Besides financial support, Salesforce’s backing can provide Datumo with several benefits, including the possibility of working with the company on its AI agents and the software giant’s customers. (Photo: Datumo)https://t.co/J3vapDXFZ2 https://t.co/umew7XM7WS ...

Core Insights - ValueSelling Associates, Inc. has announced significant innovations to its revenue technology toolset, eValuePrompter™, through integration with Salesforce's Agentforce, marking a milestone in sales enablement with AI-driven enhancements [1][2] Group 1: Product Innovations - The new ValueSelling Assistant leverages intelligent automation to enhance the daily routines of sales teams, providing real-time insights, intelligent coaching, and automated customer communications [2][3] - The enhancements are designed to simplify the adoption of the ValueSelling Framework, allowing sales professionals to prepare, execute, and follow up on customer interactions more effectively [3][6] Group 2: Benefits to Sales Teams - The ValueSelling Assistant addresses common challenges faced by sales teams, enabling them to do more with less while improving customer experience [3] - Features include importing call recordings, automated feedback on sales call effectiveness, opportunity analysis, intelligent gap analysis for follow-up questions, and quick generation of personalized customer communications [6]

AI 正在重构软件价值：基于 seat 定价的传统模式正逐步被基于使用量或结果的定价所取代。 面对这场定价范式的转变，不同类型的 AI 公司应该怎么做才能顺利实现定价转型？CEO 需要特别关注哪些方面才能真正将按量定价转化为企业竞争优 势？ 本文编译了 a16z 与 Metronome（一家为 OpenAI、Anthropic 提供按量计费平台的初创公司）CEO Scott Woody 的深度访谈，探讨了 AI 是如何从根本上改 变了软件的定价逻辑、不同类型的 AI 公司 CEO 又应该如何应对等话题。此外，我们还在文中补充了定价专家 Madhavan Ramanujam 关于 AI 产品定价四 象限的最新观点： • 由于 AI 提高了人类的效率，使用软件的人数会减少，如果软件使用 seat 定价，价值上限会很低； • 按量定价的实施难点在于：1）计费系统需要实时检测；2）定价模型是高度动态的；3）需要保留大规模的真实数据； • 决定实施按量定价的 CEO 需要关注销售人员的薪酬方案和销售的职责划分，财务团队需要升级成实时数据中枢； • 对于 infra 来说，按量定价是天然契合的模式；对于应用来说，未来几年 ...

Group 1 - The core viewpoint is that Bank of America analyst Bradley Sills reaffirms a "Buy" rating for Salesforce (CRM.US) with a target price of $350, driven by expected growth rebound in its largest business segment, Service Cloud [1] - Analysts project that Service Cloud revenue will reach $9.7 billion in fiscal year 2026, accounting for 25% of total subscription revenue [1] - The growth of Service Cloud is anticipated to accelerate to 9% in the coming quarters, with a long-term growth rate expected to reach 12% [1] Group 2 - Analysts believe that upselling additional services and the "agent power" product will be the main drivers of business growth [1] - Due to a weaker dollar in the first quarter, Salesforce is expected to benefit from favorable currency effects [1] - Salesforce's revenue guidance for the second quarter of 2026 is projected to be between $10.11 billion and $10.16 billion, representing a year-over-year growth of 8% to 9% [1]

Core Insights - A cybersecurity incident affecting Salesforce has compromised the personal information of potentially millions of individuals, impacting several major companies including Air France, KLM, Adidas, Qantas, Allianz Life, Louis Vuitton, Dior, Tiffany & Co., Chanel, and Google [1] Group 1 - The data breach involves the exposure of personally identifiable information (PII) [1] - Lynch Carpenter, LLP is investigating claims against Salesforce and the impacted companies related to this data breach [2] - Individuals who received a data breach notification from the affected companies may be entitled to compensation [2] Group 2 - Lynch Carpenter is a national class action law firm with a focus on data privacy matters and has represented millions of clients over more than a decade [3] - The firm has earned national acclaim for complex litigation for plaintiffs across the country [3]

Core Insights - Salesforce, Inc. (CRM) is experiencing significant underperformance, with a stock decline of 28% in 2025, compared to a 13.5% drop in the broader Zacks Computer and Technology sector [1][8] - The company's revenue growth has slowed considerably, with a 7.7% increase in Q1 of fiscal 2026, leading to cautious investor sentiment [5][8] - Salesforce's earnings per share (EPS) growth is projected to decline significantly, with a compound annual growth rate (CAGR) of 12.9% expected over the next five years, down from 27.8% in the previous five years [9] Sales Performance - Salesforce's revenue growth has decelerated, with Q1 fiscal 2026 revenues rising only 7.7% year-over-year, and non-GAAP EPS increasing by just 5.7% [5][8] - Analysts predict mid-to-high single-digit growth for fiscal years 2026 and 2027, indicating a continued trend of cautious enterprise spending [6] Financial Estimates - Current Zacks Consensus Estimates for Salesforce's upcoming quarters and years are as follows: - Current Quarter (7/2025): $10.13 billion - Next Quarter (10/2025): $10.29 billion - Current Year (1/2026): $41.15 billion - Next Year (1/2027): $44.94 billion - Year-over-year growth estimates are projected at 8.66% for the current quarter and 8.58% for the current year [7] Valuation Analysis - Salesforce's stock trades at a low forward P/E ratio of 20.08, significantly below the sector average of 28.16 [8][10] - Compared to peers, Salesforce's P/E is lower than SAP (38.32), Oracle (36.17), and Microsoft (33.42), suggesting a potential undervaluation [12] Strategic Implications - The current valuation may attract investors; however, the ongoing challenges related to slowing sales growth could indicate a value trap [13] - The company needs to adapt its strategy to remain competitive, as businesses are shifting towards smaller, lower-risk IT investments rather than large digital transformation projects [9] Conclusion - Salesforce is no longer viewed as a growth powerhouse, with limited upside potential due to slowing revenue and earnings growth [14] - The company currently holds a Zacks Rank 4 (Sell), suggesting that investors may want to consider other opportunities in the tech sector [14]

