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19Jan

Generative AI in CX

Generative AI in CX: Opportunities and Challenges Generative AI offers the promise of transformative efficiency and innovation in customer experience (CX). However, businesses face significant hurdles in adopting the technology, including budget constraints, compliance challenges, and internal alignment issues. A Growing Gap Between Innovation and AdoptionCX technology vendors often outpace their customers in releasing advanced features. With generative AI, this gap feels wider than ever. For example, Zendesk’s CX Trends 2025 report revealed that over 25% of surveyed businesses have delayed AI adoption due to budgetary, knowledge, or organizational support barriers. Similarly, an October survey by NTT Data found that more than half of senior IT decision-makers had yet to align generative AI strategies with business goals. While only 39% of respondents reported significant investments in generative AI, most companies remain in early phases, such as pilots and trials. Some businesses, however, have no plans to invest at all. Early Adoption in CXDespite these challenges, early adopters are exploring generative AI applications in customer service and contact centers. AI-powered bots, or “agents,” are proving effective in summarizing answers and improving efficiency. However, deploying these agents requires substantial preparation, such as organizing customer data and defining roles and processes—a significant task for many IT teams. John Seeds, CMO at TTEC Digital, emphasized the importance of using generative AI internally first:“We start by addressing inconsistencies and cleaning up data. Once that’s done, businesses can present it effectively to reduce inbound calls and enhance self-service in contact centers.” Expanding Beyond Customer ServiceGenerative AI is also being embraced by marketing and e-commerce teams. Platforms like Salesforce, Google, and Sitecore have introduced tools that assist with campaign ideation and content creation. While these tools don’t always produce polished outputs, they serve as powerful starting points for creatives. The Generative AI RevolutionAI has been a staple in CX for years, powering analytics, natural language processing, and automation. But the release of OpenAI’s ChatGPT in late 2022 revolutionized the field. John Ball, SVP at ServiceNow, noted:“Generative AI has removed the need for handcrafting every dialogue or intent model. It opens up possibilities for chat and email recommendations without requiring as much manual setup.” Similarly, Salesforce AI executives, including Silvio Savarese, highlighted the technology’s unprecedented adoption:“It was incredible to see how quickly generative AI captured global attention,” Savarese said. Questions of Autonomy and TrustThe rise of AI agents introduces questions about trust and autonomy. Can bots make decisions that keep customers happy? What happens if they make mistakes? As companies explore these possibilities, many are focusing on augmenting human workflows rather than replacing them entirely. For example, Trimedx plans to use ServiceNow’s generative AI to automate report generation for its clinical hardware in hospitals. This application aims to save time while supporting human decision-making. Similarly, Siemens has deployed its own AI “bionic agent” to handle tasks like supply chain management, with generative AI accelerating customization and productivity. Regulatory and Ethical ConsiderationsAs adoption grows, so do concerns around compliance and copyright. The Biden administration’s recent CX-related regulations, including a ban on junk fees, could influence how AI is integrated into business processes. Additionally, initiatives like Adobe’s Content Authenticity Initiative aim to ensure transparency in AI-generated content by providing tools to verify the origins and editing history of digital assets. The Road AheadGenerative AI holds immense potential to transform CX by improving efficiency, reducing costs, and driving innovation. However, businesses must address challenges in data readiness, compliance, and ethical usage to fully realize its benefits. While early adopters are making strides, widespread success will depend on thoughtful implementation and alignment with organizational goals. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 19, 2025in Data, Generative AI, Google, Salesforce, Technology0 Comments

18Jan

From Generative AI to Agentic AI

Understanding the Coming Shift: From Generative AI to Agentic AI Large Language Models (LLMs), such as GPT, excel at generating text, answering questions, and supporting various tasks. However, they operate reactively, responding only to the input they receive based on learned patterns. LLMs cannot make decisions independently, adapt to new situations, or plan ahead. Agentic AI addresses these limitations. Unlike Generative AI, Agentic AI can set goals for itself, take initiative by itself, and learn from its experiences. It is proactive, capable of adjusting its actions over time, and can manage complex, evolving tasks that demand continuous problem-solving and decision-making. This transition from reactive to proactive AI unlocks exciting new possibilities across industries. In this insight, we will explore the differences between Agentic AI and Generative AI, examining their distinct impacts on technology and industries. Let’s begin by understanding what sets them apart. What is Agentic AI? Agentic AI refers to systems capable of autonomous decision-making and action to achieve specific goals. These systems go beyond generating content—they interact with their environments, respond to changes, and complete tasks with minimal human guidance. For example: What is Generative AI? Generative AI focuses on creating content—text, images, music, or video—by learning from large datasets to identify patterns, styles, or structures. For instance: Generative AI acts like a creative assistant, producing content based on what it has learned, but it remains reactive and task-specific. Key Differences in Workflows Agentic AI employs an iterative, cyclical workflow that includes stages like “Thinking/Research” and “Revision.” This adaptive process involves self-assessment, testing, and refinement, enabling the system to learn from each phase and tackle complex, evolving tasks effectively. Generative AI, in contrast, follows a linear, single-step workflow, moving directly from input to output without iterative improvements. While efficient for straightforward tasks, it lacks the ability to revisit or refine its results, limiting its effectiveness for dynamic or nuanced challenges. Characteristics of Agentic AI vs. Generative AI Feature Agentic AI Generative AI Autonomy Acts independently, making decisions and executing tasks. Requires human input to generate responses. Behavior Goal-directed, proactively working toward specific objectives. Task-oriented, reacting to immediate prompts. Adaptation and Learning Learns from experiences, adjusting actions dynamically. Operates based on pre-trained patterns, without learning. Decision-Making Handles complex decisions, weighing multiple outcomes. Makes basic decisions, selecting outputs based on patterns. Environmental Perception Understands and interacts with its surroundings. Lacks awareness of the physical environment. Case Study: Agentic Workflow in Action Andrew Ng highlighted the power of the Agentic Workflow in a coding task. Using the HumanEval benchmark, his team tested two approaches: This illustrates how iterative methods can enhance performance, even for older AI models. Conclusion As AI becomes increasingly integrated into our lives and workplaces, understanding the distinction between Generative AI and Agentic AI is essential. Generative AI has transformed tasks like content creation, offering immediate, reactive solutions. However, it remains limited to following instructions without true autonomy. Agentic AI represents a significant leap in technology. From chatbots to today. By setting goals, making decisions, and adapting in real-time, it can tackle complex, dynamic tasks without constant human oversight. Approaches like the Agentic Workflow further enhance AI’s capabilities, enabling iterative learning and continuous improvement. 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 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

