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AI Agents and Digital Transformation

AI Agents Help Streamline Customer Service

AI Agents Help Fisher & Paykel Streamline Customer Service Through Expanded Salesforce Partnership Fisher & Paykel, the New Zealand-based luxury appliance manufacturer, is leveraging AI agents to automate customer service tasks, such as answering frequently asked questions and scheduling service appointments. This initiative is designed to free up employee time for more value-added tasks, enhancing the overall customer service experience. In collaboration with Salesforce, Fisher & Paykel is using autonomous agents that integrate seamlessly with its CRM system, providing agents with greater visibility into customers’ interaction histories. This enables more efficient, data-driven interactions and allows the company to proactively resolve issues, such as freezer temperature irregularities, by automatically notifying customers and helping them schedule necessary appointments. For instance, AI agents can diagnose appliance issues, alert the service team, and assist customers in scheduling repair appointments. These agents also support on-site technicians by providing critical information, such as appointment locations and appliance age, while offering helpful articles and generating post-service summaries. Additionally, the integration of AI agents will enhance collaboration with Fisher & Paykel’s retail, builder, and designer partners. These partners will benefit from more efficient access to inventory information, accurate quotes for multiple products, and streamlined order placement and tracking. Enhancing Automation-Ready Environments This initiative builds on existing capabilities from the partnership, combining AI, data, and CRM functions such as subscription management and consolidated customer engagement data. The results have been impressive: Fisher & Paykel saw a 206% increase in unique email opens and a 112% rise in unique clicks in 2023. They also reduced manual effort by 30 minutes per order and saved up to 3,300 hours through automation in the B2B side of their business, according to Salesforce. In addition to service automation, Fisher & Paykel is tapping into AI-driven automated journeys based on consumer buying signals and cloud-based customer service support that automates appointment confirmations. Rudi Khoury, Chief Digital Officer at Fisher & Paykel, emphasized that customer expectations for efficiency and personalized service align perfectly with the brand’s luxury offerings, highlighting the importance of AI in meeting these demands. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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AI Agents and Work

Maximizing Generative AI in Learning and Development

Maximizing Generative AI in Learning and DevelopmentHow organisations can harness the power of generative AI to enhance learning and development with strategic integration, best practices, and a culture of continuous growth CREDIT: This is an edited version of an article originally published on Vistage Organisations are increasingly recognising the value of generative AI in learning and development. While your employees may already be using it, they may not yet be maximising its potential due to limited resources or understanding. This article offers strategies for organisations to more effectively leverage generative AI and amplify its impact on their teams. A global survey of 14,000 workers by Salesforce in late 2023 revealed that 28% were already using generative AI at work, with over half doing so without formal approval. Similarly, a 2023 McKinsey report echoed these findings, and these numbers are likely even higher now. A recent study by Harvard Business School and Boston Consulting Group (BCG) highlighted the transformative impact of AI, showing that consultants using generative AI completed tasks 22% faster and produced 40% higher quality work compared to those not using it. Unlocking AI Insights Begin by conducting an internal survey to better understand how your employees are using generative AI. Gather data on the tools they use, how often they use them, and how these tools enhance their work. Frame the survey as an opportunity to learn about their experiences rather than as an evaluation or compliance check. Once you’ve analysed the results, identify employees who are using generative AI in creative and effective ways. These individuals—often informal leaders—can provide valuable insights into the practical applications of AI, as well as the challenges they face and how they overcome them. Fostering a Learning Culture Incorporating generative AI into your organisation’s learning and development strategy helps employees tap into the knowledge of early adopters while aligning AI use with broader organisational goals. Cultivate a culture that prioritises continuous learning and upskilling to stay ahead in the rapidly evolving AI landscape. Regularly update training materials to reflect new advancements in AI. Provide opportunities for employees to attend conferences, webinars, and other educational events to stay current. Encourage peer learning by fostering a culture where employees are motivated to share their experiences, tips, and best practices with one another. Developing Best Practices Leverage the expertise of your AI pioneers to establish best practices that are tailored to your organisation’s needs. Create a collaborative environment where these early adopters can share their experiences and insights, and involve them in the development of formal training programs. This ensures that the content is both relevant and practical for your workforce. Pilot these best practices with a small, controlled group of employees before rolling them out more broadly. This allows you to gather feedback, refine the practices, and address any issues. Additionally, create comprehensive guides, FAQs, and video tutorials to give employees easy access to the information they need. Tracking the progress and outcomes of your AI-related learning initiatives is essential. Use data to customise learning experiences and promote a growth mindset among employees. By integrating generative AI into your learning and development strategy, you can tap into internal expertise to drive innovation and improve efficiency across the organisation. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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AI Agents as Tools of Trust

