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Smart Communications Partners with Salesforce

Smart Communications Partners with Salesforce

Smart Communications Partners with Salesforce to Revolutionize Digital Customer Experience MANILA, Philippines — Smart Communications, the leading mobile services provider under PLDT Inc., has partnered with Salesforce to launch a next-generation digital storefront powered by Salesforce Commerce Cloud. This strategic collaboration will transform how over 50 million prepaid and postpaid subscribers in the Philippines discover, purchase, and manage telecom services—all through a seamless, AI-driven digital experience. A Unified Digital Storefront for Seamless Transactions Smart’s new platform will enable customers to: “This transformation positions Smart for long-term success in the Philippines’ competitive telecom market,” said Abraham Cuevas, Country Manager at Salesforce Philippines. AI, Automation & Scalability at the Core The solution leverages Salesforce AI, MuleSoft, and Service Cloud to:🔹 Personalize offers using customer data insights.🔹 Streamline order fulfillment with automated workflows.🔹 Integrate seamlessly with Smart’s existing CRM and backend systems. “Salesforce Commerce Cloud’s robust architecture empowers our customers with unmatched convenience,” said Gilbert Gaw, SVP of IT & Transformation at Smart & PLDT. Future Expansion: Enterprise & Beyond Smart is also exploring extending this platform to its enterprise segment, further enhancing B2B sales and support. Why It Matters:With rising digital adoption in the Philippines, this partnership ensures Smart stays ahead by delivering frictionless, scalable, and intelligent customer experiences. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce's Enterprise General Intelligence

Salesforce’s Enterprise General Intelligence

Salesforce is carving a distinct path in the AI landscape, diverging from the industry’s pursuit of Artificial General Intelligence (AGI). Instead, the company is tackling a pressing, practical challenge: ensuring AI is reliable for enterprise use. Salesforce’s Enterprise General Intelligence (EGI) framework prioritizes consistency, safety, and trustworthiness over speculative potential, aiming to deliver dependable AI for real-world business applications. The EGI FrameworkLarge language models (LLMs) excel at tasks like drafting emails or analyzing datasets but often exhibit “jagged intelligence”—impressive in some areas yet prone to basic errors or fabrications, known as hallucinations. These inconsistencies pose significant risks in enterprise settings, where errors can lead to compliance issues, financial losses, or eroded customer trust. Salesforce’s EGI framework addresses this by focusing on infrastructure that ensures AI reliability today, rather than chasing futuristic goals. From Inconsistency to DependabilitySalesforce likens LLMs to “an intern who writes flawless code but forgets to save the file.” To address this uneven performance, the company is enhancing its AI agents with layered reinforcement to boost consistency. Central to this effort is Agentforce, Salesforce’s agentic system, supported by the Atlas Reasoning Engine, which integrates internal and external data for more accurate reasoning and retrieval. Together, these form the core of EGI, aiming to make digital labor predictable and trustworthy. Rigorous Testing in Real-World ScenariosRather than relying solely on traditional benchmarks, Salesforce introduced CRMArena, a simulated environment that tests AI agents on practical CRM tasks like service support and analytics. Initial results show success rates below 65%, even with guided prompting, underscoring the challenges. However, this is precisely Salesforce’s point: stress-testing AI in realistic conditions exposes weaknesses before deployment, ensuring reliability in customer-facing roles. A Platform for Enterprise TrustSalesforce emphasizes that enterprises need more than powerful models—they require systems guaranteeing predictability and accountability at scale. EGI is positioned as a practical, present-focused solution, sidestepping AGI hype to deliver AI that businesses can trust today. While its long-term impact remains to be seen, Salesforce’s approach signals a pragmatic step toward reliable, enterprise-ready AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Data Governance for the AI Enterprise

