The Total Economic Impact™ Of Grok Build

Increased Engineering Delivery Capacity

Evidence and data. Interviewees said Grok Build increased the amount of software engineering work their teams could complete without requiring proportional increases in engineering headcount. The productivity improvements in this benefit apply specifically to coding and implementation activities. Interviewees described faster coding and implementation, higher development throughput, and the ability to direct added capacity toward roadmap work, customer initiatives, infrastructure improvements, bug fixes, and previously deferred projects. They said coding and implementation are core, recurring engineering activities, and they reported unmet engineering demand and opportunities to apply added capacity to roadmap, backlog, customer, infrastructure, and other engineering work. Across the interviews, productivity gains varied by task, development environment, and maturity of use, indicating that the benefit represented increased delivery capacity rather than an equivalent reduction in headcount.

• The engineering executive in the B2B software platform industry reported that as their organization deepened its agentic use, merged pull requests increased from 14 per active engineer per month to 23.8 between 2024 and 2026. They also said issue cycle times decreased from 3.2 days to between 1.5 and 1.9 days in 2026, allowing the organization to deliver approximately twice as many epics in Q1 than it did during the same period in 2025 without a proportional increase in engineering headcount. They summarized, “[Grok Build] took what each engineer ships up by roughly 70% inside a year without a quality regression.”

• The director of product, AI platform, at a retail technology organization said pull request throughput per engineer doubled with Grok Build while engineering headcount remained roughly flat. They estimated that customer-facing output increased by approximately 30% to 40% and said the additional capacity supported bug fixes, infrastructure improvements, and internal productivity work that historically would not have been economically justified. The interviewee explained: “We’re shipping more product, we’re not growing headcount, and that’s turning into revenue and turning into ... all the cascades through our financial performance.”

• The IT director at an energy infrastructure organization reported 30% to 50% faster software delivery for applicable work, enabling an increase to delivery capacity. The interviewee said, “[Grok Build increased] what we deliver by a third and prevented us from having to go out and hire additional staff to meet the demand in front of us.” The organization used the additional capacity to meet growing demand and reduce reliance on external consultants and contractors rather than reducing existing engineering headcount.

• Two AI engineering leads at a mining technology organization similarly described using existing engineering resources to pursue more initiatives concurrently. One characterized the change as increasing the capacity of an individual engineer rather than increasing headcount, while the other said the number of initiatives being pursued expanded from approximately one or two to four or five. The interviewees attributed the expanded capacity to engineers working at a higher level with AI-supported development tools rather than adding equivalent staff.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization has 180 engineers actively use Grok Build in Year 1, increasing to 220 in Year 2 and 225 in Year 3.

• Engineers spend 30% of their working time on coding and implementation activities addressed by this benefit.

• Grok Build improves the composite’s productivity for coding and implementation activities by 30%. This reflects reported improvements across productivity, delivery, pull-request throughput, and cycle time and applies them specifically to coding and implementation activities.

• The fully burdened hourly rate for an engineer is $90.

• The composite organization recaptures 70% of the productivity gains and redirects that capacity toward productive engineering work.

• Forrester did not quantify the remaining 30% of productivity gains to reflect that not all productivity improvements translate directly into quantifiable engineering output.

Risks. The scale of this benefit may vary from organization to organization based on:

• The number of engineers who actively use Grok Build.

• The proportion of engineering time spent on coding and implementation activities.

• The types and complexity of engineering work performed.

• The productivity improvement realized for applicable activities.

• Employees’ proficiency with AI-assisted and agentic development practices.

• The extent to which measured productivity improvements are attributable to Grok Build rather than other technologies or process changes.

• The availability of productive engineering work to absorb additional capacity.

• The organization’s ability to redirect saved time toward measurable business value.

• The relationship between model pricing, the amount of context processed per request, and the cost per unit of delivered engineering work.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $5.5 million.

