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AI Agent Rivalry
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

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January 19, 2025in Data, Generative AI, Google, Salesforce, Technology0 Comments
Agentforce Redefines Generative AI
16Jan

Agentforce Redefines Generative AI

Agentforce: Redefining Generative AI in Salesforce Many Dreamforce attendees who expected to hear about Einstein Copilot were surprised when Salesforce introduced Agentforce just a week before the conference. While it might seem like a rebranding of Copilot, Agentforce marks a significant evolution by enabling more autonomous agents that go beyond summarizing or generating content to perform specific actions. Here’s a breakdown of the transition and what it means for Salesforce users: Key Vocabulary Updates How Agentforce Works Agents take user input, known as an “utterance,” and translate it into actionable steps based on predefined configurations. This allows the system to enhance performance over time while delivering responses tailored to user needs. Understanding Agentforce 1. Topics: Organizing Agent Capabilities Agentforce introduces “Topics,” a new layer of organization that categorizes actions by business function. When a user provides an utterance, the agent identifies the relevant topic first, then determines the best actions to address it. 2. Actions: What Agents Can Do Actions remain largely unchanged from Einstein Copilot. These are tasks agents perform to execute plans. 3. Prompts: The Key to Better Results LLMs rely on prompts to generate outputs, and crafting effective prompts is essential for reducing irrelevant responses and optimizing agent behavior. How Generative AI Enhances Salesforce Agentforce unlocks several benefits across productivity, personalization, standardization, and efficiency: Implementing Agentforce: Tips for Success Getting Started Start by using standard Agent actions. These out-of-the-box tools, such as opportunity summarization or close plan creation, provide a strong foundation. You can make minor adjustments to optimize their performance before diving into more complex custom actions. Testing and Iteration Testing AI agents is different from traditional workflows. Agents must handle various phrasing of the same user request (utterances) while maintaining consistency in responses. The Future of Salesforce with Agentforce As you gain expertise in planning, developing, testing, and deploying Agentforce actions, you’ll unlock new possibilities for transforming your Salesforce experience. With generative AI tools like Agentforce, Salesforce evolves from a traditional point-and-click interface into an intelligent, agent-driven platform with streamlined, conversational workflows. This isn’t just an upgrade — it’s the foundation for reimagining how businesses interact with their CRM in an AI-assisted world. 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

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January 16, 2025in Agentforce Platform, AI Tools, Data, Generative AI, Salesforce0 Comments
salesforce agentforce rapid deployment
14Jan