Reviving Cold Leads with AI Agents

Reviving Cold Leads with AI Agents: Turning Dormant Prospects into Sales Opportunities In sales and marketing, cold or dormant leads often represent untapped potential. AI-powered agents can transform these “dead” leads into engaged prospects by analyzing past interactions, identifying key behavioral patterns, and executing data-driven re-engagement strategies. By leveraging AI, businesses can reignite interest and significantly improve conversion rates, ensuring that no potential customer is left behind. How AI Agents Revive Leads 1. Intelligent Lead Scoring and Prioritization AI can assess historical data, engagement levels, and demographic information to rank leads based on their likelihood to convert. This enables sales teams to focus on high-potential leads while automating engagement with lower-priority ones. 2. Hyper-Personalized Communication AI-driven insights allow businesses to craft highly relevant, tailored messages that align with each lead’s past interactions, preferences, and pain points. 3. Automated Nurture Campaigns AI streamlines lead nurturing through automated workflows that deliver relevant content across multiple channels, ensuring consistent engagement without manual intervention. 4. Predictive Analytics for Lead Conversion By leveraging machine learning models, AI predicts which leads are most likely to convert and recommends the best engagement strategies. 5. Real-Time Dynamic Content Adaptation AI ensures that communication remains relevant by adjusting messaging in real-time based on user behavior and engagement. Key Benefits of Using AI to Revive Leads 1. Increased Conversion Rates AI enhances engagement by delivering highly targeted, relevant messaging, increasing the likelihood of turning cold leads into paying customers. 2. Enhanced Sales Efficiency By automating lead nurturing and prioritization, AI allows sales teams to focus on high-value interactions, reducing manual workload and improving overall efficiency. 3. Cost Reduction and Resource Optimization AI minimizes wasted marketing spend by identifying which leads are worth pursuing, ensuring that budgets are allocated effectively. 4. Scalable and Consistent Engagement AI-powered systems ensure that no lead falls through the cracks, maintaining consistent follow-ups and personalized interactions at scale. 5. Data-Driven Decision Making By continuously analyzing engagement metrics and refining strategies, AI enables sales and marketing teams to make smarter, data-backed decisions. Conclusion AI agents are revolutionizing lead revival by intelligently prioritizing prospects, personalizing communication, and automating engagement strategies. Salesforce Agentforce is leading the charge. By leveraging AI-driven insights and predictive analytics, businesses can transform dormant leads into active opportunities, driving higher conversions and maximizing sales efficiency. As AI technology continues to evolve, its ability to re-engage and convert leads will only become more sophisticated, making it an essential tool for any sales and marketing team. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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 agentforce ai powered agentic agents

Agentforce 2.0

Salesforce, the leading CRM provider, is set to launch Agentforce 2.0 in February 2025—an AI-powered toolset designed as a “digital labor platform for building a limitless workforce for the enterprise.” Agentforce 2.0 is a comprehensive AI system that enhances teams with autonomous AI agents embedded in everyday workflows. Among its key offerings are AI-driven agents for Sales Development and Sales Coaching, with pricing starting at $2 per conversation. With this release, Salesforce introduces a library of pre-built skills and workflow integrations, enabling rapid customization and seamless deployment within Slack. Marc Benioff, Chair and CEO of Salesforce, stated, “We’re seamlessly bringing together AI, data, apps, and automation with humans to reshape how work gets done. Agentforce 2.0 cements our position as the leader in digital labor solutions, allowing any company to build a limitless workforce that can truly transform their business.” Agentforce 2.0 includes pre-built AI skills across CRM, Slack, Tableau, and partner-developed integrations via the AppExchange. Customers can further extend Agentforce’s capabilities using MuleSoft, enabling low-code workflows that integrate with any system. The release also introduces an enhanced Agent Builder, which interprets natural language instructions—such as “Onboard New Product Managers”—to automatically generate new AI agents. These agents combine pre-made skills with custom logic built directly in Salesforce, offering unmatched flexibility and efficiency. Additionally, Agentforce 2.0 features Tableau Skills for advanced analytics and insights, further empowering businesses to harness AI-driven decision-making. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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How To Describe The World to AI

