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Salesforce AI Evolves with the Generative AI Landscape

Salesforce AI Evolves with the Generative AI Landscape

Salesforce AI: Powering Customer Relationship Management Salesforce is a leading CRM solution that has long delivered cutting-edge cloud technologies to manage customer relationships effectively. In recent months, the platform has further advanced with the integration of generative AI and AI-powered features, primarily through its AI engine, Einstein. Salesforce AI Evolves with the Generative AI Landscape. To explore how AI operates within the Salesforce ecosystem and how various business teams can leverage these innovations, this guide delves into Salesforce’s AI capabilities, products, and features. Salesforce AI: Transforming CRM Capabilities Salesforce remains a top choice in the CRM software market, offering one of the most comprehensive solutions for managing relationships across departments, industries, and initiatives. Through dedicated cloud platforms, Salesforce enables teams to oversee marketing, sales, customer service, e-commerce, and more, with tools focused on delivering enhanced customer experiences supported by powerful data analytics. With the introduction of generative AI, Salesforce has significantly elevated its native automation, workflow management, data analytics, and assistive capabilities for customer lifecycle management. Einstein Copilot exemplifies this innovation, aiding internal users with tasks such as outreach, analysis, and improving external user experiences. What is Salesforce Einstein? Salesforce Einstein is an AI-driven suite of tools integrated natively into various Salesforce Cloud applications, including Sales Cloud, Marketing Cloud, Service Cloud, and Commerce Cloud. It also operates through assistive technologies like Einstein Copilot. Einstein is built on a multitenant platform and incorporates numerous automated machine learning features to unify organizational data with CRM capabilities. Designed to make intelligent, data-driven decisions, Einstein requires no additional installation, offering a seamless user experience when paired with a compatible subscription plan. 7 Key Features of Salesforce Einstein 7 Applications of Salesforce Einstein Future Trends in Salesforce AI Bottom Line: Salesforce AI Evolves with the Generative AI Landscape Salesforce continues to enhance its AI-powered features, keeping pace with advancements in generative and predictive AI. Whether new to the platform or a seasoned user, Salesforce offers innovative, AI-centric solutions to streamline customer relationship management and business operations. Like1 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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Mapping Data Salesforce to Canva

Mapping Data Salesforce to Canva

Mapping Data Fields in Salesforce for Canva Integration Salesforce administrators can map data fields from a brand template to Salesforce objects, enabling data from Salesforce to automatically populate placeholders in Canva designs. This feature is available exclusively for Canva Enterprise users and integrates with Salesforce Professional, Enterprise, or Unlimited editions. Mapping Data Salesforce to Canva. Steps for Mapping Data Fields in Salesforce: Pre-requisites: The following are the steps to set up field mapping using the Canva for Salesforce app. Step 1: Sync Brand Templates Before mapping fields, you need to sync brand templates from Canva to Salesforce. Here’s how: Step 2: Create a Template Mapping Template mapping connects data fields from a Salesforce object to placeholders in a Canva brand template, allowing Salesforce data to autofill the design. You need to create a separate template mapping for each Salesforce object. Unmapped Fields: You don’t have to map every field. If a field is unmapped, the placeholder in the Canva template will remain unchanged in the final design. Additional Information: Connecting Data Source Apps to Canva for Autofill You can connect data sources like Salesforce to Canva to autofill elements in your designs. Here’s a brief overview of how to connect and use Salesforce data: Creating Brand Templates for Salesforce To use Canva for Salesforce to generate sales collateral, brand designers must first create and publish a brand template. These templates include data fields that act as placeholders for Salesforce data. Mapping Data Salesforce to Canva With this setup, Salesforce admins can easily map data fields and auto-generate designs based on Salesforce 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