January 18, 2025in Agentic AI, Data, Generative AI, Technology0 Comments

14Jan

On Premise Gen AI

In 2025, enterprises transitioning generative AI (GenAI) into production after years of experimentation are increasingly considering on-premises deployment as a cost-effective alternative to the cloud. Since OpenAI ignited the AI revolution in late 2022, organizations have tested large language models powering GenAI services on platforms like AWS, Microsoft Azure, and Google Cloud. These experiments demonstrated GenAI’s potential to enhance business operations while exposing the substantial costs of cloud usage. To avoid difficult conversations with CFOs about escalating cloud expenses, CIOs are exploring on-premises AI as a financially viable solution. Advances in software from startups and packaged infrastructure from vendors such as HPE and Dell are making private data centers an attractive option for managing costs. A survey conducted by Menlo Ventures in late 2024 found that 47% of U.S. enterprises with at least 50 employees were developing GenAI solutions in-house. Similarly, Informa TechTarget’s Enterprise Strategy Group reported a rise in enterprises considering on-premises and public cloud equally for new applications—from 37% in 2024 to 45% in 2025. This shift is reflected in hardware sales. HPE reported a 16% revenue increase in AI systems, reaching $1.5 billion in Q4 2024. During the same period, Dell recorded a record .6 billion in AI server orders, with its sales pipeline expanding by over 50% across various customer segments. “Customers are seeking diverse AI-capable server solutions,” noted David Schmidt, senior director of Dell’s PowerEdge server line. While heavily regulated industries have traditionally relied on on-premises systems to ensure data privacy and security, broader adoption is now driven by the need for cost control. Fortune 2000 companies are leading this trend, opting for private infrastructure over the cloud due to more predictable expenses. “It’s not unusual to see cloud bills exceeding 0,000 or even million per month,” said John Annand, an analyst at Info-Tech Research Group. Global manufacturing giant Jabil primarily uses AWS for GenAI development but emphasizes ongoing cost management. “Does moving to the cloud provide a cost advantage? Sometimes it doesn’t,” said CIO May Yap. Jabil employs a continuous cloud financial optimization process to maximize efficiency. On-Premises AI: Technology and Trends Enterprises now have alternatives to cloud infrastructure, including as-a-service solutions like Dell APEX and HPE GreenLake, which offer flexible pay-per-use pricing for AI servers, storage, and networking tailored for private data centers or colocation facilities. “The high cost of cloud drives organizations to seek more predictable expenses,” said Tiffany Osias, vice president of global colocation services at Equinix. Walmart exemplifies in-house AI development, creating tools like a document summarization app for its benefits help desk and an AI assistant for corporate employees. Startups are also enabling enterprises to build AI applications with turnkey solutions. “About 80% of GenAI requirements can now be addressed with push-button solutions from startups,” said Tim Tully, partner at Menlo Ventures. Companies like Ragie (RAG-as-a-service) and Lamatic.ai (GenAI platform-as-a-service) are driving this innovation. Others, like Squid AI, integrate custom AI agents with existing enterprise infrastructure. Open-source frameworks like LangChain further empower on-premises development, offering tools for creating chatbots, virtual assistants, and intelligent search systems. Its extension, LangGraph, adds functionality for building multi-agent workflows. As enterprises develop AI applications internally, consulting services will play a pivotal role. “Companies offering guidance on effective AI tool usage and aligning them with business outcomes will thrive,” Annand said. This evolution in AI deployment highlights the growing importance of balancing technological innovation with financial sustainability. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 14, 2025in Data, Enterprise, Generative AI, Google, Technology0 Comments

13Jan

Payload and REDA

Payload and REDA One Launch REDA Pay Embedded Payment Solution Payload has unveiled REDA Pay, an embedded payment solution tailored for Salesforce users. This new offering stems from a strategic partnership between Payload and REDA One, aiming to streamline and enhance payment processes for businesses. “REDA One needed a payment solution that could be deployed quickly, efficiently, and effectively to expand their platform’s capabilities,” said Zach Jacob, Vice President of Partnerships at Payload. “Payload’s robust APIs proved to be the perfect match, seamlessly integrating with REDA One’s existing infrastructure.” Jacob emphasized the ease and speed of implementation, noting, “In no time, REDA One was able to activate REDA Pay, demonstrating the simplicity and adaptability of our payment tools. This collaboration underscores Payload’s commitment to delivering powerful, straightforward solutions that enable SaaS platforms like REDA One to provide cutting-edge payment experiences without unnecessary complexity.” The Growing Role of Embedded Payments Highlighting the importance of embedded payments, Jacob stated, “In today’s digital era, embedded payments are not just a feature—they are an essential element of an exceptional user experience.” With REDA Pay, Salesforce users can now process payments seamlessly within their workflows, reducing friction and enhancing efficiency. Jacob outlined three core advantages of REDA Pay: Elevating SaaS Platforms Jacob also highlighted the broader impact of this launch for SaaS providers:“REDA Pay exemplifies how effortlessly SaaS platforms can elevate their offerings by integrating embedded payment solutions. Payload’s APIs are designed for seamless integration, enabling platforms to quickly add enhanced payment capabilities for their users. This not only improves the user experience but also unlocks new opportunities for growth and revenue.” With REDA Pay, Payload and REDA One have set a new standard for embedded payment solutions in Salesforce, driving innovation and efficiency for businesses in the digital age. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 13, 2025in Salesforce0 Comments

