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Winter 25 Release Notes

Winter 25 Release Notes

The Winter ’25 release is available through the pre-release program. On August 30, 2024, Sandboxes will be upgraded, providing your organization with the Winter ’25 release experience. Set Up Your Pay Now Store Quickly and Easily Use the streamlined automated setup to get your Pay Now store up and running effortlessly. The guided process walks you through each step needed to configure your store. This feature is available in Salesforce Payments for Enterprise, Unlimited, and Developer editions. How to Set Up: Gain Insight into How User Permissions Are Granted Simplify user management with visibility into the profiles, permission sets, and permission set groups that grant permissions to a user. The User Access Summary now provides detailed information about a user’s assigned object, field, user, and custom permissions. Previously, identifying the source of a user’s permissions required multiple steps, but now you can access this information with just a few clicks. This change applies to Lightning Experience in all editions. How to Use: See How Object Access Is Granted in Object Manager Quickly view the permission sets, permission set groups, and profiles that grant access to an object, along with the level of access provided. The read-only Object Access Summary in Object Manager allows for quick checks during troubleshooting, reviews, or when deciding how to grant user access. This update is available in Lightning Experience across all editions. How to Access: Improve Performance for List Views on Custom and Standard Objects To enhance performance and meet the latest accessibility standards, list views for both custom and standard objects now render using Lightning Web Components (LWC) instead of Aura. LWC, Salesforce’s latest framework, delivers data faster and enables new features for list views. Previously, only custom object list views in sandboxes used LWC. This update applies to Lightning Experience in all editions. How to Use: Configure Record Highlights in Lightning App Builder Enhance your Lightning pages with the new Dynamic Highlights Panel, which lets you configure important fields directly within the Lightning App Builder. Previously, this was only possible through compact layouts in Setup. The Dynamic Highlights Panel can hold up to 12 fields and adjusts responsively to browser size. This feature is available in Group, Professional, Enterprise, Performance, Unlimited, and Developer editions. How to Implement: Make Record Fields Stand Out with Conditional Formatting Highlight key information on record pages using conditional formatting in Lightning App Builder. On Dynamic Forms-enabled pages, you can assign custom icons and colors to fields based on defined criteria, such as field values or other conditions on the page. This feature is available on a rolling basis starting in early September 2024 for Group, Professional, Enterprise, Performance, Unlimited, and Developer editions. How to Use: Save Time with New Messaging Components for Enhanced Bots (Generally Available) Empower customers and save service agents’ time with the new messaging components for enhanced bots. These include authentication, custom, form, and payment messaging components, which can handle more complex use cases on enhanced Apple Messages for Business channels. The form component is also available for Messaging for In-App and Web. These updates apply to Lightning Experience and Salesforce Classic in Enterprise, Performance, Unlimited, and Developer editions, with bot setup available only in Lightning Experience. How to Implement: Enhance Your LWR Site Experience by Curating Data Providers on a Page (Beta) Enhance LWR site pages by adding and configuring data providers in Experience Builder. This feature allows you to access data from different sources, such as Apex or Record data providers, directly within your site page and its components. This change is available in Professional, Enterprise, Unlimited, and Developer editions for LWR sites accessed through Lightning Experience. A community license is required to use this feature. How to Use: To configure data providers on an LWR Site page in Experience Builder: Enabling or Disabling Modernized Record Experience in Aura Sites You can now use upgraded record components based on Lightning web component technology to see stylistic changes in your Aura sites. These updates, previously limited to sandbox environments, are now available in production environments for the Create Record Form, Record Banner, and Record Detail components. This update is applicable to Aura sites accessed through Lightning Experience and Salesforce Classic in Enterprise, Performance, Unlimited, and Developer editions. When you enable the Use Lightning web components on your record pages in Aura sites setting, the Create Record Form, Record Banner, and Record Detail components display minor style changes. Some key updates include: Daily Summary of Service Appointments Requiring Immediate Attention Boost dispatcher productivity by using Einstein Copilot Field Service actions to get a daily summary of service appointments needing immediate attention, such as those with rule violations, overlaps, SLA risks, or emergencies. Each category in the summary is converted into a filter in the appointment list for quick resolution. Customize the summary to include additional categories. This feature is available in Lightning Experience in the Einstein 1 Field Service Edition with the Field Service Managed Package installed. To use this feature: Assigning Opportunity Splits to Territories Sales teams can now assign opportunity splits and opportunity product splits to territories, enabling them to report on how territories contribute to overall sales. Previously, splits could only be associated with the parent opportunity’s territory. Now, teams can also forecast based on split amounts across territories. This update applies to Lightning Experience in Enterprise, Performance, Unlimited, and Developer editions. To enable this feature: Strategic Planning with Account Plan Enhance your strategic planning with Account Plans by nurturing existing relationships and growing key accounts. Use Account Plans to research and analyze accounts, set objectives with actionable metrics, and monitor growth and development from a single repository within Salesforce. This feature applies to Lightning Experience in Enterprise, Performance, and Unlimited editions and in Einstein 1 Sales Edition. This feature will be rolled out to production environments after the Winter ’25 release and will be available to all customers by October 29, 2024. It is accessible in sandboxes only after its production release. To use Account Plans: Forecast Submissions Forecast submissions