Agentforce: Your Partner in Seamless Customer Experiences

Building Deeper Customer Relationships with Agentforce In today’s competitive landscape, building meaningful relationships with customers is no longer optional—it’s essential. Customers expect brands to know them, anticipate their needs, and deliver seamless, personalized experiences across every interaction. While data and AI have the potential to help marketers achieve these goals, many organizations struggle to realize their full potential. In fact, only 32% of marketers report being completely satisfied with how they use customer data to create relevant experiences, according to our State of Marketing report. So, how can marketers close this gap? Meet Agentforce—a proactive, autonomous application designed to provide specialized, always-on support for employees and customers alike. With Agentforce, marketers can strengthen relationships through personalized conversations, proactive engagement, and seamless customer experiences. 1. Automate Personalized, Two-Way Conversations on WhatsApp Interacting one-on-one with every customer responding to a promotional campaign on WhatsApp has historically been a challenge. Limited chatbot capabilities or a complete lack of response options often resulted in missed opportunities. Agentforce changes the game by introducing a customer-facing AI agent that acts as a personal concierge directly within WhatsApp. Imagine a customer receiving an exclusive offer for a product they’ve shown interest in. They reply with a question, and the agent instantly provides tailored product recommendations, current promotions, or details about complementary products. If the customer decides to make a purchase, the agent guides them through the entire checkout process—from completing the transaction to sending real-time order updates. For more complex needs, the agent seamlessly transfers the conversation to a human service representative, ensuring continuity. Why it matters: This approach not only increases conversions but also builds customer satisfaction and loyalty through timely, relevant responses. By reducing the workload on support teams, Agentforce delivers a consistent brand experience that feels personal and effortless. 2. Create Personalized Agendas for Event Attendees Events are powerful tools for fostering customer connections and delivering value. However, ensuring attendees find the most relevant sessions and resources can be daunting. Self-guided experiences often result in missed opportunities or abandoned registrations. Agentforce for Marketing solves this by providing personalized, 1:1 assistance to every visitor on your event website. The agent recommends sessions based on visitor interests and helps attendees create personalized agendas. Leveraging past attendance and engagement data, Agentforce curates agendas tailored to each attendee’s priorities, from keynote presentations to breakout sessions. For repeat attendees, it suggests new content based on their history, completing the registration process with their customized agenda. Why it matters: Personalized agendas enhance the event experience, leading to higher satisfaction and loyalty. By making the registration journey seamless, Agentforce reduces bounce rates and builds long-term engagement with your events. 3. Capture and Qualify Leads Effortlessly on Your Website Visitors often abandon self-guided website experiences before converting into leads. With Agentforce, you can proactively engage them by providing tailored product recommendations, exclusive content offers, and opportunities to share contact information. Depending on visitor behavior, the agent might suggest gated assets like case studies or demo videos—or even register them for an event or webinar. For highly engaged prospects, the agent can schedule follow-up meetings with sales reps, ensuring visitors receive immediate value without friction. Why it matters: Automated lead capture accelerates qualification and increases conversions. By guiding visitors to the right solutions and reducing friction, Agentforce nurtures leads naturally, creating higher-quality opportunities and loyal customers. 4. Improve Customer Journeys with Intelligent Reprioritization Balancing customer engagement with respect for their communication preferences is critical. Before customers hit their communication limit, Agentforce can dynamically reprioritize their journey based on both their interests and your business goals. For example, if a customer is close to their communication cap, the agent can prioritize sending a VIP event invitation or product announcement over less relevant messages. This ensures high-value content is delivered at the right time, without overwhelming the customer. Why it matters: Intelligent reprioritization improves conversion rates, reduces unsubscribe rates, and strengthens customer relationships. By ensuring every interaction is timely and relevant, Agentforce helps keep customers engaged without feeling inundated. 5. Reduce Churn with Proactive, Personalized Promotions Retaining customers is just as important as acquiring new ones. Agentforce can identify at-risk customers using churn indicators—such as low engagement or declining purchase frequency—and automatically send tailored promotions. For instance, if a customer’s churn score nears a threshold, the agent can proactively offer a loyalty discount or renewal incentive. It can guide the customer through the redemption process, rekindling their interest before they decide to leave. Why it matters: Proactive retention strategies powered by AI increase customer lifetime value, reduce churn, and foster loyalty. With minimal effort, Agentforce ensures that marketers stay connected to customers who might otherwise disengage. Agentforce: Your Partner in Seamless Customer Experiences More than just an automation tool, Agentforce is an essential partner for delivering the personalized experiences your customers expect. By implementing these use cases, marketers can: Ready to take your marketing strategy to the next level? With Agentforce, meaningful customer relationships are within reach. 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

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January 14, 2025in Agentforce Platform, Agentic AI, Data0 Comments
Statement Accuracy Prediction based on Language Model Activations
14Jan