A Strategic Approach to Governing Enterprise AI Systems

The Imperative of AI Governance in Modern Enterprises Effective data governance is widely acknowledged as a critical component of deploying enterprise AI applications. However, translating governance principles into actionable strategies remains a complex challenge. This article presents a structured approach to AI governance, offering foundational principles that organizations can adapt to their needs. While not exhaustive, this framework provides a starting point for managing AI systems responsibly. Defining Data Governance in the AI Era At its core, data governance encompasses the policies and processes that dictate how organizations manage data—ensuring proper storage, access, and usage. Two key roles facilitate governance: Traditional data systems operate within deterministic governance frameworks, where structured schemas and well-defined hierarchies enable clear rule enforcement. However, AI introduces non-deterministic challenges—unstructured data, probabilistic decision-making, and evolving models—requiring a more adaptive governance approach. Core Principles for Effective AI Governance To navigate these complexities, organizations should adopt the following best practices: Multi-Agent Architectures: A Governance Enabler Modern AI applications should embrace agent-based architectures, where multiple AI models collaborate to accomplish tasks. This approach draws from decades of distributed systems and microservices best practices, ensuring scalability and maintainability. Key developments facilitating this shift include: By treating AI agents as modular components, organizations can apply service-oriented governance principles, improving oversight and adaptability. Deterministic vs. Non-Deterministic Governance Models Traditional (Deterministic) Governance AI (Non-Deterministic) Governance Interestingly, human governance has long managed non-deterministic actors (people), offering valuable lessons for AI oversight. Legal systems, for instance, incorporate checks and balances—acknowledging human fallibility while maintaining societal stability. Mitigating AI Hallucinations Through Specialization Large language models (LLMs) are prone to hallucinations—generating plausible but incorrect responses. Mitigation strategies include: This mirrors real-world expertise—just as a medical specialist provides domain-specific advice, AI agents should operate within bounded competencies. Adversarial Validation for AI Governance Inspired by Generative Adversarial Networks (GANs), AI governance can employ: This adversarial dynamic improves quality over time, much like auditing processes in human systems. Knowledge Management: The Backbone of AI Governance Enterprise knowledge is often fragmented, residing in: To govern this effectively, organizations should: Ethics, Safety, and Responsible AI Deployment AI ethics remains a nuanced challenge due to: Best practices include: Conclusion: Toward Responsible and Scalable AI Governance AI governance demands a multi-layered approach, blending:✔ Technical safeguards (specialized agents, adversarial validation).✔ Process rigor (knowledge certification, human oversight).✔ Ethical foresight (bias mitigation, risk-aware automation). By learning from both software engineering and human governance paradigms, enterprises can build AI systems that are effective, accountable, and aligned with organizational values. The path forward requires continuous refinement, but with strategic governance, AI can drive innovation while minimizing unintended consequences. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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New Slack Innovations

Slack News from Salesforce

Starting today, we’re updating Slack plans and pricing to expand access to AI, Agentforce, and Salesforce for organizations of all sizes. With these changes, customers will benefit from native AI, access to digital labor, deeper CRM integrations, and enterprise-grade security so they can grow faster with Slack. Since our last pricing adjustment in 2022, Slack has evolved into a unified work operating system and conversational interface for all your enterprise apps, data, and agents. Now more than ever, AI, data, and security are integral to Slack and essential for bringing AI agents successfully into the digital employee experience. We are committed to giving every team an onramp to AI-powered productivity in Slack — and every organization a secure foundation to grow with digital labor. That’s why we’re simplifying our pricing and bringing innovations into the core Slack experience across all our plans. Slack users gain new features across every plan We’re integrating AI features across all paid plans, adding summarization and huddle notes to the Pro plan, while supercharging our Business+ plan with a range of AI features including workflow generation, recaps, translation, and search. Our new Enterprise+ plan unlocks AI-powered enterprise search and evolved task management capabilities across your organization. Additionally, AI agents from Agentforce and partner AI apps can now be deployed in all paid plans. Every Salesforce customer will get Slack (Free Plan) with access to Salesforce integrations in Slack, so every team can collaborate around CRM data with Salesforce Channels in Slack or from Salesforce. Business+ and Enterprise+ teams will gain premium Salesforce features to forecast revenue, swarm deals, coordinate approvals, and respond to real-time event triggers. We’re enhancing security across all plans, bringing session duration controls and native device management to all of our plans — including Free, and adding SAML-based SSO for Salesforce customers — giving every team a trusted foundation to securely connect their people, data, AI, and agents. What’s changing with Slack pricing Slack is the work operating system for the agentic era These plan additions reflect our rapid pace of innovation over the last 18 months to deliver the most comprehensive work operating system for the era of AI and digital labor. Together, we are reinventing work for the age of digital labor. Humans are at the center — connected in conversation, amplified by AI, with instant access to contextual data — all built on a strong foundation of security and trust. For more information on these updates, visit the Slack Plans page or contact your account representative. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Tightens Slack’s API Rules

