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AI Agents Are the Future of Enterprise

Persona-Centric Intelligence at Scale

The CIO’s Playbook for AI Success: Persona-Centric Intelligence at Scale The New Imperative: AI That Works the Way Your Teams Do In today’s digital-first economy, AI isn’t just a tool—it’s the operating system of modern business. But too many enterprises treat AI as a one-size-fits-all solution, leading to low adoption, wasted investment, and fragmented value. The winning strategy? Persona-based AI—designing intelligence that adapts to how different roles actually work. From Siloed to Strategic: The Evolution of Enterprise AI The Problem With Platform-Locked AI Most organizations deploy AI in disconnected pockets—Salesforce for sales, Workday for HR, SAP for finance. This creates:🔴 Duplicated efforts (multiple AI models doing similar tasks)🔴 Inconsistent insights (CRM AI says one thing, ERP AI another)🔴 Vendor lock-in (intelligence trapped in specific systems) The Solution: System-Agnostic Intelligence Forward-thinking CIOs are shifting to centralized AI “as a service”—decoupling intelligence from individual platforms to power seamless, cross-functional workflows. Example: 4 Pillars of a Persona-Based AI Strategy 1. Role-Specific Intelligence AI should augment, not disrupt existing workflows:🔹 Sales Reps: Real-time deal coaching, automated lead scoring🔹 Customer Support: AI-generated case summaries, sentiment-triggered escalations🔹 HR Teams: Smart resume screening, personalized onboarding bots Real-World Impact: *”Salesforce’s Agentforce cuts rep ramp time by 40% with AI role-plays tailored to each rep’s deal pipeline.”* 2. Generative AI That Works Behind the Scenes GenAI isn’t just for drafting emails—it’s automating high-value workflows:✔ Marketing: Dynamically localizing campaign creatives✔ Legal: Auto-redlining contracts against playbooks✔ IT: Converting trouble tickets into executable scripts Key Consideration: Guardrails matter—implement strict controls for data privacy and IP protection. 3. Edge AI for Real-Time Action Smart Cities Example:📍 Problem: Mumbai’s traffic gridlock costs $22B/year in lost productivity📍 AI Solution: Edge-powered cameras + sensors dynamically reroute vehicles without cloud latency📍 Outcome: 30% faster emergency response times Enterprise Use Cases: 4. Intelligent Automation: The Silent Productivity Engine Combining RPA + AI automates complex processes end-to-end:🔸 Finance: Invoice matching → fraud detection → payment approvals🔸 Supply Chain: Demand forecasting → autonomous PO generation🔸 IT: Self-healing network alerts → auto-remediation The CIO Action Plan 1. Audit Existing AI Deployments 2. Build a Central AI Layer 3. Start With High-Impact Personas Prioritize roles where AI drives measurable ROI:🎯 Field Service Techs: AR-guided repairs + parts forecasting🎯 Account Managers: Churn risk alerts + upsell scripts 4. Measure What Matters Track persona-specific metrics: The Future Is Adaptive The next frontier? “Living Intelligence”—AI that evolves with user behavior: *”By 2026, persona-driven AI will boost enterprise productivity by 35%.”*—Gartner “The best AI doesn’t feel like AI—it feels like a smarter way to work.” Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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unpatched ai

