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Total Economic Impact
Cost Savings And Business Benefits Enabled By Agentforce
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY Salesforce, November 2025
Total Economic Impact
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY Salesforce, November 2025
Customer service that is always on, infinitely scalable, and personalized will become a reality as the shift to AI-first customer service unfolds. With the ability to autonomously perform tasks, make decisions, and interact with data across systems, AI agents are transforming customer service operations traditionally hindered by overly complex systems that are difficult to manage, expensive to scale, and increasingly misaligned with the evolving needs of customers and enterprises. The future of customer service will be defined by those that embrace AI’s ability to drive scalable innovation and sustained competitive advantage by using AI agents to resolve basic inquiries, automate complex work, and assist service representatives in managing cases more efficiently.1
Agentforce is an AI agent platform that enables customers to unlock a scalable digital labor force through autonomous AI agents that work alongside human employees. Customers can use Agentforce to develop AI agents that serve a wide variety of use cases and industry-specific needs, using existing workflows, data, and integrations within Salesforce and third-party systems. Agentforce helps organizations deliver high-quality customer service experiences at scale by deploying AI agents that autonomously handle and deflect inquiries and execute tasks in the case lifecycle.
Salesforce commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Agentforce for customer service.2 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Agentforce on their organizations.
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed six decision-makers with experience using Agentforce. For the purposes of this study, Forrester aggregated the experiences of the interviewees and combined the results into a single composite organization, which is a multimillion-dollar company with global operations where customer service is essential for retention and business growth.
Interviewees said that prior to using Agentforce, their organizations typically had limited self-service, chatbot, and automation capabilities to support customer service operations and personnel, requiring customer service representatives to handle the majority of cases manually. As organizations’ customer bases and service demands increased, inefficient case management processes and an inability to deflect basic inquiries became increasingly burdensome, leading to suboptimal customer experiences and high costs to serve.
After the investment in Agentforce, the interviewees used AI agents to intelligently take in, manage, and resolve customer inquiries and automate tasks during the case lifecycle. Key results from their investments include improved case deflection rates, reduced case handling times, decreased costs to serve, and improved customer experiences.
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits for the composite organization include:
A case deflection rate of 35% and a reduction in case handling time of 50%. The composite organization uses Agentforce to handle and resolve basic customer inquiries autonomously without intervention from customer service representatives. For more complex cases, Agentforce collects relevant information before transferring customers to live support, enabling faster case resolution and lower handling times. It also automates post-call administrative tasks, such as developing case summaries and updating customer records in Salesforce, helping service representatives quickly move on to the next case. Over three years, the labor savings are worth $2.8 million for the composite organization.
Unquantified benefits. Benefits that provide value for the composite organization but are not quantified for this study include:
Operational efficiency. As the composite’s customer base grows, Agentforce helps the organization deliver consistent and effective customer service experiences without needing to hire additional headcount.
Improved customer experiences. The composite organization uses Agentforce to reduce wait times for support and improve its overall efficiency and effectiveness in providing customers with information and resolving their requests, supporting customer satisfaction and retention.
Faster time to value. The composite organization uses Agentforce to leverage existing customer data in Salesforce, reducing the time to value for AI agents.
Security and trust. The composite benefits from Salesforce’s trust layer and robust security features, which extend to Agentforce; they enable the composite to safely deploy AI agents while maintaining its security and data privacy.
Costs. Three-year, risk-adjusted PV costs for the composite organization include:
Agentforce consumption. The composite organization incurs $430,000 in Flex Credit costs for Agentforce consumption over three years.
Agent implementation, user training, and ongoing management. The composite organization incurs $134,000 in labor costs for AI agent implementation, user training, and ongoing management.
The financial analysis that is based on the interviews found that a composite organization experiences benefits of $2.8M over three years versus costs of $564K, adding up to a net present value (NPV) of $2.2M and an ROI of 396%.
