As 50,000 attendees descend on Salesforce’s Dreamforce conference this week, the enterprise software giant is making its most aggressive bet yet on artificial intelligence agents, positioning itself as the antidote to what it calls an industry-wide “pilot purgatory” where 95% of enterprise AI projects never reach production.
The company on Monday launched Agentforce 360, a sweeping reimagination of its entire product portfolio designed to transform businesses into what it calls “agentic enterprises” — organizations where AI agents work alongside humans to handle up to 40% of work across sales, service, marketing, and operations.
“We are truly in the agentic AI era, and I think it’s probably the biggest revolution, the biggest transition in technology I’ve ever experienced in my career,” said Parker Harris, Salesforce’s co-founder and chief technology officer, during a recent press briefing. “In the future, 40% of the work in the Fortune 1000 is probably going to be done by AI, and it’s going to be humans and AI actually working together.”
The announcement comes at a pivotal moment for Salesforce, which has deployed more than 12,000 AI agent implementations over the past year while building what Harris called a “$7 billion business” around its AI platform. Yet the launch also arrives amid unusual turbulence, as CEO Marc Benioff faces fierce backlash for recent comments supporting President Trump and suggesting National Guard troops should patrol San Francisco streets.
Why 95% of enterprise AI projects never launch
The stakes are enormous. While companies have rushed to experiment with AI following ChatGPT’s emergence two years ago, most enterprise deployments have stalled before reaching production, according to recent MIT research that Salesforce executives cited extensively.
“Customers have invested a lot in AI, but they’re not getting the value,” said Srini Tallapragada, Salesforce’s president and chief engineering and customer success officer. “95% of enterprise AI pilots fail before production. It’s not because of lack of intent. People want to do this. Everybody understands the power of the technology. But why is it so hard?”
The answer, according to Tallapragada, is that AI tools remain disconnected from enterprise workflows, data, and governance systems. “You’re writing prompts, prompts, you’re getting frustrated because the context is not there,” he said, describing what he called a “prompt doom loop.”
Salesforce’s solution is a deeply integrated platform connecting what it calls four ingredients: the Agentforce 360 agent platform, Data 360 for unified data access, Customer 360 apps containing business logic, and Slack as the “conversational interface” where humans and agents collaborate.
Slack becomes the front door to Salesforce
Perhaps the most significant strategic shift is the elevation of Slack — acquired by Salesforce in 2019 for $27.7 billion — as the primary interface for Salesforce itself. The company is effectively reimagining its traditional Lightning interface around Slack channels, where sales deals, service cases, and data insights will surface conversationally rather than through forms and dashboards.
“Imagine that you maybe don’t log into Salesforce, you don’t see Salesforce, but it’s there. It’s coming to you in Slack, because that’s where you’re getting your work done,” Harris explained.
The strategy includes embedding Salesforce’s Agentforce agents for sales, IT service, HR service, and analytics directly into Slack, alongside a completely rebuilt Slackbot that acts as a personal AI companion. The company is also launching “Channel Expert,” an always-on agent that provides instant answers from channel conversations.
To enable third-party AI tools to access Slack’s conversational data, Salesforce is releasing a Real-Time Search API and Model Context Protocol server. Partners including OpenAI, Anthropic, Google, Perplexity, Writer, Dropbox, Notion, and Cursor are building agents that will live natively in Slack.
“The best way to see the power of the platform is through the AI apps and agents already being built,” Rob Seaman, a Salesforce executive, said during a technical briefing, citing examples of startups “achieving tens of thousands of customers that have it installed in 120 days or less.”
Voice and IT service take aim at new markets
Beyond Slack integration, Salesforce announced major expansions into voice-based interactions and employee service. Agentforce Voice, now generally available, transforms traditional IVR systems into natural conversations that can update CRM records, trigger workflows, and seamlessly hand off to human agents.
The IT Service offering represents Salesforce’s most direct challenge to ServiceNow, the market leader. Mudhu Sudhakar, who joined Salesforce two months ago as senior vice president for IT and HR Service, positioned the product as a fundamental reimagining of employee support.
“Legacy IT service management is very portals, forms, tickets focused, manual process,” Sudhakar said. “What we had a few key tenets: conversation first and agent first, really focused on having a conversational experience for the people requesting the support and for the people providing the support.”
The IT Service platform includes what Salesforce describes as 25+ specialized agents and 100+ pre-built workflows and connectors that can handle everything from password resets to complex incident management.