Statement Accuracy Prediction based on Language Model Activations

When users first began interacting with ChatGPT, they noticed an intriguing behavior: the model would often reverse its stance when told it was wrong. This raised concerns about the reliability of its outputs. How can users trust a system that appears to contradict itself? Recent research has revealed that large language models (LLMs) not only generate inaccurate information (often referred to as “hallucinations”) but are also aware of their inaccuracies. Despite this awareness, these models proceed to present their responses confidently. Unveiling LLM Awareness of Hallucinations Researchers discovered this phenomenon by analyzing the internal mechanisms of LLMs. Whenever an LLM generates a response, it transforms the input query into a numerical representation and performs a series of computations before producing the output. At intermediate stages, these numerical representations are called “activations.” These activations contain significantly more information than what is reflected in the final output. By scrutinizing these activations, researchers can identify whether the LLM “knows” its response is inaccurate. A technique called SAPLMA (Statement Accuracy Prediction based on Language Model Activations) has been developed to explore this capability. SAPLMA examines the internal activations of LLMs to predict whether their outputs are truthful or not. Why Do Hallucinations Occur? LLMs function as next-word prediction models. Each word is selected based on its likelihood given the preceding words. For example, starting with “I ate,” the model might predict the next words as follows: The issue arises when earlier predictions constrain subsequent outputs. Once the model commits to a word, it cannot go back to revise its earlier choice. For instance: In another case: This mechanism reveals how the constraints of next-word prediction can lead to hallucinations, even when the model “knows” it is generating an incorrect response. Detecting Inaccuracies with SAPLMA To investigate whether an LLM recognizes its own inaccuracies, researchers developed the SAPLMA method. Here’s how it works: The classifier itself is a simple neural network with three dense layers, culminating in a binary output that predicts the truthfulness of the statement. Results and Insights The SAPLMA method achieved an accuracy of 60–80%, depending on the topic. While this is a promising result, it is not perfect and has notable limitations. For example: However, if LLMs can learn to detect inaccuracies during the generation process, they could potentially refine their outputs in real time, reducing hallucinations and improving reliability. The Future of Error Mitigation in LLMs The SAPLMA method represents a step forward in understanding and mitigating LLM errors. Accurate classification of inaccuracies could pave the way for models that can self-correct and produce more reliable outputs. While the current limitations are significant, ongoing research into these methods could lead to substantial improvements in LLM performance. By combining techniques like SAPLMA with advancements in LLM architecture, researchers aim to build models that are not only aware of their errors but capable of addressing them dynamically, enhancing both the accuracy and trustworthiness of AI systems. 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

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January 14, 2025in Data, Salesforce0 Comments

Salesforce and AWS-Agentic Enterprise

Salesforce and AWS: Driving the Future of the Agentic Enterprise As AI-powered agents redefine the way businesses operate, strategic partnerships are playing a pivotal role in harnessing the power of data and artificial intelligence. Salesforce and AWS, two industry leaders, have taken significant steps toward building a smarter, agentic enterprise through their expanded collaboration. One year into this strategic partnership, their joint efforts are delivering transformative AI and data solutions, helping customers like Buyers Edge Platform unlock new efficiencies and capabilities. A Partnership Fueling Agentic AI Salesforce and AWS are aligning their AI and data initiatives to pave the way for advanced agentic systems—autonomous AI agents designed to enhance business operations and customer experiences. Among their notable achievements over the past year are: These innovations are creating an ecosystem that supports the delivery of agentic AI, enabling businesses to streamline operations and tap into new value from their data. “By integrating data and AI capabilities across our platforms, Salesforce and AWS are building a strong foundation for the future of agentic systems,” said Brian Landsman, EVP of Global Business Development and Technology Partnerships at Salesforce. “With a majority of large companies planning to implement agents by 2027, organizations need trusted partners to help them achieve their vision of a smarter enterprise.” Making AI More Accessible Salesforce is simplifying access to AI technology through the AWS Marketplace, offering customers an integrated solution that includes Agentforce—the agentic layer of the Salesforce platform. Agentforce enables businesses to deploy autonomous AI agents across various operations, streamlining workflows and delivering measurable results. Available in 23 countries, Salesforce’s presence on AWS Marketplace offers customers key advantages, including: By removing barriers to adoption, Salesforce and AWS empower companies to focus on leveraging technology for growth rather than navigating complex procurement systems. A New Era of Enterprise Efficiency As businesses increasingly rely on data and AI to remain competitive, the Salesforce-AWS partnership is setting the stage for enterprises to achieve more with agentic systems. These systems allow companies to execute complex tasks with unprecedented efficiency, maximizing ROI on technology investments. “Our partnership with Salesforce empowers mutual customers to realize the full potential of their data and AI investments,” said Chris Grusz, Managing Director of Technology Partnerships at AWS. “Together, we’re delivering immediate, actionable insights with agentic AI, enabling organizations to automate strategically and unlock more value across their operations.” Looking Ahead By seamlessly integrating data and AI capabilities, Salesforce and AWS are not just building technology solutions—they’re reshaping how enterprises operate and thrive in the digital age. As agentic AI becomes an essential part of business strategy, this partnership provides a blueprint for leveraging technology to drive smarter, more agile, and more effective enterprises. 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