Customer service case deflection with Agentforce
Time to positive return on investment
Return on investment (ROI)
Benefits PV
Net present value (NPV)
| Role | Industry | Region | Employees | Revenue |
|---|---|---|---|---|
| Chief technology officer | Healthcare | US HQ, national operations | 10 to 20 | N/A |
| Executive general manager | Technology | APAC HQ, national operations | 115 | $36M |
| Chief technology officer | Professional services | US HQ, national operations | 750 | $150M to $250M |
| Head of the CIO office | Electronics | US HQ, global operations | 550 | $434M |
| VP of client sales and support | Auto | US HQ, national operations | 15,000 | $2.5B to $3B |
| Vice president of CRM | Education | UK HQ, global operations | 17,000 | $4.7B |
Prior to the investment in Agentforce, the interviewees’ organizations had limited self-service and automation capabilities for customer service across channels, requiring customer service representatives to handle the majority of cases manually. In some cases, their organizations had attempted to implement chatbots but found that they were ineffective in resolving most cases without intervention. Interviewees shared that their organizations struggled with common challenges, including:
High costs to serve. Interviewees’ existing chatbots lacked the ability to understand and take action outside of predefined topics, provide nuanced or personalized information beyond scripted responses, and interact with other systems to execute tasks, which limited customers’ ability to resolve issues independently. Basic, high-volume inquiries, such as order status updates and simple “how-to” questions, consumed significant amounts of support rep time due to the lack of automation and chatbot-enabled self-service capabilities, increasing the cost to serve customers. Several interviewees shared that case volumes rose as their organization’s customer base grew, which required increases in staffing and labor costs to keep up. The executive general manager at a technology company said: “We have about 35 agents who support our customers. As our customer base continues to grow, we can’t simply scale by adding more staff to meet demand. We needed to evolve our tooling and leverage AI to support that growth more effectively and efficiently.”
Manual processes and siloed systems. Interviewees described how manual workflows — such as inventory checks, appointment scheduling, and administrative tasks — reduced productivity for customer service staff and increased case handling and wait times. The VP of client sales and support at an auto company shared that their customer service representatives often had to manually confirm key details, such as inventory availability and insurance coverage for requested services, which significantly extended case handling times. In some instances, service reps struggled to access necessary information immediately due to siloed systems, resulting in follow-up calls and delayed resolution.
Long wait times and extra strain in peak seasons. Customers faced extended wait times, especially during periods of peak demand. Basic inquiries consumed service rep bandwidth, preventing them from focusing on more complex requests better suited to their expertise and problem-solving skills. Hiring and training staff to meet short-term demand was also inefficient and costly. The executive general manager at a technology company noted that high volumes of simple “how-to” requests and manual post-call administration work made it challenging to maintain target wait times during peak periods of the day. Similarly, the CTO at a professional services organization that provides accounting services shared that their limited chatbot functionalities hindered service efficiency, leading to long wait times, especially during tax season: “Inbound calls and chats handled by live agents were just taking too long, especially in the midst of our tax season when it got super busy. Wait times were long, even though someone might be handling five chats at once. They weren’t doing a great job, and customers weren’t getting answers immediately.”
Poor customer experiences. Interviewees explained that inefficient customer service processes led to suboptimal customer experiences. Both customers with simple inquiries and those with more complex needs often failed to receive timely and effective support, creating friction in engaging with the organizations’ employees, products, and services. In some cases, these slow and frustrating experiences affected customer loyalty, increasing the risk of churn.
Based on the interviews, Forrester constructed a TEI framework, a composite company, and an ROI analysis that illustrates the areas financially affected. The composite organization is representative of the interviewees’ organizations, and it is used to present the aggregate financial analysis in the next section. The composite organization has the following characteristics:
Description of composite. The composite organization is a multimillion-dollar company with global operations and thousands of employees. Customer service is an essential pillar of the composite’s operations, as it ensures customers receive timely support in utilizing its products and services. The composite has 50 customer service representatives who answer questions, resolve issues, and provide guidance in order to support customer satisfaction and retention. The composite organization receives 500,000 support cases annually in Year 1, with the case volume growing by 5% year over year as the business expands.