Guide to Practical Worldbuilding: Modeling Our World for AI Have you ever wondered how kids explore the world around them? How do they make sense of objects, relationships, actions, and societal rules? Picture a child seeing a cat for the first time. At first, it’s just a furry creature, walking, climbing, and purring. Then, they notice another cat with a white face and black stripes. Over time, they learn that cats are living creatures—just like dogs. But unlike dogs, cats don’t run or bark. Through exploration and reasoning, kids continuously refine their understanding of the world. How To Describe The World to AI. Now imagine a similar process, but for artificial intelligence. Like children encountering new experiences, AI requires a framework to comprehend the world—yet AI lacks the ability to crawl in the grass, taste objects, or watch sunsets. Instead, it relies on humans to provide structured models that serve as digital maps of reality. These semantic models, akin to globes in geography class, allow AI to grasp the relationships between concepts, understand unstructured data, and operate effectively within our world. 🔔🔔  Follow us on LinkedIn  🔔🔔 Why AI Needs Models of Our World While AI systems like predictive maintenance tools or autonomous cars excel at solving specific problems, they depend on carefully prepared data for training. However, generative AI has sparked excitement by working with unstructured information, leading us to believe in intelligent agents that can automate workflows, book trips, process calls, or write code. Yet, such agents often fall short because they lack a deep understanding of our world. Large Language Models (LLMs) can process information but struggle with ambiguity, such as linking corporate database entities to real-world concepts. Without models that provide contextual meaning, even advanced algorithms remain limited tools. These semantic models allow machines—and humans—to bridge vast data sources, integrate knowledge, and interpret complex systems. Modeling Reality: Key Lessons Lesson 1: Model for the Use Case Building a model is like creating a world: it depends on your goals and perspective. For instance, if you’re modeling temperature changes in an IoT system, your approach depends on whether the focus is the sensor’s behavior (event-driven) or the temperature data itself (state-driven). Similarly, some models emphasize persistent entities (continuants) like employees, while others focus on events (occurents) like meetings. Your philosophical assumptions—whether descriptive (open to integration) or prescriptive (closed to external input)—shape the model’s design. Lesson 2: Relationships Are Key Semantic models are most powerful when they show relationships between entities. These connections provide data with context, transforming raw information into actionable insights. For example, a manufacturing company could unify quality assurance, operations, and performance metrics into a shared ontology, replacing siloed dashboards with an integrated view. Visualizing these relationships helps humans see systems as interconnected rather than isolated, enabling better analysis and decision-making. Lesson 3: Serve Humans and Machines Every model must serve three audiences: Semantic models enable AI-powered tools to augment human productivity. For example, an ancient codebase can be transformed into a graph of abstract syntax trees (AST), making it accessible for AI-driven modernization. Similarly, metadata—ranging from classification labels to data lineage—plays a critical role in organizing, governing, and contextualizing data for machine learning and reasoning. The Impact of Modeling Modeling isn’t just a technical exercise; it’s a creative process akin to worldbuilding in fiction. By formalizing the relationships and rules of our domain, we create maps that help humans and machines navigate complexity. Whether you’re modeling an enterprise, designing an AI system, or simply trying to understand your organization better, semantic models offer the tools to unify knowledge, reveal insights, and drive meaningful progress. How To Describe The World to AI. In the words of Frank Herbert: “Deep in the human unconscious is a pervasive need for a logical universe that makes sense. But the real universe is always one step beyond logic.” 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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ai in marketing

Guide to AI in Marketing

The Ultimate Guide to AI in Marketing AI-powered algorithms and machine learning are revolutionizing the marketing landscape by enabling swift processing and analysis of vast datasets. Unlike traditional methods, AI efficiently organizes large volumes of data in real time, redefining how marketing strategies are created and executed. Marketing success hinges on effective data utilization, precise targeting, engaging content, and seamless workflows. AI simplifies these complexities, making them more accessible, scalable, and impactful. Here’s how AI transforms modern marketing. Unleashing AI’s Potential in Marketing AI has become a cornerstone for enhancing customer experiences and boosting marketing productivity. However, to fully leverage AI, it’s essential to understand its capabilities and implementation strategies. Think of AI as your vehicle for uncovering actionable customer insights, optimizing campaigns, and creating tailored customer experiences. While the pace of AI’s evolution may seem overwhelming, this guide will help you take control and confidently drive your AI-powered marketing efforts. Future Trends in Generative AI and Marketing Generative AI is unlocking new possibilities in customer engagement. This guide explores the challenges, advantages, and emerging trends in AI-driven marketing. From attracting customers to maximizing ROI, you’ll discover best practices and real-world examples of successful AI adoption. How AI Works in Marketing AI uses advanced algorithms and pattern recognition to simulate human intelligence in processing data. Through machine learning and deep learning, it identifies trends, predicts outcomes, and automates tasks typically requiring human intervention. Like humans learning from experience, AI improves with practice. It rapidly identifies consumer preferences, behaviors, and purchasing patterns. Two primary types of AI stand out in marketing: These AI types work together—predictive AI extracts insights from data, while generative AI uses those insights to create personalized content and solutions. This synergy enables marketers to automate tasks, segment audiences, and deliver tailored messaging based on individual preferences. AI in Action: Enhancing Customer Engagement AI enables marketers to engage with customers more effectively by: The Power of AI-Driven Marketing Analytics AI-powered analytics revolutionize decision-making by identifying patterns and offering actionable insights. Marketers can use AI tools to: Maximizing ROI with AI AI enables businesses to expand audience reach, improve conversion rates, and enhance customer relationships through personalized content and product recommendations. Its real-time analytics empower marketers to make informed decisions, while automation frees up time for strategic innovation. Navigating Challenges in AI Marketing AI’s potential comes with challenges, including: By prioritizing ethical practices, transparent data policies, and robust compliance measures, marketers can overcome these obstacles and leverage AI responsibly. Best Practices for AI-Driven Marketing To maximize the benefits of AI, marketers should: The Future: AI Copilots in Marketing AI copilots—conversational AI integrated into platforms—are transforming marketing workflows. These tools draft content, provide recommendations, and offer guidance based on CRM data, significantly enhancing efficiency. Looking Ahead: Emerging Trends in AI Marketing Over the next two years, advancements in AI will continue to reshape marketing. Key trends include: By embracing these advancements, marketers can deliver exceptional customer experiences, drive business growth, and stay competitive in an evolving digital landscape. AI is not just a tool—it’s a transformative force. By integrating AI into your marketing strategy, you can unlock unparalleled opportunities to engage customers, optimize campaigns, and propel your organization into the future. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Direct Manipulation to Intent-Driven Design