Scrape the Web for Training Data

Do AI Companies Have the Right to Scrape the Web for Training Data? For the past two years, generative AI companies have faced lawsuits—some from high-profile authors and publishers—while simultaneously striking multi-million-dollar data licensing deals. Despite the legal battles, the political tide seems to be shifting in favor of AI firms. Both the European Union and the UK appear to be leaning toward an “opt-out” model, where web scraping is permitted unless content owners explicitly forbid it. But critical questions remain: How exactly does “opting out” work? And do creators and publishers truly have a fair chance to do so? Data as the New Oil The most valuable asset in AI isn’t GPUs or data centers—it’s the training data itself. Without the vast troves of text, images, videos, and artwork produced over decades (or even centuries), there would be no ChatGPT, Gemini, or Claude. Web scraping is nothing new. Search engines like Google have relied on crawlers for decades, indexing the web to deliver search results. But the rules of the game have changed. Old Conventions, New Conflicts Historically, website owners welcomed search engine crawlers to boost visibility while others (especially news publishers) saw them as competitors. The Robots Exclusion Standard (robots.txt) emerged as a gentleman’s agreement—a way for sites to signal which pages could be crawled. While robots.txt isn’t legally binding, reputable search engines like Google and Bing generally respect it. The arrangement was symbiotic: websites got traffic, and search engines got data. But AI crawlers operate differently. They don’t drive traffic—they consume content to generate competing products, often commercializing it via AI services. Will AI companies play fair? Nick Clegg, former UK deputy PM and current Meta executive, bluntly stated that requiring permission from artists would “kill” the AI industry. If unfettered data access is seen as existential, can we expect AI firms to respect opt-outs? Can Websites Really Block AI Crawlers? Theoretically, yes—by blocking AI user agents or monitoring suspicious traffic. But this is a game of whack-a-mole, requiring constant vigilance. And what about offline content? Books, research papers, and proprietary datasets aren’t protected by robots.txt. Some AI companies have allegedly bypassed ethical scraping altogether, sourcing data from shadowy corners of the internet—like torrent sites—as revealed in a recent lawsuit against Meta. The Transparency Problem Even if content owners could opt out, how would they know if their data was already used? Why resist transparency? Only two explanations make sense: Neither is a good look. Beyond Copyright: The Bigger Questions This debate isn’t just about copyright—it’s about: And what happens when Google replaces traditional search with AI summaries? Websites may face an impossible choice: Allow AI training or disappear from search results altogether. The Future of the Open Web If AI companies continue scraping indiscriminately, the open web could shrink further, with more content locked behind paywalls and logins. Ironically, the very ecosystem AI relies on may be destroyed by its own hunger for data. The question isn’t just whether AI firms have the right to scrape the web—but whether the web as we know it will survive their appetite. Footnotes Key Takeaways ✅ AI companies are winning the legal/political battle for web scraping rights.⚠️ Opt-out mechanisms (like robots.txt) may be ignored.🔍 Transparency is lacking—many AI firms won’t disclose training data sources.🌐 Indiscriminate scraping could kill the open web, pushing content behind paywalls. Would love to hear your thoughts—should AI companies have free rein over web data, or do content creators deserve more control? Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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Agentforce to the Team

How Agentforce 2.0’s New Model Changes the Game

Salesforce Reinvents AI Pricing: How Agentforce 2.0’s New Model Changes the Game From Conversations to Actions: Salesforce’s Bold Pricing Shift When Salesforce launched Agentforce 2.0 in October 2024, it raced ahead of competitors like Microsoft, SAP, and ServiceNow, positioning itself as the go-to platform for enterprise AI agents. The initial -per-conversation model worked well for simple use cases—like AI handling frontline customer chats—but as businesses experimented further, limitations emerged. Now, Salesforce is rolling out a game-changing update: action-based pricing. The New Pricing Model: Pay for What the AI Actually Does Bill Patterson, EVP of Corporate Strategy at Salesforce, explains: “We’re moving to an action-oriented model—charging for the actual work AI agents perform, not just conversations.” Key Features of the New Pricing: ✅ Flex Credits – Universal currency for AI actions across Sales, Service, and Marketing Clouds✅ $0.10 per action (20 credits) – Only pay when the AI completes a task✅ No hidden fees – Unlike hyperscalers, no separate charges for compute, storage, or LLM calls Example: “Think of it like electricity—you don’t pay differently for your fridge vs. your stove. Flex Credits power all AI agents uniformly.”— Bill Patterson Two Major Additions: Flex Agreement & Digital Wallet 1. Flex Agreement: Convert Unused Licenses into AI Credits Many companies overbuy CRM licenses during hiring surges. Now, they can trade unused licenses into Flex Credits for AI agents. Why It Matters: 2. Digital Wallet: Control & Monitor AI Spending A new centralized dashboard lets companies:📊 Track AI agent usage in real-time🛑 Set spending limits (e.g., cap expensive agents)📈 Measure ROI per agent “This isn’t about nickel-and-diming customers—it’s about fair, scalable pricing that grows with AI adoption.” How Does Salesforce Compare to Competitors? Pricing Model Salesforce Hyperscalers (AWS, Azure) AI Startups Basis Actions completed Compute + microservices “Employee replacement” flat fees Flexibility ✅ Universal Flex Credits ❌ Complex tiered pricing ❌ Rigid per-agent costs Transparency ✅ Clear per-action cost ❌ Hidden API/LLM fees ✅ Fixed but inflexible Salesforce’s edge? Agentforce One: The Next Evolution Coming in July 2025, Salesforce is rebranding Einstein One as Agentforce One—a bundled AI package for Sales & Service Cloud users. What’s Included? Goal: Lower the barrier to entry and accelerate AI adoption across Salesforce’s 150,000+ customers. Will This Boost Agentforce Adoption? ✅ 8,000 companies already use Agentforce (fastest-growing Salesforce product ever).✅ Flex Credits remove cost uncertainty.✅ Digital Wallet enables better budgeting. But… 8,000 is just 5% of Salesforce’s customer base. The new pricing could be the push needed to unlock mass adoption. The Bottom Line Salesforce’s pricing shift isn’t just about cost—it’s about trust. By moving to action-based billing, they’re ensuring customers:✔ Only pay for valuable AI work✔ Can scale AI across departments✔ Gain full visibility into ROI What’s next? As AI costs normalize, Salesforce’s flexible, transparent model could set the industry standard. 🚀 Ready to explore Agentforce?Contact us today! “This is the pricing model AI-powered businesses have been waiting for.”— CIO, Fortune 500 Salesforce Customer Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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LLMs and AI