Deployment characteristics. To keep pace cost-effectively with its growing customer base and their support needs, the composite organization uses Agentforce to build AI agent capabilities that take in customer requests via the website, telephone, and email channels; leverage knowledge bases to answer questions; and perform case management tasks, such as issuing refunds, processing order changes, and updating case information and customer profiles in Salesforce. For more complex cases, the AI agent collects basic intake information before transferring the case to a live representative.
Global company
500,000 annual customer service cases
50 customer service representatives
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Customer service savings | $1,058,958 | $1,129,013 | $1,203,426 | $3,391,397 | $2,799,909 |
| Total benefits (risk-adjusted) | $1,058,958 | $1,129,013 | $1,203,426 | $3,391,397 | $2,799,909 |
Evidence and data. Interviewees reported that implementing Agentforce enabled them to provide more efficient customer service operations and ensure customers received faster, high-quality support for their inquiries and requests, even during peak periods in demand. They noted that AI support agents intelligently answered questions and resolved support requests, including order status updates, refunds, and troubleshooting support, deflecting cases away from human reps. For more complex cases requiring intervention from customer service reps, interviewees said that AI agents collected basic intake information upfront and helped customers be ready with the right information before being transferred: This reduced the time spent on the initial triage and context gathering. Interviewees shared that Agentforce impacted:
Case deflection. The interviewees’ organizations deployed agents to take in and resolve straightforward customer inquiries autonomously without requiring escalation to customer service reps. Agents referenced knowledge bases — such as product documentation, troubleshooting guides, and policy information — and worked across systems to help customers find relevant information and perform tasks, such as appointment scheduling and refunds, by themselves. As a result, the interviewees’ organizations saw case deflection rates ranging from 15% to 37% in the first year of their agent deployments. The chief technology officer at a professional services company shared that they deployed agents across customer service channels to take in customer requests, provide answers from knowledge base information, and schedule appointments with tax advisors when necessary. This deflected cases away from customer service reps and reduced calls with tax advisors, improving the rate of deflection and resolution without human intervention from under 10% with their previous chatbot to over 30% with Agentforce.
Case handling times. Interviewees reported that AI agents collected relevant information for cases that needed to be escalated to human support reps. This reduced the amount of time those service reps spent gathering context, improving overall support efficiency and case handling times. The head of the CIO office at an electronics company said that in more complex scenarios, such as device returns, AI agents prompted customers to prepare the necessary information before transferring them to a live representative, which streamlined resolution processes. Similarly, the VP of client sales and support at an auto company reported that Agentforce verifies customer information, such as vehicle details and insurance coverage, and updates case information in Service Cloud; this expedites support workflows, reduces case handling time, and reduces intake questions and manual work for customer service representatives.
Post-case administration. The executive general manager at a technology company shared that their organization built an agent to automate post-call administration tasks so that service reps can move on to their next case more quickly. They explained that the agent autogenerates case summaries that document the customer’s requests, resolutions for the case, and other relevant notes within their Salesforce platform for future reference by support reps and account teams. As a result, they measured significant reductions in post-call wrap-up time and average wait times: “Before Agentforce, we measured the average post-call wrap-up time at roughly 5.5 minutes. Now, we’ve managed to reduce that by 30%. That means our agents can get back on the phone faster so we can hit our target wait times even during peaks. During our POC [proof of concept] and rolling forward to today, we’ve reduced our average wait time by 70%, which has helped us hit our target of below 3 minutes.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite organization experiences a 5% growth in customer service cases year over year, receiving 500,000 cases in Year 1, 525,000 in Year 2, and 551,250 in Year 3.
Agentforce deflects 25% of cases in Year 1, 30% in Year 2, and 35% in Year 3..
The average case handling time before Agentforce is 8 minutes.
The fully burdened hourly rate for a customer service representative is $23.
