Tatiana Lloret

Every business needs an AI agent strategy. #ad Salesforce just dropped a free 48-page guide. Here's what you need to know: → 78% of companies use AI (up from 55% last year) → Workers using AI daily are 64% more productive → 81% more satisfied with their work → $6 trillion economic impact expected by 2030 But here's the real insight: Leadership, not employee readiness, is the biggest barrier to AI success. The best companies are creating what Salesforce calls the "dual dividend": Customer delight AND employee empowerment. They're focusing on scaling capabilities, not reducing headcount. Get the free playbook: https://sforce.co/4ngEXHq Companies have seen: • Reduced hiring time by 50% • 50% of support resolved instantly • Instant verification vs human delays • Salesforce: 85% help portal resolution rate These companies became "agentic enterprises" designed for human-AI collaboration from the ground up. My takeaway: We’re moving from single-player to multiplayer AI. Agents can take action for us autonomously without human intervention. Smart companies are already building the hybrid workforce of the future. The playbook breaks down their exact 7-step framework. This is your competitive advantage. #Salesforce #AgenticAI

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Salesforce is shifting from 'we have agents' to 'we operate agents at enterprise scale.' In a recent interview with Frank Defesche, SVP & GM of Life Sciences at the company, spoke on the promise of AI agents in the clinical trials space and across life sciences. "'To me, AI is your personal assistant and your personal research team,'" he said. The company has forged alliances with IQVIA, Takeda, and dozens of migration partners as it prepares for the industry's biggest platform shift. With Veeva's Salesforce-based CRM ending support in 2030, thousands of pharma and life science teams face a choice. "A majority of the top-30 life sciences companies will have made a selection this year," Defesche predicts. Defesche, who spent 16 years building Veeva before returning to Salesforce, sees opportunity in the disruption: "This competition is good for the market." Full article in the link... #LifeSciences #Pharma #ClinicalTrials #AI #Salesforce #HealthTech

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💡 👩🏻‍💻 👇 𝗔𝗴𝗲𝗻𝘁𝗯𝗹𝗮𝘇𝗲𝗿 𝗟𝗲𝗴𝗲𝗻𝗱: 𝗙𝗶𝗿𝘀𝘁 𝗦𝘁𝗲𝗽 𝗧𝗮𝗸𝗲𝗻 💡 👩🏻‍💻 👇 "An Agentblazer Legend designs advanced agent customizations, crafts AI-driven business strategies, and mentors others across their organization and community." It's a path that 𝗲𝗹𝗲𝘃𝗮𝘁𝗲𝘀 𝘆𝗼𝘂𝗿 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 𝗮𝗻𝗱 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗶𝗻 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱 𝗼𝗳 𝗔𝗜, which starts with becoming Agentforce Specialist certified in the official Salesforce certification process. The knowledge you'll gain is extensive, covering 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗮𝘀𝗽𝗲𝗰𝘁𝘀 𝗼𝗳 𝗔𝗴𝗲𝗻𝘁𝗳𝗼𝗿𝗰𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: • Advanced Agent #Customization: How to customize agents using prompts, flows, and Apex. • Agent #DataManagement: Leveraging Data Cloud for personalized experiences, grounding agents in data, and working with unstructured data. • Agent #TestingAndMonitoring: Developing robust testing strategies and utilizing the Agentforce Testing Center for optimal performance. • Agent #Deployment: Creating and deploying agents seamlessly to platforms like Slack. • Agentforce #DevelopmentTools: Building agents with powerful tools such as Agentforce DX, the Agent API, and the Models API. 𝗛𝗼𝘄 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺 𝘆𝗼𝘂𝗿 𝘀𝗸𝗶𝗹𝗹𝘀? 🎯 Beyond the technical knowledge, this Trailhead learning journey hones crucial skills: • Customize and manage advanced agents. • Design AI-driven business strategies that propel organizations forward. • Lead AI adoption efforts and effectively bridge the gap between technical teams and business objectives. 𝗜 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝘁𝗼𝗼𝗸 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝘀𝘁𝗲𝗽, 𝘆𝗼𝘂𝗿 𝘁𝘂𝗿𝗻! 🚀😊 Jakub Katny Justyna Krajewska Łukasz Bujło will you give it a try? #Agentblazer #SalesforceAI #AICertification #Trailhead

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Salesforce built Customer 360 around a simple idea: Every customer interaction should be connected, consistent, and governed by a single source of truth. It solved a decades-long problem: fragmented data across sales, service, and marketing. With Data Cloud, companies finally unified their data fabric. But now, a new kind of fragmentation has arrived. This time, it’s not data. It’s agents. Sales bots, service bots, marketing bots are each powered by its own LLM, each acting in its own domain, none speaking the same language. The result? Disconnected actions, duplicated logic, and rising risk. If Data Cloud unified what we know about the customer, then MuleSoft Agent Fabric will unify how our agents act on that knowledge. Here’s what that looks like: 👉 Agentforce builds the intelligent agents. 👉 Data Cloud gives those agents a unified, real-time memory of the customer. 👉 Agent Fabric orchestrates, governs, and observes them. Together, they create Agent 360. A governed network of intelligent agents working with shared context and enterprise control. This is the next evolution of Customer 360: From unified data → to unified intelligence. From Customer 360 → to Agent 360. Because in the next era, the customer experience won’t be defined by how much data you know. It’ll be defined by how intelligently and responsibly your agents act on it. How close do you think companies really are to building an Agent 360? Are we ready for that level of orchestration yet or still stuck in pilot mode? #MuleSoft #AgentFabric #Agentforce #DataCloud #AIIntegration #AgenticEnterprise  MuleSoft Community