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A Company in Transition

A Company in Transition

OpenAI Restructures: Increased Flexibility, But Raises Concerns OpenAI’s decision to restructure into a for-profit entity offers more freedom for the company and its investors but raises questions about its commitment to ethical AI development. Founded in 2015 as a nonprofit, OpenAI transitioned to a hybrid model in 2019 with the creation of a for-profit subsidiary. Now, its restructuring, widely reported this week, signals a shift where the nonprofit arm will no longer influence the day-to-day operations of the for-profit side. CEO Sam Altman is set to receive equity in the newly restructured company, which will operate as a benefit corporation (B Corp), similar to competitors like Anthropic and Sama. A Company in Transition This move comes on the heels of a turbulent year. OpenAI’s board initially voted to remove Altman over concerns about transparency, but later rehired him after significant backlash and the resignation of several board members. The company has seen a number of high-profile departures since, including co-founder Ilya Sutskever, who left in May to start Safe Superintelligence (SSI), an AI safety-focused venture that recently secured $1 billion in funding. This week, CTO Mira Murati, along with key research leaders Bob McGrew and Barret Zoph, also announced their departures. OpenAI’s restructuring also coincides with an anticipated multi-billion-dollar investment round involving major players such as Nvidia, Apple, and Microsoft, potentially pushing the company’s valuation to as high as $150 billion. Complex But Expected Move According to Michael Bennett, AI policy advisor at Northeastern University, the restructuring isn’t surprising given OpenAI’s rapid growth and increasingly complex structure. “Considering OpenAI’s valuation, it’s understandable that the company would simplify its governance to better align with investor priorities,” said Bennett. The transition to a benefit corporation signals a shift towards prioritizing shareholder interests, but it also raises concerns about whether OpenAI will maintain its ethical obligations. “By moving away from its nonprofit roots, OpenAI may scale back its commitment to ethical AI,” Bennett noted. Ethical and Safety Concerns OpenAI has faced scrutiny over its rapid deployment of generative AI models, including its release of ChatGPT in November 2022. Critics, including Elon Musk, have accused the company of failing to be transparent about the data and methods it uses to train its models. Musk, a co-founder of OpenAI, even filed a lawsuit alleging breach of contract. Concerns persist that the restructuring could lead to less ethical oversight, particularly in preventing issues like biased outputs, hallucinations, and broader societal harm from AI. Despite the potential risks, Bennett acknowledged that the company would have greater operational freedom. “They will likely move faster and with greater focus on what benefits their shareholders,” he said. This could come at the expense of the ethical commitments OpenAI previously emphasized when it was a nonprofit. Governance and Regulation Some industry voices, however, argue that OpenAI’s structure shouldn’t dictate its commitment to ethical AI. Veera Siivonen, co-founder and chief commercial officer of AI governance vendor Saidot, emphasized the role of regulation in ensuring responsible AI development. “Major players like Anthropic, Cohere, and tech giants such as Google and Meta are all for-profit entities,” Siivonen said. “It’s unfair to expect OpenAI to operate under a nonprofit model when others in the industry aren’t bound by the same restrictions.” Siivonen also pointed to OpenAI’s participation in global AI governance initiatives. The company recently signed the European Union AI Pact, a voluntary agreement to adhere to the principles of the EU’s AI Act, signaling its commitment to safety and ethics. Challenges for Enterprises The restructuring raises potential concerns for enterprises relying on OpenAI’s technology, said Dion Hinchcliffe, an analyst with Futurum Group. OpenAI may be able to innovate faster under its new structure, but the reduced influence of nonprofit oversight could make some companies question the vendor’s long-term commitment to safety. Hinchcliffe noted that the departure of key staff could signal a shift away from prioritizing AI safety, potentially prompting enterprises to reconsider their trust in OpenAI. New Developments Amid Restructuring Despite the ongoing changes, OpenAI continues to roll out new technologies. The company recently introduced a new moderation model, “omni-moderation-latest,” built on GPT-4o. This model, available through the Moderation API, enables developers to flag harmful content in both text and image outputs. A Company in Transition As OpenAI navigates its restructuring, balancing rapid innovation with maintaining ethical standards will be crucial to sustaining enterprise trust and market leadership. 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

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Data Cloud and Autonomous Agents

Data Cloud and Autonomous Agents

Salesforce is building momentum with Data Cloud, the heartbeat of its platform and foundation for Agentforce, fueled by strong business demand for unified data to deliver personalized, contextually relevant, and timely customer experiences across its Customer 360 applications, Flow, analytics, and Agentforce—Salesforce’s groundbreaking suite of autonomous AI agents. This week, Salesforce unveiled a major pivot in its AI strategy during its annual Dreamforce conference. The company is introducing AI tools that can handle tasks without human supervision, alongside a new pricing model. Customers will now pay US per conversation held by Salesforce’s new AI “agents,” which are designed to manage tasks such as customer service and scheduling sales meetings autonomously. This shift in strategy reflects Salesforce’s forward-thinking approach to AI and its potential to transform not only technology but also business models. By focusing on AI agents, Salesforce is responding to a market demand for increased workforce capacity without the need for full-time hires or gig workers—a point emphasized by CEO Marc Benioff during his keynote speech. Building on its predictive Einstein platform, Agentforce represents Salesforce’s next step in AI evolution. “Think of it as the next evolution of our AI wave,” said Muralidhar Krishnaprasad, Salesforce’s president and CTO. “We had AI wave one with Einstein’s predictive capabilities, AI wave two with generative AI copilots, and now we’re entering the age of agents.” Agentforce is designed to augment work by handling tasks across platforms, leveraging Salesforce’s Data Cloud to channel structured and unstructured data into agentic experiences. These agents, powered by the Atlas reasoning engine, use dynamic plans and Retrieval-Augmented Generation (RAG) techniques to address real-time customer questions and deliver actionable insights. Salesforce’s AI agents can operate autonomously, supporting businesses by handling a range of customer interactions and tasks with minimal human intervention. Adding to the AI-driven innovations, Salesforce introduced several new Data Cloud advancements that further enhance an organization’s ability to transform customer experiences using data and AI. These include: Data Cloud continues to drive impressive growth, with a 130% YoY increase in paid customers, processing 2.3 quadrillion records in the second quarter alone. Customers like The Adecco Group, Aston Martin, and Air India rely on Data Cloud to unify their data and deliver personalized, real-time customer experiences. For example, Air India uses Data Cloud to integrate data across its loyalty, reservations, and flight systems, allowing it to manage over 550,000 service cases each month. As AI reshapes the industry, Salesforce’s pivot to autonomous agents and a conversation-based pricing model shows its commitment to leading the charge in enterprise AI adoption, with Data Cloud as its driving force. Despite some software vendors struggling to capitalize on AI advancements, Salesforce’s new model positions it to thrive in a market where AI’s impact is just beginning to unfold. 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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Salesforce to Acquire Zoomin