Apple's Privacy Changes: A Call for Email Marketing Innovation

09Jan

Liar Liar Apple on Fire

Apple Developing Update After AI System Generates Inaccurate News Summaries Apple is working on a software update to address inaccuracies generated by its Apple Intelligence system after multiple instances of false news summaries were reported. The BBC first alerted Apple in mid-December to significant errors in the system, including a fabricated summary that falsely attributed a statement to BBC News. The summary suggested Luigi Mangione, accused of killing United Healthcare CEO Brian Thompson, had shot himself, a claim entirely unsubstantiated. Other publishers, such as ProPublica, also raised concerns about Apple Intelligence producing misleading summaries. While Apple did not respond immediately to the BBC’s December report, it issued a statement after pressure mounted from groups like the National Union of Journalists and Reporters Without Borders, both of which called for the removal of Apple Intelligence. Apple assured stakeholders it is working to refine the technology. A Widespread AI Issue: Hallucinations Apple joins the ranks of other AI vendors struggling with generative AI hallucinations—instances where AI produces false or misleading information. In October 2024, Perplexity AI faced a lawsuit from Dow Jones & Co. and the New York Post over fabricated news content attributed to their publications. Similarly, Google had to improve its AI summaries after providing users with inaccurate information. On January 16, Apple temporarily disabled AI-generated summaries for news apps on iPhone, iPad, and Mac devices. The Core Problem: AI Hallucination Chirag Shah, a professor of Information Science at the University of Washington, emphasized that hallucination is inherent to the way large language models (LLMs) function. “The nature of AI models is to generate, synthesize, and summarize, which makes them prone to mistakes,” Shah explained. “This isn’t something you can debug easily—it’s intrinsic to how LLMs operate.” While Apple plans to introduce an update that clearly labels summaries as AI-generated, Shah believes this measure falls short. “Most people don’t understand how these headlines or summaries are created. The responsible approach is to pause the technology until it’s better understood and mitigation strategies are in place,” he said. Legal and Brand Implications for Apple The hallucinated summaries pose significant reputational and legal risks for Apple, according to Michael Bennett, an AI adviser at Northeastern University. Before launching Apple Intelligence, the company was perceived as lagging in the AI race. The release of this system was intended to position Apple as a leader. Instead, the inaccuracies have damaged its credibility. “This type of hallucinated summarization is both an embarrassment and a serious legal liability,” Bennett said. “These errors could form the basis for defamation claims, as Apple Intelligence misattributes false information to reputable news sources.” Bennett criticized Apple’s seemingly minimal response. “It’s surprising how casual Apple’s reaction has been. This is a major issue for their brand and could expose them to significant legal consequences,” he added. Opportunity for Publishers The incident highlights the need for publishers to protect their interests when partnering with AI vendors like Apple and Google. Publishers should demand stronger safeguards to prevent false attributions and negotiate new contractual clauses to minimize brand risk. “This is an opportunity for publishers to lead the charge, pushing AI companies to refine their models or stop attributing false summaries to news sources,” Bennett said. He suggested legal action as a potential recourse if vendors fail to address these issues. Potential Regulatory Action The Federal Trade Commission (FTC) may also scrutinize the issue, as consumers paying for products like iPhones with AI capabilities could argue they are not receiving the promised service. However, Bennett believes Apple will likely act to resolve the problem before regulatory involvement becomes necessary. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 9, 2025in Generative AI, Google, Laws, Technology0 Comments

08Jan

A Revolution in Enterprise AI

Salesforce Unveils Agentforce 2.0: A Revolution in Enterprise AI Salesforce has launched Agentforce 2.0, a cutting-edge update poised to redefine how enterprises design, deploy, and manage AI-driven solutions. With a suite of innovative features, this upgrade emphasizes seamless collaboration, enhanced integration, and unprecedented flexibility in creating AI-powered workflows. Agentforce 2.0 focuses on three core advancements: headless agents for programmatic control, deep Slack integration for streamlined teamwork, and a revamped API-driven architecture that simplifies development and deployment. Core Highlights of Agentforce 2.0 1. Enhanced Integration Architecture Agentforce 2.0 introduces a sophisticated integration framework designed to streamline workflows and accelerate development. By leveraging MuleSoft for Flow, it provides 40 pre-built connectors for seamless integration with enterprise systems. At the heart of this architecture is the API Catalog, a centralized hub for discovering, managing, and optimizing APIs within Salesforce. The Topic Center simplifies deployment by embedding Agentforce metadata into API design workflows, minimizing manual configurations and reducing time-to-market. Key features of the API Catalog include: This API-first approach empowers DevOps teams to manage and optimize AI capabilities efficiently through a single interface. 2. Upgraded Atlas Reasoning Engine The Atlas Reasoning Engine takes enterprise AI capabilities to the next level, enabling smarter and more effective AI-driven operations. Key enhancements include: Preliminary testing shows a 33% improvement in response accuracy and a doubling of relevance in complex scenarios compared to previous models. The engine uniquely combines System 1 reasoning (fast, intuitive responses) with System 2 reasoning (deep analytical processing), setting a new benchmark for enterprise AI intelligence. 3. Headless Agents for Greater Control A game-changing feature of Agentforce 2.0 is the introduction of headless agents, which operate autonomously without requiring direct user interaction. Key capabilities include: This feature enables enterprises to build robust, autonomous workflows, making Agentforce 2.0 an indispensable tool for optimizing digital operations. 4. Deep Slack Integration Agentforce 2.0 seamlessly integrates AI with Slack, Salesforce’s collaboration platform, fostering real-time, AI-enhanced teamwork. Technical advancements include: By embedding AI agents directly into Slack, teams can break down silos, enabling smoother collaboration and faster decision-making across departments. 5. Data Cloud Integration Agentforce 2.0 leverages Salesforce’s Data Cloud to enhance data accessibility and intelligence. Key features include: This integration ensures that AI agents can provide real-time, actionable insights by tapping into a comprehensive, unified data ecosystem. Final Thoughts Agentforce 2.0 represents a transformative leap in enterprise AI, combining cutting-edge technologies like headless agents, deep Slack integration, and an advanced API-driven architecture. By empowering organizations to create intelligent, autonomous workflows, Agentforce 2.0 sets a new standard for AI innovation in the enterprise sector. With its ability to streamline collaboration, optimize operations, and unlock new levels of productivity, Agentforce 2.0 positions Salesforce as a leader in the evolving AI landscape, helping businesses stay ahead in the digital age. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 8, 2025in Data, Enterprise, Mulesoft, Salesforce0 Comments