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Salesforce #sponsored my post about data during an AI hype cycle, which begs the question: If agentic AI is the future of business, why are we all still talking about data? AI has a last-mile problem: Agents work well in demos but struggle in the real world. That’s because agents can’t create value without access to data. The business’s AI agents can be running GPT-7, but if they can’t pull up the customer’s order history data in a few seconds, they can’t process a return or reorder. Data is critical for agency or the ability to take action. Salesforce’s Data Cloud calls it ‘Right-Time’ data because real-time (sub-second) is expensive and rarely necessary to support the use case. However, keep a customer waiting too long and they’ll go elsewhere. Salesforce executives shared 3 more agentic ROI success secrets with me. No action, no ROI. AI and agents work, but without trusted data, they don’t work reliably enough to do anything useful. No trust, no ROI. If data governance doesn’t align with use cases, agents reveal too much or go off the rails and lose trust. No scale, no ROI. Data must scale across the enterprise and its products for agents to succeed, but moving data around the business is expensive, so metadata management and Zero Copy are critical. The intelligent core of every business runs on information. Learn how Data Cloud helps Salesforce scale its agents to deliver quantifiable ROI that defies the hype. https://lnkd.in/gEx2hH7y

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AI > SaaS Salesforce beat earnings. Stock still dropped. Why? Because Wall Street sees through the AI hype. Salesforce announced 4,000 human jobs gone, replaced by “Agentforce.” BUT growth is stalling. Guidance disappointed. Core SaaS products are soft. And the AI halo for legacy SaaS? It’s fading. Here’s the real story: AI isn’t saving legacy SaaS ... it’s disrupting it. AI-native platforms aren’t augmenting software. They’re replacing it. This isn’t Salesforce story. It’s a warning shot for every legacy software vendor. The future isn’t SaaS + AI. It’s AI > SaaS.

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I’ll never use Salesforce data for analysis again — here’s why and what we’re using instead Why Salesforce data was never that great Let’s say you want to understand why you win or lose against a competitor. Good luck. The data is: - Inconsistent — some reps are great at filling out Salesforce, others don’t fill it out at all - Incomplete — even great reps don’t always know the real reasons why a deal was won or lost - Oversimplified — sometimes there are multiple complex factors, and Salesforce forces a checkbox or dropdown When your analysis depends on human memory and manual input, you get a muddy picture at best. Or worse, you build a strategy on bad data. Why there’s a better alternative now Gong + AI. Here's what changes: - Gong captures the actual conversation with the customer. - AI is insanely good at parsing large volumes of messy text and surfacing key themes. - You get a comprehensive, consistent view of what customers are saying — not what sales reps (maybe) remember. Now, I can answer: - Why are we actually winning against competitor X? - What feature requests are popping up in late-stage deals? - What trends are emerging across wins and losses? It’s still not 100% perfect because you don’t know what a customer might not say out loud. But it’s 1000x better than the old way.

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𝗠𝗼𝘀𝘁 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗮𝗶𝗹 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝘁𝗵𝗲𝘆 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗰𝗼𝗺𝗳𝗼𝗿𝘁, 𝗻𝗼𝘁 𝗽𝗿𝗼𝗴𝗿𝗲𝘀𝘀. Too often, companies adopt Salesforce with one goal in mind: 𝘮𝘢𝘬𝘦 𝘦𝘹𝘪𝘴𝘵𝘪𝘯𝘨 𝘱𝘳𝘰𝘤𝘦𝘴𝘴𝘦𝘴 𝘧𝘢𝘴𝘵𝘦𝘳. But here’s the problem—speed means nothing if the direction is wrong.  • If your approvals still take three layers,  • If your leads still get lost in handoffs,  • If your reports still reflect outdated KPIs... Then you haven’t transformed. You’ve just made the status quo more efficient. Salesforce isn’t meant to enshrine the way things have always been. It’s built to challenge how things should be. At Zordial Technologies, before we build a single flow, we ask: “𝗜𝗳 𝘄𝗲 𝘄𝗲𝗿𝗲 𝗱𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝘁𝗼𝗱𝗮𝘆 — 𝘄𝗶𝘁𝗵 𝘇𝗲𝗿𝗼 𝗹𝗲𝗴𝗮𝗰𝘆 — 𝘄𝗵𝗮𝘁 𝘄𝗼𝘂𝗹𝗱 𝗶𝘁 𝗹𝗼𝗼𝗸 𝗹𝗶𝗸𝗲?” That’s when real innovation begins. That’s when Salesforce shifts from a tool to a transformation engine. So the real question isn’t “How can we automate this?” It’s “𝘚𝘩𝘰𝘶𝘭𝘥 𝘵𝘩𝘪𝘴 𝘦𝘷𝘦𝘯 𝘦𝘹𝘪𝘴𝘵 𝘪𝘯 𝘵𝘩𝘦 𝘧𝘪𝘳𝘴𝘵 𝘱𝘭𝘢𝘤𝘦?” 𝗪𝗵𝗮𝘁 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗻𝗴 — 𝘁𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗻𝗲𝗲𝗱𝘀 𝗿𝗲𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴?

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