Salesforce to Acquire Zoomin

Salesforce to Acquire Zoomin: Enhancing AI Capabilities with Unstructured Data Salesforce, the world’s leading AI CRM, has signed a definitive agreement to acquire Zoomin, a top data management provider specializing in unstructured data. This acquisition is a pivotal move that will strengthen Salesforce’s Data Cloud, empowering AI agents with more personalized, context-aware capabilities. With Zoomin’s technology, Salesforce’s Agentforce platform will gain new intelligence, allowing customers to build AI that delivers real-time, data-driven responses tailored to individual needs. The acquisition is expected to close in the fourth quarter of Salesforce’s fiscal year 2025, subject to customary closing conditions. “Proprietary unstructured data is powerful fuel our customers can use for AI agents and customer experiences,” said Rahul Auradkar, EVP & GM of Unified Data Services & Einstein at Salesforce. “Zoomin’s proven expertise and technology will accelerate Data Cloud’s innovation and enable our customers to get better value from Agentforce. This transaction underscores our commitment to help customers harness the value of all their data, offering contextual AI experiences backed by enterprise-leading trust controls.” Strategic Value of the Acquisition With the integration of Zoomin’s technology, Salesforce can unlock new use cases for customers across various touchpoints. For example, Service Cloud users will be able to automate service interactions by leveraging enterprise knowledge, enhancing the efficiency of Agentforce for service representatives. This integration will lead to faster issue resolution, increased customer satisfaction, and reduced operational costs. Zoomin’s ability to consolidate unstructured data from multiple sources will empower service teams with a comprehensive understanding of their customers, turning distributed knowledge into actionable insights. Zoomin’s CEO, Gal Oron, echoed this sentiment: “We’re both humbled and excited to join forces with Salesforce. As organizations accelerate their enterprise AI transformation, our joint mission is to support them and ensure AI doesn’t hit the data wall. As part of the #1 AI CRM, we’ll enable customers to leverage their existing enterprise data in ways they never thought possible.” A Long-Standing Partnership Zoomin has been a Salesforce AppExchange partner since 2018 and became a part of the Salesforce Ventures portfolio in 2019. Through this partnership, hundreds of Salesforce customers already use Zoomin’s unified knowledge platform to deliver intuitive customer experiences. This acquisition builds on that foundation, with Zoomin set to enhance Salesforce’s AI-driven platforms by making enterprise knowledge more accessible and usable for AI agents. Despite the significance of this acquisition, Salesforce noted that it would not result in any changes to its financial guidance provided in August 2024, and no further financial details will be disclosed. This move is part of Salesforce’s broader strategy to push deeper into AI-powered customer experiences, enabling customers to utilize the full potential of their data for more intelligent, personalized interactions across all channels. 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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Agentforce - AI's New Role in Sales and Service

Agentforce – AI’s New Role in Sales and Service

From Science Fiction to Reality: AI’s Game-Changing Role in Service and Sales AI for service and sales has reached a critical tipping point, driving rapid innovation. At Dreamforce in San Francisco, hosted by Salesforce we explored how Salesforce clients are leveraging CRM, Data Cloud, and AI to extract real business value from their Salesforce investments. In previous years, AI features branded under “Einstein” had been met with skepticism. These features, such as lead scoring, next-best-action suggestions for service agents, and cross-sell/upsell recommendations, often required substantial quality data in the CRM and knowledge base to be effective. However, customer data was frequently unreliable, with duplicate records and missing information, and the Salesforce knowledge base was underused. Building self-service capabilities with chatbots was also challenging, requiring accurate predictions of customer queries and well-structured decision trees. This year’s Dreamforce revealed a transformative shift. The advancements in AI, especially for customer service and sales, have become exceptionally powerful. Companies now need to take notice of Salesforce’s capabilities, which have expanded significantly. Agentforce – AI’s New Role in Sales and Service Some standout Salesforce features include: At Dreamforce, we participated in a workshop where they built an AI agent capable of responding to customer cases using product sheets and company knowledge within 90 minutes. This experience demonstrated how accessible AI solutions have become, no longer requiring developers or LLM experts to set up. The key challenge lies in mapping external data sources to a unified data model in Data Cloud, but once achieved, the potential for customer service and sales is immense. How AI and Data Integrate to Transform Service and Sales Businesses can harness the following integrated components to build a comprehensive solution: Real-World Success and AI Implementation OpenTable shared a successful example of building an AI agent for its app in just two months, using a small team of four. This was a marked improvement from the company’s previous chatbot projects, highlighting the efficiency of the latest AI tools. Most CEOs of large enterprises are exploring AI strategies, whether by developing their own LLMs or using pre-existing models. However, many of these efforts are siloed, and engineering costs are high, leading to clunky transitions between AI and human agents. Tectonic is well-positioned to help our clients quickly deploy AI-powered solutions that integrate seamlessly with their existing CRM and ERP systems. By leveraging AI agents to streamline customer interactions, enhance sales opportunities, and provide smooth handoffs to human agents, businesses can significantly improve customer experiences and drive growth. Tectonic is ready to help businesses achieve similar success with AI-driven innovation. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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Oracle Advertising Sundown