Cases that aren’t initially resolved by the Agentforce agent are transferred to customer service representatives. These staff experience a 50% reduction in case handling time as the AI agent completes the initial intake work. Once these cases are resolved, Agentforce generates a summary of the case and updates customer records, avoiding 2 minutes of manual post-call administration work per case.
Risks. Forrester recognizes that these results may not be representative of all experiences, and the benefit will vary depending on:
The number of support cases an organization receives, the complexity of those cases, and the channel mix.
Customer service representative training and their effectiveness in resolving cases.
The case handling time before Agentforce.
The rates for customer service representatives.
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 $2.8 million.
Case deflection
Reduction in case handling time
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| A1 | Customer service cases received | Composite | 500,000 | 525,000 | 551,250 | |
| A2 | Percentage of cases deflected with Agentforce | Interviews | 25% | 30% | 35% | |
| A3 | Cases deflected by Agentforce | A1*A2 | 125,000 | 157,500 | 192,938 | |
| A4 | Case handling time before Agentforce (minutes) | Interviews | 8 | 8 | 8 | |
| A5 | Fully burdened hourly rate for a customer service representative | Composite | $23 | $23 | $23 | |
| A6 | Subtotal: Case deflection savings | A3*A4*(A5/60) | $383,333 | $483,000 | $591,677 | |
| A7 | Reduction in case handling time for customer service representatives | Interviews | 50% | 50% | 50% | |
| A8 | Avoided case handling time for customer service representatives (minutes) | A4*A7 | 4 | 4 | 4 | |
| A9 | Avoided manual post-call administration effort per case (minutes) | Interviews | 2 | 2 | 2 | |
| A10 | Subtotal: Case handling and administration savings | (A1-A3)*(A5/60)*(A8+A9) | $862,500 | $845,250 | $824,118 | |
| At | Customer service savings | A6+A10 | $1,245,833 | $1,328,250 | $1,415,795 | |
| Risk adjustment | ↓15% | |||||
| Atr | Customer service savings (risk-adjusted) | $1,058,958 | $1,129,013 | $1,203,426 | ||
| Three-year total: $3,391,397 | Three-year present value: $2,799,909 | |||||
Spotlight: Additional Use Cases For Agentforce
Beyond customer service, interviewees said that they are developing AI agents for other use cases, including:
Sales development. Several interviewees noted that their organizations have deployed Agentforce to assist in engaging prospects and supporting lead conversion.
The vice president of CRM at an education company noted that their organization built a proof of concept for an AI agent that could engage prospective customers through their website by answering product questions, sharing relevant content, and passing qualified leads to sales reps. The goal of the AI agent is to create incremental sales opportunities and prioritize leads so sales reps know where to focus time. They said: “We have thousands of sales opportunities across our company. Increasing that by even 1% could translate into millions of dollars in additional revenue.”
The VP of client sales and support at an auto company shared that their organization deployed an AI agent to engage website visitors shopping for auto repair services. The AI agent captures contact and vehicle details, verifies insurance coverage, checks inventory availability across locations, and schedules services in near real time. By streamlining the booking process and ensuring part availability, the organization saw a reduction in abandoned website leads and appointment cancellations. They shared: “Bailout through the website was roughly around 20% to 25% before. Right now, we’ve decreased that to 8%.”
The chief technology officer at a healthcare company described two AI agents designed to engage prospects and increase referrals. A lead sourcing agent engaged potential patients responding to ads by answering questions, capturing prospect information in Salesforce, and scheduling onboarding calls with providers. The organization also built a sales development agent that automated outreach to local doctors to secure referral relationships for the company’s care services.