Reduced Modernization And Migration Engineering Effort

Evidence and data. Interviewees said Grok Build reduced the engineering effort required for modernization, migration, upgrade, and material refactoring initiatives by helping engineers understand legacy applications, plan changes, refactor code, execute repetitive transformations, and validate results. The productivity improvements in this benefit apply specifically to discrete modernization and migration initiatives. Interviewees reported reductions of approximately 50% and, in some cases, substantially greater improvements. Interviewees noted their organizations used these efficiencies to accelerate initiatives already underway and undertake modernization work that otherwise would have required substantially more time or engineering resources. They also described deferred modernization work and additional qualifying initiatives that their organizations could pursue as engineering capacity became available. However, modernization and migration are discrete, project-based activities, and the timing of additional work may depend on project sequencing, organizational priorities, technical dependencies, and available resources.

• The engineering manager at a financial services organization described a framework migration in which three engineers had previously migrated approximately 50 microservices during an entire quarter. They said that with self-hosted Grok Build agents, one engineer subsequently migrated 100 microservices in one month, representing a reported 36-fold increase in migration throughput per engineer. The interviewee said the project duration for large-scale migrations could be reduced by approximately 50%: “A three-month project would take a month to a month and a half now.”

• Two AI engineering leads at a mining technology organization described how Grok Build accelerated delivery of two large modernization initiatives. It required only eight months to deliver a data platform that was estimated to require two to three years and 20 additional engineers, and it needed just six months to deliver an Angular-to-React migration estimated to require three to five years. One of the interviewees said Grok Build helped engineers reason over legacy applications much faster, describing how work previously spent “reading and trying to understand how systems communicate” was reduced to hours.

• The director of product, AI platform, in the retail technology industry said their organization used Grok Build cloud agents to address a large legacy migration from MobX to native React state management. Supporting customer evidence indicated the work was expected to require approximately 18 months of manual effort from a full engineering team if done manually. Using Grok Build cloud agents, the organization instead had one engineer coordinate a group of AI agents that performed much of the work. The director of product, AI platform, at a retail technology organization identified modernization as an area where agentic development had a particularly significant impact. They said, “I think it’s one of the areas where the impact is larger.”

• The IT director in the energy infrastructure industry said AI-assisted development changed their organization’s engineering requirements associated with modernizing large applications. They noted that the organization expects to complete a large front-end rewrite comparable to a previous project that cost approximately $10 million and took two years in half the time with roughly half the costs. In follow-up correspondence, the interviewee estimated that Grok Build saved three weeks of developer time on an Angular system upgrade and dependency migration.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization undertakes four qualifying modernization and migration initiatives annually. Qualifying initiatives include discrete migrations, upgrades, replatforming, rewrites, or material refactoring of existing applications, frameworks, services, or technology environments. Routine application development is excluded.

• Prior to using Grok Build, each qualifying initiative required six engineers working for nine months.

• Each engineer contributes 173 productive hours per month to the applicable initiative.

• Grok Build reduces the engineering effort the composite requires for qualifying modernization and migration initiatives by 40%. This reflects the portion of the improvement attributed to Grok Build after accounting for the contribution of engineering expertise, processes, orchestration, infrastructure, automation, and other supporting factors.

• The fully burdened hourly rate for an engineer is $90.

• The composite organization recaptures 60% of the productivity gains and redirects that capacity toward productive engineering work.

• Forrester did not quantify the remaining 40% to account for these constraints, as well as normal workflow friction, experimentation, learning, coordination, and refinement of AI-assisted modernization practices.

Risks. The scale of this benefit may vary from organization to organization based on:

• The number and frequency of qualifying modernization and migration initiatives.

• The size and complexity of the applications, frameworks, services, or technology environments being modernized.

• The baseline engineering resources and duration required for qualifying initiatives.

• The suitability of modernization and migration work for AI-assisted and agentic execution.

• The maturity of the organization’s development practices, testing processes, automation, and technical guardrails.

• The portion of modernization improvements attributable to Grok Build rather than other technologies, processes, or organizational changes.

• The extent to which the organization can redirect saved engineering time toward productive work.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $1.7 million.

