Salesforce Raises Annual Revenue and Profit Forecasts as AI Products Boost Enterprise Demand
Salesforce has raised its full-year revenue and profit forecasts for fiscal 2027 after stronger enterprise demand for artificial-intelligence products helped the cloud-software company deliver one of its strongest quarters in recent years.
For the fiscal year ending January 2027, Salesforce now expects revenue of $46.1 billion to $46.4 billion, up from its previous guidance of $45.9 billion to $46.2 billion. The company also raised its adjusted earnings-per-share forecast to $16.67–$16.71, from an earlier range of $14.06–$14.12. (Reuters)
The stronger outlook came as Salesforce reported second-quarter revenue of approximately $11.3 billion, up 11% year on year, while adjusted diluted earnings per share reached $5.90, more than doubling from a year earlier. (Salesforce Investor Relations)
But the most important numbers increasingly sit inside Salesforce's AI portfolio.
Annual recurring revenue from Agentforce and Data 360 reached nearly $3.9 billion, growing more than 210% year on year, while Agentforce ARR alone surpassed $1.5 billion, up more than 240%. (Salesforce Investor Relations)
The results suggest Salesforce is beginning to convert years of investment in generative AI, data infrastructure and autonomous software agents into measurable enterprise revenue.
Salesforce Raises FY27 Revenue Guidance
Salesforce now expects fiscal 2027 revenue of:
$46.1 billion to $46.4 billion.
That implies approximately:
11% to 12% year-on-year growth.
The new range is $200 million higher than the company's previous reported guidance. On a constant-currency basis, Salesforce described the increase as approximately $300 million. (Salesforce Investor Relations)
Revenue Guidance Includes Acquisition Contribution
The revised forecast includes expected contributions from Salesforce's pending acquisitions of:
Contentful
and
Fin.
The company expects both transactions to close independently during its fiscal third quarter. (Salesforce Investor Relations)
Salesforce said the guidance increase reflects approximately:
$100 million of additional organic growth,
$200 million from the pending acquisitions,
and a roughly $100 million foreign-exchange headwind. (Salesforce Investor Relations)
This means AI-driven organic momentum remains important even though acquisitions will contribute to headline growth.
Profit Forecast Also Moves Higher
Salesforce raised its full-year adjusted diluted EPS outlook to:
$16.67–$16.71.
That compares with its previous forecast of:
$14.06–$14.12. (Reuters)
The increase reflects a combination of stronger operating performance and a reduced share count as Salesforce continues a major accelerated share-repurchase programme.
Second-Quarter Revenue Reaches $11.3 Billion
Salesforce reported second-quarter fiscal 2027 revenue of approximately:
$11.3 billion.
That represented:
11% year-on-year growth. (Salesforce Investor Relations)
Subscription and support revenue reached:
$10.8 billion
and increased approximately 12%.
The company's Informatica acquisition contributed $456 million to total quarterly revenue and $440 million to subscription and support revenue. (Salesforce Investor Relations)
Adjusted Earnings More Than Double
Non-GAAP diluted earnings per share reached:
$5.90
during the quarter.
That represented growth of:
103% year on year. (Salesforce Investor Relations)
GAAP diluted earnings per share reached $4.29, up 119%.
The sharp improvement demonstrates how Salesforce is combining renewed revenue momentum with continued focus on profitability.
Operating Margin Remains Strong
Salesforce reported a non-GAAP operating margin of:
34.1%.
Its GAAP operating margin reached:
20.5%. (Salesforce Investor Relations)
The company continues to balance AI investment with an operating model significantly more focused on margins than during earlier periods of aggressive expansion.
AI and Data ARR Nears $4 Billion
One of the quarter's most important metrics was annual recurring revenue from:
Agentforce and Data 360.
That figure reached nearly:
$3.9 billion
and increased:
more than 210% year on year. (Salesforce Investor Relations)
Salesforce CEO Marc Benioff said AI and data ARR is approaching the $4 billion threshold.
The figure demonstrates that AI is becoming a material business rather than merely a product roadmap.
Agentforce ARR Exceeds $1.5 Billion
Agentforce annual recurring revenue surpassed:
$1.5 billion.