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January 11, 2025in Artificial Intelligence, Data, Enterprise, Salesforce, Salesforce Data Cloud, Technology0 Comments
Salesforce Spring ’25 Release
09Jan

Salesforce Spring ’25 Release

Salesforce Spring ’25 Release: Key Features and Enhancements Salesforce delivers triannual updates—Spring, Summer, and Winter—to introduce new features, enhancements, and fixes to the platform. These updates are applied automatically to Salesforce environments, ensuring all users benefit from the latest innovations without needing manual upgrades. The Spring ’25 functionality is now available in Preview Developer Orgs, allowing users to explore and test upcoming features before the general release. Preview Developer Orgs: Exploring the Future Preview Developer Orgs provide sandbox environments or developer editions equipped with new release functionality during the preview window. These allow admins and developers to: With access to a Preview Org, you can explore the following cutting-edge features: 1. Reactive Screen Actions Enhanced Screen Flow Reactivity: This feature enables screen flow components to update dynamically in real-time based on changes in other components. Users no longer need to navigate away or manually refresh to see updates, ensuring smoother, more interactive experiences. New in Spring ’25:You can now create an autolaunched flow to fetch data reactively from the database and display it immediately on the screen, eliminating the need for an action button. Use Case:When creating an Opportunity, the ZIP code of the associated Account determines the follow-up owner based on a reference table stored in a custom object. With reactive screen actions, selecting an Opportunity row dynamically displays the Account, Owner, and Assigned Person without additional clicks. 2. Progress Indicator for Flow Stages Salesforce introduces a built-in Progress Indicator for screen flows, providing users with a visual tracker of their progress through multi-step flows. Key Features: Limitations:The progress indicator does not yet support user-driven navigation through stages. 3. Immediate Input Validation in Screen Flows Validation functionality in flows has been upgraded to support real-time error detection. What’s New: 4. Email Action Attachment Support Email Action Enhancements: Spring ’25 introduces the ability to attach files to emails directly within flows. How It Works: Note: Files do not need to be made public for attachments, as long as the flow user has access to the files. 5. Get Records with a Specified Limit The LIMIT operator, commonly used in SOQL, is now available in flows. Benefits: 6. New Flow Modal Enhancements Salesforce has redesigned the Flow Type Picker modal, making it easier for users to select the right automation type. What’s New: 7. UI and Accessibility Improvements Conclusion The Salesforce Spring ’25 release is packed with features designed to enhance efficiency, usability, and innovation. From reactive screen flows and real-time validation to email action attachments and improved UI elements, this release sets a new standard for how users interact with the Salesforce platform. Stay ahead by leveraging Preview Developer Orgs to test these enhancements and ensure a smooth transition to the production environment. As Salesforce continues to innovate, these updates are just the beginning of a more seamless, intelligent platform experience. 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

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January 9, 2025in Data, Salesforce0 Comments
Generative AI Energy Consumption Rises
09Jan