Reduced Software Planning And Documentation Effort

Evidence and data. Interviewees said Grok Build reduced the effort required to understand existing code, develop requirements and specifications, create user stories, and produce technical documentation. These activities previously required engineers and other technical employees to manually gather information, navigate unfamiliar codebases, identify dependencies, document requirements, and translate that information into specifications or documentation before implementation could proceed. Planning and documentation activities are recurring activities embedded throughout the software development lifecycle and include requirements and specification work, code discovery and understanding, and technical documentation. This benefit excludes coding and implementation; discrete modernization and migration initiatives; and testing, review, debugging, and remediation.

• The IT director in the energy infrastructure industry estimated their organization reduced the time spent documenting requirements and generating initial specifications by 50% to 70% while also reducing the time spent creating first drafts of technical and business documentation by 70% to 90%. In follow-up correspondence, the interviewee reported that using Grok Build to translate business-level descriptions into detailed user stories saved two to three days per cycle, while using it to clarify requirements, generate questions for business stakeholders, and refine requirements and user stories saved approximately one week of effort.

• The same IT director reported a 25% to 50% reduction in time spent locating relevant code, database objects, APIs, and dependencies, and a 20% to 40% reduction in the time required to understand unfamiliar areas of an application. They said, “[These improvements returned] the equivalent of several developer hours per engineer per week while simultaneously improving consistency and reducing manual effort.”

• The engineering executive at a B2B software platform organization said gaining the ability to navigate unfamiliar code and generate documentation led to significant time savings for engineers and reduced their reliance on senior colleagues when trying to understand unfamiliar systems. They explained: “It used to mean scheduling a meeting with a senior engineer to walk through the system. [We] don’t need that anymore.”

• An AI engineering lead in the mining technology industry said Grok Build helped their organization understand unfamiliar systems and move from discovery into planning. They said engineers could reason over application structure and dependencies and use that understanding to develop technical specifications for proposed changes, reducing the time spent manually analyzing and understanding the system before implementation.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite has 180 engineers actively use Grok Build in Year 1, increasing to 220 in Year 2 and 225 in Year 3.

• Engineers spend 15% of their working time on applicable planning and documentation activities (e.g., requirements and specification work, code discovery and understanding, technical documentation).

• Grok Build reduces the effort the composite requires for these activities by 35%. This assumption is below several of the improvements interviewees reported for individual planning, code-understanding, requirements, and documentation activities and recognizes variation across tasks and users.

• The fully burdened hourly rate for an engineer is $90.

• The composite organization recaptures 70% of the productivity gains and redirects that capacity toward productive engineering work.

• Forrester did not quantify the remaining 30% to account for normal workflow friction as well as additional analysis, experimentation, learning, and refinement of AI-assisted practices that may create value but do not translate directly into measurable additional output.

Risks. The scale of this benefit may vary from organization to organization based on:

• The number of engineers who actively use Grok Build.

• The proportion of engineering time spent on applicable planning, code-understanding, requirements, and documentation activities.

• The complexity and documentation quality of the applications and codebases being analyzed.

• Employees’ familiarity with the applications and codebases being analyzed.

• The types of requirements, specifications, and documentation being produced.

• Employees’ proficiency with AI-assisted and agentic development practices.

• The effort reduction realized across applicable planning and documentation activities.

• The extent to which the organization can redirect saved engineering time toward productive work.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $3.2 million.

Reduced Engineering And QA Effort

Evidence and data. Interviewees said Grok Build reduced engineering and QA effort across testing, code review, debugging and failure investigation, remediation, and related quality activities. They explained that their organizations used AI-assisted and agentic workflows to generate and expand tests, identify and investigate issues, review code changes, and remediate defects and vulnerabilities, which reduced the manual effort required to validate software as development output increased. This benefit captures internal engineering and QA labor efficiency and excludes automated-testing software maintenance savings quantified separately, as well as activities captured under coding and implementation, modernization and migration, and software planning and documentation.

• The IT director at an energy infrastructure organization estimated that Grok Build reduced manual test-design effort by approximately 30% to 60% and reduced testing and debugging effort by approximately 20% to 30%, depending on the use case. They noted these efficiencies reduced the engineering effort required to validate changes and investigate problems while development activity increased.

