What Is Salesforce Agentforce? How It Works, Use Cases, Alternatives & Pricing 2025 Revealed

Q1: What Exactly is Salesforce Agentforce and Why Are Sales Teams Skeptical? [toc=Agentforce Overview]

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Salesforce Agentforce represents the company's "next generation" AI platform, developed separately from their earlier Einstein system. Launched as part of Salesforce's strategic pivot toward autonomous AI agents, Agentforce promises to deliver intelligent automation across customer-facing workflows. However, early market adoption reveals widespread skepticism, with sales teams actively questioning its effectiveness and ROI potential.

The skepticism stems from Agentforce's fundamental strategic shift away from Salesforce's B2B sales origins toward B2C customer success applications. This pivot has left traditional B2B sales organizations feeling underserved, as most Agentforce use cases focus on chatbots, customer support agents, and B2C commerce rather than complex sales cycle management that B2B teams require.

Traditional revenue intelligence platforms like Gong and Chorus, built over a decade ago, require extensive manual adoption and constant user intervention to extract value. These legacy systems create workflow friction by demanding sales teams manually interpret dashboards, configure complex rules, and maintain data hygiene—tasks that often go undone in fast-paced sales environments.

Modern AI-native platforms eliminate these adoption barriers through autonomous operation within existing workflows. Oliv.ai directly addresses the B2B sales segment abandoned by Salesforce's B2C focus, offering specialized agents like the Revenue Intelligence Agent and Deal Driver Agent that automatically capture conversation insights, update CRM records, and provide predictive deal guidance without requiring manual interaction.

Real User Feedback Reveals Implementation Challenges:

"The price of Agentforce is not clear and hard to find. Adoption is low because of the lack of knowledge on the subject as AI is a new field. Customers are finding issues in deploying and using agents in Salesforce."
— Anusha T., Web Developer G2 Verified Review

"My primary concern, which became clear even during early testing, is the significant learning curve involved in truly optimizing Agentforce. While its prompt-driven capabilities are incredibly exciting, getting consistent and accurate results isn't as simple as just 'telling' the agent what to do."
— Alessandro N., Salesforce Administrator G2 Verified Review

A revenue operations leader recently shared: "After evaluating Agentforce, we realized we needed a solution built specifically for B2B sales workflows, not adapted from B2C use cases. Oliv.ai delivered immediate pipeline visibility and deal insights that our sales team actually uses daily."

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Q2: How Does Agentforce Actually Work and What's the Atlas Reasoning Engine? [toc=How It Works]

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Core Architecture and Components

Salesforce Agentforce operates through the Atlas Reasoning Engine, branded as the "brain of the agent." This reasoning model processes natural language instructions and executes actions through Salesforce's broader ecosystem, including Data Cloud, Service Cloud, and Sales Cloud integrations.

Agent Builder Platform

The platform provides a low-code Agent Builder interface where administrators can configure custom AI agents using:

• Standard Actions: Pre-built workflows for common tasks like case creation, lead qualification, and opportunity updates
• Custom Actions: Flow-based automations tailored to specific business processes
• Topic Configuration: Defining conversation parameters and response guidelines
• Prompt Templates: Natural language instructions that guide agent behavior

Data Cloud Integration Requirements

Agentforce functionality depends heavily on Salesforce's Data Cloud platform, which serves as a Customer Data Platform (CDP) unifying disparate data sources. This integration enables:

• Unified Customer Profiles: Aggregating data from multiple touchpoints
• Real-time Data Access: Enabling agents to access current customer context
• Cross-platform Connectivity: Linking marketing, sales, and service data streams

Technical Implementation Process

Step 1: Enable Einstein and related dependencies in your Salesforce org
Step 2: Configure Data Cloud connections to relevant data sources
Step 3: Build agents using the Agent Builder with predefined templates or custom flows
Step 4: Set up topic modeling and conversation parameters
Step 5: Deploy agents through chat interfaces or embedded components

Performance and Limitations

User feedback indicates significant challenges with prompt engineering requirements and configuration complexity:

"Settings can be annoying at times... you need to activate Einstein and other stuff if you want to use Agentforce. But why don't you enable dependency if I directly wanna start Agentforce in a single click?"
— Shivam A., Product Researcher G2 Verified Review

How Oliv.ai Simplifies Implementation:
Unlike complex enterprise platforms that require extensive configuration, Oliv.ai alternatives eliminate these technical barriers through autonomous setup and built-in data intelligence, requiring only a one-time integration to automatically begin delivering revenue insights without complex configuration or prompt engineering expertise.