03Jan

Speed to Launch of Agentforce

Agentforce isn’t just another AI platform that requires months of customization. At most customers, they quickly saw its power, launching transformative generative AI experiences in just days—no AI engineers needed. For companies with larger admin teams, the benefits can be even greater. Unlike other platforms, Agentforce places a strong emphasis on data privacy, building on the trust that Salesforce is known for, making these virtual assistants invaluable. We began with employee-facing use cases, saving our team several hours per week. Now, with Agentforce, we’re seeing even more opportunities to drive efficiencies and better serve our customers. “We’re excited to leverage Agentforce to completely overhaul recruitment and enrollment at Unity Environmental University. Instead of traditional forms or chatbots, our students will soon engage with an autonomous recruitment agent directly on our website, offering personalized support throughout the college application process.”– Dr. Melik Khoury, President & CEO, Unity Environmental University “For first-generation college students, the 1:385 coach-to-student ratio makes personalized guidance challenging. By integrating Agentforce into our platform, we’re deploying cutting-edge solutions to better support students. These agents enable our coaches to focus on high-touch, personalized experiences while handling vital tasks like sharing deadlines and answering common questions—24/7.”– Siva Kumari, CEO, College Possible “Agentforce offers organizations a unique opportunity to move beyond incremental improvements and achieve exponential ROI. By automating customer interactions, improving outcomes, and reducing costs, it integrates data, flows, and user interfaces to mitigate risks and accelerate value creation. This agent-based platform approach allows businesses to harness AI’s full potential, revolutionizing customer engagement and paving the way for exponential growth.”– Rebecca Wettemann, CEO and Principal Analyst, Valoir “Autonomous agents powered by Salesforce’s Agentforce are revolutionizing customer experiences by providing fast, accurate, and personalized support around the clock. With advanced AI making decisions and taking actions autonomously, businesses can resolve customer issues more efficiently, fostering deeper interactions and enhancing satisfaction. This innovation enables companies to reallocate human resources to more complex tasks, boosting individual productivity and scaling business growth. Agentforce is setting new standards for seamless sales, service, marketing, and commerce interactions, reinforcing its leadership in customer experience.”– Michael Fauscette, CEO and Chief Analyst, Arion Research LLC “The best way to predict the future is to invent it.” — Alan Kay, Computer Science Pioneer Technology progresses in what biologists call punctuated equilibrium, with new capabilities slowly emerging from labs and tinkerers until a breakthrough shifts the axis of possibility. These pioneering feats create new paradigms, unleashing waves of innovation—much like the Apple Macintosh, the iPhone, and the Salesforce Platform, which revolutionized the enterprise software-as-a-service (SaaS) model and sparked an entire industry. The Age of Agentforce Begins At Dreamforce 2024, Salesforce Futures reflected on the launch of Agentforce, inspired by visions like the Apple Knowledge Navigator. In 2023, we used this inspiration to craft our Salesforce 2030 film, which showcased the collaboration between humans and autonomous AI agents. Now, with Agentforce, we’re witnessing that vision come to life. Agentforce is a suite of customizable AI agents and tools built on the Salesforce Platform, offering an elegant solution to the complexity of AI deployment. It addresses the challenges of integrating data, models, infrastructure, and applications into a unified system. With powerful tools like Agent Builder and Model Builder, organizations can easily create, customize, and deploy AI agents. Salesforce’s Atlas Reasoning Engine empowers these agents to handle both routine and complex tasks autonomously. A New Era of AI Innovation At Dreamforce 2024, over 10,000 attendees raced to build their own agents using the “Agent Builder” experience, turning verbal instructions into fully functioning agents in under 15 minutes. This wasn’t just another chatbot—it’s a new breed of AI that could transform how businesses operate and deliver superior customer experiences. Companies like Saks, OpenTable, and Wiley have quickly embraced this technology. As Mick Costigan and David Berthy of Salesforce Futures explain, “When we see signals like this, it pushes us toward the future. Soon, we’ll see complex, multi-agent systems solving higher-order challenges, both in the enterprise and in consumer devices.” Shaping the Future Agentforce isn’t just a product—it’s a platform for experimentation. With hundreds of thousands of Salesforce customers soon gaining access, the full potential of these tools will unfold in ways we can’t yet imagine. As with every major technological shift, the real magic will lie in how people use it. Every interaction, every agent deployed, and every problem solved will shape the future in unexpected ways. Platform Evolution Adam Evans, Salesforce SVP of Product, notes that Agentforce builds on the company’s transformation over the past four years, following the pattern of Salesforce’s original disruption of enterprise software. Unlike traditional solutions, Agentforce eliminates the need for customers to build their own AI infrastructure, providing a ready-to-use solution. At the core of Agentforce is the Atlas Reasoning Engine, delivering results that are twice as relevant and 33% more accurate than competing solutions. This engine integrates Salesforce Data Cloud, Flow for automation, and the Einstein Trust Layer for governance. Early Customer Results Early Agentforce deployments highlight how organizations are using autonomous agents to enhance, rather than replace, human workers: George Pokorny, Senior VP of Global Customer Success at OpenTable, shared, “Just saving two minutes on a ten-minute call lets our service reps focus on strengthening customer relationships, thanks to seamless integration with Service Cloud, giving us a unified view of diner preferences and history.” 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 3, 2025in Agentforce Platform, Data, Enterprise, Generative AI, Salesforce, Salesforce Data Cloud, Technology0 Comments