Why Writers Are Disappointed with LLMs

Researchers Explore Why Writers Are Disappointed with LLMs—And Propose a Solution Despite their transformative impact on writing, communication, and creativity, large language models (LLMs) often leave professional writers unsatisfied. A collaborative study by Stony Brook University and Salesforce AI Research investigates this disconnect, identifying key shortcomings in AI-generated text and proposing a manually refined model to better align machine output with human expression. While LLMs like GPT, Claude, and Llama have revolutionized tasks—from scientific writing to creative storytelling—they still struggle to match the depth and originality of human-authored content. A recent study led by Stony Brook’s Assistant Professor Tuhin Chakrabarty, in collaboration with professional writers, pinpoints these limitations and suggests pathways for improvement. The paper received a Best Paper nomination and Honorable Mention at CHI 2025. “A major issue is that LLM-generated text often lacks originality and variation,” says Chakrabarty. The overreliance on LLMs has led to what researchers call algorithmic monoculture—a homogenization of style, where outputs become repetitive, clichéd, and rhetorically shallow. Unlike human writers, who employ nuanced narrative techniques, LLMs frequently default to telling rather than showing, missing the layered complexity that defines compelling writing. Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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Why 89% of AI Pilots Fail – And How to Beat the Odds

The AI Pilot Paradox: High Hopes, Low Deployment Your leadership team gets excited about AI. They greenlight an agentic AI pilot. Employees test it enthusiastically. Then… nothing happens. The project collects dust while the organization moves on to the next shiny tech initiative. This scenario plays out in 89% of companies, according to our analysis of industry data. While AI pilot projects surged 76% year-over-year in 2024 (KPMG), only 11% ever reach full deployment. The 7 Deadly Sins of AI Pilot Failure 1. Solution Looking for a Problem (60% of failures) The Trap: Starting with technology rather than business needsThe Fix: 2. The Ivory Tower Syndrome (45% of failures) The Trap: IT-led projects without business unit buy-inThe Fix: 3. Perfection Paralysis (38% of failures) The Trap: Waiting for flawless performance before launchThe Fix: 4. Data Debt Disaster (52% of failures) The Trap: Unstructured, outdated, or siloed dataThe Fix: 5. Zero-to-Hero Expectations (41% of failures) The Trap: Expecting full competency on Day 1The Fix: 6. Launch-and-Leave Mentality (63% of failures) The Trap: No ongoing optimizationThe Fix: 7. Build vs. Buy Blunders (72% of failures) The Trap: Underestimating custom AI development costsThe Fix: The Agentforce Advantage: 3 Deployment Success Stories 1. Clinical Trial AcceleratorChallenge: 6-month participant screening backlogSolution: AI agent pre-qualifies candidates using EHR dataResult: 58% faster trial enrollment 2. Luxury Retail ConciergeChallenge: High-touch customers demanded 24/7 styling adviceSolution:* Agentforce-powered shopping assistant with: 3. Global Support TransformationChallenge: 45% first-call resolution rateSolution:* Tiered AI agent deployment: Your AI Deployment Checklist ✅ [ ] Identify 3-5 measurable pain points✅ [ ] Form cross-functional pilot team✅ [ ] Conduct data health assessment✅ [ ] Select phased rollout approach✅ [ ] Define success metrics (KPIs)✅ [ ] Plan ongoing optimization process Pro Tip: Companies using this framework see 3.2x higher deployment success rates compared to ad-hoc approaches. Beyond the Pilot: The AI Maturity Journey Where is your organization on this path? The most successful enterprises treat AI adoption as a continuous transformation – not a one-time project. Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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Agentic AI Race