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Q3: What Are Agentforce's Real-World Use Cases and Why Are They Mostly B2C? [toc=Use Cases Analysis]

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Salesforce's strategic direction with Agentforce has concentrated primarily on B2C and customer success applications, reflecting their broader platform evolution away from core B2B sales functionality. Current agent types include merchant agents for e-commerce, buyer agents for procurement, campaign optimizer agents for marketing automation, and customer shopper agents that guide website visitors through purchase decisions.

This B2C focus stems from Salesforce's positioning of Agentforce as part of their Data Cloud strategy, emphasizing customer experience optimization over sales process automation. The platform excels in scenarios like healthcare patient engagement, retail customer support, and marketing campaign management—all distinctly different from complex B2B sales cycle requirements.

Traditional enterprise AI platforms attempt to serve broad markets but lack the specialized intelligence needed for intricate B2B sales processes. Complex deal cycles involving multiple stakeholders, extended evaluation periods, and consultative selling approaches require domain-specific AI that understands sales methodologies, pipeline management, and revenue forecasting—capabilities that generic customer service agents cannot provide. This is why many organizations are exploring Gong alternatives and revenue intelligence solutions specifically built for B2B sales.

Oliv.ai specifically addresses this gap with purpose-built B2B sales agents. The Meeting Assistant Agent automatically captures conversation intelligence from sales calls, the CRM Manager Agent maintains data hygiene and opportunity progression, and the Forecast Agent provides predictive analytics for pipeline management. These agents understand B2B sales nuances like deal qualification frameworks, competitive positioning, and stakeholder mapping.

User Experience Challenges with Current Use Cases:

"It can be complex to set up and often requires skilled administrators or developers to customize and integrate properly, which adds time and cost. Licensing fees can be high, especially as the number of agents grows."
— Verified User in Marketing and Advertising G2 Verified Review

"As much as I love what Agentforce can do, setting it up wasn't as smooth as I expected. The UI felt a bit clunky at times—especially when trying to manage multiple prompts or agent versions."
— Ayushmaan Y., Senior Associate G2 Verified Review

Measurable B2B Sales Impact:
A mid-market technology company reported that Oliv.ai's specialized B2B agents delivered 40% reduction in CRM data entry time, 25% faster deal progression, and 90% improvement in forecast accuracy within the first 30 days—metrics directly relevant to sales team performance rather than customer service efficiency. This contrasts sharply with traditional platforms like Gong that require months of configuration and training.

The fundamental disconnect between Agentforce's B2C orientation and B2B sales requirements has created a significant market opportunity for specialized revenue intelligence platforms that understand the complexity and strategic nature of enterprise sales processes. Organizations evaluating their options should consider comprehensive comparisons between generic enterprise AI and purpose-built B2B sales solutions.

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Q4: What Are the Critical Data Problems That Make Agentforce Fail in Real Sales Organizations? [toc=Data Problems]

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The AI industry's current "trough of disillusionment" reveals a critical oversight: most agentic AI platforms, including Salesforce Agentforce, underestimate the foundational importance of clean and well-structured sales data. Without accurate, modeled customer and sales data, AI agents struggle to provide reliable insights or automation.

Traditional AI solutions typically assume the presence of pristine CRM data. However, real-world sales environments contend with duplicate accounts, misassociated activities, incomplete opportunity records, and patchy data entry practices. These issues cause AI models to hallucinate or errantly associate customer activities, drastically reducing trust and usability. This is why many organizations are exploring Gong alternatives that address these fundamental data challenges.

Leading AI-native platforms like Oliv.ai sidestep these problems by integrating intelligent data cleaning into their agents. Oliv.ai's AI-driven approach automatically identifies and merges duplicate accounts and contacts, associates activities from calls and emails with correct opportunities, and contextualizes interactions based on content, providing a holistic and accurate sales narrative. Learn how Oliv.ai's AI-driven data cleaning outperforms legacy tools like Gong and other traditional platforms.

Unlike legacy platforms requiring extensive manual data cleanup projects spanning years, Oliv.ai offers rapid deployment—often fully operational within two weeks—delivering immediate value by improving CRM hygiene and enabling dependable AI-driven sales insights. Organizations comparing revenue intelligence solutions find that purpose-built AI platforms solve data problems more effectively than enterprise-wide solutions.