That represented growth of:
more than 240% year on year. (Salesforce Investor Relations)
Beginning in the second quarter, Salesforce's Agentforce ARR metric also includes AI offerings such as Slackbot and Headless 360.
Even allowing for the broader definition, the growth rate illustrates strong enterprise adoption.
Agentforce Is Salesforce’s AI-Agent Platform
Agentforce allows companies to build and deploy autonomous or semi-autonomous AI agents within Salesforce.
These agents can perform tasks across areas such as:
sales,
customer service,
commerce,
and internal operations.
Instead of simply generating text, an AI agent can interact with enterprise data and execute actions.
That distinction is central to Salesforce's strategy.
AI Agents Are Moving Beyond Chatbots
Traditional enterprise chatbots mainly answered questions.
Agentic AI attempts to do more.
An agent may:
identify a customer request,
retrieve relevant information,
update a record,
trigger a workflow,
and complete part of the business process.
This makes AI significantly more valuable to enterprises if it can operate reliably.
Salesforce Has Delivered 7 Billion Agentic Work Units
Salesforce said Agentforce and Slack had delivered approximately:
7 billion Agentic Work Units
to date. (Salesforce Investor Relations)
An Agentic Work Unit represents a discrete task executed by an AI agent in production.
During the second quarter alone, Salesforce recorded:
3.2 billion AWUs
representing 97% quarter-on-quarter growth. (Salesforce Investor Relations)
This metric gives investors another way to measure actual AI usage rather than simply contracts signed.
AI Usage Is Increasing Rapidly
AI software economics depend partly on whether customers actually use the products after purchasing them.
A large number of contracted licences can look impressive.
But enterprise value ultimately comes from productive usage.
The rapid increase in Agentic Work Units suggests companies are moving from AI pilots toward production workloads.
Bookings for Premium AI Products More Than Doubled
Salesforce said bookings for Agentforce One Edition and Agentforce for Apps more than doubled quarter on quarter. (Salesforce Investor Relations)
These premium offerings integrate AI capabilities directly into Salesforce's sales and service products.
That matters because Salesforce does not need customers to purchase an entirely separate AI platform.
It can embed AI into software enterprises already use.
Installed Customer Base Is Major Advantage
Salesforce has spent decades building customer relationships across large enterprises.
Those companies already use Salesforce for:
CRM,
service,
marketing,
commerce,
and analytics.
That installed base provides a natural distribution channel for AI products.
Instead of convincing a company to adopt an entirely new vendor, Salesforce can add AI capabilities to existing workflows.
Data 360 Is Central to AI Strategy
AI agents need enterprise data.
Without accurate information, an agent cannot reliably answer questions or execute workflows.
Salesforce's Data 360 platform is designed to unify customer and enterprise information so that AI systems can work with it.
During the quarter, Data 360 ingested approximately:
104 trillion records
up 355% year on year. (Salesforce Investor Relations)
Zero Copy Data Growth Accelerates
Salesforce said approximately:
82 trillion records
were ingested through Zero Copy architecture.
That represented:
731% year-on-year growth. (Salesforce Investor Relations)
Zero Copy allows companies to access data without repeatedly duplicating it across different systems.
This can simplify enterprise data architectures and reduce unnecessary movement of information.
AI Cannot Work Well Without Enterprise Context
A generic AI model may understand language.
But it does not automatically know:
a company's customers,
contracts,
policies,
pricing,
or internal workflows.
Enterprise AI needs access to this context.
Salesforce's competitive strategy is built around controlling the layer connecting AI models to corporate data and business logic.
Salesforce Is Expanding Headless 360
Salesforce has also expanded Headless 360, designed to turn Salesforce applications into reusable capabilities that authorised AI agents can access through open standards. (Salesforce)
The approach allows agents to securely discover and use:
business logic,
workflows,
data,
and actions
within Salesforce.
This reflects a broader transition in enterprise software.
Applications may increasingly become infrastructure used by AI agents rather than interfaces operated only by humans.
AI Agents Could Become New Software Interface
Traditional enterprise software requires employees to open an application and perform actions manually.
Agentic systems could change that.
A worker might instruct an AI agent:
“Update the customer opportunity and schedule a follow-up.”
The agent could perform those tasks across several systems.