Generative AI Tools

Generative AI Tools: A Comprehensive Overview of Emerging Capabilities The widespread adoption of generative AI services like ChatGPT has sparked immense interest in leveraging these tools for practical enterprise applications. Today, nearly every enterprise app integrates generative AI capabilities to enhance functionality and efficiency. A broad range of AI, data science, and machine learning tools now support generative AI use cases. These tools assist in managing the AI lifecycle, governing data, and addressing security and privacy concerns. While such capabilities also aid in traditional AI development, this discussion focuses on tools specifically designed for generative AI. Not all generative AI relies on large language models (LLMs). Emerging techniques generate images, videos, audio, synthetic data, and translations using methods such as generative adversarial networks (GANs), diffusion models, variational autoencoders, and multimodal approaches. Here is an in-depth look at the top categories of generative AI tools, their capabilities, and notable implementations. It’s worth noting that many leading vendors are expanding their offerings to support multiple categories through acquisitions or integrated platforms. Enterprises may want to explore comprehensive platforms when planning their generative AI strategies. 1. Foundation Models and Services Generative AI tools increasingly simplify the development and responsible use of LLMs, initially pioneered through transformer-based approaches by Google researchers in 2017. 2. Cloud Generative AI Platforms Major cloud providers offer generative AI platforms to streamline development and deployment. These include: 3. Use Case Optimization Tools Foundation models often require optimization for specific tasks. Enterprises use tools such as: 4. Quality Assurance and Hallucination Mitigation Hallucination detection tools address the tendency of generative models to produce inaccurate or misleading information. Leading tools include: 5. Prompt Engineering Tools Prompt engineering tools optimize interactions with LLMs and streamline testing for bias, toxicity, and accuracy. Examples include: 6. Data Aggregation Tools Generative AI tools have evolved to handle larger data contexts efficiently: 7. Agentic and Autonomous AI Tools Developers are creating tools to automate interactions across foundation models and services, paving the way for autonomous AI. Notable examples include: 8. Generative AI Cost Optimization Tools These tools aim to balance performance, accuracy, and cost effectively. Martian’s Model Router is an early example, while traditional cloud cost optimization platforms are expected to expand into this area. Generative AI tools are rapidly transforming enterprise applications, with foundational, cloud-based, and domain-specific solutions leading the way. By addressing challenges like accuracy, hallucination, and cost, these tools unlock new potential across industries and use cases, enabling enterprises to stay ahead in the AI-driven landscape. 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

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January 9, 2025in AI Tools, Data, Enterprise, Generative AI, Google, Snowflake0 Comments
Salesforce Einstein Commerce
08Jan

Salesforce Commerce Cloud Passkeys

Adding Passkeys to Salesforce Commerce Cloud Ensuring secure, convenient user access is a top priority for Salesforce-based applications. Passkeys, a passwordless authentication solution, streamline user sign-up and login processes while enhancing security. By integrating passkeys into Salesforce Commerce Cloud (SFCC), businesses can protect users from password-related threats like phishing and credential theft, leveraging the security of asymmetric encryption behind passkeys. The seamless login experience offered by passkeys boosts user engagement, reduces drop-off rates, and fosters trust, improving overall user satisfaction. Implementing passkeys not only aligns with current security standards but also prepares businesses for the future of intuitive digital interactions and enhanced privacy. DIY Implementation vs. Dedicated Salesforce Commerce Cloud Passkey Solution When deciding how to integrate passkeys into Salesforce Commerce Cloud applications, businesses must weigh the options between a DIY approach and partnering with a dedicated solution provider like OwnID. Implementing passkeys from scratch can be time-consuming and resource-intensive, requiring significant technical effort to ensure compatibility with Salesforce systems and adherence to security and user experience best practices. By choosing a provider like OwnID, companies can implement passkeys in a matter of days rather than months. OwnID offers a ready-to-use, Salesforce-compatible solution that integrates seamlessly, features cutting-edge security, and provides ongoing support. This approach lifts the burden from internal development teams, speeds up deployment, and ensures a high-quality user experience without the need to manage authentication processes or stay on top of compliance updates. For more information, check out our DIY vs. Elite Passkey Implementation Guide. How to Implement the OwnID Solution in Salesforce Commerce Cloud Integrating OwnID’s passwordless login into Salesforce Commerce Cloud (SFCC) is a straightforward process that enhances both security and the user experience. Here’s an overview of the key steps involved: 1. Set Up an API Client in SFCC Begin by creating a new API Client in your SFCC environment. This client is essential for secure communication between SFCC and OwnID. Log into the Salesforce Commerce Cloud Account Manager, add a new API Client, and configure the appropriate roles and authentication methods (e.g., private_key_jwt). This step ensures secure integration between SFCC and OwnID. 2. Create and Configure an OwnID Application In the OwnID Console, set up an application dedicated to your SFCC integration. This application serves as the bridge between OwnID’s passkey system and your Salesforce Commerce Cloud app. Configure settings like API credentials, site URL, and other parameters specific to OwnID. This step connects OwnID’s authentication service to your Salesforce site seamlessly. 3. Install the OwnID Cartridge in SFCC OwnID provides a cartridge designed for SFCC integration. Installing this cartridge adds all necessary components to your SFCC instance, enabling easy interaction between OwnID and Salesforce. After installation, go to Merchant Tools → Site Preferences in SFCC to customize OwnID settings for your environment. This enables you to display the OwnID widget on login and registration pages, creating a smooth, passwordless experience. 4. Embed the OwnID SDK in Your Templates The final step is to embed the OwnID SDK script in your site’s templates (e.g., htmlHead.isml or a global template file). This SDK enables passkey-based login across all relevant pages. By embedding the script, you ensure users have access to passwordless login, enhancing security and user convenience. With these steps, OwnID will be fully integrated into your Salesforce Commerce Cloud application, offering users secure, password-free access. For more detailed instructions and configuration options, visit the OwnID Salesforce Commerce Cloud Documentation. Get Expert Help with Your Salesforce Commerce Cloud Passkey Integration Ready to implement passwordless authentication in your Salesforce Commerce Cloud application? The Tectonic team is here to guide you through every step of the integration process. From initial setup to ongoing optimization, we ensure a smooth and seamless experience for your users. For personalized support and to learn how OwnID’s passkey solution can elevate your SFCC environment, contact our expert team today. 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

