Salesforce Einstein Archives - gettectonic.com - Page 9

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Paradox of Writing With AI

Paradox of Writing With AI

It seems like some people honestly believe they can spot AI-generated content immediately, but that’s not always the case. Well-written content isn’t inherently AI-generated, and if it is AI-generated, that doesn’t necessarily mean it’s well-written. The quality of writing often depends more on the writer’s skill than the tools they use. Paradox of Writing With AI is that it will make a good writer better. And it will make a bad writer worse. The real difference in human versus AI content lies in the accessibility of writing tools and the lack of proper ethical regulation for their use. This ease of access makes it simple for people to feel entitled to judge written content. True, if you publish your writing – online or elsewhere – you open it up for judgement. But imagine if UX design or data applications were graded as indiscriminately—those discussions would likely be confined to experts rather than becoming public debates on social media condemning all well-written content. Good writing requires creativity, flair, and uniqueness, among other skills, to truly impress readers. Good writing is well-organized and flows well with consistent style or voice from beginning to end. Good writing is also free from mistakes and errors in spelling, punctuation and grammar. But that alone doesn’t make it engaging or meaningful. A good writer will brainstorm for great ideas and follow them up with research. A good writer can think of fresh angles to view a topic. A good writer is sure to re-write and self-edit to make a better draft. AI has been integrated into various tools and applications long before ChatGPT was launched. Search engines use it to provide relevant results; social media algorithms keep your favorite content visible; Siri and Alexa rely on natural language processing and speech recognition; Netflix and Spotify use AI recommendation systems to cater to your tastes, and so on. AI enhances human ideas, not just in writing, but across many fields. Writing With AI is Inevitable For instance, Chinese Nobel laureate Mo Yan surprised everyone at the 65th-anniversary celebration of Shouhuo magazine by revealing he uses ChatGPT. During his speech praising fellow author Yu Hua, he mentioned that he struggled to write a commendation and asked a doctoral student to use ChatGPT for help. This revelation caused quite a stir, as it was unexpected for a Nobel Prize winner to use AI for writing. Why shouldn’t he? If AI makes a good writer better, then most of us should be employing it. Mo Yan isn’t alone. Rie Kudan, the 17th winner of Japan’s Akutagawa Prize, admitted to using ChatGPT for her novel, Tokyo-to Dojo-to. She stated that about 5% of the book consists of AI-generated sentences. Kudan, who is introverted, shared that frequent interactions with the AI tool allowed her to express personal thoughts she couldn’t comfortably discuss with others. ChatGPT’s responses often sparked dialogue in her novel, adding a unique dimension to her writing process. Grammarly, another AI tool, is why some people’s writing doesn’t reflect their irritation when discussing AI-generated content online. Grammarly has been widely used for editing and proofreading, ensuring users’ writing maintains a promotional tone and corrects errors without sounding sarcastic or bored. The Problem with Sounding Alike & The Uniqueness of a Writer’s Voice A significant issue with AI-generated content is that many written works sound similar. Writers need to develop unique voices. While Jane Austen, Mary Shelley, and the Brontë sisters are admirable, emulating their ornate language can interfere with communication’s primary purpose. Excessive fanciness can make speech overly flamboyant, akin to Oscar Wilde’s works. However asking AI to work through your content and put it in the voice of a known writer, add humor, or change the tense is time saving. The problem isn’t that AI enables people to produce well-crafted content. Many individuals have exceptional writing skills and huge vocabularies. The real issue is the uniformity in everyone’s writing, a lack of diversity that AI can perpetuate. Yet, you only have to Google any topic and you will find many blog posts and articles that share the same view, and perhaps the same voice. Some discussions about AI resemble early 2000s conspiracy theories about cell phones. While the context has changed, the tone remains similar. The Importance of Creativity in Writing & Our Language Creativity is essential in writing. Even AI relies on human creativity. Without our input, machines would repeatedly generate the same content. Machine learning in AI is about learning from people. Our role is crucial, demonstrating the value of our unique voices. Developing a unique voice takes time and effort, which is why creatives like Kelly McKernan, Nicki Minaj, Elin Hilderbrand, and Jonathan Franzen are suing AI companies for copyright infringement. These unique voices significantly impact language evolution, and it’s vital for us to continue growing creatively. Writers play a crucial role in language evolution by creating new words or phrases that captivate readers. Over time, these innovations can enrich the language. A writer’s distinctive style can set trends, leading to significant changes in language use. This power must be used wisely. Famous writers’ narrative structures and dialogue usage can inspire others. For example, Dr. Seuss coined “nerd,” J.R.R. Tolkien introduced “tween,” Milton created “pandemonium”, novelist William Gibson first used “cyberspace”, Johnathon Swift gave us “yahoo” in Gulliver’s Travels, and Charles Dickens gave us “boredom.” The core of a good piece of writing is a great idea. With a strong core idea, the writer can easily layer the content around it. Content even can build the framework from which comes a whole new word. Content includes interesting examples to which the reader can relate. That content needs to be well-organized and clear in form so that the reader can easily see the message or find the intended meaning. In addition, the writing should have style and the right voice that matches its topic and theme while also reflecting what the author believes.  Writing Through the Centuries Writing has evolved over centuries, influencing language development. During