If this model develops successfully, enterprise software usage could shift from:
humans navigating applications
to
AI agents invoking enterprise capabilities.
Slack Is Becoming Part of Salesforce’s AI Strategy
Slack also delivered strong momentum during the quarter.
Salesforce said Slack produced its fastest quarterly net-new annual order value growth since its acquisition.
Slackbot users increased more than:
150% quarter on quarter. (Salesforce Investor Relations)
This suggests Salesforce increasingly views Slack as a conversational interface through which employees interact with AI and enterprise systems.
Slack Could Become the AI Front Door
Many knowledge workers already spend substantial time inside workplace messaging applications.
If AI assistants are embedded there, employees may not need to open multiple business applications manually.
They can potentially ask Slackbot to:
retrieve data,
summarise information,
or trigger business actions.
This turns Slack from a communication product into part of Salesforce's agentic interface.
cRPO Growth Accelerates to 14%
Salesforce reported current remaining performance obligation of:
$33.5 billion.
That grew:
14% year on year in constant currency. (Salesforce Investor Relations)
cRPO represents contracted revenue expected to be recognised during the coming 12 months.
Investors closely watch the measure because it can provide visibility into future subscription growth.
Total Remaining Performance Obligation Reaches $66.3 Billion
Total remaining performance obligation reached:
$66.3 billion
and increased:
11% year on year. (Salesforce Investor Relations)
This backlog gives Salesforce significant visibility because much of its business operates through recurring subscription contracts.
New Order Growth Is Strongest in Four Years
Salesforce President and Chief Financial and Operating Officer Robin Washington said net-new annual order value growth was the strongest in approximately:
four years. (Salesforce Investor Relations)
The company expects this momentum to support organic revenue reacceleration during the second half of the fiscal year.
That is particularly important because investors have been waiting for Salesforce to demonstrate that AI can improve its underlying organic growth rate.
Enterprise AI Spending Is Broadening
Salesforce is not alone in reporting stronger AI demand.
Cloud and enterprise-software companies increasingly describe customers moving beyond experimentation into production deployments.
Businesses are attempting to use AI for:
customer support,
sales productivity,
software development,
data analysis,
and operational automation.
This creates a potentially enormous enterprise software cycle.
Companies Want AI to Produce Measurable Returns
The first phase of generative AI was dominated by experimentation.
Companies tested chatbots and copilots.
The second phase is more financially demanding.
Chief executives want to know:
How much labour does this save?
Does it increase revenue?
Does it improve customer service?
Can it complete business workflows?
Agentforce is designed around those questions.
AI Agents Could Reduce Cost-to-Serve
Customer service represents a straightforward example.
A company may employ thousands of service agents handling repetitive issues.
AI agents can potentially resolve part of that workload automatically.
If successful, this reduces the cost per customer interaction.
That creates measurable economic value.
Sales Productivity Is Another Opportunity
Sales employees spend substantial time on administration.
They may need to:
update CRM records,
research customers,
prepare follow-ups,
and summarise calls.
AI agents can automate parts of this work.
Salespeople can then spend more time with customers.
For Salesforce, this creates a natural opportunity because CRM is already its core business.
AI Can Increase the Value of Existing Salesforce Products
This is strategically important.
Salesforce does not need AI to become an entirely separate business.
AI can make existing products more valuable.
A customer may pay more for Sales Cloud if AI substantially improves salesperson productivity.
The same applies to Service Cloud and other products.
AI therefore potentially raises both:
product adoption
and
pricing power.
Salesforce Is Expanding Anthropic Partnership
Alongside its earnings announcement, Salesforce expanded its relationship with Anthropic around a new initiative known as Claudeforce, bringing Claude models more deeply into Salesforce's enterprise AI ecosystem. (Reuters)
The partnership reflects Salesforce's broader strategy of supporting multiple AI models rather than depending exclusively on a single model provider.
Enterprises Want Model Choice
Large companies may prefer different AI models for different tasks.
One model may perform better at:
coding.
Another may be stronger at:
reasoning,
or long-context analysis.
Enterprise software platforms therefore increasingly need to support multiple models.
Salesforce wants its data and workflow layer to remain valuable regardless of which foundation model a customer chooses.
This Could Be Salesforce’s Strategic Moat
Foundation models are evolving rapidly.