The Shift from Direct Manipulation to Intent-Driven Design: How AI is Reshaping User Interaction The way we interact with software is constantly evolving — sometimes through gradual changes, other times through disruptive leaps. Today, as AI-powered applications gain momentum, design pioneers like Vitaly Friedman, Emily Campbell, and Greg Nudelman are exploring the emerging design patterns that are reshaping user experiences. This shift is more than just another tech trend — it represents a fundamental transformation in human-computer interaction. The shift can be compared to the transition from film cameras to digital photography. In the past, users manually adjusted settings like exposure and film speed. With digital cameras, the process became automated — users simply clicked a button, and the camera handled the rest. AI is now bringing a similar transformation to software interfaces, allowing users to express their desired outcomes without dictating every step of the process. As Jakob Nielsen notes, this shift moves us away from rigid, step-by-step commands toward a goal-driven approach. In his words: “With new AI systems, the user no longer tells the computer what to do. Rather, the user tells the computer what outcome they want.” This transformation is not just technological — it’s philosophical. It challenges traditional ideas about control, agency, and human-computer collaboration. Where users once defined every step in an interaction, they now express their intent and let AI determine the optimal approach to achieving it. Direct Manipulation: The Foundation of Intuitive Design Before diving into how AI reshapes user interaction, it’s essential to understand the principles of direct manipulation, which have long defined intuitive user interfaces. In 1985, Edwin Hutchins, James Hollan, and Don Norman introduced the concept of direct manipulation in user interfaces. Direct manipulation refers to interaction styles where users directly engage with on-screen objects using physical, incremental, and reversible actions. For example, when you drag a file from one folder to another, you are directly manipulating the object. This interaction style is intuitive because it minimizes cognitive load — users can see immediate feedback as they interact with digital objects, reinforcing a sense of control. The Transition to Goal-Oriented Interactions AI is now challenging the dominance of direct manipulation by introducing goal-driven interactions. Instead of dictating each step of a process, users now express their desired outcome, and the system interprets and executes the task. Consider the AI-powered ‘Erase’ feature in Windows Photos. Instead of manually editing pixels to remove an unwanted object from a photo, users simply select the object and let the AI complete the task. This shifts the interaction from direct manipulation to intent-driven collaboration. Researchers like Desolda have explored this shift in their model of human-AI interaction. In traditional direct manipulation, users act in a linear sequence — recognize a goal, take an action, receive feedback. With AI, interactions become iterative and dynamic — users provide high-level input, AI executes, and users refine the output as needed. Enhancing Rather Than Replacing Direct Manipulation While AI introduces new interaction paradigms, it does not eliminate direct manipulation; instead, it layers new capabilities on top of it. For example, open input fields — like those found in ChatGPT or generative design tools — are built upon familiar UI patterns. These patterns reduce friction while allowing AI to extend the user‘s capabilities. Similarly, emerging frameworks like ‘Promptframes’ — introduced by Evan Sunwall — blend traditional wireframing with AI-generated content, accelerating design workflows without discarding familiar structures. This hybrid approach illustrates how AI can augment direct manipulation rather than replace it. Designing Seamless AI Interactions The ultimate goal of AI in design is to make interactions seamless. The most effective AI experiences do not draw attention to themselves — they quietly enhance user workflows. A prime example is Netflix’s recommendation engine. It does not ask users to configure settings or provide detailed input — it simply learns, adapts, and presents relevant content. This is the gold standard for AI-powered design: reducing friction, minimizing cognitive load, and allowing users to focus on their goals rather than the mechanics of interaction. As we design for AI, the focus should remain on enabling users to achieve outcomes effortlessly, rather than demanding their continuous attention. The future of user experience lies in balancing direct manipulation with AI-driven augmentation — empowering users to act with minimal friction while achieving powerful, intelligent outcomes. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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agetnforce for nonprofits