Administration and customer communications. The chief technology officer at a professional services company shared that they were in the early stages of using Agentforce to automate client communications and reminders, replacing manual work previously handled by administrative staff. The AI agent proactively monitors client records and activity to identify missing documents, information, or required actions for each customer account; it then triggers personalized outreach. By automating account monitoring, document chasing, and outreach, the interviewee conservatively expects to achieve an estimated 10% reduction in administrative overhead. They said: “The agent looks at the client records to determine what communications they should receive. If the client is missing data or needs to take action, it sends messages prompting them to complete those tasks … We think it’s a 10% savings overall just because our advisor’s assistants won’t be chasing down data and documents that we’re now going to collect through the agent.”
HR and IT support. The head of the CIO office at an electronics company noted that their organization had recently launched AI agents to support IT help desk and HR support workflows. Employees can submit inquiries and requests through Slack: AI agents attempt to resolve these using existing knowledge base content, thus offloading simple requests from IT and HR teams. They shared: “Now, employees can interact with Agentforce in Slack using natural language. Instead of filling out forms and waiting for IT to respond, they simply describe their problem, and the agent provides troubleshooting tips leveraging our knowledge base. Often, that effectively resolves straightforward issues, but if not, a ticket is automatically created in our IT service management platform. Similarly, with the HR agent we launched, employees can post directly in the HR Slack channel and receive immediate responses. This approach has been highly successful and helps offload routine cases from our HR team.”
Healthcare delivery. The chief technology officer at a healthcare company detailed how their organization leveraged Agentforce to improve patient experiences and outcomes. Their organization configured Agentforce’s out-of-the-box sales coach functionality to train and coach patient care teams to deliver onboarding, support, and services more effectively and empathetically. They shared: “We’ve repurposed the sales coach functionality for what we call a provider coach and loaded it with reams of cutting-edge, state-of-the-art psychometric guidance based on transactional analysis, psychology research, and training resources. It’s helping them manage patients with greater empathy and make them feel that we understand them and their issues. Patients seem more receptive to and compliant with care plans [with this approach], and therefore we’ve seen measurable outcomes that are increasing on the patient wellness side.”
Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:
Operational efficiency. The interviewees said that Agentforce helped their organizations deliver effective customer service experiences at scale without needing to hire additional headcount. By using AI agents to handle and deflect straightforward inquiries and automate workflows, the organizations positioned themselves for customer growth while providing consistent and personalized support experiences. The chief technology officer at a professional services company noted that Agentforce helped their organization cost-effectively manage rising customer service needs as their client base grew by 40% from the prior year — and even projected a decline in customer service costs in the future. Similarly, the executive general manager at a technology company said: “With Agentforce, we are continuing to grow our customer base at 3% to 4% each year, but we don’t have to increase our FTE [full-time employee] count at all. When we made the business case, we positioned Agentforce as an opportunity for FTE avoidance, and that seems to be bearing fruit today.”
Improved customer experience. The vice president of CRM at an education company said: “To me, the value of Agentforce is around creating a frictionless experience. It makes working with our company easier, because clients can self-serve and get information and the support they need quickly.” The chief technology officer at a professional services company reported that Agentforce helped them reduce wait times and ensure clients received timely and accurate support during high-demand periods like tax season, which supported customer satisfaction and retention. They said: “Regardless of whether it is tax season or not, our clients will receive a high-quality support experience. It’s a significant improvement in client experience, which can be hard to quantify [the impact of]. We know that we will save on human capital, but the real value is going to come in renewals and retention from just having a significantly better client experience.”
Time to value. The interviewees noted that Agentforce helped their organizations use and extend data and capabilities within their existing Salesforce solutions, improving the time to value compared to alternative solutions. With Agentforce and the support of Data Cloud, agents can easily tap into existing customer profiles and data to deliver timely and personalized support experiences without extensive integration efforts or the need to build redundant systems. The executive general manager at a technology company detailed the advantage of using Salesforce rather than a bespoke AI customer service solution they evaluated: “We have the benefit of everyone and everything being in Salesforce today, including account information, email records, and more. With [a different vendor], the time to get up and running as well as the costs for consulting to support the implementation, subscriptions, and the internal labor to manage a separate system would have far exceeded that of Agentforce.”