No single AI-model provider can be guaranteed permanent leadership.
Salesforce therefore has an incentive to remain model-neutral.
Its most defensible assets may instead be:
customer data,
workflows,
permissions,
business logic,
and integrations.
Those are much harder for a new AI startup to replicate.
AI Governance Is Critical for Enterprises
Companies cannot give autonomous AI unrestricted access to corporate systems.
Agents need:
permissions,
security,
auditability,
and governance.
A customer-service agent should not automatically access confidential finance information.
An AI assistant should not modify sensitive records without authorisation.
Salesforce is positioning its platform around this enterprise trust layer.
Enterprise Trust Could Differentiate Salesforce
Consumer AI products can move quickly.
Large companies cannot accept the same level of unpredictability.
They need:
reliable data handling,
access controls,
and compliance.
Salesforce's long history serving regulated and complex organisations may provide an advantage as AI moves deeper into business operations.
Informatica Strengthens Data Capabilities
Salesforce's acquisition of Informatica also expands its enterprise-data position.
Informatica contributed:
$456 million
to second-quarter revenue. (Salesforce Investor Relations)
Data integration is particularly valuable in an AI environment because large organisations typically store information across many systems.
AI agents cannot function effectively if relevant data remains fragmented.
Contentful Could Strengthen Digital Experience Layer
Salesforce's planned acquisition of Contentful can expand capabilities around digital content infrastructure.
Modern businesses increasingly need content that can be delivered across:
websites,
apps,
AI assistants,
and other interfaces.
That creates another connection between Salesforce's core platform and emerging AI-driven customer experiences.
Fin Adds Customer-Service AI Capability
Salesforce's pending acquisition of Fin also fits directly into the enterprise AI strategy.
Customer service is one of the largest markets for AI agents.
Combining Fin's technology with Salesforce's service workflows could strengthen its competitive position in automated support.
The financial contribution from these acquisitions is already incorporated into the updated guidance, subject to closing. (Salesforce Investor Relations)
Salesforce Continues Large Share Buyback
The company is also executing a:
$25 billion accelerated share repurchase programme.
Final settlement is expected in October 2026. (Salesforce Investor Relations)
Buybacks reduce the number of shares outstanding.
This can increase earnings per share even when total profit grows more slowly.
The repurchase programme therefore contributes to Salesforce's higher EPS outlook.
Cash Flow Improves Sharply
Operating cash flow reached approximately:
$1.3 billion
during the quarter.
That increased:
71% year on year.
Free cash flow reached approximately:
$1.1 billion
and rose:
81%. (Salesforce Investor Relations)
Strong cash generation gives Salesforce flexibility to invest in AI while continuing acquisitions, dividends and share repurchases.
Salesforce Returned $364 Million Through Dividends
The company returned approximately:
$364 million
to shareholders through dividends during the quarter. (Salesforce Investor Relations)
This illustrates how Salesforce has evolved from a pure high-growth software company into a mature technology platform balancing:
growth investment,
profitability,
and capital returns.
Market Responds Positively
Salesforce shares rose sharply after the results and updated guidance.
Reuters reported the stock gaining about 14% in extended trading after the company raised its forecasts and announced the expanded Anthropic partnership. (Reuters)
The reaction suggests investors increasingly believe enterprise AI could become a meaningful growth driver for software companies rather than being dominated only by semiconductor suppliers.
Software AI Trade Has Lagged Chips
Much of the early AI investment boom centred on:
Nvidia,
memory manufacturers,
and data-centre infrastructure.
Software companies faced a different question:
When would enterprises begin paying meaningfully for AI applications?
Salesforce's results provide evidence that monetisation is accelerating.
Agentforce ARR growth above 240% reinforces that interpretation.
AI Infrastructure Spending Eventually Needs Applications
Companies cannot indefinitely invest billions in AI chips without generating economic applications.
The longer-term value of AI depends on businesses using computing capacity to:
increase productivity,
automate work,
and create new services.
Enterprise software companies sit at that application layer.
Salesforce wants to become one of the primary platforms translating AI infrastructure into business outcomes.
Competition Will Remain Intense
Salesforce faces major competitors including:
Microsoft,
Oracle,
ServiceNow,
SAP,
and a growing number of AI-native startups.