• The engineering manager at a financial services organization described using agentic workflows to extend automation beyond code generation into validation and remediation. They explained that engineers used agents to make code changes, run builds and tests inside the organization’s environment, monitor CI results, address identified problems, and prepare changes for human review. The interviewee explained that gaining the ability to have an agent write code and test it internally in the organization’s private cloud was an important requirement for these workflows.

• The director of product, AI platform, in the retail technology industry said Grok Build materially increased their organization’s ability to perform quality verification and testing as code generation increased. The organization also used Grok Build for code review and security-focused agent workflows. The interviewee characterized the improvement in quality verification and testing as significant, while noting that rapidly increasing development throughput continued to create additional quality-management demands.

• The engineering executive in the B2B software platform industry said their organization’s primary use cases for Grok Build are generating tests and expanding test coverage, remediating security vulnerabilities, reviewing pull requests, and conducting exploratory testing. The organization increasingly combined these activities into workflows where one engineer could run several agents in parallel across implementation, testing, review, and remediation tasks.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite has 180 engineers actively use Grok Build in Year 1, increasing to 220 in Year 2 and 225 in Year 3.

• Engineers spend 10% of their working time on testing, code review, debugging, remediation, and related quality activities.

• Grok Build reduces the effort required for these activities by 21%. The modeled improvement represents the portion of the efficiency gain attributed to Grok Build after accounting for the contribution of existing testing and development tools, automation, engineering processes, and human review.

• The fully burdened hourly rate for an engineer is $90.

• The composite organization recaptures 70% of the productivity gains and redirects that capacity toward productive engineering and quality work. The remaining 30% is not monetized to account for normal workflow friction as well as experimentation, learning, and refinement of AI-assisted quality practices that may create value but do not translate directly into measurable additional output.

Risks. The scale of this benefit may vary from organization to organization based on:

• The number of engineers who actively use Grok Build.

• The proportion of engineering time spent on testing, review, debugging, and remediation activities.

• The types, complexity, and volume of software changes that require testing and review.

• The maturity and automation of the organization’s existing testing, CI/CD, code-review, and remediation processes.

• Employees’ proficiency with AI-assisted and agentic quality workflows.

• The effort reduction attributable to Grok Build rather than existing tools, automation, processes, and human expertise.

• The extent to which the organization can redirect saved engineering time toward productive work.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $1.3 million.

Automated Testing Software Maintenance Cost Savings

Evidence and data. Interviewees said Grok provided opportunities to avoid technology costs by enabling engineering teams to build internal capabilities that reduced reliance on externally purchased software. This benefit only covers avoided external software maintenance costs; engineering labor efficiencies are not included. One interviewee noted their organization avoided a significant portion of the maintenance expenses associated with an automated testing solution after developing an internal alternative.

The IT director in the energy infrastructure industry reported their organization was preparing to renew an automated testing software license that included approximately $250,000 in annual maintenance costs. They said using Grok Build helped develop an internal alternative in a relatively short period of time, reducing the need to renew the existing software at its previous level.

The example represented external technology-spend avoidance rather than engineering labor productivity. The savings were therefore economically distinct from the engineering and QA efficiencies quantified separately in this study.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization incurs $250,000 annually in maintenance costs for an existing automated testing software solution.

• After developing an internal alternative with Grok Build, the composite organization eliminates 70% of the legacy software maintenance cost.

• Forrester retained the remaining 30% of the cost to recognize that the organization may continue to require portions of the legacy solution or related capabilities.

Risks. The scale of this benefit may vary from organization to organization based on:

• The cost of the organization’s existing automated testing software.

• The portion of the legacy software and associated maintenance expenses that can be eliminated with Grok Build.

• The functionality that must be retained in the existing testing solution.

• The organization’s ability to develop and maintain an internal alternative that meets its requirements.

• The extent to which avoided software costs are attributable to capabilities developed with Grok Build.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $370,000.