Security and trust. The interviewees described how their organizations benefit from security tools and configurable guardrails designed to keep data secure. The chief technology officer at a healthcare company said: “Salesforce’s trust layer underpins its entire ecosystem, and enterprise-level trust, verification, and compliance features are deeply integrated with Agentforce, allowing us to apply real-time filtering rules and make sure that access is verified and vetted. We could create that security posture in other systems but would have to maintain it ourselves. Having those features integrated deeply in Salesforce is incredibly valuable.”
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Agentforce and later realize additional uses and business opportunities, including:
Future innovation with Agentforce. Interviewees saw opportunities to innovate and build out a variety of use cases in the future. The vice president of CRM at an education company said: “We have a lot of ideas for Agentforce on our list. For example, we’re thinking about developing an agent that supports sales by coaching reps on how to win more deals. Additionally, Salesforce recently acquired Spiff, a sales compensation tool that we use. I see an opportunity to use Agentforce with that tool to tell the reps which deals to focus on, what meetings to prep for, and how they’re performing against quotas — almost like a personal assistant.” The chief technology officer at a professional services company shared: “The real value that we’re hoping to realize this upcoming year is orchestrating workflows after a client interaction. So, this year, the agent can give clients an answer. Next year, it’s going to give them their answer but also remind them that they are behind on their payments and provide them with a link to get caught up. Or, when they’re engaging with our chat agent, it will be able to identify that a new employee was hired, recommend our payroll services, and further that opportunity. So, it’s not just addressing the immediate interaction but adding a workflow to it on the backend. We see a lot of value in those types of use cases that will be agentically driven. And we’re going to expand out into everything next year.”
Increased AI agent autonomy. Organizations may find that implementing Agentforce gives them a starting point for their journey to agentic AI systems that can adapt, learn, and take autonomous action. The interviewees’ organizations were able to use Agentforce to develop retrieval-augmented generation (RAG) and solver agents that operate within predefined workflows and scripted rules with narrow levels of autonomy, offering a lower-risk entry point to validate value, build trust, and develop internal skill sets. These initial successes supported a phased approach toward more advanced use cases, involving higher levels of autonomy, adaptability, and orchestration: AI agents will then be able to control and execute more complex actions and coordinate with other agents, unlocking opportunities to reimagine business processes and drive higher levels of productivity.3
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Btr | Agentforce costs | $0 | $165,000 | $173,250 | $181,913 | $520,163 | $429,855 |
| Ctr | Agent implementation, user training, and ongoing management | $40,496 | $37,663 | $37,663 | $37,663 | $153,485 | $134,158 |
| Total costs (risk-adjusted) | $40,496 | $202,663 | $210,913 | $219,576 | $673,648 | $564,013 |
Evidence and data. Salesforce offers conversation-based, Flex-Credit-based, and per-user licensing options for Agentforce. Agentforce costs for the interviewees’ organizations were typically based on Flex Credit consumption, in which specific actions executed by AI agents, such as updating records and answering inquiries, consume a set number of credits. Pricing may vary. Contact Salesforce for additional details.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite organization incurs Agentforce consumption costs of $150,000 in Year 1, $157,500 in Year 2, and $165,375 in Year 3 as the number of cases that Agentforce impacts grows over time.
Risks Forrester recognizes that these results may not be representative of all experiences. The impact of this cost will vary depending on the following:
The number of Flex Credits consumed by each customer service case.
Agentforce pricing models.