Salesforce Tightens Slack’s API Rules

Salesforce Tightens Slack’s API Rules, Restricting AI Data Access Salesforce, the parent company of workplace messaging platform Slack, has quietly updated its API terms to block third-party software firms from indexing or storing Slack messages—a move that could significantly impact enterprise AI tools. According to a report from The Information, the changes prevent apps like Glean (a workplace AI search provider) from accessing Slack data for long-term storage or analysis. In a statement to Reuters, Salesforce framed the shift as a data security measure, saying: “As AI raises critical considerations around how customer data is handled, we’re reinforcing safeguards around how data accessed via Slack APIs can be stored, used, and shared.” What Does This Actually Mean? APIs (Application Programming Interfaces) allow different software systems to communicate. Until now, companies could use Slack’s API to: Now, those capabilities are restricted. Third-party apps can still access Slack data in real time, but they can’t retain it—meaning AI models can’t learn from past conversations. Glean reportedly warned customers that the change “hampers your ability to use your data with your chosen enterprise AI platform.” Why Is Salesforce Doing This? Officially, the company says it’s about security and responsible AI. But critics argue it’s a strategic lock-in play: Industry Backlash: “This Is Anti-Innovation” The move has sparked frustration across the tech sector, with critics accusing Salesforce of building a walled garden: The Bigger Picture: AI’s Data Wars This isn’t just about Slack—it’s part of a broader battle over AI training data: Salesforce’s move suggests that enterprise AI will increasingly run on proprietary data silos—meaning companies that control the data control the AI. What Happens Next? One thing’s clear: The age of open data for AI is ending—and the age of data feudalism is here. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Learning AI

The Open-Source Agent Framework Landscape

The Open-Source Agent Framework Landscape: Beyond CrewAI & AutoGen The AI agent ecosystem has exploded with new frameworks—each offering unique approaches to building autonomous systems. While CrewAI and AutoGen dominate discussions, alternatives like LangGraph, Agno, SmolAgents, Mastra, PydanticAI, and Atomic Agents are gaining traction. Here’s a breakdown of how they compare, their design philosophies, and which might be right for your use case. What Do Agent Frameworks Actually Do? Agentic AI frameworks help structure LLM workflows by handling:✅ Prompt engineering (formatting inputs/outputs)✅ Tool routing (API calls, RAG, function execution)✅ State management (short-term memory)✅ Multi-agent orchestration (collaboration & hierarchies) At their core, they abstract away the manual work of: But too much abstraction can backfire—some developers end up rewriting parts of frameworks (like LangGraph’s create_react_agent) for finer control. The Frameworks Compared 1. The Big Players: CrewAI & AutoGen Framework Best For Key Differentiator CrewAI Quick prototyping High abstraction, hides low-level details AutoGen Research/testing Asynchronous, agent-driven collaboration CrewAI lets you spin up agents fast but can be opaque when debugging. AutoGen excels in freeform agent teamwork but may lack structure for production use. 2. The Rising Stars Framework Philosophy Strengths Weaknesses LangGraph Graph-based workflows Fine-grained control, scalable multi-agent Steep learning curve Agno (ex-Phi-Data) Developer experience Clean docs, plug-and-play Newer, fewer examples SmolAgents Minimalist Code-based routing, Hugging Face integration Limited scalability Mastra (JS) Frontend-friendly Built for web devs Less backend flexibility PydanticAI Type-safe control Predictable outputs, easy debugging Manual orchestration Atomic Agents Lego-like modularity Explicit control, no black boxes More coding required Key Differences in Approach 1. Abstraction Level 2. Agency vs. Control 3. Multi-Agent Support What’s Missing? Not all frameworks handle:🔹 Multimodality (images/audio)🔹 Long-term memory (beyond session state)🔹 Enterprise scalability (LangGraph leads here) Which One Should You Choose? Use Case Recommended Framework Quick prototyping CrewAI, Agno Research/experiments AutoGen, SmolAgents Production multi-agent LangGraph, PydanticAI Strict control & debugging Atomic Agents, PydanticAI Frontend integration Mastra For beginners: Start with Agno or CrewAI.For engineers: LangGraph or PydanticAI offer the most flexibility. Final Thoughts The “best” framework depends on your needs: While some argue these frameworks overcomplicate what SDKs already do, they’re invaluable for scaling agent systems. The space is evolving fast—expect more consolidation and innovation ahead. Try a few, see what clicks, and build something awesome!  l Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Absorbs AI Recruitment Startup Moonhub