Early customers report dramatic efficiency gains
Customer results suggest the approach is gaining traction. Reddit reduced average support resolution time from 8.9 minutes to 1.4 minutes — an 84% improvement — while deflecting 46% of cases entirely to AI agents. “This efficiency has allowed us to provide on-demand help for complex tasks and boost advertiser satisfaction scores by 20%,” said John Thompson, Reddit’s VP of sales strategy and operations, in a statement.
Engine, a travel management company, reduced average handle time by 15%, saving over $2 million annually. OpenTable resolved 70% of restaurant and diner inquiries autonomously. And 1-800Accountant achieved a 90% case deflection rate during the critical tax week period.
Salesforce’s own internal deployments may be most telling. Tallapragada’s customer success organization now handles 1.8 million AI-powered conversations weekly, with metrics published at help.salesforce.com showing how many agents answer versus escalating to humans.
Even more significantly, Salesforce has deployed AI-powered sales development representatives to follow up on leads that would previously have gone uncontacted due to cost constraints. “Now, Agentforce has an SDR which is doing thousands of leads following up,” Tallapragada explained. The company also increased proactive customer outreach by 40% by shifting staff from reactive support.
The trust layer problem enterprises can’t ignore
Given enterprise concerns about AI reliability, Salesforce has invested heavily in what it calls the “trust layer” — audit trails, compliance checks, and observability tools that let organizations monitor agent behavior at scale.
“You should think of an agent as a human. Digital labor. You need to manage performance just like a human. And you need these audit trails,” Tallapragada explained.
The company encountered this challenge firsthand when its own agent deployment scaled. “When we started at Agentforce at Salesforce, we would track every message, which is great until 1,000, 3,000,” Tallapragada said. “Once you have a million chats, there’s no human, we cannot do it.”
The platform now includes “Agentforce Grid” for searching across millions of conversations to identify and fix problematic patterns. The company also introduced Agent Script, a new scripting language that allows developers to define precise guardrails and deterministic controls for agent behavior.
Data infrastructure gets a major upgrade
Underlying the agent capabilities is significant infrastructure investment. Salesforce’s Data 360 includes “Intelligent Context,” which automatically extracts structured information from unstructured content like PDFs, diagrams, and flowcharts using what the company describes as “AI-powered unstructured data pipelines.”
The company is also collaborating with Databricks, dbt Labs, and Snowflake on the “Universal Semantic Interchange,” an attempt to standardize how different platforms define business metrics. The pending $8 billion acquisition of Informatica, expected to close soon, will expand metadata management capabilities across the enterprise.
The competitive landscape keeps intensifying
Salesforce’s aggressive AI agent push comes as virtually every major enterprise software vendor pursues similar strategies. Microsoft has embedded Copilot across its product line, Google offers agent capabilities through Vertex AI and Gemini, and ServiceNow has launched its own agentic offerings.
When asked how Salesforce’s announcement compared to OpenAI’s recent releases, Tallapragada emphasized that customers will use multiple AI tools simultaneously. “Most of the time I’m seeing they’re using OpenAI, they’re using Gemini, they’re using Anthropic, just like Salesforce, we use all three,” he said.
The real differentiation, executives argued, lies not in the AI models but in the integration with business processes and data. Harris framed the competition in terms familiar from Salesforce’s founding: “26 years ago, we just said, let’s make Salesforce automation as easy as buying a book on Amazon.com. We’re doing that same thing. We want to make agentic AI as easy as buying a book on Amazon.”
The company’s customer success stories are impressive but remain a small fraction of its customer base. With 150,000 Salesforce customers and one million Slack customers, the 12,000 Agentforce deployments represent roughly 8% penetration — strong for a one-year-old product line, but hardly ubiquitous.
The company’s stock, down roughly 28% year to date with a Relative Strength rating of just 15, suggests investors remain skeptical. This week’s Dreamforce demonstrations — and the months of customer deployments that follow — will begin to provide answers to whether Salesforce can finally move enterprise AI from pilots to production at scale, or whether the “$7 billion business” remains more aspiration than reality.
Original Source: https://venturebeat.com/ai/salesforce-bets-on-ai-agents-to-fix-what-it-calls-a-usd7-billion-problem-in
Original Source: https://venturebeat.com/ai/salesforce-bets-on-ai-agents-to-fix-what-it-calls-a-usd7-billion-problem-in
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