Empowering Nonprofits with Salesforce Technology

Nonprofit organizations face unique challenges, from managing donor relationships and tracking donations to optimizing operations and driving impactful campaigns. AgentForce by Salesforce is an AI-powered solution designed to address these needs, helping nonprofits streamline workflows, enhance donor engagement, and amplify their mission impact. Why Choose AgentForce for Nonprofit Organizations? AgentForce simplifies nonprofit operations by integrating donor management, program tracking, and fundraising tools into a single platform. This allows organizations to focus on what matters most—fulfilling their mission. Powered by AI and automation, AgentForce strengthens donor relationships, improves transparency, and supports data-driven decision-making. Key Benefits of AgentForce for Nonprofits Key Features of AgentForce for Nonprofits Why Partner with Tectonic? At Tectonic, we specialize in empowering nonprofits by implementing AgentForce to meet their unique needs. With a team of Salesforce-certified experts, we ensure seamless integration that maximizes the platform’s capabilities, helping you achieve your goals efficiently. How We Help Nonprofits Real-World Impact of AgentForce in Nonprofits Ready to Transform Your Nonprofit Operations? Empower your team, engage supporters, and amplify your mission impact with AgentForce by Salesforce. Contact Tectonic Today Schedule a free meeting to learn how AgentForce can revolutionize your nonprofit’s operations and help you achieve your goals. Let’s work together to make the world a nicer place! 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Public Sector Spring 25 Advances

Public Sector Spring 25 Advances

The Salesforce Spring ’25 Release: Transforming Public Sector Operations The Salesforce Spring ’25 release has arrived, bringing transformative updates to public sector workflows, including faster document generation, AI-powered household insights, and smarter grantmaking processes. At Tectonic, we’re passionate about driving digital transformation for our clients. Here’s a deep dive into the key enhancements and how they can elevate your public sector operations. 1. Faster, More Flexible Document Generation OmniStudio Document Generation 2.0 introduces significant improvements in speed and flexibility for public sector workflows. With higher batch limits, support for custom fonts, and a document previewer, teams can generate documents more efficiently and accurately. Whether you’re managing applications, approvals, or citizen communications, this update reduces processing times and enhances overall workflows. This transition also improves performance by moving PDF generation from client-side to server-side, ensuring a seamless upgrade with minimal regression impact. The enhanced functionality makes it easier to handle high-demand periods and large document volumes. Pro Tip: Transition to OmniStudio Document Generation 2.0 before Document Generation 1.0 is retired in July 2025. Use the preview tool to refine templates during peak times. 2. AI-Powered Household Overviews for Caseworkers Salesforce Generative AI introduces a new household overview feature, empowering caseworkers with detailed insights into benefit applicants’ households. This tool streamlines eligibility assessments, enabling faster and more accurate decisions. It even automates energy savings calculations for Clean Energy Programs, aligning citizen support with sustainability goals. By simplifying data collection and decision-making, caseworkers can focus on high-priority cases, ensuring faster and more equitable approvals. Pro Tip: Pair this feature with Energy Cloud insights to enhance decision-making and allocate resources more effectively for citizens in need. 3. Supercharge Grantmaking with Stage Management Stage Management automates key grantmaking tasks, ensuring compliance and improving efficiency. Grant managers can bulk-assign reviews, reducing manual workload and freeing up time for high-priority tasks. This feature provides better control by defining each stage of the grant process, enabling faster and more accurate progress. With automated workflows and robust progress tracking, Stage Management ensures timely execution of grant operations. Pro Tip: Use automated workflows to manage multiple grants simultaneously, ensuring deadlines are met and every stage is completed on time. 4. Empower Employees with Personalized Care Plans Spring ’25 introduces personalized care plans, a game-changer for public sector organizations. These plans allow agencies to create and assign tailored growth and well-being strategies for employees. By setting customizable goals and aligning benefits with individual needs, organizations can foster a supportive work environment that drives employee engagement and retention. This targeted approach enhances morale and supports professional development, making it invaluable for workforce motivation and talent retention. Pro Tip: Use personalized care plans during onboarding to set new hires up for success or integrate them into professional development initiatives for ongoing growth and engagement. 5. Unified Voice Routing for Seamless Citizen Interaction (Beta) Unified Voice Routing consolidates communication channels in Salesforce, streamlining citizen interactions. By routing voice calls based on skills or specific representatives, public sector teams can reduce wait times and deliver more effective service. This feature also introduces a new Reassign button, enabling teams to transfer work between queues, service reps, AI agents, skills, or Omni-Channel flows. Reassigned tasks are automatically routed to the correct destination. Pro Tip: Combine Unified Voice Routing with Amazon Connect to route calls to the most qualified representatives, ensuring quick and effective resolutions. Conclusion The Salesforce Spring ’25 updates are a game-changer for public sector organizations, enabling teams to deliver faster, more efficient, and more impactful services. From AI-powered household insights to smarter grantmaking and seamless communication, these tools empower organizations to better serve their communities. At Tectonic, we’re excited to help you leverage these updates to optimize your operations and make a greater impact in your community. Want to learn more about how these tools can transform your workflows? Contact us today, and let’s explore the possibilities together! 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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salesforce agentforce ai powered agentic agents