Salesforce Absorbs AI Recruitment Startup Moonhub

Salesforce Absorbs AI Recruitment Startup Moonhub in Talent Acquisition Push Salesforce has effectively acquired Moonhub, an AI-powered recruitment startup, though the financial terms remain undisclosed. The move follows Salesforce’s recent $8 billion deal for Informatica and its purchase of Convergence.ai, signaling aggressive expansion in enterprise AI. Moonhub, a Menlo Park-based firm founded in 2022 by ex-Meta engineer Nancy Xu, announced on its website that its team would transition to Salesforce, an early investor. While Salesforce clarified to TechCrunch that this does not constitute a formal acquisition (Moonhub will cease operations), key personnel will join the tech giant to bolster its AI initiatives, including Agentforce, Salesforce’s AI agent ecosystem. Why Moonhub? Moonhub specialized in AI-driven talent sourcing, automating candidate discovery, outreach, onboarding, and payroll. Its clients included Fortune 500 companies, and it had raised $14.4 million from backers like Khosla Ventures, GV (Google Ventures), and Salesforce Ventures. Xu emphasized cultural alignment, stating: “Salesforce shares our core values—customer trust and a belief in AI’s role in global innovation. Together, we’ll accelerate this mission.” The Bigger Picture: AI’s HR Takeover The deal reflects the rapid adoption of AI in HR, with 93% of Fortune 500 CHROs already deploying such tools (Gallup). However, reactions remain mixed as automation reshapes recruitment. What’s Next? With Moonhub’s team now inside Salesforce, expect tighter integration of AI agents into Salesforce’s talent solutions. Meanwhile, the startup’s standalone product will sunset, marking another example of Big Tech absorbing innovative AI ventures. Key Takeaways:✅ Moonhub’s team joins Salesforce (no formal acquisition, but a strategic absorption).🤖 Focus on AI recruitment tools (automated hiring, onboarding, payroll).📈 Part of Salesforce’s broader AI push (following Informatica, Convergence.ai deals).💡 HR AI adoption is booming—but not without controversy. Update: Clarified acquisition status per Salesforce’s statement. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce’s AI Evolution