Oracle Advertising Sundown

Oracle Shifts Focus to B2B CX, Introduces New Fusion Cloud Features Despite winding down its online advertising products, Oracle is doubling down on its investment in customer experience (CX) technology, particularly in enabling B2B buying and supporting subscription and consumption models. During the Oracle CloudWorld conference on Wednesday, the company unveiled new capabilities for its Fusion Cloud Customer Experience and Unity Customer Data Platform. These enhancements empower Oracle CX users to analyze customer profiles to assemble B2B buying teams, leverage generative AI tools like native analytics, and utilize industry-specific accelerators to speed up the adoption of customer data tools. Key features include the ability to create self-service sites for individual accounts, enabling customers to review and summarize contracts using generative AI, receive quotes, and renew subscriptions. Other features enhance “assisted buying experiences,” blending self-service and human interaction, while tools like account onboarding and AI-powered email drafting simplify full-service sales processes. Subscription models, though still in their early stages for B2B, offer a streamlined alternative to traditional procurement processes. As Liz Miller, an analyst at Constellation Research, noted, subscription-based buying is easier and quicker, avoiding the lengthy procurement cycles many B2B buyers are familiar with. “The pain of traditional B2B buying is still fresh in everyone’s mind,” she said. Oracle Advertising Shuts Down Oracle’s advertising product support will end on September 30, as confirmed by CEO Safra Catz during the company’s June earnings call. The Oracle Advertising Data Management Platform (DMP), built from its BlueKai acquisition, is being retired, following in the footsteps of Salesforce, which discontinued its Audience Studio in 2021. Despite Oracle winding down its ad platform, this move shouldn’t be seen as a shift away from customer experience. Oracle founder Larry Ellison remains deeply involved in shaping the company’s CX strategy, with a focus on marketing tools and Apex low-code platforms, said Rob Pinkerton, Oracle’s senior vice president. Oracle’s modernized CX suite, built on the Fusion Cloud platform, has evolved significantly in recent years, though questions remain about whether it’s too late to regain market share. “Oracle as a CX platform has fallen off the radar for many buyers,” said Miller, adding that customers are no longer debating between Oracle, Microsoft, and Salesforce in the CX space. New Industry-Specific Tools for CX Oracle has also expanded its CX platform with industry-specific tools designed to accelerate the adoption of its customer data platform (CDP) across sectors such as high tech, manufacturing, professional services, telecommunications, utilities, financial services, travel, and retail. According to Rebecca Wettemann, CEO of research firm Valoir, Oracle’s Fusion platform has matured significantly and now supports the complexity of modern customer needs. Wettemann highlighted how common components like customer interaction summaries can be adapted for multiple industries, delivering faster results than traditional applications. Oracle’s Clinical Digital Assistant is one such example of this approach, illustrating the platform’s versatility and AI-driven enhancements. With these developments, Oracle continues to refine its CX offerings to better meet the unique demands of B2B customers, providing tools that streamline operations and enhance customer experiences across various industries. 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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Salesforce Success Story

Case Study: Salesforce Advanced Forcasting and Streamline Operations Yields Big Change and Bigger Results

Case Study: Salesforce Advanced Forcsting and Streamline Operations Yields Big Change and Bigger Results

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Next Gen Commerce Cloud

Next Gen Commerce Cloud

Salesforce has launched the next generation of Commerce Cloud, delivering a unified platform that connects B2C, DTC, and B2B commerce, along with Order Management, Payments, and more, to drive seamless customer experiences and revenue growth. With these innovations, businesses can scale across digital and physical channels while leveraging trusted AI and enterprise-wide data for smarter operations. Next Gen Commerce Cloud. Key features include Autonomous Agentforce Agents, which enhance commerce for merchants, buyers, and shoppers by automating tasks such as product recommendations and order tracking. Companies like MillerKnoll have seen success by using Commerce Cloud’s innovations to scale their workforce and drive revenue across multiple channels. New Agentforce Agents for Commerce — Merchant, Buyer, and Personal Shopper — autonomously manage tasks and improve the customer journey. They handle tasks without human intervention, such as product recommendations or order lookups, drawing insights from rich data sources like customer interactions, inventory, orders, and reviews. By tapping into unified data, these agents augment employees, offering tailored experiences and increasing efficiency, while strictly adhering to privacy and security standards. Salesforce’s Commerce Cloud now natively integrates every part of the commerce journey, helping businesses break down data silos and offer consistent, personalized interactions. As Michael Affronti, SVP and GM of Commerce Cloud, highlights: “Unified commerce is the future, breaking down silos to deliver seamless experiences across all channels.” Key new features and functionalities include: With these advancements, Commerce Cloud empowers businesses to create seamless, AI-powered experiences that drive customer loyalty, operational efficiency, and revenue growth across every touchpoint. 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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Tableau Einstein is Here