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Salesforce Einstein Features

Salesforce Einstein Features

Salesforce Einstein Discover the power of the #1 AI for CRM with Einstein. Built into the Salesforce Platform, Einstein uses powerful machine learning and large language models to personalize customer interactions and make employees more productive. With Einstein powering the Customer 360, teams can accelerate time to value, predict outcomes, and automatically generate content within the flow of work. Einstein is for everyone, empowering business users, Salesforce Admins and Developers to embed AI into every experience with low code. Salesforce Einstein Features. Einstein Copilot Sales Actions: Sell faster with an AI assistant in the flow of work.Call Exploration: Ask Einstein to synthesize important call information in seconds. Ask Einstein to identify important takeaways and customer sentiment, so you have the context you need to move deals forward.

 Sales Summaries: Summarize records to identify likelihood the deal will close, the competitors involved, key activities, and more. Forecast Guidance: Ask Einstein to inform your forecast and help you identify which deals need your attention. Close Plan: Generate a customized action plan personalized to your customer and sales process. Increase conversion rates with step-by-step guidance and milestones grounded in CRM data. Salesforce Einstein Features Sales Generative AI features: ° Knowledge Creation: ° Search Answers for Agents and Customers: Einstein Copilot Service Actions: Streamline service operations by drafting Knowledge articles and surfacing answers, grounded in knowledge, to the most commonly asked questions. Summarize support interactions to save agent time and formalize institutional knowledge. Surface generated answers to agents’ & customers’ questions that are grounded in your trusted Knowledge base directly into your search page. Search Answers for Agents is included in the Einstein for Service Add-on SKU and Search Answers for Customers is included in the Einstein 1 Service Edition.
Empower agents to deliver more personalized service and reach resolutions faster with an AI assistant built into the flow of work. You can leverage out-of-the-box actions like summarize conversations or answer questions with Knowledge or you can build custom actions to fit your unique business needs. Service Salesforce Einstein Features This Release Einstein CopilotSell faster with an AI assistant. No data requirements
Included in Einstein 1 Sales Edition.hEinstein Copilot: Sales ActionsSell faster with an AI assistant.No data requirements. 
 Call explorer and meeting follow-up requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Generative AIBoost productivity by automating time-consuming tasks.No data requirements. 
 Call summaries and call explorer requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Einstein will use a global model until enough data is available for a local model. For a local model: ≥1,000 lead records created and ≥120 of those converted in the last 6 monthsEinstein Automated Contacts Automatically add new
contacts & events to your CRM≥ 30 business accounts. If you use Person Accounts, >= 50 percent of accounts must be business accounts Einstein Recommended ConnectionsGet insights about your teams network to see who knows your customers and can help out ona deal ≥ 2 users to be connected to Einstein Activity Capture
and Inbox (5 preferred) Einstein Forecasting Easily predict sales forecasts inside
of Salesforce Collaborative Forecasting enabled; use a standard fiscal year; measure forecasts by opportunity revenue; forecast hierarchy must include at least one forecasting enabled user who reports to a forecast manager; opportunities must be in Salesforce ≥ 24 months;Einstein Email Insights Prioritize your inbox with actionable intelligence Einstein Activity Capture enabledEinstein Activity Metiics (Activity 360) Get insight into the activities you enter
manually and automatically from Einstein
Activity Capture Einstein Activity Capture enabled Sales Analytics Get insights into the most common sales KPIs No data requirements. User specific requirements like browser and device apply Einstein Conveisation Insights Gain actionable insights from your sales calls with conversational intelligenceCall or video recordings from Lightning Dialer, Service Cloud Voice, Zoom and other supported CTI audio and video partners.Buyer Assistant Replace web-to-lead forms with real-time conversations. No data requirements – Sales Cloud UE or Sales Engagement. Einstein Opportunity ScoringEinstein Activity CaptuiePrioritize the opportunities most likely to convertAutomatically capture data & add to your CRMEinstein will use a global model until enough data is available for a local model. For a local model: ≥ 200 closed won and ≥ 200 closed lost opportunities in the last 2 years, each with a lifespan of at least 2 days≥ 30 accounts, contacts, or leads; Requires Gmail, Microsoft Exchange 2019, 2016, or 2013 Einstein Relationship Insights Speed prospecting with AI that researches for you. No data requirements. Einstein Next Best Action Deliver optimal recommendations at the point of maximumimpactNo data requirements. User specific requirements like browser and device apply Sales AIGenerate emails, prioritize leads & opportunities most likely to convert, uncover pipeline trends, predict sales forecasts, automate data capture, and more with Einstein for Sales. Generative AIPrompt BuilderEinstein Lead ScoringEinstein Opportunity ScoringEinstein Activity CaptureEinstein Automated ContactsEinstein Recommended ConnectionsEinstein ForecastingEinstein Email InsightsEinstein Activity Metrics (Activity 360)Sales AnalyticsEinstein Conversation InsightsBuyer Assistant Sales AIGenerative AI: 
Feature Why is it so Great? What do I need? Automate common questions and business processes to solve customer requests fasterBoost productivity by auto-generating service replies, summarizing conversations during escalations andtransfers or closed interactions, drafting knowledge articles, and surfacing relevant answers grounded inknowledge for agents’ and customers’ commonly asked questions. Deliver optimal recommendations at the point of maximum impactEliminate the guesswork with AI-powered recommendations for everyoneDecrease time spent on manual data entry for incoming cases and improve case field accuracy and completionAutomate case triage and solve customer requests fasterDecrease time spent selecting field values needed to close a case with chat conversations and improved field accuracySurface the best articles in real time to solve any customer’s questionEliminate time spent typing responses to the most common customer questionsGet insights into contact center operations, understand customers, and deliver enhanced customerexperiencesChat or Messaging channels, minimum of 20 examples for most languagesNo data requirements. User specific requirements like browser and device apply Make sure that your dataset has the minimum records to build a successful recommendation. Recipient Records need a minimum of 100 records,Recommended Item Records need a minimum of 10 records, andPositive Interaction Examples need a minimum of 400 records