Results. To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $430,000.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| B1 | Agentforce consumption costs | Interviews | $150,000 | $157,500 | $165,375 | |
| Bt | Agentforce consumption costs | B1 | $150,000 | $157,500 | $165,375 | |
| Risk adjustment | ↑10% | |||||
| Btr | Agentforce costs (risk-adjusted) | $0 | $165,000 | $173,250 | $181,913 | |
| Three-year total: $520,163 | Three-year present value: $429,855 | |||||
Evidence and data. Interviewees’ organizations incurred costs in the following areas:
Agent implementation. Interviewees reported implementation timelines for their customer service use cases ranging from two weeks to six months. They described internal implementation teams comprising one to five FTEs and including roles such as Salesforce admins, architects, developers, application managers, and customer service managers. Additional contributors often included technical and customer service leaders and other business stakeholders. Key steps of the implementation process included integrating data sources, which was often accomplished through Data Cloud; refining knowledge bases; and developing, testing, and fine-tuning AI agents. Several of the interviewees’ organizations participated in beta programs for Agentforce and received discounted professional services support for their implementations.
User training. Interviewees stated that customer service reps needed minimal training and change management, as Agentforce primarily deflected cases and automated tasks rather than significantly altering core workflows.
Ongoing management. Interviewees reported that ongoing management of their AI agents required between 0.05 and 0.75 FTEs, covering tasks such as user support, troubleshooting, and performance monitoring.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The average fully burdened annual salary of a resource involved in implementation and ongoing management efforts is $131,000.
The implementation team spends 550 hours on developing and deploying AI agents to support customer service use cases.
One-quarter of an FTE’s time is dedicated to managing the customer service agents.
The composite organization has 50 customer service reps who receive 30 minutes of training to familiarize themselves with AI agent functionalities.
The average fully burdened hourly rate for a customer service rep is $23.
Risks. Forrester recognizes that these results may not be representative of all experiences. The impact of this cost will vary depending on the following:
The technical skill sets required to develop and maintain AI agents.
Agent training requirements.
The need for and associated costs of systems integrator or professional services support.
The number of AI agents built on Agentforce to support customer service operations.
The complexity of the AI agents developed, including the number of tasks they can perform, their level of autonomy and reasoning capabilities, and the extent to which developers use out-of-the-box functionality.
The quality of existing knowledge bases.
Data integration requirements.
Training requirements for customer service representatives.
Ongoing management and maintenance requirements.
Additional costs incurred to implement and utilize Salesforce Data Cloud.
Results. To account for these risks, Forrester adjusted this cost upward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $134,000.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| C1 | Fully burdened annual salary for resources involved in implementation and ongoing management | Composite | $131,000 | $131,000 | $131,000 | $131,000 |
| C2 | Implementation effort (hours) | Interviews | 550 | |||
| C3 | Subtotal: Implementation costs | C1/2,080*C2 | $34,639 | |||
| C4 | Customer service representatives receiving training | Composite | 50 | |||
| C5 | Training per customer service representative (hours) | Composite | 0.5 | |||
| C6 | Fully burdened hourly rate of a customer service representative | A5 | $23 | |||
| C7 | Subtotal: Training costs | C4*C5*C6 | $575 | |||
| C8 | FTEs dedicated to ongoing management | Interviews | 0.25 | 0.25 | 0.25 | |
| C9 | Subtotal: Ongoing management costs | C1*C8 | $32,750 | $32,750 | $32,750 | |
| Ct | Agent implementation, user training, and ongoing management | C3+C7+C9 | $35,214 | $32,750 | $32,750 | $32,750 |
| Risk adjustment | ↑15% | |||||
| Ctr | Agent implementation, user training, and ongoing management (risk-adjusted) | $40,496 | $37,663 | $37,663 | $37,663 | |
| Three-year total: $153,485 | Three-year present value: $134,158 | |||||
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($40,496) | ($202,663) | ($210,913) | ($219,576) | ($673,648) | ($564,013) |
| Total benefits | $0 | $1,058,958 | $1,129,013 | $1,203,426 | $3,391,397 | $2,799,909 |
| Net benefits | ($40,496) | $856,295 | $918,100 | $983,851 | $2,717,750 | $2,235,896 |
| ROI | 396% | |||||
| Payback | <6 months |
The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback period for the composite organization’s investment. Forrester assumes a yearly discount rate of 10% for this analysis.
These risk-adjusted ROI, NPV, and payback period values are determined by applying risk-adjustment factors to the unadjusted results in each Benefit and Cost section.