AI for Membership Sites

AI for Membership Sites: How Artificial Intelligence is Driving New Revenue for Member-Only Platforms Membership sites are entering a transformative era where “AI is the New UI.” Two recent developments illustrate this trend and underscore how artificial intelligence is redefining user interaction and unlocking new revenue streams. The first insight comes from Dr. John Sviokla’s Forbes article, “AI Is The New UI: 3 Steps Business Leaders Must Take Now”. Sviokla emphasizes a fundamental shift: “For decades, we’ve interacted with technology through screens, buttons, and menus. But a fundamental shift is underway — artificial intelligence is becoming the new user interface.” The second example involves a large members-only association in the airline industry. This organization has implemented custom AI chatbots within its member portal to address a growing challenge: members no longer have time to sift through lengthy PDFs or dense slide decks. Instead, they crave fast, ChatGPT-style access to information—and they’re willing to pay for it. A Paradigm Shift in User Interfaces Historically, intuitive gestures and responsive designs revolutionized how people interacted with technology. Today, AI is driving the next evolution, moving interfaces from static designs to dynamic, user-centric experiences. Dr. Sviokla notes: “This transformation isn’t just about chatbots; it’s about AI becoming the primary means through which we interact with systems, data, and machines. For business leaders, this shift represents both an opportunity and an imperative to reimagine how their organizations engage with customers and operate internally.” AI-powered interfaces offer users immediate, conversational, and personalized access to information, bypassing the traditional maze of links and menus. For membership sites, this evolution is particularly significant, as it transforms how members interact with content and services. The “ChatGPT Effect” on Membership Sites The rise of ChatGPT has shifted consumer expectations for digital interactions. Websites are now adopting chatbots and virtual assistants that provide tailored experiences. For membership sites, this technology enables: For example, organizations are deploying AI assistants on their websites to handle various functions, such as sales inquiries, product support, and pricing guidance. These tools enhance member satisfaction and provide opportunities for new revenue streams. AI as a Revenue Generator Membership sites leveraging AI are seeing measurable financial benefits. Consider a crypto token regulation platform that integrated custom AI chatbots. These tools allow members to interact with proprietary data in real time, transforming static content into a dynamic, accessible resource. This shift has significantly increased the platform’s value proposition, attracting and retaining members willing to pay a premium for enhanced access. Starting Small: A Scalable Approach to AI Implementing AI doesn’t require a complete system overhaul. Membership sites can begin with a simple, custom chatbot built using existing content, such as publicly available documents or FAQs. By monitoring member interactions and gathering feedback, organizations can gradually expand their AI capabilities. The key is to focus on enhancing the member experience. Missteps often occur when organizations adopt overly complex solutions that fail to address real user needs. A phased approach ensures AI integration adds value and aligns with member expectations. The Future of AI in Membership Sites The potential for AI in membership sites extends far beyond chatbots. Future applications include: For example, the Martin Trust Center for MIT Entrepreneurship recently launched an AI-powered tool specifically designed to serve its members. These types of innovations highlight how AI can enhance the member experience while driving operational and financial success. Reimagining Member Engagement Membership sites that embrace AI as a foundational component of their user experience are positioning themselves for long-term success. By focusing on solving real problems and delivering meaningful interactions, organizations can strengthen member relationships and drive sustainable growth. For membership sites, the question is no longer whether to adopt AI but how quickly they can integrate it. AI represents an opportunity—and an imperative—to transform the way members interact with content, data, and services. The sites that act now will set the standard for the future of member-driven platforms. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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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AI Market Heat