Tableau Einstein is Here

Tableau Einstein marks a new chapter for Tableau, transforming the analytics experience by moving beyond traditional reports and dashboards to deliver insights directly within the flow of a user’s work. This new AI-powered analytics platform blends existing Tableau and Salesforce capabilities with innovative features designed to revolutionize how users engage with data. The platform is built around four key areas: autonomous insight delivery through AI, AI-assisted development of a semantic layer, real-time data access, and a marketplace for data and AI products, allowing customers to personalize their Tableau experience. Some features, like Tableau Pulse and Tableau Agent, which provide autonomous insights, are already available. Additional tools, such as Tableau Semantics and a marketplace for AI products, are expected to launch in 2025. Access to Tableau Einstein is provided through a Tableau+ subscription, though pricing details remain private. Since being acquired by Salesforce in 2019, Tableau has shifted its focus toward AI, following the trend of many analytics vendors. In February, Tableau introduced Tableau Pulse, a generative AI-powered tool that delivers insights in natural language. In July, it also rolled out Tableau Agent, an AI assistant to help users prepare and analyze data. With AI at its core, Tableau Einstein reflects deeper integration between Tableau and Salesforce. David Menninger, an analyst at Ventana Research, commented that these new capabilities represent a meaningful step toward true integration between the two platforms. Donald Farmer, founder of TreeHive Strategy, agrees, highlighting that while the robustness of Tableau Einstein’s AI capabilities compared to its competitors remains to be seen, the platform offers more than just incremental add-ons. “It’s an impressive release,” he remarked. A Paradigm Shift in Analytics A significant aspect of Tableau Einstein is its agentic nature, where AI-powered agents deliver insights autonomously, without user prompts. Traditionally, users queried data and analyzed reports to derive insights. Tableau Einstein changes this model by proactively providing insights within the workflow, eliminating the need for users to formulate specific queries. The concept of autonomous insights, represented by tools like Tableau Pulse and Agentforce for Tableau, allows businesses to build autonomous agents that deliver actionable data. This aligns with the broader trend in analytics, where the market is shifting toward agentic AI and away from dashboard reliance. Menninger noted, “The market is moving toward agentic AI and analytics, where agents, not dashboards, drive decisions. Agents can act on data rather than waiting for users to interpret it.” Farmer echoed this sentiment, stating that the integration of AI within Tableau is intuitive and seamless, offering a significantly improved analytics experience. He specifically pointed out Tableau Pulse’s elegant design and the integration of Agentforce AI, which feels deeply integrated rather than a superficial add-on. Core Features and Capabilities One of the most anticipated features of Tableau Einstein is Tableau Semantics, a semantic layer designed to enhance AI models by enabling organizations to define and structure their data consistently. Expected to be generally available by February 2025, Tableau Semantics will allow enterprises to manage metrics, data dimensions, and relationships across datasets with the help of AI. Pre-built metrics for Salesforce data will also be available, along with AI-driven tools to simplify semantic layer management. Tableau is not the first to offer a semantic layer—vendors like MicroStrategy and Looker have similar features—but the infusion of AI sets Tableau’s approach apart. According to Tableau’s chief product officer, Southard Jones, AI makes Tableau’s semantic layer more agile and user-friendly compared to older, labor-intensive systems. Real-time data integration is another key component of Tableau Einstein, made possible through Salesforce’s Data Cloud. This integration enables Tableau users to securely access and combine structured and unstructured data from hundreds of sources without manual intervention. Unstructured data, such as text and images, is critical for comprehensive AI training, and Data Cloud allows enterprises to use it alongside structured data efficiently. Additionally, Tableau Einstein will feature a marketplace launching in mid-2025, which will allow users to build a composable infrastructure. Through APIs, users will be able to personalize their Tableau environment, share AI assets, and collaborate across departments more effectively. Looking Forward As Tableau continues to build on its AI-driven platform, Menninger and Farmer agree that the vendor’s move toward agentic AI is a smart evolution. While Tableau’s current capabilities are competitive, Menninger noted that the platform doesn’t necessarily set Tableau apart from competitors like Qlik, MicroStrategy, or Microsoft Fabric. However, the tight integration with Salesforce and the focus on agentic AI may provide Tableau with a short-term advantage in the fast-changing analytics landscape. Farmer added that Tableau Einstein’s autonomous insight generation feels like a significant leap forward for the platform. “Tableau has done great work in creating an agentic experience that feels, for the first time, like the real deal,” he said. Looking ahead, Tableau’s roadmap includes a continued focus on agentic AI, with the goal of providing each user with their own personal analyst. “It’s not just about productivity,” said Jones. “It’s about changing the value of what can be delivered.” Menninger concluded that Tableau’s shift away from dashboards is a reflection of where business intelligence is headed. “Dashboards, like data warehouses, don’t solve problems on their own. What matters is what you do with the information,” he said. “Tableau’s push toward agentic analytics and collaborative decision-making is the right move for its users and the market as a whole.” Like1 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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Is Agentforce Different?

Is Agentforce Different?