02Jan

Agentic AI Revolution

The Agentic AI Revolution: Lead, Follow, or Get Out of the Way The era of agentic AI is here, and the message is clear—if you’re not leading the charge, you’re falling behind. Companies like Wiley and OpenTable are reshaping their industries with autonomous AI agents that don’t just assist but also analyze, strategize, and execute tasks with unparalleled efficiency. As these organizations demonstrate, the key to AI success lies in rewriting the rules of your industry rather than playing catch-up. Rewriting Industry Standards with Agentic AI Wiley: The education giant leveraged Agentforce, a digital labor platform for deploying autonomous AI agents, to transform its customer service operations. By onboarding representatives 50% faster and improving case resolution by 40%, Wiley streamlined its processes in just a few weeks. AI agents now handle registration and payment inquiries, directing students to resources and reducing the workload on human representatives. OpenTable: As the go-to reservation platform for 1.7 billion diners annually, OpenTable deploys AI agents to manage reservation changes and loyalty points. This allows employees to focus on customer relationships. Even a two-minute efficiency gain per interaction translates to massive operational savings. Salesforce Help Site: With over 60 million annual visits, the Salesforce Help site integrated Agentforce to resolve 83% of queries without human involvement. In just weeks, Agentforce doubled its capacity, handling over 32,000 automated conversations. These examples showcase a new era of digital labor where AI agents orchestrate high-value, multistep tasks, working tirelessly to deliver results. Far from replacing humans, they supercharge productivity and innovation, enabling companies to do more than ever before. How to Empower Your Workforce with AI Empowering your workforce for the next wave of AI doesn’t require months of preparation or millions of dollars. You don’t need to build or train your own large language model (LLM). Instead, integrating AI with existing data, automation, and workflows is the key to success, as demonstrated by leaders like Wiley and OpenTable. Here’s how to get started: 1. Real-Time Data Access AI thrives on real-time, high-quality data. Platforms like Salesforce Data Cloud unify structured and unstructured data, connecting it seamlessly to the LLM. Techniques such as retrieval-augmented generation (RAG) and semantic search ensure AI agents can access the most relevant data for any task. 2. Advanced Reasoning AI agents aren’t just about answering queries—they execute complex, multistep tasks. For example, they can process returns, reorder items, and even flag anomalies. Powered by reasoning engines, these agents draw data from systems like CRM, refine plans, and adapt dynamically until the task is completed correctly. 3. Built-In Security AI agents must operate within clear guardrails, knowing their limits and handing tasks off to humans when necessary. Strong permissions and security protocols are essential to ensure data protection and prevent unauthorized actions. 4. Action-Oriented Workflows Generative AI’s real value lies in action. By integrating tools like Salesforce Flow for task automation and MuleSoft APIs for system connectivity, AI agents can execute business workflows such as fraud detection, customer outreach, and case management. 5. Human-AI Collaboration The future of work isn’t AI replacing humans—it’s AI and humans working together. While agents handle data-intensive and repetitive tasks, humans bring strategic thinking, empathy, and creativity. This synergy leads to smarter decisions and redefines workflows across industries. Why Training Your Own LLM May Not Be the Answer Many companies assume training a proprietary LLM will give them a competitive edge. In reality, this process is costly, time-intensive, and requires constant updates to remain accurate. An LLM trained on static data quickly becomes outdated, much like a GPS that fails after the first detour. Instead, companies are turning to out-of-the-box AI solutions that integrate seamlessly with their existing systems. These tools offer the flexibility to scale quickly and adapt in real time, enabling businesses to stay competitive without the heavy lift of building from scratch. Scaling AI for the Future Many organizations remain stuck in pilot phases with AI due to data quality issues and a limited understanding of use cases. Companies like Wiley and OpenTable, however, have cracked the code: integrating prebuilt AI systems with robust data flows, automation, and workflows. By embracing agentic AI, forward-thinking organizations are creating digital labor forces that unlock new efficiencies, enhance customer experiences, and position themselves for long-term success. The trillion-dollar AI opportunity awaits—will you lead or trail behind? 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

January 2, 2025in Agentforce Platform, Agentic AI, Data, Generative AI, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Flow0 Comments

Salesforce Business Automation

Streamlining Business Automation: A Guide to Successful Salesforce Implementation Salesforce is a lightning jolt for business automation, offering powerful tools to enhance efficiency and productivity. However, implementing Salesforce is a complex process that requires strategic planning and execution. This insight will walk you through best practices for Salesforce implementation, helping you avoid common pitfalls and maximize the platform’s benefits. From defining clear business objectives to post-implementation performance measurement, we’ve got you covered. Understanding Salesforce Implementation Implementing Salesforce is more than simply installing software—it’s a strategic process that must align with your business goals. Successful implementation requires understanding each critical phase, including: Each phase builds toward a solution that drives operational improvements and delivers measurable results. The Role of Salesforce in Business Automation Salesforce transforms business processes by automating repetitive tasks, integrating workflows, and providing real-time analytics. These capabilities empower teams to focus on strategic activities, fostering growth and improving customer engagement. The platform’s automation features enhance decision-making, streamline operations, and deliver actionable insights, making it an essential tool for any data-driven organization. Best Practices for Salesforce Implementation 1. Define Clear Business Objectives Set specific, measurable, and strategic goals that Salesforce can address. Identify business challenges and align objectives with user needs to ensure widespread adoption and long-term success. 2. Conduct a Thorough Needs Analysis Analyze existing processes, identify gaps, and engage stakeholders to gather input. A detailed needs analysis ensures Salesforce is configured to address real pain points and deliver value. 3. Develop a Comprehensive Roadmap Create an implementation roadmap outlining timelines, responsibilities, resources, and risk mitigation strategies. A clear roadmap keeps the project on track and fosters effective communication. 4. Prioritize Data Quality and Governance Start by cleansing existing data to remove inaccuracies and duplicates. Implement governance policies to maintain data integrity, ensuring Salesforce delivers accurate insights. 5. Customize Thoughtfully Tailor Salesforce to enhance existing workflows rather than disrupting them. Engage users to understand their needs and avoid unnecessary complexity that could hinder usability or future updates. 6. Engage Certified Salesforce Partners Collaborate with experienced Salesforce partners to leverage best practices, avoid common pitfalls, and tailor the platform to your unique requirements. The Importance of User Adoption and Training User adoption is crucial for Salesforce’s success. Engage end-users early, involve them in the process, and provide tailored, hands-on training. Post-launch, offer continuous support and advanced training to help users unlock Salesforce’s full potential. Strategies to maximize adoption include: Post-Implementation Success Once Salesforce is live, focus on monitoring performance, gathering feedback, and fostering continuous improvement. 1. Measure Success with KPIs Track key performance indicators (KPIs) to evaluate Salesforce’s impact on your business objectives. Identify trends, address challenges, and ensure the platform remains aligned with your goals. 2. Establish a Feedback Mechanism Encourage users to share feedback and suggest improvements. Regularly review input to refine the system and ensure it evolves with your organization’s needs. 3. Provide Ongoing Support Maintain a dedicated support team to address queries and troubleshoot issues promptly. Continuous training sessions keep users updated and confident in leveraging new features. Avoiding Common Pitfalls Awareness of potential challenges can help you mitigate risks. Common pitfalls to avoid include: By addressing these challenges proactively, you set your Salesforce implementation up for success. Embracing the Salesforce Journey Implementing Salesforce is a transformative opportunity for your business. With strategic planning, stakeholder engagement, and a commitment to continuous improvement, Salesforce can revolutionize your operations. If you’re seeking a streamlined solution, consider leveraging tools like Sweep, an AI-powered visual workspace that simplifies Salesforce implementation. With Sweep’s no-code interface, you can design processes, customize fields, and automate workflows effortlessly. Ready to transform your business with Salesforce?Connect with our experts today and unlock the full potential of Salesforce for your organization. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 30, 2024in Salesforce0 Comments

