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Quoting should be simple. But for most sales reps, it’s anything but. They are forced to hunt for the right combination of SKUs, interpret complex pricing rules, check legal terms, and wait on approvals, all while under pressure to move fast. A single mistake can lead to delays, rework, or worse: sending an incorrect quote. This inefficiency directly slows down deal velocity and revenue. That’s why Salesforce is introducing Agentforce for Revenue. It brings digital labor that takes on routine work like quoting, follow-ups, and data entry, so every rep can focus on building relationships and driving revenue. Embedded in Revenue Cloud, this solution combines the power of humans and AI agents to streamline the entire quote-to-cash process, from quoting and contracting to ordering and invoicing, with greater speed, accuracy, and confidence. Instant quotes with Agentforce for Revenue Agentforce empowers reps to create accurate, customized quotes in seconds. Reps simply describe what they need — like “Quote a new generator with the usage-based energy pack” — and Agentforce instantly generates the quote, automatically pulling the correct products, pricing, and terms. Salesforce is already using Agentforce internally and has seen a 75% decrease in quoting time along with an 87% reduction in clicks for its own sales team. And it’s not just Salesforce seeing results. Agentforce is designed to deliver quoting speed and accuracy to customers across any industry, from manufacturing to healthcare. Take AdMed, Inc., a leader in pharmaceutical and biotech training, which is now leveraging Revenue Cloud to modernize its sales process. “Revenue Cloud is transforming the way we do business,” said Bill Francy, President of Client Services at AdMed, Inc. “We’re currently piloting the new quoting agent, and we expect it to cut manual work, accelerate deal cycles, and get quotes to clients faster than ever. It’s not just about efficiency. It’s about unlocking more closed-won opportunities and scaling smarter.”  Block Quote Faster, smarter product configuration Generating a quote is only the first step. To truly unlock speed and accuracy across the entire quoting journey, sellers also need a smarter way to configure products. After a quote is kicked off by Agentforce, sellers use Revenue Cloud’s enhanced Product Configurator to quickly tailor complex offerings, including quotes with more than a thousand line items. Unlike traditional CPQ tools that rely solely on rigid, rule-heavy systems, Salesforce’s new constraint-based logic engine augments those traditional approaches, giving customers the flexibility to handle whatever complexity their business demands. It uses bidirectional rules and point-and-click templates to dramatically reduce rule maintenance and authoring time. Think of it as a GPS for quoting that guides reps to valid configurations in real time, speeding up time-to-quote. Why it matters Today’s revenue operations are more complex than ever. According to Deloitte, 71% of B2B executives struggle with manual, fragmented sales processes — and 13% of deals are lost because of disconnected tools. As hybrid monetization models become the norm, reps don’t have time to manually piece together subscriptions, usage-based pricing, and service offerings. Revenue Cloud, powered by Agentforce, eliminates that complexity, unifying all transaction types on a single quote, and carrying the transaction data through to the order and invoice. How it works To make this possible, Salesforce rebuilt its CPQ solution as the all-new Revenue Cloud: the industry’s first composable, AI agent-powered revenue platform. Its API-first architecture embeds every revenue business process within accessible APIs, making it easy for agents to sit atop and interact with those processes. “Salesforce CPQ helped usher in the second wave of revenue management by enabling recurring revenue at scale,” said Meredith Schmidt, EVP and GM of Revenue Cloud at Salesforce. “Now, with Revenue Cloud, we’re delivering the third wave: revenue management powered by an API-first, composable, and agent-ready platform that lets revenue flow seamlessly across every channel, from sales reps and partner portals to self-service and field service.” Agentforce and Revenue Cloud unify structured and unstructured data (purchase history, product catalogs, connected asset insights) for timely, accurate actions. This data, harmonized in Data Cloud, powers Agentforce’s agentic AI, enabling teams to deploy autonomous, goal-oriented agents that can reason and act. Unlike traditional AI assistants that merely suggest next steps, Agentforce executes tasks end-to-end, freeing sellers for higher-value work. Throughout the entire process, data is protected by the Salesforce Trust Layer. Agents operate securely within employee-specific permissions, helping to ensure both agent and employee access only authorized data and actions. This allows every quote to comply with company policies, pricing rules, and customer data, significantly reducing time-to-quote. Dig deeper These innovations are part of Salesforce’s Summer ’25 release, the biggest yet