These AI software stocks could be poised for a big rebound if analysts are right. Salesforce could have a lot of room to run. The consensus 12-month price target for the stock is 45% above the current share price. One especially bullish analyst thinks Salesforce could skyrocket more than 80% higher. The right AI investments could make you plenty of money, too. But which stocks are great picks right now? Wall Street analysts have some ideas you might want to check out. Here are three AI stocks that analysts ...

Core Viewpoint - The rise of artificial intelligence (AI) is significantly impacting the job market, particularly for entry-level positions, leading to increased unemployment rates among recent graduates and young professionals in the technology sector [1][3][5]. Group 1: Impact of AI on Employment - Over 10,000 jobs in the U.S. have been lost due to generative AI applications in the first seven months of this year, with entry-level positions being the most affected [3][4]. - The unemployment rate for U.S. graduates surged from 4.0% in December 2023 to 8.1% [3][5]. - AI has become one of the top five reasons for layoffs in the U.S., with over 806,000 layoffs announced by companies in 2025, the highest since 2020 [3][4]. Group 2: Challenges for Young Job Seekers - Nearly half of U.S. Generation Z job seekers believe that AI has devalued their degrees, with the unemployment rate for recent college graduates rising to 6%, significantly above the national average of around 4% [5][6]. - The technology sector has seen the most significant impact, with unemployment rates for employees aged 20-30 increasing by approximately 3 percentage points this year [6][7]. Group 3: Shift in Hiring Practices - Companies are increasingly using AI to replace tasks traditionally performed by entry-level employees, leading to a 15% decline in job postings for entry-level positions [4][8]. - Major companies like Shopify and McKinsey have publicly stated that they will not hire new employees if AI can perform the tasks [8].

Core Insights - The excitement surrounding artificial intelligence (AI) has significantly increased stock prices for major tech companies, with Nvidia's market cap exceeding $4 trillion since the launch of ChatGPT in late 2022 [1][2] Company Summaries Amazon - Amazon Web Services (AWS) is the largest public cloud computing platform, generating $116.4 billion in the last 12 months, approximately 50% larger than Microsoft's Azure [5] - AWS experienced a decline in operating margin due to stock-based compensation timing and significant investments in capacity, but it maintains higher margins than smaller competitors [7] - Despite a recent stock price drop following disappointing earnings, Amazon's long-term potential, especially in AWS, remains strong, presenting a buying opportunity for long-term investors [9] Salesforce - Salesforce's Data Cloud has seen a 120% year-over-year growth in recurring revenue, reaching $1 billion in the most recent quarter, with strong adoption in major deals [11][12] - The company is well-positioned to benefit from increased spending on AI, as its software suite is deeply integrated into enterprise operations, making it difficult for companies to switch away [13] - Shares are trading at 22 times forward earnings estimates, indicating a favorable buying opportunity [13] Meta Platforms - Meta is projected to spend between $66 billion and $72 billion on AI capital expenditures, positioning itself as a major player in generative AI [14] - The company reported a 22% revenue increase and a 38% growth in operating income, driven by AI-enhanced advertising and user engagement [18] - Meta shares trade at an attractive valuation of around 16 times forward EBITDA estimates, and 27 times forward P/E, suggesting strong investment potential [19][20]

Core Insights - The performance of AI products increasingly relies on data quality and freshness rather than just model size [1][2][3] - Companies like Salesforce and IBM are acquiring data infrastructure firms to enhance their AI capabilities with real-time, structured data [2][5][6] - The definition of "good data" includes being domain-specific, continuously updated, structured, deduplicated, and real-time actionable [4][5][6] Data Infrastructure Importance - Data collection is now seen as a critical infrastructure rather than a secondary task, emphasizing the need for reliable, real-time access to data [2][9][22] - The modern AI data stack has evolved into a value chain that includes data acquisition, transformation, organization, and storage [10][22] - Effective data retrieval quality surpasses prompt engineering, as outdated or irrelevant data can hinder model performance [7][19] Strategic Data Collection - Data collection must be strategic, providing structured and immediate data for AI agents [12][13] - It should handle dynamic user interfaces, CAPTCHAs, and mixed extraction methods to ensure comprehensive data gathering [14][15] - Data collection infrastructure should be scalable and compliant with legal standards, moving beyond fragile scraping tools [16][22] Future of AI Systems - The future of AI performance will depend more on knowledge acquisition speed and context management rather than just model size [23][24] - Companies that view data collection as a foundational capability will likely achieve faster and more cost-effective success [25]