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Slack and Salesforce

AI in Slack

Introducing AI in Slack If you are unfamiliar with the Slack collaboration tool, learn more here. Incorporating Artificial Intelligence (AI) into Slack marks a significant milestone, one that is a real gamechanger. Slack’s ability to consolidate projects, data, and conversations into one platform has been a time saver for businesses, fostering collaboration and enhancing productivity. Now, with the introduction of native AI features, users can leverage their collective knowledge more efficiently than ever before. “For the past decade, Slack has transformed the way we work, facilitating seamless integration of people, apps, and systems. With Slack AI, we’re poised to elevate this transformation further. These new AI capabilities empower our customers to tap into the wealth of knowledge within Slack, enabling smarter work processes, faster decision-making, and more focus on innovation and growth.” Denise Dresser, CEO of Slack Enhancing Work Efficiency with AI The traditional approach to work often comes with productivity challenges, particularly when employees lack access to critical, time based information. Studies reveal that nearly half of digital workers struggle to find necessary information, leading to suboptimal decision-making. By integrating AI features into Slack, users can instantly access contextual information related to any project or policy within their organization’s history. This streamlines workflows and enables teams to make better-informed decisions efficiently. Slack’s Commitment to Simplified Work Processes Slack has always aimed to simplify work processes, bringing conversations, automation, and productivity tools into one unified platform. From channel-based discussions to real-time collaboration and process automation, Slack offers a comprehensive solution for teams. Moreover, Slack seamlessly integrates with popular tools like Salesforce, Workday, and Google Drive, facilitating smoother business operations and accelerating task completion. AI in Slack With Slack’s channel-based model serving as the foundation, users can create a centralized repository of information. Every message, canvas, and clip contributes to this repository, forming a searchable database of collective knowledge. Intelligent search functionality further enhances accessibility, enabling users to retrieve relevant information effortlessly. AI-powered features, such as channel recaps, thread summaries, and search answers, revolutionize how teams interact with information. Channel recaps provide key highlights from discussions, allowing users to catch up quickly and make informed decisions. Thread summaries condense lengthy conversations, facilitating faster comprehension and decision-making. Additionally, search answers offer concise responses to queries, leveraging relevant Slack messages to provide valuable insights. Embracing AI for Future Growth As businesses recognize the potential of AI to drive efficiency and productivity, Slack’s AI features offer a seamless transition. By embedding AI tools directly into the Slack workspace, users can harness the power of AI effortlessly, without the need for complex configurations or separate applications. Overall, Slack AI empowers teams to reach their full potential by leveraging corporate knowledge effectively. With AI-driven insights at their fingertips, teams can save time, make better decisions, and drive meaningful outcomes for their organizations. AI in Slack 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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Public Sector Solutions Record Aggregation