30Dec

2024 The Year of Generative AI

Was 2024 the Year Generative AI Delivered? Here’s What Happened Industry experts hailed 2024 as the year generative AI would take center stage. Operational use cases were emerging, technology was simplifying access, and general artificial intelligence felt imminent. So, how much of that actually came true? Well… sort of. As the year wraps up, some predictions have hit their mark, while others — like general AI — remain firmly in development. Let’s break down the trends, insights from investor Tomasz Tunguz, and what’s ahead for 2025. 1. A World Without Reason Three years into our AI evolution, businesses are finding value, but not universally. Tomasz Tunguz categorizes AI’s current capabilities into: While prediction and search have gained traction, reasoning models still struggle. Why? Model accuracy. Tunguz notes that unless a model has repeatedly seen a specific pattern, it falters. For example, an AI generating an FP&A chart might succeed — but introduce a twist, like usage-based billing, and it’s lost. For now, copilots and modestly accurate search reign supreme. 2. Process Over Tooling A tool’s value lies in how well it fits into established processes. As data teams adopt AI, they’re realizing that production-ready AI demands robust processes, not just shiny tools. Take data quality — a critical pillar for AI success. Sampling a few dbt tests or point solutions won’t cut it anymore. Teams need comprehensive solutions that deliver immediate value. In 2025, expect a shift toward end-to-end platforms that simplify incident management, enhance data quality ownership, and enable domain-level solutions. The tools that integrate seamlessly and address these priorities will shape AI’s future. 3. AI: Cost Cutter, Not Revenue Generator For now, AI’s primary business value lies in cost reduction, not revenue generation. Tools like AI-driven SDRs can increase sales pipelines, but often at the cost of quality. Instead, companies are leveraging AI to cut costs in areas like labor. Examples include Klarna reducing two-thirds of its workforce and Microsoft boosting engineering productivity by 50-75%. Cost reduction works best in scenarios with repetitive tasks, hiring challenges, or labor shortages. Meanwhile, specialized services like EvenUp, which automates legal demand letters, show potential for revenue-focused AI use cases. 4. A Slower but Smarter Adoption Curve While 2023 saw a wave of experimentation with AI, 2024 marked a period of reflection. Early adopters have faced challenges with implementation, ROI, and rapidly changing tech. According to Tunguz, this “dress rehearsal” phase has informed organizations about what works and what doesn’t. Heading into 2025, expect a more calculated wave of AI adoption, with leaders focusing on tools that deliver measurable value — and faster. 5. Small Models for Big Gains In enterprise AI, small, fine-tuned models are gaining favor over massive, general-purpose ones. Why? Small models are cheaper to run and often outperform their larger counterparts when fine-tuned for specific tasks. For example, training an 8-billion-parameter model on 10,000 support tickets can yield better results than a general model trained on a broad corpus. Legal and cost challenges surrounding large proprietary models further push enterprises toward smaller, open-source solutions, especially in highly regulated industries. 6. Blurring Lines Between Analysts and Engineers The demand for data and AI solutions is driving a shift in responsibilities. AI-enabled pipelines are lowering barriers to entry, making self-serve data workflows more accessible. This trend could consolidate analytical and engineering roles, streamlining collaboration and boosting productivity in 2025. 7. Synthetic Data: A Necessary Stopgap With finite real-world training data, synthetic datasets are emerging as a stopgap solution. Tools like Tonic and Gretel create synthetic data for AI training, particularly in regulated industries. However, synthetic data has limits. Over time, relying too heavily on it could degrade model performance, akin to a diet lacking fresh nutrients. The challenge will be finding a balance between real and synthetic data as AI advances. 8. The Rise of the Unstructured Data Stack Unstructured data — long underutilized — is poised to become a cornerstone of enterprise AI. Only about half of unstructured data is analyzed today, but as AI adoption grows, this figure will rise. Organizations are exploring tools and strategies to harness unstructured data for training and analytics, unlocking its untapped potential. 2025 will likely see the emergence of a robust “unstructured data stack” designed to drive business value from this vast, underutilized resource. 9. Agentic AI: Not Ready for Prime Time While AI copilots have proven useful, multi-step AI agents still face significant challenges. Due to compounding accuracy issues (e.g., 90% accuracy over three steps drops to ~50%), these agents are not yet ready for production use. For now, agentic AI remains more of a conversation piece than a practical tool. 10. Data Pipelines Are Growing, But Quality Isn’t As enterprises scale their AI efforts, the number of data pipelines is exploding. Smaller, fine-tuned models are being deployed at scale, often requiring hundreds of millions of pipelines. However, this rapid growth introduces data quality risks. Without robust quality management practices, teams risk inconsistent outputs, bottlenecks, and missed opportunities. Looking Ahead to 2025 As AI evolves, enterprises will face growing pains, but the opportunities are undeniable. From streamlining processes to leveraging unstructured data, 2025 promises advancements that will redefine how organizations approach AI and data strategy. The real challenge? Turning potential into measurable, lasting impact. 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 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