for Revenue Cloud, and all are available today. With this release, Revenue Cloud provides teams with greater power, flexibility, and speed than ever before. Additional capabilities include: Seamless Workflows with Slack and CRM: Agentforce is available in Slack via API, as well as from the opportunity, quote, and account records within Salesforce. This means sellers can start, edit, and finalize quotes from wherever they are, all within the same flow of work. Quotes follow the transaction, so there’s no rekeying or duplication. Revenue Cloud Billing: As a complete revenue platform, Revenue Cloud’s API-first architecture empowers users to create their own agents to support any process across the quote-to-cash lifecycle, including billing. With all data from quote to invoice on a single platform, Revenue Cloud Billing facilitates accurate and transparent invoicing. Revenue Management Intelligence: Sales, finance, and operations teams can accelerate decision-making with real-time visibility into their entire revenue lifecycle. Tableau Next, embedded in Revenue Cloud, provides a clear view of key metrics like pricing trends, order flow, and revenue performance, empowering teams to act instantly on insights. For current customers Salesforce remains committed to supporting current Salesforce CPQ customers, as it continues to be a robust solution for many businesses. Customers can renew contracts, add licenses, and count on full support. For those ready to begin their migration to Revenue Cloud as their complete, agentic revenue platform, Salesforce offers a strong ecosystem of trusted partners to help guide the transition.

Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, today announced the release of the AI Energy Score, a first-of-its-kind benchmarking tool that enables AI developers and users to evaluate, identify, and compare the energy consumption of AI models. Salesforce also announced it will be the first AI model developer to disclose the energy efficiency data of its proprietary models under the new framework. Why it matters: The AI Energy Score aims to address the lack of transparency about the environmental impact of AI models. Similar to how ENERGY STAR transformed energy efficiency standards for appliances and electronics, this initiative establishes a clear, trusted benchmark for AI model sustainability.  Go deeper: The AI Energy Score will debut at the AI Action Summit, where leaders from over 100 countries, the private sector, and civil society will convene to harness AI for good. By enhancing transparency, the score can drive market preference for efficient models and incentivize sustainable AI development. Recognized by the French Government and the Paris Peace Forum for its transformative potential, the AI Energy Score features: Standardized Energy Ratings: A standardized framework for measuring and comparing AI model energy efficiency.  Public Leaderboard: A comprehensive leaderboard that features scores for 10 common AI tasks — such as text generation, image generation, and summarization — performed by 166 models, including Salesforce’s SFR-Embedding, xLAM, and SF-TextBase.  Benchmarking Portal: A platform where AI developers can submit their open or proprietary AI models to be evaluated and added to the leaderboard. Open models can be automatically tested, while closed models can be evaluated through a secured testing sandbox. Recognizable Energy Use Label: A new 1- to 5-star label that rates AI model energy use, with five stars indicating the highest efficiency. This helps developers and users easily identify and choose more sustainable models. Once rated, AI developers can generate standardized labels to share their models’ energy score, with built-in guidance on the proper label display for visibility and impact. Block Quote How Salesforce addresses sustainability through Agentforce: Last fall, the company introduced Agentforce, the agentic layer of the Salesforce Platform for deploying autonomous AI agents across any business function. Agentforce offers tools to build and customize agents, as well as a library of ready-to-use skills for sales, service, marketing, commerce, Tableau, Slack, and more. Agentforce is built with sustainability at its core, delivering high performance while minimizing environmental impact. Unlike DIY AI approaches that require energy-intensive model training for each customer, Agentforce is optimized out-of-the-box, eliminating the need for costly, or carbon-heavy training. Its agentic architecture goes beyond reliance on a single large language model (LLM), instead leveraging efficient small language models combined with agentic reasoning and other advanced AI tools, significantly reducing energy consumption. For example, Salesforce’s SFR-RAG is a small language model optimized for accurate, reliable tasks. It cites sources, extracts precise facts, and handles complex questions, delivering trustworthy answers with greater efficiency and lower energy use. Additionally, Agentforce leverages tailored data and metadata from Salesforce Data Cloud and the Salesforce Platform, enabling high accuracy and responsiveness while minimizing wasted computational resources.