Public Sector Solutions Record Aggregation to Simplify Information Access for Caseworkers Caseworkers often need to review benefit applications and associated benefits for household members to determine eligibility. However, this process can be complex due to the indirect relationship between benefit assignments and party relationship groups. Caseworkers must navigate through multiple objects to access this information, which can be time-consuming and inefficient. Record aggregation offers a solution to this challenge by allowing caseworkers and other users to easily access information from two unrelated objects. With record aggregation, records from one object (e.g., benefit assignments) are aggregated and linked to records of another unrelated object (e.g., party relationship group). This consolidated view helps users quickly access relevant information without navigating through multiple layers of data. Setting Public Sector Solutions Record Aggregation To implement record aggregation: Benefits of Record Aggregation Record aggregation enables: By leveraging record aggregation, public sector organizations can streamline processes for caseworkers and enhance efficiency in benefit application reviews. This approach ensures that relevant information is readily available, ultimately improving service delivery and decision-making. 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 Einstein

Einstein Opportunity Scoring Explained

Utilize Artificial Intelligence to Optimize Opportunity Management: Einstein Opportunity Scoring Explained Let artificial intelligence (AI) empower you and your team to focus on the most promising opportunities and maximize deal closure rates. Each opportunity is assigned a score ranging from 1 to 99, providing valuable insights into its potential outcome. These scores are readily available on opportunity records and list views, ensuring easy access to critical information. Moreover, if you utilize Collaborative Forecasts, opportunity scores are also integrated into the forecasts page, enhancing visibility and forecasting accuracy. Einstein Opportunity Scoring is a versatile tool accessible to users with or without a Sales Cloud Einstein license. It provides a predictive assessment of the likelihood that an opportunity will result in a successful deal. For each opportunity score generated by Einstein, users gain visibility into the key factors influencing the score, both positively and negatively. In the Lightning Experience interface, opportunity scores are conveniently displayed on the compact layout of opportunity records or on the Details tab. Hovering over the score reveals a breakdown of the contributing factors, allowing users to understand why a particular score was assigned. For instance, a high score may indicate that the opportunity is progressing rapidly through the sales stages compared to others. For users navigating Salesforce Classic, the opportunity score is presented on the record detail of opportunity records, accompanied by the contributing factors. Customizing Opportunity Management with Opportunity Scores: Admins have the flexibility to incorporate the Opportunity Score field into various opportunity list views, empowering users to prioritize and manage opportunities effectively. In Lightning Experience, hovering over the score in list views provides insights into the factors influencing the score. However, in Salesforce Classic, users need to navigate to the opportunity record detail page to access this information. Furthermore, for organizations leveraging Collaborative Forecasts, admins can seamlessly integrate opportunity scores into the opportunity list on the forecasts page, enhancing forecasting accuracy and sales planning. Understanding Opportunity Score Criteria: The opportunity score is derived from a comprehensive analysis of various factors, including market demand, competitive landscape, potential return on investment, and resource requirements. By considering these criteria, Einstein Opportunity Scoring provides actionable insights to guide decision-making and resource allocation. Exploring Einstein Lead Scoring Criteria: In addition to opportunity scoring, Einstein offers lead scoring functionality to identify high-quality leads. By analyzing past leads, Einstein determines which current leads share similarities with those that have previously converted. Admins can customize lead scoring criteria by including or excluding specific lead fields based on their relevance to lead quality. Sales Cloud Einstein Scoring Hierarchy: Einstein Opportunity Scoring is part of Sales Cloud Einstein Scoring, which encompasses both opportunity and lead scoring capabilities. In this hierarchy, Einstein Lead Scoring falls under the broader umbrella of Salesforce’s Sales Cloud Einstein model. Together, these scoring mechanisms empower sales teams with predictive insights to optimize their sales processes and drive success. Einstein Opportunity Scoring equips sales professionals with predictive analytics to assess opportunity viability accurately. By leveraging AI-driven scoring, organizations can streamline opportunity management, prioritize resources effectively, and ultimately, enhance sales performance and revenue growth. Like1 Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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Salesforce Generative AI

Is Slack Secure?