AI Market Heat

Alibaba Feels the Heat as DeepSeek Shakes Up AI Market Chinese tech giant Alibaba is under pressure following the release of an AI model by Chinese startup DeepSeek that has sparked a major reaction in the West. DeepSeek claims to have trained its model—comparable to advanced Western AI—at a fraction of the cost and with significantly fewer AI chips. In response, Alibaba launched Qwen 2.5-Max, its latest AI language model, on Tuesday—just one day before the Lunar New Year, when much of China’s economy typically slows down for a 15-day holiday. A Closer Look at Qwen 2.5-Max Qwen 2.5-Max is a Mixture of Experts (MoE) model trained on 20 trillion tokens. It has undergone supervised fine-tuning and reinforcement learning from human feedback to enhance its capabilities. MoE models function by using multiple specialized “minds,” each focused on a particular domain. When a query is received, the model dynamically routes it to the most relevant expert, improving efficiency. For instance, a coding-related question would be processed by the model’s coding expert. This MoE approach reduces computational requirements, making training more cost-effective and faster. Other AI vendors, such as France-based Mistral AI, have also embraced this technique. DeepSeek’s Disruptive Impact While Qwen 2.5-Max is not a direct competitor to DeepSeek’s R1 model—the release of which triggered a global selloff in AI stocks—it is similar to DeepSeek-V3, another MoE-based model launched earlier this month. Alibaba’s swift release underscores the competitive threat posed by DeepSeek. As the world’s fourth-largest public cloud vendor, Alibaba, along with other Chinese tech giants, has been forced to respond aggressively. In the wake of DeepSeek R1’s debut, ByteDance—the owner of TikTok—also rushed to update its AI offerings. DeepSeek has already disrupted the AI market by significantly undercutting costs. In 2023, the startup introduced V2 at just 1 yuan ($0.14) per million tokens, prompting a price war. By comparison, OpenAI’s GPT-4 starts at $10 per million tokens—a staggering difference. The timing of Alibaba and ByteDance’s latest releases suggests that DeepSeek has accelerated product development cycles across the industry, forcing competitors to move faster than planned. “Alibaba’s cloud unit has been rapidly advancing its AI technology, but the pressure from DeepSeek’s rise is immense,” said Lisa Martin, an analyst at Futurum Group. A Shifting AI Landscape DeepSeek’s rapid growth reflects a broader shift in the AI market—one driven by leaner, more powerful models that challenge conventional approaches. “The drive to build more efficient models continues,” said Gartner analyst Arun Chandrasekaran. “We’re seeing significant innovation in algorithm design and software optimization, allowing AI to run on constrained infrastructure while being more cost-competitive.” This evolution is not happening in isolation. “AI companies are learning from one another, continuously reverse-engineering techniques to create better, cheaper, and more efficient models,” Chandrasekaran added. The AI industry’s perception of cost and scalability has fundamentally changed. Sam Altman, CEO of OpenAI, previously estimated that training GPT-4 cost over $100 million—but DeepSeek claims it built R1 for just $6 million. “We’ve spent years refining how transformers function, and the efficiency gains we’re seeing now are the result,” said Omdia analyst Bradley Shimmin. “These advances challenge the idea that massive computing power is required to develop state-of-the-art AI.” Competition and Data Controversies DeepSeek’s success showcases the increasing speed at which AI innovation is happening. Its distillation technique, which trains smaller models using insights from larger ones, has allowed it to create powerful AI while keeping costs low. However, OpenAI and Microsoft are now investigating whether DeepSeek improperly used their models’ data to train its own AI—a claim that, if true, could escalate into a major dispute. Ironically, OpenAI itself has faced similar accusations, leading some enterprises to prefer using its models through Microsoft Azure, which offers additional compliance safeguards. “The future of AI development will require stronger security layers,” Shimmin noted. “Enterprises need assurances that using models like Qwen 2.5 or DeepSeek R1 won’t expose their data.” For businesses evaluating AI models, licensing terms matter. Alibaba’s Qwen 2.5 series operates under an Apache 2.0 license, while DeepSeek uses an MIT license—both highly permissive, allowing companies to scrutinize the underlying code and ensure compliance. “These licenses give businesses transparency,” Shimmin explained. “You can vet the code itself, not just the weights, to mitigate privacy and security risks.” The Road Ahead The AI arms race between DeepSeek, Alibaba, OpenAI, and other players is just beginning. As vendors push the limits of efficiency and affordability, competition will likely drive further breakthroughs—and potentially reshape the AI landscape faster than anyone anticipated. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Opportunity Scoring with Einstein