Each is attempting to become the enterprise layer through which AI agents interact with corporate data.
The market could therefore become one of the most important competitive battles in enterprise software.
Microsoft Has Distribution Advantage
Microsoft controls enormous enterprise distribution through:
Microsoft 365,
Azure,
Dynamics,
and Teams.
Its Copilot products provide AI directly inside applications employees already use.
Salesforce counters with deep CRM data and customer workflows.
The competition will increasingly centre on which platform owns the agentic layer.
ServiceNow Is Strong in Workflows
ServiceNow has a major presence in enterprise workflow automation.
That makes it another natural competitor in agentic AI.
If autonomous agents increasingly execute workflows, companies with deep process integration gain strategic advantages.
Salesforce needs Agentforce to expand beyond CRM-specific tasks into broader enterprise actions.
AI-Native Startups Could Attack Individual Use Cases
Specialised startups can move quickly.
One company may focus exclusively on:
AI sales agents.
Another may specialise in:
customer support.
These startups can sometimes offer more advanced capabilities in narrow areas.
Salesforce's advantage is integration and enterprise distribution.
Customers May Prefer Fewer Vendors
Large businesses often struggle with technology complexity.
If Salesforce can provide:
data,
AI,
CRM,
service,
analytics,
and collaboration
within one governed platform, customers may prefer that integrated approach.
This can increase switching costs.
It can also expand Salesforce's revenue per customer.
Salesforce Calls This the Agentic Enterprise
The company's broader vision is what it calls the:
Agentic Enterprise.
The concept involves humans and AI agents working across:
applications,
data,
and workflows
within a unified platform. (Salesforce Investor Relations)
Whether this becomes a durable new software architecture or simply another stage of automation will depend on customer adoption.
Current growth suggests enterprises are at least beginning to test the model at meaningful scale.
Third-Quarter Guidance Remains Strong
Salesforce expects third-quarter fiscal 2027 revenue of:
$11.42 billion to $11.5 billion.
That represents approximately:
11% to 12% year-on-year growth. (Salesforce Investor Relations)
The company also expects current remaining performance obligation growth of approximately:
14%
in both reported and constant-currency terms.
Full-Year Margin Guidance Remains High
Salesforce maintained its full-year non-GAAP operating-margin forecast at:
34.3%.
GAAP operating-margin guidance was updated to:
20.1%. (Salesforce Investor Relations)
This means management expects to sustain substantial profitability while continuing to invest aggressively in AI.
AI Must Eventually Reaccelerate Organic Revenue
Salesforce's long-term challenge remains straightforward.
Investors want AI growth to become large enough to accelerate the company's overall organic revenue growth.
A 240% growth rate in a smaller product can be impressive but needs to become material at company scale.
Agentforce and Data 360 approaching $4 billion in ARR suggests that threshold is getting closer.
Conclusion
Salesforce's decision to raise its fiscal 2027 revenue and profit forecasts provides some of the clearest evidence yet that enterprise spending on AI software is beginning to translate into meaningful financial results.
The company now expects full-year revenue of $46.1 billion to $46.4 billion, while adjusted earnings per share are forecast at $16.67–$16.71. (Salesforce Investor Relations)
Second-quarter revenue increased 11% to approximately $11.3 billion, while adjusted EPS more than doubled to $5.90.
But the more important strategic metrics sit inside Salesforce's emerging AI business.
Agentforce and Data 360 ARR reached nearly $3.9 billion, while Agentforce ARR surpassed $1.5 billion and grew more than 240% year on year. (Salesforce Investor Relations)
Salesforce is attempting to position itself at the centre of an enterprise transition from traditional software applications toward systems where AI agents can understand company data, invoke business logic and execute workflows.
Its advantage is not simply access to powerful AI models.
It is the enormous amount of enterprise data, permissions, customer relationships and workflow infrastructure already embedded inside Salesforce products.
If enterprises continue moving AI agents from experiments into production, that installed platform could become increasingly valuable.
The latest earnings therefore suggest Salesforce's AI strategy is moving into a more consequential phase: Agentforce is beginning to evolve from a promising product category into a material revenue engine capable of influencing the growth outlook of one of the world's largest enterprise-software companies.