The Salesforce hype machine is in full swing, with product announcements like Chatter, Einstein GPT, and Data Cloud, all positioned as revolutionary tools that promise to transform how we work. Is Agentforce Different? However, it’s often difficult to separate fact from fiction in the world of Salesforce. The cloud giant thrives on staying ahead of technological advancements, which means reinventing itself every year with new releases and updates. You could even say three times per year with the major releases. Why Enterprises Need Multiple Salesforce Orgs Over the past decade, Salesforce product launches have been hit or miss—primarily miss. Offerings like IoT Cloud, Work.com, and NFT Cloud have faded into obscurity. This contrasts sharply with Salesforce’s earlier successes, such as Service Cloud, the AppExchange, Force.com, Salesforce Lightning, and Chatter, which defined its first decade in business. One notable exception is Data Cloud. This product has seen significant success and now serves as the cornerstone of Salesforce’s future AI and data strategy. With Salesforce’s growth slowing quarter over quarter, the company must find new avenues to generate substantial revenue. Artificial Intelligence seems to be their best shot at reclaiming a leadership position in the next technological wave. Is Agentforce Different? While Salesforce has been an AI leader for over a decade, the hype surrounding last year’s Dreamforce announcements didn’t deliver the growth the company was hoping for. The Einstein Copilot Studio—comprising Copilot, Prompt Builder, and Model Builder—hasn’t fully lived up to expectations. This can be attributed to a lack of AI readiness among enterprises, the relatively basic capabilities of large language models (LLMs), and the absence of fully developed use cases. In Salesforce’s keynote, it was revealed that over 82 billion flows are launched weekly, compared to just 122,000 prompts executed. While Flow has been around for years, this stat highlights that the use of AI-powered prompts is still far from mainstream—less than one prompt per Salesforce customer per week, on average. When ChatGPT launched at the end of 2022, many predicted the dawn of a new AI era, expecting a swift and dramatic transformation of the workplace. Two years later, it’s clear that AI’s impact has yet to fully materialize, especially when it comes to influencing global productivity and GDP. However, Salesforce’s latest release feels different. While AI Agents may seem new to many, this concept has been discussed in AI circles for decades. Marc Benioff’s recent statements during Dreamforce reflect a shift in strategy, including a direct critique of Microsoft’s Copilot product, signaling the intensifying AI competition. This year’s marketing strategy around Agentforce feels like it could be the transformative shift we’ve been waiting for. While tools like Salesforce Copilot will continue to evolve, agents capable of handling service cases, answering customer questions, and booking sales meetings instantly promise immediate ROI for organizations. Is the Future of Salesforce in the Hands of Agents? Despite the excitement, many questions remain. Are Salesforce customers ready for agents? Can organizations implement this technology effectively? Is Agentforce a real breakthrough or just another overhyped concept? Agentforce may not be vaporware. Reports suggest that its development was influenced by Salesforce’s acquisition of Airkit.AI, a platform that claims to resolve 90% of customer queries. Salesforce has even set up dedicated launchpads at Dreamforce to help customers start building their own agents. Yet concerns remain, especially regarding Salesforce’s complexity, technical debt, and platform sprawl. These issues, highlighted in this year’s Salesforce developer report, cannot be overlooked. Still, it’s hard to ignore Salesforce’s strategic genius. The platform has matured to the point where it offers nearly every functionality an organization could need, though at times the components feel a bit disconnected. For instance: Salesforce is even hinting at usage-based pricing, with a potential $2 charge per conversation—an innovation that could reshape their pricing model. Will Agents Be Salesforce’s Key to Future Growth? With so many unknowns, only time will tell if agents will be the breakthrough Salesforce needs to regain the momentum of its first two decades. Regardless, agents appear to be central to the future of AI. Leading organizations like Copado are also launching their own agents, signaling that this trend will define the next phase of AI innovation. In today’s macroeconomic environment, where companies are overstretched and workforce demands are high, AI’s ability to streamline operations and improve customer service has never been more critical. Whoever cracks customer service AI first could lead the charge in the inevitable AI spending boom. We’re all waiting to see if Salesforce has truly cracked the AI code. But one thing is certain: the race to dominate AI in customer service has begun. And Salsesforce may be at the forefront. 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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chatGPT open ai 01