Agentforce Versus Einstein

Salesforce offers a variety of tools and platforms to help businesses manage customer relationships, automate processes, and leverage AI for better decision-making. Two of its prominent offerings in the customer service and AI space are Service Cloud (Agent Console) and Einstein AI. Here’s a comparison of Agent Console (part of Service Cloud) and Einstein: 1. Salesforce Agent Console (Service Cloud) The Agent Console is a core component of Salesforce’s Service Cloud, which is designed to help customer service agents manage cases, interactions, and customer data efficiently. Key Features: Use Case: The Agent Console is ideal for customer service teams that need a centralized platform to manage customer interactions and resolve issues quickly. 2. Salesforce Einstein Einstein is Salesforce’s AI platform that integrates artificial intelligence across Salesforce products, including Service Cloud, Sales Cloud, Marketing Cloud, and more. It provides predictive analytics, automation, and personalized recommendations. Key Features: Use Case: Einstein is ideal for organizations looking to leverage AI to enhance customer service, improve decision-making, and automate routine tasks. Agent Console vs. Einstein: Key Differences Feature/Aspect Agent Console (Service Cloud) Einstein AI Purpose Centralized platform for managing customer service operations. AI-powered insights, automation, and personalization. Core Functionality Case management, omnichannel support, and agent productivity tools. Predictive analytics, chatbots, and AI-driven recommendations. Automation Workflow automation for case management and task routing. AI bots and automated responses for customer inquiries. Insights Basic reporting and analytics for agent performance. Advanced predictive analytics and AI-driven insights. Integration Part of Service Cloud, focused on customer service. Integrated across Salesforce products (Sales, Service, Marketing, etc.). User Interaction Primarily used by customer service agents. Used by agents, managers, and customers (via bots). How They Work Together The Agent Console and Einstein are not mutually exclusive; they complement each other. For example: Which One Should You Use? In many cases, businesses use both together to create a seamless, AI-enhanced customer service 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Agentforce Custom AI Agents

Understanding AI Agents

Understanding AI Agents: How They Differ from Copilots and Assistants The AI landscape is evolving rapidly, with terms like AI agents, copilots, and assistants often used interchangeably. But what truly distinguishes them? This analysis clarifies their differences, maps them against real-world AI tools, and identifies gaps in today’s market. Why This Distinction Matters Understanding AI agent capabilities is crucial for: By 2025, AI agents are expected to become enterprise-ready, with the market projected to grow 45% annually, reaching $47 billion by 2030 (MarketsandMarkets). Microsoft CEO Satya Nadella even suggests that agentic applications could replace traditional SaaS. But what makes an AI tool an agent rather than just a copilot or assistant? Defining AI Agents, Copilots, and Assistants 1. AI Agents: Autonomous Goal-Seekers Gartner’s definition (2024): “AI agents are autonomous or semi-autonomous software entities that use AI techniques to perceive, make decisions, take actions, and achieve goals in their digital or physical environments.” Key capabilities:✔ Autonomy – Acts independently.✔ Goal-driven behavior – Works toward broader objectives.✔ Environmental interaction – Uses tools (actions), sensors (perception), and data retrieval.✔ Learning & memory – Adapts over time.✔ Proactivity – Acts on triggers, not just user commands. Example: Agentforce (Salesforce’s AI agent) autonomously creates marketing campaigns by analyzing CRM data. 2. AI Copilots: Collaborative Partners Microsoft’s perspective: “Copilots enhance decision-making by offering context-specific recommendations and work collaboratively with humans.” Key differences from agents: Example: Cursor (AI coding assistant) helps developers by auto-completing and refining code in real time. 3. AI Assistants: Task-Based Helpers Example: ChatGPT (basic version) answers questions but doesn’t autonomously execute tasks. The Agent-Copilot-Assistant Spectrum Feature AI Assistant AI Copilot AI Agent Autonomy ❌ No ⚠️ Semi ✅ Yes Goal-driven ❌ No ⚠️ Partial ✅ Yes Tools & Actions ❌ No ⚠️ Limited ✅ Yes Sensors/Triggers ❌ No ❌ No ✅ Yes Memory & Learning ❌ No ✅ Yes ✅ Yes Proactivity ❌ No ⚠️ Some ✅ Yes Current Market Gaps: Where AI Tools Fall Short Despite advancements, most AI tools today don’t fully meet agent or copilot criteria: 1. Most “Agents” Lack True Autonomy 2. Copilots Often Lack Memory 3. Assistants Dominate the Market Many popular AI tools (Grammarly, Canva AI, Remove.bg) are task-specific assistants, not true copilots or agents. The Future of AI Agents & Copilots Key Takeaways ✔ AI agents act autonomously, copilots collaborate, and assistants follow commands.✔ Today’s “agents” are semi-autonomous—true autonomy is still evolving.✔ Most AI tools are still assistants, with only a few (like GitHub Copilot) qualifying as copilots.✔ Memory, proactivity, and sensors are the biggest gaps in current AI offerings. For businesses and developers, this presents an opportunity: those who build true copilots and safe agents will lead the next wave of AI adoption. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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