Salesforce Summer 25 Release

Salesforce Summer ’25 Release: Key Updates & Action Items The Salesforce Summer ’25 release is here—packed with AI-driven innovations, critical deprecations, and tools to modernize your org. Whether you’re an admin, developer, or business leader, these changes will shape your Salesforce strategy. Let’s break down what matters most. 1. Legacy Tools Sunset: Time to Migrate Salesforce is accelerating its shift to modern automation: 2. Flow’s Quantum Leap Flow becomes more powerful and user-friendly: 3. Flow-Based Approvals (Next-Gen) Classic approval processes get a Flow-powered successor: 4. Agentforce Goes Enterprise-Wide AI-powered agents expand beyond customer service: 5. Admin Efficiency Boosters 6. Critical Dates & Prep Checklist Rollout: Sandbox previews began May 9; production deploys hit May 16–June 13.Check your org’s date at status.salesforce.com. ✅ Your Action Plan Priority Task Urgent Migrate Workflow Rules/Process Builder to Flow High Update API integrations to v31+ Medium Test outbound messaging under 20s timeout Pilot Explore Flow approvals & Agentforce templates The Bottom Line Salesforce is betting big on Flow, AI, and modular development. Proactively adopting these tools will future-proof your org. Resources: Need help? Join the Release Readiness Trailblazer Community. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Building the Foundation for AI Success

Building the Foundation for AI Success

The Data Imperative: Building the Foundation for AI Success The AI Revolution Demands a Data-First Approach As enterprises race to deploy generative AI, AI agents, and Model Context Protocol (MCP) systems, one critical truth emerges: AI is only as powerful as the data that fuels it. Why Data Platforms Are the Unsung Heroes of AI Modern data platforms solve five existential challenges for AI adoption: 1. Unified Data Fabric 2. Real-Time Performance at Scale 3. Context-Aware Intelligence 4. Governance Without Friction 5. Rapid AI Experimentation Model Context Protocol (MCP): The Nervous System for AI What Makes MCP Revolutionary Traditional AI Integration MCP Approach Custom APIs per system Standardized protocol Months of development Plug-and-play connectivity Brittle point-to-point links Adaptive ecosystem How MCP Transforms AI Capabilities The Strategic Imperative Organizations leading the AI race share three traits: “The AI winners won’t have better algorithms—they’ll have better data systems.”— MIT Technology Review, 2025 AI Predictions Next Steps for Enterprises: The future belongs to organizations that build data moats—not just models. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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The Rise of AI Agents

The Rise of AI Agents: How Autonomous AI is Reshaping Business As artificial intelligence advances, so does the terminology around it. The term “AI agent” is gaining traction as generative AI becomes deeply embedded in business operations. Unlike traditional AI tools that follow rigid scripts, AI agents are autonomous programs capable of learning, adapting, and executing tasks with minimal human intervention. Why AI Agents Are Booming The rapid expansion of large language models (LLMs) has slashed the cost of developing AI agents, fueling a surge in startups specializing in industry-specific AI solutions. According to Stripe’s 2024 research, AI startups achieved record revenue growth last year, signaling a shift from generic AI tools (like ChatGPT) to verticalized AI agents tailored for specific sectors. In their annual letter, Stripe co-founders Patrick and John Collison noted: “Just as SaaS evolved from horizontal platforms (Salesforce) to vertical solutions (Toast), AI is following the same path. Industry-specific AI agents ensure businesses fully harness LLMs by integrating contextual data and workflows.” AI Agents in Action: Industry Success Stories From manufacturing to finance, AI agents are already delivering tangible benefits: David Lodge, VP of Engineering at IBS Software, explains: “Fragmented systems limit AI’s potential. Unifying CRM, PMS, and loyalty data into a single platform is critical for AI to drive real transformation.” Hospitality’s AI Revolution: Breaking Down Data Silos Hotels like Wyndham and IHG have partnered with Salesforce to consolidate millions of guest records, enabling AI agents to deliver hyper-personalized service. In February 2025, Apaleo launched an AI Agent Marketplace for hospitality, allowing hotels to integrate AI solutions without costly system overhauls. Case Study: mk Hotels The Future: Autonomous Agents Redefining Workflows In September 2024, Salesforce introduced Agentforce, a platform for building secure, data-grounded AI agents that automate complex workflows. Jan Erik Aase, Partner at ISG, predicts: “The shift to agent-driven enterprises isn’t just technological—it’s cultural. As AI agents grow smarter, they’ll redefine customer interactions and decision-making.” Key Takeaways The AI agent revolution is here—and businesses that embrace it will lead the next wave of productivity and innovation. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Why Salesforce Isn't Alarmist About AI