ChatGPT Open AI o1

OpenAI has firmly established itself as a leader in the generative AI space, with its ChatGPT being one of the most well-known applications of AI today. Powered by the GPT family of large language models (LLMs), ChatGPT’s primary models, as of September 2024, are GPT-4o and GPT-3.5. In August and September 2024, rumors surfaced about a new model from OpenAI, codenamed “Strawberry.” Speculation grew as to whether this was a successor to GPT-4o or something else entirely. The mystery was resolved on September 12, 2024, when OpenAI launched its new o1 models, including o1-preview and o1-mini. What Is OpenAI o1? The OpenAI o1 family is a series of large language models optimized for enhanced reasoning capabilities. Unlike GPT-4o, the o1 models are designed to offer a different type of user experience, focusing more on multistep reasoning and complex problem-solving. As with all OpenAI models, o1 is a transformer-based architecture that excels in tasks such as content summarization, content generation, coding, and answering questions. What sets o1 apart is its improved reasoning ability. Instead of prioritizing speed, the o1 models spend more time “thinking” about the best approach to solve a problem, making them better suited for complex queries. The o1 models use chain-of-thought prompting, reasoning step by step through a problem, and employ reinforcement learning techniques to enhance performance. Initial Launch On September 12, 2024, OpenAI introduced two versions of the o1 models: Key Capabilities of OpenAI o1 OpenAI o1 can handle a variety of tasks, but it is particularly well-suited for certain use cases due to its advanced reasoning functionality: How to Use OpenAI o1 There are several ways to access the o1 models: Limitations of OpenAI o1 As an early iteration, the o1 models have several limitations: How OpenAI o1 Enhances Safety OpenAI released a System Card alongside the o1 models, detailing the safety and risk assessments conducted during their development. This includes evaluations in areas like cybersecurity, persuasion, and model autonomy. The o1 models incorporate several key safety features: GPT-4o vs. OpenAI o1: A Comparison Here’s a side-by-side comparison of GPT-4o and OpenAI o1: Feature GPT-4o o1 Models Release Date May 13, 2024 Sept. 12, 2024 Model Variants Single Model Two: o1-preview and o1-mini Reasoning Capabilities Good Enhanced, especially in STEM fields Performance Benchmarks 13% on Math Olympiad 83% on Math Olympiad, PhD-level accuracy in STEM Multimodal Capabilities Text, images, audio, video Primarily text, with developing image capabilities Context Window 128K tokens 128K tokens Speed Fast Slower due to more reasoning processes Cost (per million tokens) Input: $5; Output: $15 o1-preview: $15 input, $60 output; o1-mini: $3 input, $12 output Availability Widely available Limited to specific users Features Includes web browsing, file uploads Lacks some features from GPT-4o, like web browsing Safety and Alignment Focus on safety Improved safety, better resistance to jailbreaking ChatGPT Open AI o1 OpenAI o1 marks a significant advancement in reasoning capabilities, setting a new standard for complex problem-solving with LLMs. With enhanced safety features and the ability to tackle intricate tasks, o1 models offer a distinct upgrade over their predecessors. 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

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Agentforce and Thinking AI

Agentforce and Thinking AI

Agentforce is how humans with AI drive customer success together, equips organizations with autonomous agents that boost scale, efficiency, and satisfaction across service, sales, marketing, commerce, and more New Agentforce Atlas Reasoning Engine autonomously analyzes data, makes decisions, and completes tasks, providing reliable and accurate results With Agentforce, any organization can build, customize, and deploy their own agents quickly and easily, with low-code tools New Agentforce Partner Network allows customers to deploy pre-built agents and use agent actions from partners like Amazon Web Services, Google, IBM, Workday, and more Customers like OpenTable, Saks, and Wiley are turning to Agentforce because it is integrated with their apps, works across customer channels, augments their employees, and scales capacity for business needs SAN FRANCISCO — September 12, 2024 – Salesforce (NYSE: CRM), the world’s #1 AI CRM, today unveiled Agentforce, a groundbreaking suite of autonomous AI agents that augment employees and handle tasks in service, sales, marketing, and commerce, driving unprecedented efficiency and customer satisfaction. Agentforce enables companies to scale their workforces on demand with a few clicks. Agentforce’s limitless digital workforce of AI agents can analyze data, make decisions, and take action on tasks like answering customer service inquiries, qualifying sales leads, and optimizing marketing campaigns. With Agentforce, any organization can easily build, customize, and deploy their own agents for any use case across any industry. The future of AI is agents, and it’s here. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.” MARC BENIOFF, CHAIR, CEO & CO-FOUNDER, SALESFORCE “Agentforce represents the Third Wave of AI—advancing beyond copilots to a new era of highly accurate, low-hallucination intelligent agents that actively drive customer success. Unlike other platforms, Agentforce is a revolutionary and trusted solution that seamlessly integrates AI across every workflow, embedding itself deeply into the heart of the customer journey. This means anticipating needs, strengthening relationships, driving growth, and taking proactive action at every touchpoint,” said Marc Benioff, Chair and CEO, Salesforce. “While others require you to DIY your AI, Agentforce offers a fully tailored, enterprise-ready platform designed for immediate impact and scalability. With advanced security features, compliance with industry standards, and unmatched flexibility. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.” In contrast to now-outdated copilots and chatbots that rely on human requests and struggle with complex or multi-step tasks, Agentforce offers a new level of sophistication by operating autonomously, retrieving the right data on demand, building action plans for any task, and executing these plans without requiring human intervention. Like a self-driving car, Agentforce uses real-time data to adapt to changing conditions and operates independently within an organizations’ customized guardrails, ensuring every customer interaction is informed, relevant, and valuable. And when desired, Agentforce seamlessly hands off to human employees with a summary of the interaction, an overview of the customer’s details, and recommendations for what to do next. Industry leaders like OpenTable, Saks, and Wiley are already experiencing the transformative power of Agentforce. For example, Agentforce is helping organizations like Wiley provide customers with dynamic, conversational self-service. Agentforce is configured to answer questions using Wiley’s knowledge base already built into Salesforce so it can automatically resolve account access. It also triages registration and payment issues, directing customers to the appropriate resources. With Agentforce handling routine inquiries, Wiley has seen an over 40% increase in case resolution, outperforming their old chatbot and giving their human agents more time to focus on complex cases. Why it Matters An estimated 41% of employee time is spent on repetitive, low-impact work, and 65% of desk workers believe generative AI will allow them to be more strategic, according to the Salesforce Trends in AI Report. Every company has more jobs to be done than the resources available to do them. As a result, many jobs go unaddressed or uncompleted. Agentforce provides relief to overstretched teams with its ability to scale capacity on demand so humans can focus on higher-touch, higher-value, and more strategic outcomes. The future of work is a hybrid workforce composed of humans with agents, enabling companies to compete in an ever-changing world. Supporting Customer Quotes “Piloting Agentforce has made a noticeable difference during one of our busiest periods — back-to-school season. It’s been exciting to go live with our first agent thanks to the no-code builder, and we’ve seen a more than 40% increase in case resolution, outperforming our old bot. Agentforce helps to manage routine responsibilities and free up our service teams for more complex cases.” – Kevin Quigley, Senior Manager, Continuous Improvement, Wiley “Every interaction that restaurants and diners have with our support team must be accurate, fast, and reflective of the hospitality that restaurants show their guests. Agentforce has incredible potential to help us deliver that high touch attentiveness and support while significantly freeing up our team to address more complex needs.” – George Pokorny, SVP Customer Success, OpenTable “As we advance our personalization strategy, we believe Agentforce and its AI-powered capabilities have the potential to make a real impact on our approach to customer engagement, raising the bar in luxury retail. Agentforce will improve our effectiveness across customer touchpoints, empowering our employees and augmenting their ability to deliver the elevated and more individualized shopping experiences for which Saks is known.” – Mike Hite, Chief Technology Officer, Saks Global Like1 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