User Reviews Highlighting Data Challenges:

"Settings can be annoying at times. I can definitely imagine -- actually predict that in future you could change settings, find things via chat button right as well. - for example, you need to activate einstein and other stuff if you want to use agentforce. but why don't you enable dependency if i directly wanna start agentforce in a single click?"
— Shivam A., Product Researcher G2 Verified Review

"My primary concern, which became clear even during early testing, is the significant learning curve involved in truly optimizing Agentforce. While its prompt-driven capabilities are incredibly exciting, getting consistent and accurate results isn't as simple as just 'telling' the agent what to do."
— Alessandro N., Salesforce Administrator G2 Verified Review

"As much as I love what Agentforce can do, setting it up wasn't as smooth as I expected. The UI felt a bit clunky at times—especially when trying to manage multiple prompts or agent versions."
— Ayushmaan Y., Senior Associate G2 Verified Review

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Q5: Why Is Agentforce's Chat-Based Approach Leading to 'Barely Any Adoption'? [toc=Chat-Based UX]

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A critical flaw in Agentforce's current design is its heavy reliance on a chat-based user experience. Sales teams find themselves forced to manually engage with AI agents via chat interfaces separate from their core workflows, resulting in poor adoption and minimal impact.

Legacy AI platforms often present AI as chatbots or conversational agents that require context-switching and active user initiation. This interrupts natural sales activities and creates additional friction rather than streamlining workflows. Many organizations evaluating Gong vs other platforms discover that chat-based interfaces create adoption barriers across sales teams.

In the generative AI era, autonomous systems that embed seamlessly into existing sales tools and processes are becoming essential. Oliv.ai's platform integrates natively with CRM systems, automatically analyzing meetings, updating records, and generating insights without waiting for manual prompts or chatting. See how Oliv.ai contrasts with traditional products like Gong and other legacy solutions.

By eliminating the need for manual engagement, Oliv.ai achieves 90%+ adoption rates, compared to sub-20% seen in chat-based platforms like Agentforce. This results in significant time savings and higher data completeness, leading to improved sales execution.

User Voices on UX Challenges:

"As much as I love what Agentforce can do, setting it up wasn't as smooth as I expected. The UI felt a bit clunky at times—especially when trying to manage multiple prompts or agent versions."
— Ayushmaan Y., Senior Associate G2 Verified Review

"My primary concern, which became clear even during early testing, is the significant learning curve involved in truly optimizing Agentforce. While its prompt-driven capabilities are incredibly exciting, getting consistent and accurate results isn't as simple as just 'telling' the agent what to do."
— Alessandro N., Salesforce Administrator G2 Verified Review

"Lots of clicking to get select the right options. UX needs improvement. Everything opens in a new browser tabs clustering the browser. Lots of jumping back and forth between tabs to enable settings."
— Verified User in Consulting G2 Verified Review

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Q6: How Much Does Agentforce Really Cost and What Are the Hidden Implementation Expenses? [toc=Pricing & Costs]

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Salesforce Agentforce's pricing model is opaque and complicated by its dependencies on multiple Salesforce products and licensing layers. While exact prices vary, industry feedback suggests significant costs beyond the base Salesforce licenses.

Key cost components include:

• Salesforce core licenses ($200-$250 per user per month)
• Einstein AI add-ons (e.g., Sales Cloud Einstein, Einstein Account Insights)
• Data Cloud platform subscriptions
• Agentforce licenses
• Professional services for configuration and integration

This multi-layer purchasing requirement can escalate total expenses to $500 or more per user monthly, depending on organizational scale and usage. Organizations comparing pricing across platforms often discover hidden costs in enterprise AI implementations.

Implementation services add additional costs due to the platform's complexity, training needs for prompt engineering, and customization demands. Projects can range from several months to years before realizing measurable ROI. Many organizations find that specialized alternatives offer more transparent pricing structures.

In contrast, Oliv.ai offers a transparent, simplified pricing model focused on delivering value quickly with minimal setup effort. Its AI-native architecture eliminates costly integration layers, providing rapid ROI and clear cost predictability.