December 30, 2024in Agentic AI, Artificial Intelligence, Data, Enterprise, Generative AI, Technology0 Comments

29Dec

ThoughtSpot AI agent Spotter enables conversational BI

ThoughtSpot Unveils Spotter: A Generative AI-Powered Data Agent ThoughtSpot, a leading analytics vendor, has launched Spotter, an advanced generative AI-powered agent designed to revolutionize how users interact with data. Spotter enables conversational data exploration, contextual understanding, and autonomous analysis, making it a significant leap forward in the analytics landscape. Spotter’s Role in ThoughtSpot’s Evolution Spotter replaces Sage, ThoughtSpot’s earlier generative AI-powered interface, which debuted in March 2023. Despite moving from private to public preview and gaining new capabilities, Sage never reached general availability. Spotter is now generally available for ThoughtSpot Analytics, while its embedded version is in beta testing. Unlike earlier AI tools that focused on question-and-answer interactions, such as Sage and Microsoft’s copilots, Spotter takes the concept further by integrating contextual awareness and autonomous decision-making. Spotter doesn’t just respond to queries; it suggests follow-up questions, identifies anomalies, and provides proactive insights, functioning more like a virtual analyst than a reactive chatbot. Key Features of Spotter Spotter is built to enhance productivity and insight generation through the following capabilities: Generative AI’s Growing Impact on BI ThoughtSpot has long aimed to make analytics accessible to non-technical users through natural language search. However, previous NLP tools often required users to learn specific vocabularies, limiting widespread adoption. Generative AI bridges this gap. By leveraging extensive vocabularies and LLM technology, tools like Spotter enable users of all skill levels to access and analyze data effortlessly. Spotter stands out with its ability to deliver proactive insights, identify trends, and adapt to user behavior, enhancing the decision-making process. Expert Perspectives on Spotter Donald Farmer, founder of TreeHive Strategy, highlighted Spotter’s autonomy as a game-changer: “Spotter is a big move forward for ThoughtSpot and AI. The natural language interface is more conversational, but the key advantage is its autonomous analysis, which identifies trends and insights without users needing to ask.” Mike Leone, an analyst at TechTarget’s Enterprise Strategy Group, emphasized Spotter’s ability to adapt to users: “Spotter’s ability to deliver personalized and contextually relevant responses is critical for organizations pursuing generative AI initiatives. This goes a long way in delivering unique value across a business.” Farmer also pointed to Spotter’s embedded capabilities, noting its growing appeal as an embedded analytics solution integrated with productivity tools like Salesforce and ServiceNow. Competitive Positioning Spotter aligns ThoughtSpot with other vendors embracing agentic AI in analytics. Google recently introduced Conversational Analytics in Looker, and Salesforce’s Tableau platform now includes Tableau Agent. ThoughtSpot’s approach builds on its core strength in search-based analytics while expanding into generative AI-driven capabilities. Leone observed: “ThoughtSpot is right in line with the market in delivering an agentic experience and is laying the groundwork for broader AI functionality over time.” A Step Toward the Future of Analytics With Spotter, ThoughtSpot is redefining the role of AI in business intelligence. The tool combines conversational ease, proactive insights, and seamless integration, empowering users to make data-driven decisions more efficiently. As generative AI continues to evolve, tools like Spotter demonstrate how businesses can unlock the full potential of their data. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 29, 2024in AI Tools, Data, Enterprise, Generative AI, Google, Salesforce, Technology0 Comments

27Dec

Salesforce Channels

Channels Email Messaging Voice Open CTI Social Media Chat Channel Tools Email Updates Messaging Enhancements Voice Improvements Social Media Chat Updates Other Channel Tools These updates enhance the messaging, email, voice, and chat experiences, streamlining agent workflows, improving customer interactions, and providing greater customization. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 27, 2024in Google, Salesforce0 Comments