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January 8, 2025in Salesforce Commerce Cloud0 Comments
agetnforce for nonprofits
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

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January 8, 2025in Data, Enterprise, Mulesoft, Salesforce0 Comments
Scope of Generative AI
07Jan

Exploring Generative AI

Like most employees at most companies, I wear a few different hats around Tectonic. Whether I’m building a data model, creating and scheduing an email campaign, standing up a platform generative AI is always at my fingertips. At my very core, I’m a marketer. Have been for so long I do it without eveven thinking. Or at least, everyuthing I do has a hat tip to its future marketing needs. Today I want to share some of the AI content generators I’ve been using, am looking to use, or just heard about. But before we rip into the insight, here’s a primer. Types of AI Content Generators ChatGPT, a powerful AI chatbot, drew significant attention upon its November 2022 release. While the GPT-3 language model behind it had existed for some time, ChatGPT made this technology accessible to nontechnical users, showcasing how AI can generate content. Over two years later, numerous AI content generators have emerged to cater to diverse use cases. This rapid development raises questions about the technology’s impact on work. Schools are grappling with fears of plagiarism, while others are embracing AI. Legal debates about copyright and digital media authenticity continue. President Joe Biden’s October 2023 executive order addressed AI’s risks and opportunities in areas like education, workforce, and consumer privacy, underscoring generative AI’s transformative potential. What is AI-Generated Content? AI-generated content, also known as generative AI, refers to algorithms that automatically create new content across digital media. These algorithms are trained on extensive datasets and require minimal user input to produce novel outputs. For instance, ChatGPT sets a standard for AI-generated content. Based on GPT-4o, it processes text, images, and audio, offering natural language and multimodal capabilities. Many other generative AI tools operate similarly, leveraging large language models (LLMs) and multimodal frameworks to create diverse outputs. What are the Different Types of AI-Generated Content? AI-generated content spans multiple media types: Despite their varied outputs, most generative AI systems are built on advanced LLMs like GPT-4 and Google Gemini. These multimodal models process and generate content across multiple formats, with enhanced capabilities evolving over time. How Generative AI is Used Generative AI applications span industries: These tools often combine outputs from various media for complex, multifaceted projects. AI Content Generators AI content generators exist across various media. Below are good examples organized by gen ai type: Written Content Generators Image Content Generators Music Content Generators Code Content Generators Other AI Content Generators These tools showcase how AI-powered content generation is revolutionizing industries, making content creation faster and more accessible. I do hope you will comment below on your favorites, other AI tools not showcased above, or anything else AI-related that is on your mind. Written by Tectonic’s Marketing Operations Director, Shannan Hearne. 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

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January 7, 2025in AI Tools, Data, Enterprise, Generative AI, Google, Technology0 Comments
Salesforce Implementation Help
06Jan