Slack and AI are here. Seems Promising, but Is Slack Secure? At Slack and Salesforce, trust is paramount. When it comes to AI, security is the top concern voiced by their customers. They are dedicated to developing AI products that are safe, responsible, and ethical. Their decision-making is guided by a set of product values aimed at upholding your trust. Is slack secure? You Maintain Control Over Your Data In a landscape where some companies view customer data as a commodity, Salesforce and Slack prioritize user safety and data privacy. Their new AI features are integrated within Slack’s secure infrastructure, ensuring that your data remains under your control. They neither sell, rent, nor utilize your information for commercial purposes because they firmly believe that your trust cannot be bought. Slack does not share customer data with large language model (LLM) providers nor utilize customer data to train LLMs. Slack AI operates on Slack’s infrastructure, adhering to the same stringent security practices and compliance standards expected from Slack itself. The entire ecosystem upholds a high level of security and compliance, including features like Enterprise Key Management, which empowers customers to manage their encryption keys independently. You Can Verify Results Tectonic recognizes that trust in technology hinges on its integrity. Slack AI features are designed to be transparent, allowing you to delve into the results and independently verify them. AI should complement, not replace, human judgment, and our aim is to provide tools that empower users to make informed decisions. Explore More AI Tools in Slack Today Slack’s AI capabilities are both subtle and powerful, complemented by a growing array of third-party AI apps vetted for reliability. One such app is Claude, a conversational chatbot from Anthropic available to Slack Enterprise Grid users. Claude functions as a knowledgeable personal assistant, adept at tasks like account planning, contract reviews, and strategy generation, all while maintaining privacy. Using Claude is straightforward; simply tag @Claude in channels or group messages to initiate tasks visible to your team. Additionally, Slack offers integration with other AI-powered apps such as Box, PagerDuty, Perplexity, and Notion, enhancing collaboration and efficiency. This Is Just the Beginning As Salesforce and Slack introduce user-friendly AI tools in Slack, they’re opening doors to limitless possibilities. Starting with robust features designed to simplify and streamline work processes, they plan to unveil more intelligent features aimed at helping teams maximize their organizational impact. 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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Salesforce's Get Ready for AI Report

Salesforce’s Get Ready for AI Report

Welcome to the future of business – Get Ready for AI is for analytics and data leaders. The tools for those who are interested in positioning themselves for AI success. From strategy to governance, you’ll learn what’s top-of-mind with other thought leaders, and see what actions you can take to be a more effective leader in a rapidly changing technology and business environment.  Salesforce’s Get Ready for AI Report This insight introduces four topics that are essential for data leaders beginning their AI journey: Access the full report here. Salesforce’s Get Ready for AI Report Data is at the center of any AI initiative, and organizations that are leading the way are focused on ensuring their data sources are current, authoritative, and complete. From talent, to strategy, to infrastructure, organizations that are prioritizing data across every business unit are ready to ride the AI wave. Positioning themselves for a significant competitive advantage over their peers. Salesforce’s Get Ready for AI Report As with any digital transformation, success depends on an enterprise-wide commitment. Data leaders are in a unique position to help guide their organizations through this transition, and achieve the benefits that AI can deliver. 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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AI Then and Now