Pricing Transparency Insights:

"Also, the pricing caught us off guard. Once we started scaling to more users and use cases, the cost ramped up pretty quickly. We had to rethink a few workflows just to stay within budget."
— Ayushmaan Y., Senior Associate G2 Verified Review

"It can be complex to set up and often requires skilled administrators or developers to customize and integrate properly, which adds time and cost. Licensing fees can be high, especially as the number of agents grows."
— Verified User in Marketing and Advertising G2 Verified Review

"The price of Agentforce is not clear and hard to find. Adoption is low because of the lack of knowledge on the subject as AI is a new field. Customers are finding issues in deploying and using agents in Salesforce."
— Anusha T., Web Developer G2 Verified Review

Q7: What Are Sales Teams Actually Saying About Agentforce Performance? [toc=User Feedback]

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Sales teams evaluating Salesforce Agentforce express a mix of cautious optimism and frustration. While the platform promises innovative AI-driven assistance, many users report that adoption remains limited due to usability challenges and unclear ROI. Current market sentiment reveals widespread uncertainty, with sales teams actively questioning whether the platform delivers measurable value.

Traditional enterprise AI platforms like Agentforce often over-promise transformational outcomes while under-delivering on practical implementation. Organizations invest heavily in complex deployments only to discover adoption challenges, usability issues, and inconsistent performance that fails to meet initial expectations or justify significant licensing costs. This pattern is similar to challenges seen with Gong implementations and other legacy platforms.

Specialized AI platforms focused exclusively on revenue intelligence prioritize proven, measurable outcomes with transparent capabilities and realistic implementation timelines. Rather than making broad promises across multiple use cases, they deliver documented results in specific areas that directly impact sales performance and revenue generation.

Oliv.ai delivers quantified ROI through specific metrics: 40% reduction in manual CRM data entry, 25% faster deal cycle velocity, and 90% improvement in forecast accuracy within the first 30 days of deployment. The Revenue Intelligence Agent and Deal Progression Agent work autonomously within existing sales workflows, eliminating adoption friction while providing immediate, tangible value.

Authentic User Feedback from G2 Reviews:

"It felt like giving our support reps a smart assistant who never sleeps! The impact was immediate—within the first week, the team reported a noticeable drop in average case handling time."
— Ayushmaan Y., Senior Associate G2 Verified Review

"Lots of clicking to get select the right options. UX needs improvement. Everything opens in a new browser tabs clustering the browser. Lots of jumping back and forth between tabs to enable settings."
— Verified User in Consulting G2 Verified Review

"The pricing caught us off guard. Once we started scaling to more users and use cases, the cost ramped up pretty quickly. We had to rethink a few workflows just to stay within budget."
— Ayushmaan Y., Senior Associate G2 Verified Review

Organizations implementing Oliv.ai report 90%+ adoption rates because sales teams don't need to learn new interfaces or remember to engage with AI agents—the intelligence operates automatically within their existing workflows, delivering immediate value without behavioral change requirements.

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Q8: How Does Agentforce's Limited Sales Coaching Compare to Advanced AI Training Solutions? [toc=Sales Coaching]

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Salesforce Agentforce's coaching capabilities remain fundamentally limited, offering basic "live role play on one or two opportunities" without identifying individual seller weaknesses, creating personalized development paths, or measuring skill improvement over time. This generic approach fails to address the sophisticated coaching needs of modern B2B sales organizations.

Traditional AI coaching platforms provide scripted scenarios and generic feedback without analyzing individual performance patterns or correlating coaching outcomes with actual deal results. These legacy systems lack the conversational intelligence required to identify specific skill gaps and create targeted improvement programs that evolve with seller performance. This contrasts with modern revenue intelligence platforms that offer comprehensive coaching capabilities.

Advanced AI coaching platforms analyze actual sales conversations across entire deal portfolios to detect individual communication patterns, objection handling effectiveness, and closing techniques. They automatically generate personalized coaching recommendations, simulate realistic role-play scenarios based on actual customer interactions, and track measurable skill development over time.

Oliv.ai's Conversation Intelligence Agent analyzes every sales interaction to identify individual seller strengths and weaknesses, automatically generating customized coaching materials and measuring improvement through correlation with deal outcomes. The Sales Performance Agent tracks skill development across the entire sales process, providing managers with data-driven insights for targeted coaching interventions.

User Feedback on Coaching Limitations:

"It still needs some serious debugging. I built the default agent, went well, then went to create a second agent and could not get past an error when I clicked Create."
— Jessica C., Senior Business Analyst G2 Verified Review

"It's not as robust just yet but it will be as it continues to learn."
— Omer M., Salesforce Admin G2 Verified Review

A recent case study demonstrated Oliv.ai's coaching effectiveness: sales teams using personalized AI coaching showed 35% improvement in objection handling and 28% increase in deal closure rates within 90 days, compared to organizations using generic role-play training modules. This performance advantage stems from analyzing real conversation data rather than relying on simulated scenarios.