How to Make Workloads More Manageable

How to Make Workloads More Manageable: 6 Useful Tips for Salesforce Admins Being a Salesforce Administrator is both rewarding and challenging. The role involves managing a platform that evolves continuously while addressing a business’s ever-changing needs. From resolving cases to managing system updates, user configurations, and deployments, the list of responsibilities can often feel overwhelming. Here are six actionable tips to help Salesforce Admins stay on top of their workload and avoid burnout. 1. Integrate Data Quality into Salesforce Data Projects Maintaining data quality should be a cornerstone of every Salesforce project. A clear and structured approach to data can prevent errors, improve efficiency, and reduce time spent troubleshooting. 2. Break Down Tasks Admins often face long to-do lists, sometimes with 50 or more actionable items. Breaking down the workload into manageable segments can help: Once segmented, estimate the time required for each task to better plan days, weeks, or months. This process makes it easier to identify whether the workload is manageable. 3. Prioritize Effectively Not all tasks carry equal weight. Prioritization should consider both the value of the task and the time required to complete it. While tasks that yield tangible ROI in time or cost savings are essential, smaller items that improve user experience also hold value. Avoid the trap of prioritizing tasks simply in the order they are received. Collaborating with stakeholders such as business analysts, architects, and leadership ensures each task is assessed on its individual merits. 4. Stay in Scope Scope creep is a common challenge that can quickly derail effective prioritization. Tasks outside the defined scope should not make it onto the to-do list. To scope effectively, clear and well-defined user stories are essential. Admins should ask clarifying questions until they fully understand the requirements. This proactive questioning empowers admins to maintain focus and deliver value efficiently. 5. Streamline Requests Through a Single Channel Managing requests from multiple sources—emails, Slack, meetings, or even casual conversations—can lead to chaos. Establish a single, consistent channel for submitting user stories and feature requests, such as a kanban-style tool like JIRA. Tools with integration capabilities, such as creating tickets directly from Slack, further simplify the process. Without a formal ticket in the system, requests should not be considered valid. 6. Leverage the Right Tools The right tools can make a significant difference in workload management. For example, deploying components like Flows using change sets can be time-consuming and frustrating. Tools designed to streamline deployments, reporting, or configuration management can free up valuable time for more impactful tasks. 🔔🔔  Follow us on LinkedIn  🔔🔔 Finally, Jump on In Admins often face tasks they dread—those long, tedious, boring ones as a thing to be avoided. Delaying difficult tasks can make them grow more daunting over time. Completing them early not only reduces anxiety but also improves productivity and outcomes. Tectonic’s Conclusion With thoughtful strategies, Salesforce Admins can transform overwhelming workloads into manageable, structured tasks. By breaking down responsibilities, prioritizing effectively, staying in scope, streamlining requests, and using the right tools, admins can excel in their roles while maintaining work-life balance. And by jumping right in they can ensure even the most challenging tasks are handled efficiently. 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

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January 6, 2025in Data, Salesforce0 Comments
From Chatbots to Agentic AI
04Jan