How Agentic AI is Redefining Customer Service

Australia’s AI-Powered CX Revolution: How Agentic AI is Redefining Customer Service The Rise of Autonomous Customer Experience Australia has become a global proving ground for a radical shift in customer service – one where AI agents don’t just assist but independently resolve issues, predict needs, and transform brand interactions. This isn’t about simple chatbots following scripts; it’s about agentic AI – intelligent digital agents capable of complex problem-solving, seamless human handoffs, and continuous self-improvement. Leading companies like Zendesk, Salesforce, and digital accommodation provider Urban Rest are already deploying these systems at scale, fundamentally reshaping what customer experience means in 2024 and beyond. Why Agentic AI Changes Everything 1. From Scripted Responses to Genuine Problem-Solving 2. The New Pricing Model: Pay for Resolution, Not Interactions Zendesk is pioneering a radical approach: 3. The Marketing Transformation Salesforce ANZ’s Leandro Perez sees CMOs becoming CX orchestrators: Real-World Deployments Right Now Salesforce’s AI Layer Urban Rest’s Digital Concierge The Human-AI Balance: Trust & Transparency Key insights from frontline deployments: What Leaders Need to Do Now “The last generation managed only humans. The next will manage teams of AI agents,” notes Perez. “That changes everything about leadership.” How Agentic AI is Redefining Customer Service Agentic AI isn’t coming – it’s already here. Early adopters are seeing: As Zendesk’s Gavin puts it: “Don’t wait for perfect. Start learning now – because your competitors certainly are.” The question isn’t whether to adopt, but how fast you can implement responsibly. Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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Salesforce’s AI Evolution

AI-Powered Sales Enablement

AI-Powered Sales Enablement: The Future of High-Performance Selling The AI Revolution in Sales Artificial intelligence is fundamentally transforming sales organizations, with adoption rates skyrocketing 76% since 2018. Top-performing sales teams are 2.8X more likely to leverage AI than underperformers, and for good reason – AI-powered enablement delivers measurable results: 5 Game-Changing AI Applications for Sales Teams 1. Intelligent Content Delivery The Problem: 73% of sales content goes unused because reps can’t find it during critical moments. AI Solution: Context-aware AI agents surface battlecards, case studies and competitive intelligence in real-time during calls based on: Impact: Deere & Company reduced sales cycles by 22% after implementing AI-powered content recommendations. 2. Conversational Intelligence The Problem: 68% of deals stall due to poor discovery and misaligned follow-ups. AI Solution: NLP-powered tools that: Impact: SAP saw 31% more deals progressing to next stages after implementation. 3. Predictive Deal Guidance The Problem: Complex B2B deals often veer off course without visibility. AI Solution: AI that: Impact: A Fortune 500 tech firm increased win rates by 19% using predictive deal scoring. 4. Automated Coaching The Problem: Only 26% of sales training is applied on the job. AI Solution: Personalized coaching platforms that: Impact: Cisco reduced new hire ramp time by 40% with AI coaching. 5. Marketing-Sales Feedback Loop The Problem: 82% of marketing content misses the mark for sales teams. AI Solution: AI that: Impact: A SaaS company improved content ROI by 300% with AI-driven insights. Implementing AI for Maximum Impact Getting Started Critical Success Factors The Future of AI in Sales As generative AI matures, we’ll see: “The sales organizations that will dominate this decade aren’t those with the most reps, but those that best leverage AI to amplify human potential.” – Gartner Sales Practice Ready to transform your sales enablement? Contact Tectonic today! Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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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 AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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Moving Beyond Large Language Models

The Future of Generative AI: Moving Beyond Large Language Models Why LLMs Aren’t Enough Large Language Models (LLMs) like GPT-4, Claude, and Llama have revolutionized AI with their ability to generate human-like text. But they come with critical limitations: These flaws make LLMs unreliable for high-stakes applications like legal research, medical diagnosis, or real-time decision-making. So, what comes next? Emerging Alternatives to LLMs While LLMs won’t disappear, the next wave of AI will likely combine them with smarter, more efficient models. 1. Logical Reasoning Systems Potential Hybrid Approach:LLMs generate responses → Logical AI verifies accuracy. 2. Real-Time Learning Models (e.g., AIGO) 3. Liquid Learning Networks (LLNs) 4. Small Language Models (SLMs) The Future: Hybrid AI Systems The most powerful AI won’t rely on just one model—it will combine the best of each: This hybrid approach could finally deliver AI that’s both smart and reliable. What’s Next? The AI revolution isn’t over—it’s just getting started. Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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Does Salesforce Have Artificial Intelligence?