AI Then and Now

AI: Transforming User Interactions and Experiences Have you ever been greeted by a waitress who already knows your breakfast order? It’s a relief not to detail every aspect — temperature, how do you want your eggs, what kind of juice, bacon or sausage, etc. This example encapsulates the journey we’re navigating with AI today. AI Then and Now. This article isn’t about ordering breakfast; it’s about the evolution of user interactions, particularly how generative AI might evolve based on past trends in graphical user interfaces (GUIs) and emerging trends in AI interactions. We’ll explore the significance of context bundling, user curation, trust, and ecosystems as key trends in AI user experience in this Tectonic insight. From Commands to Conversations Let’s rewind to the early days of computing when users had to type precise commands in a Command-Line Interface (CLI). Imagine the challenge of remembering the exact command to open a file or copy data. This complexity meant that only a few people could use computers effectively. To reach a broader audience, a shift was necessary. You might think Apple’s creation of the mouse and drop down menues was the pinnacle of success, but truly the evolution predates Apple. Enter ELIZA in 1964, an early natural language processing program that engaged users in basic conversations through keyword recognition and scripted responses. Although groundbreaking, ELIZA’s interactions were far from flexible or scalable. Around the same time, Xerox PARC was developing the Graphical User Interface (GUI), later popularized by Apple in 1984 and Microsoft shortly thereafter. GUIs transformed computing by replacing complex commands with icons, menus, and windows navigable by a mouse. This innovation made computers accessible and intuitive for everyday tasks, laying the groundwork for technology’s universal role in our lives. Not only did it make computing accessible to the masses but it layed the foundation upon which every household would soon have one or more computers! The Evolution of AI Interfaces Just as early computing transitioned from the complexity of CLI to the simplicity of GUIs, we’re witnessing a parallel evolution in generative AI. User prompts are essentially mini-programs crafted in natural language, with the quality of outcomes depending on our prompt engineering skills. We are moving towards bundling complex inputs into simpler, more user-friendly interfaces with the complexity hidden in the background. Context Bundling Context bundling simplifies interactions by combining related information into a single command. This addresses the challenge of conveying complex instructions to achieve desired outcomes, enhancing efficiency and output quality by aligning user intent and machine understanding in one go. We’ve seen context bundling emerge across generative AI tools. For instance, sample prompts in Edge, Google Chrome’s tab manager, and trigger-words in Stable Diffusion fine-tune AI outputs. Context bundling isn’t always about conversation; it’s about achieving user goals efficiently without lengthy interactions. Context bundling is the difference in ordering the eggs versus telling the cook how to crack and prepare it. User Curation Despite advancements, there remains a spectrum of needs where users must refine outputs to achieve specific goals. This is especially true for tasks like researching, brainstorming, creating content, refining images, or editing. As context windows and multi-modal capabilities expand, guiding users through complexity becomes even more crucial. Humans constantly curate their experiences, whether by highlighting text in a book or picking out keywords in a conversation. Similarly, users interacting with ChatGPT often highlight relevant information to guide their next steps. By making it easier for users to curate and refine their outputs, AI tools can offer higher-quality results and enrich user experiences. User creation takes ordering breakfast from a manual conversational process to the click of a button on a vending-like system. Designing for Trust Trust is a significant barrier to the widespread adoption of generative AI. To build trust, we need to consider factors such as previous experiences, risk tolerance, interaction consistency, and social context. Without trust, in AI or your breakfast order, it becomes easier just to do it yourself. Trust is broken if the waitress brings you the wrong items, or if the artificial intelligence fails to meet your reasonable expectations. Context Ecosystems Generative AI has revolutionized productivity by lowering the barrier for users to start tasks, mirroring the benefits and journey of the GUI. However, modern UX has evolved beyond simple interfaces. The future of generative AI lies in creating ecosystems where AI tools collaborate with users in a seamless workflow. We see emergent examples like Edge, Chrome, and Pixel Assistant integrating AI functionality into their software. This integration goes beyond conversational windows, making AI aware of the software context and enhancing productivity. The Future of AI Interaction Generative AI will likely evolve to become a collaborator in our daily tasks. Tools like Grammarly and Github Copilot already show how AI can assist users in creating and refining content. As our comfort with AI grows, we may see generative AI managing both digital and physical aspects of our lives, augmenting reality and redefining productivity. The evolution of generative AI interactions is repeating the history of human-computer interaction. By creating better experiences that bundle context into simpler interactions, empower user curation, and augment known ecosystems, we can make generative AI more trustworthy, accessible, usable, and beneficial for everyone. 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 Einstein