1 Billion Enterprise AI Agents

Inside Salesforce’s Ambition to Deploy 1 Billion Enterprise AI Agents Salesforce is making a bold play in the enterprise AI space with its recently launched Agentforce platform. Introduced at the annual Dreamforce conference, Agentforce is positioned to revolutionize sales, marketing, commerce, and operations with autonomous AI agents, marking a significant evolution from Salesforce’s previous Einstein AI platform. What Makes Agentforce Different? Agentforce operates as more than just a chatbot platform. It uses real-time data and user-defined business rules to proactively manage tasks, aiming to boost efficiency and enhance customer satisfaction. Built on Salesforce’s Data Cloud, the platform simplifies deployment while maintaining powerful customization capabilities: “Salesforce takes care of 80% of the foundational work, leaving customers to focus on the 20% that truly differentiates their business,” explains Adam Forrest, SVP of Marketing at Salesforce. Forrest highlights how Agentforce enables businesses to build custom agents tailored to specific needs by incorporating their own rules and data sources. This user-centric approach empowers admins, developers, and technology teams to deploy AI without extensive technical resources. Early Adoption Across Industries Major brands have already adopted Agentforce for diverse use cases: These real-world applications illustrate Agentforce’s potential to transform workflows in industries ranging from retail to hospitality and education. AI Agents in Marketing: The New Frontier Salesforce emphasizes that Agentforce isn’t just for operations; it’s poised to redefine marketing. AI agents can automate lead qualification, optimize outreach strategies, and enhance personalization. For example, in account-based marketing, agents can analyze customer data to identify high-value opportunities, craft tailored strategies, and recommend optimal engagement times based on user behavior. “AI agents streamline lead qualification by evaluating intent signals and scoring leads, allowing sales teams to focus on high-priority prospects,” says Jonathan Franchell, CEO of B2B marketing agency Ironpaper. Once campaigns are launched, Agentforce monitors performance in real time, offering suggestions to improve ROI and resource allocation. By integrating seamlessly with CRM platforms, the tool also facilitates better collaboration between marketing and sales teams. Beyond B2C applications, AI agents in B2B contexts can evaluate customer-specific needs and provide tailored product or service recommendations, further enhancing client relationships. Enabling Creativity Through Automation By automating repetitive tasks, Agentforce aims to free marketers to focus on strategy and creativity. Dan Gardner, co-founder of Code and Theory, describes this vision: “Agentic AI eliminates friction and dissolves silos in data, organizational structures, and customer touchpoints. The result? Smarter insights, efficient distribution, and more time for creatives to do what they do best: creating.” Competitive Landscape and Challenges Despite its promise, Salesforce faces stiff competition. Microsoft—backed by its integration with OpenAI’s ChatGPT—has unveiled AI tools like Copilot, and other players such as Google, ServiceNow, and HubSpot are advancing their own AI platforms. Salesforce CEO Marc Benioff has not shied away from the rivalry. On the Masters of Scale podcast, he criticized Microsoft for overpromising on products like Copilot, asserting that Salesforce delivers tangible value: “Our tools show users exactly what is possible, what is real, and how easy it is to derive huge value from AI.” Salesforce must also demonstrate Agentforce’s scalability across diverse industries to capture a significant share of the enterprise AI market. A Transformative Vision for the Future Agentforce represents Salesforce’s commitment to bringing AI-powered automation to the forefront of enterprise operations. With its focus on seamless deployment, powerful customization, and real-time capabilities, the platform aims to reshape how businesses interact with customers and optimize internal processes. By targeting diverse use cases and emphasizing accessibility for both technical and non-technical users, Salesforce is betting on Agentforce to drive adoption at scale—and position itself as a leader in the increasingly competitive AI market. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 27, 2024in Agentforce Platform, AI Tools, Data, Enterprise, Google, Salesforce, Technology0 Comments

26Dec

No-Code Generative AI

The future of AI belongs to everyone, and no-code platforms are the key to making this vision a reality. By embracing this approach, enterprises can ensure that AI-driven innovation is inclusive, efficient, and transformative.

December 26, 2024in Data, Enterprise, Generative AI0 Comments

23Dec

Student Experience Modernization

Transforming the Student Journey: Utah State University Launches ‘OneUSU CRM’ with Salesforce Utah State University (USU) proudly announces the launch of OneUSU CRM, an AI-driven Customer Relationship Management (CRM) and Marketing Automation Platform built on Salesforce Education Cloud for Student Experience Modernization. This forward-thinking initiative is set to transform the student experience by simplifying services, enhancingfor engagement, and creating personalized educational journeys for all students—from prospective applicants to lifelong alumni. “USU is redefining student support, starting from the first interaction as prospective students to ongoing engagement as alumni,” said Margo Martinez, VP & GM of Education at Salesforce. “With their AI-powered engagement platform, USU is enabling deeper collaboration among faculty and staff, delivering holistic, personalized support, and strengthening lifelong relationships with students. These efforts will enhance retention and institutional impact.” Breaking Down Silos for a Unified Experience For years, USU’s student data and communication systems operated independently, resulting in fragmented processes. OneUSU CRM consolidates these disparate systems into a single, unified platform, providing a 360-degree view of students and donors. This comprehensive approach enables USU to offer seamless, student-centric experiences, streamline processes, and improve service delivery across the university. “Implementing Salesforce as an enterprise solution will revolutionize how we operate,” said Bill Plate, VP of Marketing and Communications at USU. “It will foster unprecedented collaboration across the university, breaking down silos, enhancing communication, and allowing us to better engage with students and alumni. The result is an elevated experience that strengthens our institutional impact.” The Lifecycle Connection The CRM will connect every touchpoint in the student lifecycle—from recruitment and admissions to active alumni engagement. This integration provides actionable insights to better serve stakeholders, boost enrollment, improve retention, and cultivate stronger relationships with alumni and donors. The initiative aligns with USU’s mission to leverage data for meaningful improvements in the university experience. “This project lays the groundwork for USU to provide personalized support at every stage of the student lifecycle,” added Niel Nickolaisen, USU’s IT Director. “By making comprehensive data accessible to those best positioned to assist, we are better equipped to meet students’ needs, enhance their learning journey, and create stronger institutional bonds.” Four Pillars of Transformation in Student Experience Modernization The OneUSU CRM initiative will roll out in four key phases over 18 months, each focusing on a core area: Guiding Implementation USU’s Operational Strategy division will oversee the rollout, with cross-divisional teams led by Rene Eborn spearheading the transition to Salesforce Education Cloud. By adopting agile principles, minimizing customizations, and redesigning legacy processes, USU is committed to a smooth and effective implementation. “After an extensive analysis, we’re ready to transform and simplify services for our students and community,” noted Eborn. “This initiative will reimagine how we operate, ensuring a seamless transition and delivering optimal performance across the university.” Driving Institutional Impact The project began in November, with the first phase launching in summer 2025. Each phase will build on the previous one, and progress updates will be shared regularly. “This initiative is an opportunity to streamline processes and create a connected experience for students, faculty, and alumni,” said Eric Hawley, CIO at USU. “By improving data, communication, and marketing with a student-first focus, we aim to boost enrollment and retention, shorten time to graduation, and foster lasting relationships with alumni and donors.” Student Experience Modernization Students, faculty, and staff can expect a more connected, responsive campus environment. Detailed updates and training opportunities will be provided to ensure a smooth transition. Student Experience Modernization. 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

December 23, 2024in Data, Enterprise, Marketing Automation, Salesforce, Salesforce Education Cloud0 Comments

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