Why Salesforce Isn’t Alarmist About AI

Salesforce CEO Dismisses AI Job Loss Fears as “Alarmist,” Even as Company Cuts Hiring Due to AI San Francisco, CA — Salesforce isn’t alarmist about AI because they view it as a tool to augment human capabilities and enhance business processes, not as a threat to jobs. They are actively developing and implementing AI solutions like Einstein AI and Agentforce to improve efficiency and customer experience. While Salesforce has reduced some hiring in certain areas due to AI automation, they are also expanding hiring in other areas, according to the Business Journals.  Salesforce CEO Marc Benioff pushed back against warnings of widespread job losses from artificial intelligence during the company’s Wednesday earnings call, calling such predictions “alarmist.” However, his remarks came just as one of his top executives confirmed that AI is already reducing hiring at the tech giant. The debate over AI’s impact on employment—from generative tools like ChatGPT to advanced robotics and hypothetical human-level “digital workers”—has raged in the tech industry for years. But tensions escalated this week when Anthropic CEO Dario Amodei told Axios that businesses and governments are downplaying the risk of AI rapidly automating millions of jobs. “Most of them are unaware that this is about to happen,” Amodei reportedly said. “It sounds crazy, and people just don’t believe it.” Benioff, however, dismissed the notion. When asked about Amodei’s comments, he argued that AI industry leaders are succumbing to groupthink. He emphasized that AI lacks consciousness and cannot independently run factories or build self-replicating machines. “We aren’t exactly even to that point yet where all these white-collar jobs are just suddenly disappearing,” Benioff said. “AI can do some things, and while this is very exciting in the enterprise, we all know it cannot do everything.” He cited AI’s tendency to produce inaccurate “hallucinations” as a key limitation, noting that even if AI drafts a press release, humans would still need to refine it. While expressing respect for Amodei, Benioff maintained that “some of these comments are alarmist and get a little aggressive in the current form of AI today.” Yet, even as Benioff downplayed AI’s threat to jobs, Salesforce COO Robin Washington revealed that the company is already cutting hiring due to AI efficiencies. AI agents now handle vast numbers of customer service inquiries, reducing the need for new hires. About 500 customer support employees are being shifted to “higher-impact, data-plus-AI roles.” Washington also told Bloomberg that Salesforce is hiring fewer engineers, as AI agents act as assistants, boosting productivity without expanding headcount. (One area still growing? Sales teams pitching AI to other companies, according to Chief Revenue Officer Miguel Milano.) Salesforce’s Agentforce landing page highlights its AI-human collaboration model, boasting “Agents + Humans. Driving Customer Success together since October 2024.” A live tracker shows AI handling nearly as many support requests as humans—though human agents still lead by about 12%. The Broader AI Fear Factor Public anxiety around AI centers on: Hollywood dystopias like The Terminator and Maximum Overdrive amplify these fears, but experts argue reality is far less dramatic. Why AI Panic May Be Overblown Dr. Sriraam Natarajan, a computer science professor at UT Dallas and an AI researcher, reassures that AI lacks consciousness and cannot “think” like humans. “AI-driven Armageddon is not happening,” Natarajan said. “‘The Terminator’ is a great movie, but it’s fiction.” Key limitations of current AI: Natarajan acknowledges risks—like bad actors misusing AI—but stresses that safeguards are a major research focus. “I don’t fear AI; I fear people who misuse AI,” he said. Rather than replacing jobs, Natarajan sees AI as a productivity booster, handling repetitive tasks while humans focus on creativity and strategy. He highlights AI’s potential in medicine, climate science, and disaster prediction—but emphasizes responsible deployment. The Bottom Line While Benioff and other tech leaders dismiss doomsday scenarios, AI is already reshaping hiring—even at Salesforce. The real challenge lies in balancing innovation with workforce adaptation, ensuring AI augments rather than replaces human roles. For now, the robots aren’t taking over—but they are changing how companies operate. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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