perform (or has performed) a specific job based on how well the agent resolved past incidents. The metrics may include the time to resolve a specific type of ticket, the kick back rate of the ticket, and the like. The information may include status of a currently assigned ticket (e.g., metrics as to whether the agent is working at or above capacity). With this information being fed back to the system. Adrian et al. [para. 0035]. … The incident creation user interface 505 may be a user interface operating on a client (e.g., personal) computer. … The business logic server 510 may include functions to update data stored on the data storage 515. Adrian et al. [para. 0063-0068; Fig. 5]. … the display information may include the user (or agent) assigned to resolve the ticket, information about the ticket (e.g., ticket ID), target resolution date (and time), and the like. Adrian et al. [para. 0075, 0085 (continuous monitoring)]. … ticket assignment queue management module 1015 may be configured to assign tickets to users or agents based on ticket assignment rules and metrics, monitor and maintain metrics associated with the ticket assignments and reassign tickets as desired, and provide information to user interfaces. Adrian et al. [para. 0101-0107; Fig. 8A-8B, 9]).
Regarding Claim 14, Adrian et al., Beshears et al. and Zhang et al. combined disclose the method, further comprising, further comprising: defining, by the AI-enabled utility plug-in, escalation rules based on the severity and impact of the IT incident; and automatically triggering, by the AI-enabled utility plug-in, escalations to higher-level authorities based on the defined escalation rules, ensuring prompt attention and resolution of critical incidents. (tickets assigned to the user may be auto-ordered based on some pre-defined organization objectives. For example, an organization may decide to order ticket based on target date, followed by priority. … The escalation module 1030 may be configured to determine an issue(s) (e.g., a breach of or failure to meet an organizational goal or requirement (e.g., completion date) associated with the ticket) with ticket assignments and make a manager and/or user aware of the issue(s). For example, the escalation module 1030 may be configured to notify a manager of active tickets with expired estimated start dates. In order to monitor the ticket assignment queue status, an escalation may be developed to look for any potential breaching tickets. The escalation may be configured to look for tickets with expired (or about to expire) "estimated start time". The escalation module 1030 may be configured to look monitor missed "estimated start time" instead of "target date" because the "estimated start time" is the time the user or agent is supposed to start working on the ticket in order to meeting the "target date". Adrian et al. [para. 0102, 0109]).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Adrian et al. (US 2014/0278646) in view of Beshears et al. (US 2010/0076898), and in further view of Zhang et al. (US 2023/0009268), and in further view of Riley et al. (US 2002/0123983)
Regarding Claim 3, While Adrian et al. discloses crating new data records and updating existing data (Adrian et al. [para. 0068], Adrian et al., Beshears et al. and Zhang et al. combined fail to disclose the method, further comprising, further comprising: identifying, by the AI-enabled utility plug-in, that a third-party vendor is required for resolving the IT incident; and enabling, by the AI-enabled utility plug-in, additional fields in the IT incident management tool to capture vendor-related information, including vendor name, incident number, and status. Riley et al. discloses these limitations. (FIG. 4 is a flow chart for a method 40 of processing service requests. Riley et al. [para. 0094]. … All service requests (either automatic or manual) should be assigned a unique identification number or Ticket ID. Riley et al. [para. 0105-0109 (record information in pre-prepared forms), 0135-0137 (assignment); Fig. 4]. … Tier 3 personnel are usually the designers and developers of the systems. These could be the application development or maintenance staff, network management, certain operators, or 3rd party vendors. Service requests are escalated to Tier 3 personnel when Tier 1 or Tier 2 personnel are unable to resolve them. … Tier 3 resolves problems that cannot be resolved by the first two levels of support and require additional technical or programming expertise or vendor assistance. Riley et al. [para. 0203]) It would have been obvious to one of ordinary skill in the art of data management and plug-in configuration before the effective filing date of the claimed invention to modify the data management steps of Adrian et al., Beshears et al. and Zhang et al. combined to include identifying, by the AI-enabled utility plug-in, that a third-party vendor is required for resolving the IT incident; and enabling, by the AI-enabled utility plug-in, additional fields in the IT incident management tool to capture vendor-related information, including vendor name, incident number, and status as disclosed by Riley et al. to provide a service solution to meet business problems (Riley et al. [para. 0053]), in a manner that would yield predictable results.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure:
Gillam (US 2024/0086859) – system can obtain attributes associated with calendar items, and can analyze those attributes to determine how those calendar items are to be processed, without the necessity of outside metadata or storage, task management service facilitates dynamic scheduling, rescheduling, and processing of calendar items. Such attributes may be an activation keyword or activation attribute.
Puri et al. (US 11,736,378) - Information technology environment monitoring systems perform analytics over machine data received from networked entities. Outputs of such a system may be useful to help a user identify a problem and resolve an incident. Inventive aspects enable user interactions to trigger automatic connection with network servers to establish communication channels for conveying analytics and other information related to the problem between and among network nodes participating in the resolution of the problem or incident.
Ramadoss et al. (US 2025/0267081) – Methods, systems, and computer-program products for ticket management. The methods, systems, and computer-program products include receiving input data having information relating to one or more incidents, classifying each incident of the one or more incidents, escalating an incident of the one or more incidents based, at least in part, on at least one of the classification of each incident or a prioritization level associated with each incident and generating a resolution for the incident, the resolution including at least one of a solution to the incident or an assignment of the incident to a related team.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LETORIA G KNIGHT whose telephone number is (571)270-0485. The examiner can normally be reached M-F 9am-5pm.
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/L.G.K/Examiner, Art Unit 3623
/CHARLES GUILIANO/Primary Examiner, Art Unit 3623