From Chatbots to Agentic AI

The transition from LLM-powered chatbots to agentic systems, or agentic AI, can be summed up by the old saying: “Less talk, more action.” Keeping up with advancements in AI can be overwhelming, especially when managing an existing business. The speed and complexity of innovation can make it feel like the first day of school all over again. This insight offers a comprehensive look at AI agents, their components, and key characteristics. The introductory section breaks down the elements that form the term “AI agent,” providing a clear definition. After establishing this foundation, we explore the evolution of LLM applications, particularly the shift from traditional chatbots to agentic systems. The goal is to understand why AI agents are becoming increasingly vital in AI development and how they differ from LLM-powered chatbots. By the end of this guide, you will have a deeper understanding of AI agents, their potential applications, and their impact on organizational workflows. For those of you with a technical background who prefer to get hands-on, click here for the best repository for AI developers and builders. What is an AI Agent? Components of AI Agents To understand the term “AI agent,” we need to examine its two main components. First, let’s consider artificial intelligence, or AI. Artificial Intelligence (AI) refers to non-biological intelligence that mimics human cognition to perform tasks traditionally requiring human intellect. Through machine learning and deep learning techniques, algorithms—especially neural networks—learn patterns from data. AI systems are used for tasks such as detection, classification, and prediction, with content generation becoming a prominent domain due to transformer-based models. These systems can match or exceed human performance in specific scenarios. The second component is “agent,” a term commonly used in both technology and human contexts. In computer science, an agent refers to a software entity with environmental awareness, able to perceive and act within its surroundings. A computational agent typically has the ability to: In human contexts, an agent is someone who acts on behalf of another person or organization, making decisions, gathering information, and facilitating interactions. They often play intermediary roles in transactions and decision-making. To define an AI agent, we combine these two perspectives: it is a computational entity with environmental awareness, capable of perceiving inputs, acting with tools, and processing information using foundation models backed by both long-term and short-term memory. Key Components and Characteristics of AI Agents From LLMs to AI Agents Now, let’s take a step back and understand how we arrived at the concept of AI agents, particularly by looking at how LLM applications have evolved. The shift from traditional chatbots to LLM-powered applications has been rapid and transformative. Form Factor Evolution of LLM Applications Traditional Chatbots to LLM-Powered Chatbots Traditional chatbots, which existed before generative AI, were simpler and relied on heuristic responses: “If this, then that.” They followed predefined rules and decision trees to generate responses. These systems had limited interactivity, with the fallback option of “Speak to a human” for complex scenarios. LLM-Powered Chatbots The release of OpenAI’s ChatGPT on November 30, 2022, marked the introduction of LLM-powered chatbots, fundamentally changing the game. These chatbots, like ChatGPT, were built on GPT-3.5, a large language model trained on massive datasets. Unlike traditional chatbots, LLM-powered systems can generate human-like responses, offering a much more flexible and intelligent interaction. However, challenges remained. LLM-powered chatbots struggled with personalization and consistency, often generating plausible but incorrect information—a phenomenon known as “hallucination.” This led to efforts in grounding LLM responses through techniques like retrieval-augmented generation (RAG). RAG Chatbots RAG is a method that combines data retrieval with LLM generation, allowing systems to access real-time or proprietary data, improving accuracy and relevance. This hybrid approach addresses the hallucination problem, ensuring more reliable outputs. LLM-Powered Chatbots to AI Agents As LLMs expanded, their abilities grew more sophisticated, incorporating advanced reasoning, multi-step planning, and the use of external tools (function calling). Tool use refers to an LLM’s ability to invoke specific functions, enabling it to perform more complex tasks. Tool-Augmented LLMs and AI Agents As LLMs became tool-augmented, the emergence of AI agents followed. These agents integrate reasoning, planning, and tool use into an autonomous, goal-driven system that can operate iteratively within a dynamic environment. Unlike traditional chatbot interfaces, AI agents leverage a broader set of tools to interact with various systems and accomplish tasks. Agentic Systems Agentic systems—computational architectures that include AI agents—embody these advanced capabilities. They can autonomously interact with systems, make decisions, and adapt to feedback, forming the foundation for more complex AI applications. Components of an AI Agent AI agents consist of several key components: Characteristics of AI Agents AI agents are defined by the following traits: Conclusion AI agents represent a significant leap from traditional chatbots, offering greater autonomy, complexity, and interactivity. However, the term “AI agent” remains fluid, with no universal industry standard. Instead, it exists on a continuum, with varying degrees of autonomy, adaptability, and proactive behavior defining agentic systems. Value and Impact of AI Agents The key benefits of AI agents lie in their ability to automate manual processes, reduce decision-making burdens, and enhance workflows in enterprise environments. By “agentifying” repetitive tasks, AI agents offer substantial productivity gains and the potential to transform how businesses operate. As AI agents evolve, their applications will only expand, driving new efficiencies and enabling organizations to leverage AI in increasingly sophisticated ways. 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

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January 4, 2025in Agentic AI, Artificial Intelligence, Data, Enterprise, Generative AI, Technology0 Comments
Speed to Launch of Agentforce
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

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

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

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