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Q9: What Are the Best Agentforce Alternatives for B2B Sales Organizations? [toc=Alternatives]

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The market for "Agentforce alternatives" shows minimal competition, with very few AI agent platforms specifically targeting B2B sales needs. This limited competitive landscape indicates that most sales organizations haven't found effective AI agent solutions addressing their complex, multi-stakeholder deal environments and extended sales cycles.

Traditional enterprise AI platforms like Microsoft Copilot and Google Duet AI focus on broad market applicability, leaving specialized B2B sales requirements unaddressed. These platforms require extensive customization, expensive implementation projects, and ongoing technical expertise that most sales organizations lack, resulting in poor adoption and limited value realization. Organizations often end up comparing multiple alternatives before finding suitable solutions.

Specialized B2B sales AI platforms provide purpose-built functionality with deep domain expertise, faster implementation timelines, and transparent pricing models designed specifically for revenue organizations. They understand the nuances of complex deal cycles, pipeline management, and sales forecasting that generic enterprise AI cannot address effectively.

Oliv.ai specifically targets the underserved B2B sales segment with 2-week deployment, out-of-the-box functionality, and AI-driven data cleaning that solves fundamental CRM challenges. The Pipeline Intelligence Agent and Deal Acceleration Agent address core B2B sales workflows without requiring extensive customization or technical implementation projects.

User Insights on Alternative Needs:

"Can be complex to set up and customize. Expensive, especially for smaller teams. Steep learning curve for new users."
— Shubham G., Senior BDM G2 Verified Review

The fundamental disconnect between Agentforce's B2C orientation and B2B sales requirements has created a significant market opportunity for specialized revenue intelligence platforms that understand the complexity and strategic nature of enterprise sales processes.

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Q10: Should Your Sales Organization Invest in Agentforce or Consider Purpose-Built Alternatives? [toc=Investment Decision]

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The decision between Salesforce Agentforce and specialized AI platforms requires careful evaluation of your organization's current Salesforce ecosystem, data quality status, AI readiness, and specific B2B sales requirements. Organizations heavily invested in Salesforce may find Agentforce appealing, but implementation complexity and B2C focus often limit B2B sales effectiveness.

Traditional enterprise AI implementations like Agentforce typically require 2-3 year projects, extensive data cleanup initiatives, expensive consulting engagements, and specialized prompt engineering expertise. These substantial investments often fail to deliver measurable ROI for sales organizations, particularly those needing immediate pipeline visibility and deal acceleration capabilities. Many organizations end up evaluating comprehensive platform comparisons to find better alternatives.

Modern specialized AI platforms provide immediate value through out-of-the-box functionality, built-in data cleaning, and expert-guided implementation that delivers results within weeks rather than years. They eliminate the complexity and cost associated with traditional enterprise AI while providing superior outcomes for revenue-focused use cases.

Oliv.ai offers expert consultation with company founders who serve as AI strategy advisors, helping organizations assess data readiness, define implementation roadmaps, and deploy proven revenue intelligence solutions with guaranteed outcomes. This founder-led approach ensures strategic guidance throughout the AI adoption process.

Strategic Investment Considerations:

• Current Salesforce Investment: Heavy Salesforce users may prefer ecosystem consistency despite limitations
• Data Quality Status: Organizations with clean CRM data have more options; those with data challenges need AI-driven cleaning
• Timeline Requirements: Immediate results favor specialized platforms; long-term strategic alignment may favor enterprise solutions
• Budget Constraints: Complex enterprise licensing vs. transparent per-user pricing models
• Technical Resources: Available prompt engineering expertise vs. out-of-the-box functionality needs

User Perspective on Investment Decisions:

"The price of Agentforce is not clear and hard to find. Adoption is low because of the lack of knowledge on the subject as AI is a new field. Customers are finding issues in deploying and using agents in Salesforce."
— Anusha T., Web Developer G2 Verified Review

Call to Action:
Talk to the founders of Oliv.ai as AI strategy experts to assess your specific organizational context, evaluate data readiness, and determine the optimal approach for implementing revenue intelligence that delivers measurable results quickly and efficiently. Unlike complex enterprise implementations, Oliv.ai's proven approach ensures you get immediate value from your AI investment.

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