Use AI to Prep for Meetings

Sales is fundamentally a relationship-oriented endeavor, where representatives invest substantial time delving into lead interests, needs, and behaviors to fortify connections. What if you could Using AI to prep for meetings? Imagine a tool that assumes this responsibility, endowing you with the ability to swiftly acquaint yourself with pertinent information. Here’s what AI can accomplish: it undertakes the arduous research, analyzing both public and CRM data to succinctly encapsulate vital prospect details essential for pre-meeting preparation. If you have specific queries, just pose a question, and AI promptly provides a powered response. Consider this scenario: A sales representative steps in for a colleague on leave, aiming to catch up on major accounts. They leverage Einstein in Sales Cloud, filtering deals with a revenue exceeding $100,000. Many of these deals boast extensive historical data, a formidable amount to sift through. Einstein streamlines the process by presenting deal summaries encompassing crucial information such as involved parties, recent activities, potential risks, and recommended next steps. How to use AI to prep for meetings Einstein goes a step further, flagging an email from a customer with pricing queries awaiting a response. The rep seeks guidance: “What key information should I know about this customer before addressing the email?” Einstein synthesizes the deal in plain language, offering key account details and insights from past meetings to seamlessly resume the conversation. In other words, Einstein answers the reps question – in seconds. Sales Summaries for Sales Cloud becomes the go-to solution for instant meeting preparation, enabling sellers to navigate meetings with agility. Elevate your selling velocity with integrated AI directly in your CRM. Provide each seller with an AI assistant to turbocharge sales across the cycle, automating tasks, expediting decisions, and steering sellers towards swift closures. Einstein 1 allows effortless customization and integration of AI into various workspaces. Here are some key functionalities: 1. Call Summaries & Exploration: Bid farewell to tedious note-flipping. Ask Einstein to synthesize critical call information swiftly, generating concise summaries or identifying pivotal takeaways and customer sentiment from sales calls. 2. Prospect and Account Research: Streamline research on prospects and accounts. Summarize CRM records to gauge deal viability, competitor involvement, and more. Fetch real-time data updates from the news, and direct Einstein to update lead or opportunity records effortlessly. 3. Call Insights: Identify crucial moments from sales conversations. Instantly recognize objections, pricing attitudes, and questions asked without sifting through entire calls. Accelerate deal progression with conversation insights related to opportunities. 4. Relationship Graphs: Discern relationship networks effortlessly. Grasp prospect and customer networks for each deal, with automatic population of contacts and relevant details to fortify relationships with decision-makers. 5. Relationship Insights: Unearth new relationship insights with support from external data. Gain vital context from diverse sources across the web, seamlessly integrated into your CRM, and automatically update existing records with newfound information. Generative AI for Sales: Generative AI employs straightforward prompts to craft copy (e.g., prospecting emails) and provide recommendations (e.g., suggestions for quick-win deals). It analyzes existing sales and customer data to assist in drafting emails and determining messages or resources that would propel a sales conversation forward. Integration into a CRM, the hub of sales and customer data, is the likely destination for these capabilities. And while we’re at it – Real-Time Improvement of Sales Presentations: Crafting compelling presentations demands significant time and effort. Generative AI, activated through text-based prompts in presentation tools, facilitates the creation of customized decks and pitches within minutes. Early versions of real-time coaching are emerging, where AI-based guidance, embedded in video conferencing tools, evaluates live presentations to ensure they address the prospect’s pain points effectively. This advanced system, triggered by specific keywords, can recommend prospect-specific information, transforming your presentation into a tailored and impactful experience. Like Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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Salesforce Education Cloud for Educational Challenges

Salesforce Education Cloud for Educational Challenges

Educational institutions today confront a multitude of complex challenges, ranging from disjointed information systems to the need for agility in meeting evolving educational demands. Salesforce Education Cloud presents a unified solution aimed at overcoming these obstacles by enhancing operational efficiencies, boosting student engagement, and ensuring compliance with ever-changing educational standards. Below is an in-depth examination of the prevalent challenges faced by educational institutions and the tailored solutions provided by Salesforce Education Cloud. Key Challenges in the Education Sector Salesforce Education Cloud: Tailored Solutions for Education Salesforce Education Cloud addresses these challenges through a suite of customized features and tools designed to streamline operations, enhance student services, and promote effective communication. Real-World Impact of Salesforce Education Cloud Implementation of Salesforce Education Cloud yields transformative benefits across educational institutions: Conclusion Salesforce Education Cloud offers a comprehensive solution to the diverse challenges faced by educational institutions. By integrating this robust platform, schools, colleges, and universities can enhance operational efficiency, improve student outcomes, and cultivate a collaborative educational environment. Institutions seeking to explore the benefits of Education Cloud or enhance their existing systems are encouraged to consult with a Salesforce Education Cloud Consultant for tailored guidance and implementation strategies. 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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Gov Agencies AI Workforce Challenges

Gov Agencies AI Workforce Challenges

Federal agencies are placing a higher priority on providing AI training to their workforces with a focus on principles of transparency and accountability, officials announced at ATARC’s GITEC conference in Charlottesville, Virginia earlier. Gov Agencies AI Workforce Challenges. Alexis Bonnell, Air Force Research Laboratory CIO and Director of the Digital Capabilities Directorate, emphasized the importance of upholding existing ethics standards rather than creating new ones. She stressed that agencies need to exercise the ethical principles they have always been expected to follow. President Biden’s October 2023 executive order on artificial intelligence mandated that agencies develop ethical AI and establish AI offices, among other directives. While agencies like the Defense Department and the Department of Homeland Security are optimistic about AI’s potential, leaders remain cautious about its ethical implications and stress the importance of safe technology development. It’s not just technologists who require AI training. To ensure all employees understand AI’s risks and benefits, government leaders are prioritizing education and upskilling efforts. Steven Brand, Energy Deputy CIO of Resource Management, highlighted the initiative to provide foundational AI training across his department, emphasizing that the goal is not to make employees experts. Tammy Hornsby-Fink, Executive Vice President and System CISO at the Federal Reserve Bank of Richmond, emphasized the need for accessible learning opportunities for all department members, from data scientists to executive assistants, to grasp AI concepts in manageable increments. Hornsby-Fink also emphasized the importance of providing sandboxes for employees to experiment with new technologies safely, stressing that experimentation is key to understanding how these technologies can create business value. According to Tony Boese, Department of Veterans Affairs Interagency Programs Manager, consistent education is essential to combat misinformation about AI. He mentioned the agency’s ASPIRE data-literacy program, which leverages AI to identify skills gaps and tailor educational pathways for individuals. Karen Howard, IRS Office of Online Services Executive Director, highlighted the need to modernize recruitment strategies and change management principles to attract top talent and leverage digital transformation and AI effectively. Jamie Holcombe, U.S. Patent and Trademark Office CIO, emphasized the importance of diversifying agency workforces by bringing in new perspectives from industry, such as those from Silicon Valley, to move away from outdated organizational playbooks. Gov Agencies AI Workforce Challenges 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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Learning AI