AI Goes Mainstream

AI Goes Mainstream: How Small Businesses Are Harnessing Autonomous Agents for Growth Artificial intelligence is no longer just for big corporations. As generative AI tools have become more accessible, small and medium-sized businesses (SMBs) are rapidly adopting AI—with 75% now investing in AI solutions, according to recent data. High-growth SMBs are nearly twice as likely to embrace AI than those struggling to stay afloat. The shift from generative AI to agentic AI—where AI systems autonomously make decisions and take action—is unlocking even greater potential for SMBs. “We’re entering a new era of productivity that will transform businesses of all sizes, especially SMBs,” says Adam Evans, EVP & GM of Salesforce AI, who leads Agentforce, a platform that embeds AI agents into business workflows. “With autonomous AI, small teams can scale like never before.” A serial entrepreneur who sold two AI startups to Salesforce, Evans understands the challenges SMBs face. “Small businesses are always stretched thin. Agentforce gives them a 24/7 digital workforce across sales, service, and marketing—unlocking unlimited capacity.” Here’s how forward-thinking SMBs are using AI to drive growth: 1. Automated Marketing at Scale Many SMBs have tiny (or even one-person) marketing teams. AI-powered agents can:✅ Generate campaign briefs in seconds✅ Identify high-value audience segments✅ Create personalized content and customer journeys✅ Optimize campaigns in real time based on performance “Agentforce doesn’t just set up campaigns—it continuously refines them, ensuring maximum impact,” says Evans. 2. Hyper-Personalized Sales Outreach Generic sales emails don’t cut it anymore. AI agents can now craft bespoke outreach by:📊 Pulling CRM data on past interactions🏢 Analyzing prospect company profiles📑 Applying a business’s best sales playbooks “The AI synthesizes all this to write emails tailored to each lead’s role, industry, and interests,” Evans explains. 3. AI-Powered Shopping Assistants Imagine an AI personal shopper that:🛍️ Guides customers to the perfect product💬 Answers questions via chat (on websites, WhatsApp, etc.)🤝 Upsells and cross-sells intelligently “Agentforce acts as a 24/7 sales rep, helping convert browsers into buyers while freeing up human teams for high-touch relationships,” says Evans. The Bottom Line With AI handling repetitive tasks, SMBs can:✔ Compete with larger players despite smaller teams✔ Deliver enterprise-grade personalization✔ Turn data into actionable insights instantly “The businesses that thrive will be those that deploy AI agents to handle routine work while humans focus on strategy and creativity,” Evans predicts. “This isn’t the future—it’s happening right now.” For SMBs, the message is clear: AI adoption is no longer optional. It’s the key to staying relevant, efficient, and competitive. Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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Expanded Availability of Marketing Cloud Growth and Advanced

Expanded Availability of Marketing Cloud Growth and Advanced

What the Expanded Global Availability of Marketing Cloud Growth and Advanced Editions Means for You Salesforce is bringing more power, more reach, and more connections to marketers around the globe. Since the debut of Marketing Cloud Growth and Advanced Editions last spring, Salesforce has steadily expanded their global footprint—bringing powerful capabilities to marketers worldwide. In 2024, these editions rolled out across North America, Asia/Middle East, and Latin America, enabling organizations to unify marketing, sales, service, and commerce on a single platform. With built-in access to Agentforce, teams can now save time and unlock smarter marketing by tapping into data from across the Salesforce ecosystem. Now, in spring 2025, Salesforce is extending access even further—launching in five new regions and enabling new channels like WhatsApp. This means more businesses can take advantage of unified workflows, regional data residency, and AI-powered customer journeys at scale. 🌍 New Regions Now Supported As of early 2025, Marketing Cloud Growth and Advanced Editions (and Data Cloud) are now available in five additional regions, enhancing data residency and local compliance: Why it matters:Data residency—storing and processing data in the same region it’s collected—is critical for compliance, trust, and security. These new region-specific deployments help businesses meet local regulations and ensure a secure, performant experience for users. What’s next?Additional regions, including markets across ASEAN, are set to go live in the first half of 2025. 📲 Channel Expansion: Now with Native WhatsApp Salesforce has also expanded channel support for Marketing Cloud Growth and Advanced Editions by introducing native WhatsApp messaging. 🚀 The Big Picture With expanded regional support, native WhatsApp messaging, and seamless integration with Agentforce and Data Cloud, Marketing Cloud Growth and Advanced Editions are empowering global teams to deliver more personalized, automated, and compliant experiences—at scale. This is marketing that meets the moment—wherever your customers are. Like Related Posts AI Automated Offers with Marketing Cloud Personalization AI-Powered Offers Elevate the relevance of each customer interaction on your website and app through Einstein Decisions. Driven by a Read more 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

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