Unquantified Benefits

Benefits that provide value for the composite organization but are not quantified for this study include:

• Improved software quality and reliability. Interviewees reported improvements in software quality as teams increased their use of Grok Build for code generation, testing, review, and remediation. The engineering executive in the B2B software platform industry said their organization’s composite quality score increased roughly 9%, and customer escalations to engineering fell approximately 25% year over year during the transition to Grok Build, even as engineering throughput increased. The engineering executive said, “The thing I was most worried about was the effect on quality, but it held through the transition, and on several measures it improved.” The composite organization could similarly improve its ability to maintain software quality as development output increases. Quantifying this benefit would require connecting improvements in quality measures to avoided defects, incidents, escalations, or remediation costs.

• Improved access to institutional and technical knowledge. Interviewees said Grok Build made it easier for employees to understand unfamiliar and complex codebases without depending as heavily on individuals with historical knowledge of those systems. The IT director at an energy infrastructure organization described legacy applications that had been in place for 20 years and said, “Whereas before we were afraid of losing specific talent because of their tribal knowledge … we certainly can overcome that challenge a lot better with these tools now.” The composite organization can use Grok Build to make existing technical knowledge more accessible and reduce dependencies around unfamiliar systems and codebases. Quantifying this benefit would require measuring changes in onboarding time, specialist support requirements, or the business impact associated with knowledge concentration.

• Enhanced employee experience and access to modern development tools. Interviewees generally described increased enthusiasm and empowerment among employees using Grok Build, although experiences varied as engineering roles changed. The engineering manager at a financial services organization reported a 22% increase in developer happiness after deploying self-hosted agents. The director of product, AI platform, at a retail technology organization said access to advanced AI development tools has also become important to retaining technical talent, stating, “[Grok Build] is a tool that belongs on the list of tools that great companies use.” The composite organization could improve its engineering employee experience by equipping teams with tools that reduce repetitive work and support emerging ways of working. Quantifying this benefit would require establishing a relationship between improvements in employee experience and measurable outcomes such as retention, recruiting costs, or productivity.

• Greater business and engineering agility. Interviewees said lowering their organizations’ development effort changed which ideas and projects were economically practical to pursue. The engineering executive at the B2B software platform organization explained, “Work that we would have had to say no to is now affordable,” citing framework upgrades, legacy reporting, and dashboards as examples. Interviewees at the mining technology organization similarly described being able to prototype multiple alternatives before committing to an approach because development had become less time-intensive. The composite organization could use this additional agility to experiment with more ideas, develop prototypes earlier, and pursue initiatives that previously may not have justified scarce engineering capacity. Quantifying this benefit would require measuring incremental projects pursued and connecting those initiatives to resulting revenue, cost savings, or other business outcomes.

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Grok Build and later realize additional uses and business opportunities, including:

• Expand agentic development beyond engineering. The composite organization expects to extend Grok Build to a broader population of product managers, designers, subject matter experts, and other business users as it establishes the appropriate processes and guardrails. Interviewees anticipated this expansion. An AI engineering lead at the mining technology organization described the next stage as using AI to “really upscale everyone within the business” and enable employees to automate time-consuming workflows. The composite could use this broader adoption to increase the capacity of functions outside software engineering and enable more employees to turn business requirements and ideas into working solutions.

• Expand autonomous and orchestrated agent workflows. As the composite organization’s use of Grok Build matures, it could move beyond individual AI-assisted development activities toward greater orchestration of agents across the software development lifecycle. Interviewees described emerging approaches involving multiple agents working in parallel and automating activities across planning, implementation, testing, review, and remediation. The engineering executive at the B2B software platform organization described the direction as “one engineer running several agents in parallel lanes doing all of those things in combination.” Additional investment in processes, infrastructure, governance, and employee capabilities could allow the composite to automate more complex workflows and further increase its development capacity.

• Translate greater development capacity into new products and business opportunities. For the composite organization, continued improvements in the economics and speed of software development could lower the threshold for pursuing ideas that previously did not justify scarce engineering resources. Interviewees anticipated using this capacity to experiment more rapidly, pursue additional initiatives, and potentially create new customer-facing products and services. An AI engineering lead at the mining technology organization described the opportunity as enabling “the entire company engine, not just software engineering, to build and deliver products faster.” With additional investment and strategic focus, the composite could increasingly measure the value of Grok Build through incremental products, faster market entry, or revenue-generating opportunities rather than engineering efficiency alone.

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).