The New Age of Compliance with AI

How can small businesses ensure compliance? Business in the New Age of Compliance with AI can be challenging. While larger corporations often allocate resources for extensive research and development to maintain compliance, smaller businesses may lack the means to conduct thorough due diligence. In such cases, it becomes crucial for them to pose the right questions to vendors and technology partners within their ecosystem. Even as Salesforce takes strides in creating trustworthy generative AI solutions for its customers, these customers also engage with other vendors and processors. It is imperative for them to remain vigilant about potential risks and not rely solely on trust. Salesforce and Tectonic suggest that smaller companies should inquire about: For smaller companies, depending on the due diligence of third-party service providers becomes essential. Evaluating privacy protocols, security procedures, identification of potential harms, and safeguarding measures are critical aspects that demand close attention. In this New Age of Compliance with AI everyone is responsible. Choosing an AI savvy Salesforce partner like Tectonic protects you and your company. The Einstein Trust Layer is your insurance that you are doing artificial intelligence right. 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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Custom Copilot Actions

Custom Copilot Actions

How to Create a Custom Copilot Action Custom Copilot Actions allow you to extend Copilot’s functionality within Salesforce, enabling users to perform tasks specific to your business needs. By utilizing invocable Apex classes, autolaunched flows, and prompt templates, you can build custom actions tailored to your organization’s requirements. Extend your unified copilot with custom actions. Before You Begin: Steps to Create a Custom Copilot Action: Testing and Deployment: Understanding Einstein Copilot Einstein Copilot is Salesforce’s AI assistant designed to enhance productivity and user experience across various applications and departments. Admins can configure and deploy Copilots to empower users with AI capabilities, streamlining workflows and increasing efficiency. Out-of-the-Box Actions: In the Spring ’24 release, Einstein Copilot offers several out-of-the-box actions, including: Customization and Future Development: Admins can create custom actions to tailor Copilot’s capabilities to their organization’s specific requirements. Custom actions enable tasks such as updating records and integrating with external systems, enhancing productivity and efficiency. When you create a custom action, you build it on top of platform functionality you want to make available in Einstein Copilot, such as invocable Apex classes, autolaunched flows, or prompt templates. Adding custom actions lets you customize your copilot and get more mileage out of your current Salesforce platform capabilities. Access to a custom copilot action depends on the type of Salesforce action it references. For example, if a custom action was built using a flow, the custom action adheres to the permissions, field-level security, and sharing settings configured in the flow. Use Cases and Considerations: Typical Use Cases: Considerations: Building Custom Copilot Actions: Power of Custom Actions: Custom actions extend Copilot’s capabilities, offering a wide range of use cases and functionalities. Actions can be built using flows, prompts, or Apex, providing flexibility and customization options. Descriptive Instructions: Accurate descriptions of actions, inputs, and outputs are essential for Copilot’s understanding and execution. Clear instructions provide context and improve response accuracy. Best Practices: Einstein Copilot, coupled with custom actions, empowers organizations to optimize workflows and drive efficiency. By following best practices and leveraging the full potential of Copilot, Salesforce admins can enhance user experiences and unlock new levels of productivity. Explore these features within your organization to realize the benefits of Salesforce Einstein Copilot Custom Actions. Assign an action to your copilot from the Copilot Actions page, the record page for an action, or the Copilot Action Library tab of the actions panel in the Copilot Builder. Your copilot must be deactivated. To test your action and preview how the output appears in a copilot conversation, open the copilot in the Copilot Builder and start a preview conversation. Enter utterances that you expect to trigger your action, and then make adjustments to the copilot action instructions based on your results. What powers Einstein Copilot custom actions? By facilitating the flow of work through smart, AI-driven actions, Einstein Copilot enhances efficiency and decision-making. Here’s how organizations can harness its power through the design of custom actions, ensuring their operations are as streamlined and effective as possible. 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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