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Large Action Models and AI Agents

Large Action Models and AI Agents

The introduction of LAMs marks a significant advancement in AI, focusing on actionable intelligence. By enabling robust, dynamic interactions through function calling and structured output generation, LAMs are set to redefine the capabilities of AI agents across industries.

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Data Governance Frameworks

Data Governance Frameworks

Examples of Data Governance Frameworks Data governance is not a one-size-fits-all approach. Organizations must carefully choose a framework that aligns with their unique goals, structure, and culture. Data is one of an organization’s most valuable assets, and proper governance is key to unlocking its potential. Without a well-designed framework, companies risk poor data quality, privacy breaches, regulatory noncompliance, and missed insights. A data governance framework provides a structured way to manage data throughout its lifecycle, including policies, processes, and standards to ensure data is accurate, accessible, and secure. By putting clear guidelines in place, organizations can increase trust in their data and improve decision-making. Key Pillars of a Data Governance Frameworks A robust data governance framework typically rests on four key pillars: 1. Center-Out Model The center-out model places a centralized team, such as a data governance council, at the core of the governance process. This group establishes policies and oversees data management across the organization, balancing consistency with flexibility for different departments. The Data Governance Institute’s framework is an example of this model. It focuses on creating a Data Governance Office responsible for managing key governance functions such as setting data policies, assigning data stewards, and monitoring compliance. The framework provides a clear structure while allowing business units some leeway in adapting governance practices to their needs. PwC’s model also adopts a center-out approach, with an emphasis on using data governance to monetize data assets. It highlights the importance of maintaining consistency while minimizing the risk of data silos. 2. Top-Down Model In the top-down model, data governance is driven by executive leadership, ensuring alignment with strategic goals. This model provides authority for enforcing governance standards but may face challenges if business units feel disconnected from the central governance team. McKinsey’s framework exemplifies this approach, focusing on integrating data governance with broader business transformation efforts. Executive leadership plays a key role in ensuring that governance initiatives receive the necessary attention and resources. 3. Hybrid Model The hybrid model combines centralized governance with flexibility for individual business units. It establishes an enterprise-wide framework while allowing departments to adapt governance practices to their specific needs. The Eckerson Group’s Modern Data Governance Framework represents a hybrid approach. It emphasizes the importance of people and culture, alongside technology and processes, and encourages organizations to create a roadmap for governance that evolves as needs change. This model provides a balance between centralized control and decentralized flexibility. 4. Bottom-Up Model In the bottom-up model, data governance is driven by subject matter experts and data stakeholders across the organization. This approach promotes collaboration and buy-in from the people closest to the data, ensuring that governance policies are practical and effective. The DAMA-DMBOK framework, developed by the Data Management Association, is a prime example. Although flexible, it often starts as a bottom-up initiative, driven by IT departments and data experts who later gain executive support. 5. Silo-In Model The silo-in model allows individual business units or departments to create their own governance practices. While this approach addresses localized data issues, it often leads to inconsistencies and challenges when the organization needs to integrate data across the enterprise. Though not widely recommended, the silo-in approach may emerge when specific business units take the initiative to establish governance due to regulatory requirements or data management needs within their domains. However, as organizations mature, they often transition to more holistic frameworks to support cross-functional collaboration and data integration. Choosing the Right Framework Selecting the right data governance framework involves evaluating the organization’s needs, structure, and culture. Whether an organization adopts a center-out, top-down, hybrid, bottom-up, or silo-in approach, success depends on involving key stakeholders, securing executive buy-in, and committing to continuous improvement. By treating data as a critical asset and implementing a governance framework that aligns with its business strategy, an organization can ensure that its data management practices support growth, innovation, and regulatory compliance. 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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