The initial investment column contains costs incurred at “time 0” or at the beginning of Year 1 that are not discounted. All other cash flows are discounted using the discount rate at the end of the year. PV calculations are calculated for each total cost and benefit estimate. NPV calculations in the summary tables are the sum of the initial investment and the discounted cash flows in each year. Sums and present value calculations of the Total Benefits, Total Costs, and Cash Flow tables may not exactly add up, as some rounding may occur.
From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in Agentforce.
The objective of the framework is to identify the cost, benefit, flexibility, and risk factors that affect the investment decision. Forrester took a multistep approach to evaluate the impact that Agentforce can have on an organization.
Interviewed Salesforce stakeholders and Forrester analysts to gather data relative to Agentforce.
Interviewed six decision-makers at organizations using Agentforce to obtain data about costs, benefits, and risks.
Designed a composite organization based on characteristics of the interviewees’ organizations.
Constructed a financial model representative of the interviews using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewees.
Employed four fundamental elements of TEI in modeling the investment impact: benefits, costs, flexibility, and risks. Given the increasing sophistication of ROI analyses related to IT investments, Forrester’s TEI methodology provides a complete picture of the total economic impact of purchase decisions. Please see Appendix A for additional information on the TEI methodology.
Benefits represent the value the solution delivers to the business. The TEI methodology places equal weight on the measure of benefits and costs, allowing for a full examination of the solution’s effect on the entire organization.
Costs comprise all expenses necessary to deliver the proposed value, or benefits, of the solution. The methodology captures implementation and ongoing costs associated with the solution.
Flexibility represents the strategic value that can be obtained for some future additional investment building on top of the initial investment already made. The ability to capture that benefit has a PV that can be estimated.
Risks measure the uncertainty of benefit and cost estimates given: 1) the likelihood that estimates will meet original projections and 2) the likelihood that estimates will be tracked over time. TEI risk factors are based on “triangular distribution.”
The present or current value of (discounted) cost and benefit estimates given at an interest rate (the discount rate). The PV of costs and benefits feed into the total NPV of cash flows.
The present or current value of (discounted) future net cash flows given an interest rate (the discount rate). A positive project NPV normally indicates that the investment should be made unless other projects have higher NPVs.
A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.
The interest rate used in cash flow analysis to take into account the time value of money. Organizations typically use discount rates between 8% and 16%.
The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.
Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
1 Source: The Customer Service Solutions Landscape, Q3 2025, Forrester Research, Inc., September 29, 2025; Customer Service Must Evolve To Unlock AI’s Full Potential, Forrester Research, Inc., July 15, 2025; Agentic AI Glossary, Forrester Research, Inc., October 8, 2025.
2 Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
3 Source: Agentic AI Agents Are A Rare Sighting, Forrester Research, Inc., April 14, 2025.
Readers should be aware of the following:
This study is commissioned by Salesforce and delivered by Forrester Consulting. It is not meant to be used as a competitive analysis.
Forrester makes no assumptions as to the potential ROI that other organizations will receive. Forrester strongly advises that readers use their own estimates within the framework provided in the study to determine the appropriateness of an investment in Agentforce. For any interactive functionality, the intent is for the questions to solicit inputs specific to a prospect’s business. Forrester believes that this analysis is representative of what companies may achieve with Agentforce based on the inputs provided and any assumptions made. Forrester does not endorse Salesforce or its offerings. Although great care has been taken to ensure the accuracy and completeness of this model, Salesforce and Forrester Research are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein. The interactive tool is provided ‘AS IS,’ and Forrester and Salesforce make no warranties of any kind.
Salesforce reviewed and provided feedback to Forrester, but Forrester maintains editorial control over the study and its findings and does not accept changes to the study that contradict Forrester’s findings or obscure the meaning of the study.
Salesforce provided the customer names for the interviews but did not participate in the interviews.
Kara Luk
November 2025
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