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Generative AI Overview

Generative AI Overview

Editor’s Note: AI Cloud, Einstein GPT, and other cloud GPT products are now Einstein. For the latest on Salesforce Einstein The Rise of Generative AI: What It Means for Business and CRM Generative artificial intelligence (AI) made headlines in late 2022, sparking widespread curiosity and questions about its potential impact on various industries. What is Generative AI? Generative AI is a technology that creates new content—such as poetry, emails, images, or music—based on a set of input data. Unlike traditional AI, which focuses on classifying or predicting, generative AI can produce novel content with a human-like understanding of language, as noted by Salesforce Chief Scientist Silvio Savarese. However, successful generative AI depends on the quality of the input data. “AI is only as good as the data you give it, and you must ensure that datasets are representative,” emphasizes Paula Goldman, Salesforce’s Chief Ethical and Humane Use Officer. How Does Generative AI Work? Generative AI can be developed using several deep learning approaches, including: Other methods include Variational Autoencoders (VAEs) and Neural Radiance Fields (NeRFs), which generate new data or create 2D and 3D images based on sample data. Generative AI and Business Generative AI has captured the attention of global business leaders. A recent Salesforce survey found that 67% of IT leaders are focusing on generative AI in the next 18 months, with 33% considering it a top priority. Salesforce has long been exploring generative AI applications. For instance, CodeGen helps transform simple English prompts into executable code, and LAVIS makes language-vision AI accessible to researchers. More recently, Salesforce’s ProGen project demonstrated the creation of novel proteins using AI, potentially advancing medicine and treatment development. Ketan Karkhanis, Salesforce’s Executive VP and GM of Sales Cloud, highlights that generative AI benefits not just large enterprises but also small and medium-sized businesses (SMBs) by automating proposals, customer communications, and predictive sales modeling. Challenges and Ethical Considerations Despite its potential, generative AI poses risks, as noted by Paula Goldman and Kathy Baxter of Salesforce’s Ethical AI practice. They stress the importance of responsible innovation to ensure that generative AI is used safely and ethically. Accuracy in AI recommendations is crucial, and the authoritative tone of models like ChatGPT can sometimes lead to misleading results. Salesforce is committed to building trusted AI with embedded guardrails to prevent misuse. As generative AI evolves, it’s vital to balance its capabilities with ethical considerations, including its environmental impact. Generative AI can increase IT energy use, which 71% of IT leaders acknowledge. Generative AI at Salesforce Salesforce has integrated AI into its platform for years, with Einstein AI providing billions of daily predictions to enhance sales, service, and customer understanding. The recent launch of Einstein GPT, the world’s first generative AI for CRM, aims to transform how businesses interact with customers by automating content creation across various functions. Salesforce Ventures is also expanding its Generative AI Fund to $500 million, supporting AI startups and fostering responsible AI development. This expansion includes investments in companies like Anthropic and Cohere. As Salesforce continues to lead in AI innovation, the focus remains on creating technology that is inclusive, responsible, and sustainable, paving the way for the future of CRM and business. The Future of Business: AI-Powered Leadership and Decision-Making Tomorrow’s business landscape will be transformed by specialized, autonomous AI agents that will significantly change how companies are run. Future leaders will depend on these AI agents to support and enhance their teams, with AI chiefs of staff overseeing these agents and harnessing their capabilities. New AI-powered tools will bring businesses closer to their customers and enable faster, more informed decision-making. This shift is not just a trend—it’s backed by significant evidence. The Slack Workforce Index reveals a sevenfold increase in leaders seeking to integrate AI tools since September 2023. Additionally, Salesforce research shows that nearly 80% of global workers are open to an AI-driven future. While the pace of these changes may vary, it is clear that the future of work will look vastly different from today. According to the Slack Workforce Index, the number of leaders looking to integrate AI tools into their business has skyrocketed 7x since September 2023. Mick Costigan, VP, Salesforce Futures In the [still] early phases of a major technology shift, we tend to over-focus on the application of technology innovations to existing workflows. Such advances are important, but closing the imagination gap about the possible new shapes of work requires us to consider more than just technology. It requires us to think about people, both as the customers who react to new offerings and as the employees who are responsible for delivering them. Some will eagerly adopt new technology. Others will resist and drag their feet. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI Assisting Nursing

AI Assisting Nursing

Leveraging AI to Alleviate the Documentation Burden in Nursing As the nursing profession grapples with increasing burnout, researchers are investigating the potential of large language models to streamline clinical documentation and care planning. Nurses play an essential role in delivering high-quality care and improving patient outcomes, but the profession is under significant strain due to shortages and burnout. AI Assisting Nursing could lessoning burnout while improving communication. What role could Salesforce play? The American Nurses Association (ANA) emphasizes that to maximize nurses’ potential, healthcare organizations must prioritize maintaining an adequate workforce, fostering healthy work environments, and supporting policies that back nurses. The COVID-19 pandemic has exacerbated existing challenges, including increased healthcare demand, insufficient workforce support, and a wave of retirements outpacing the influx of new nurses. Tectonic has nearly two decades of experience providing IT solutions for the health care industry. Salesforce, as a leader in the field of artificial intelligence, is a top tool for health care IT. AI Assisting Nursing In response to these growing demands, some experts argue that AI technologies could help alleviate some of the burden, particularly in areaTes like clinical documentation and administrative tasks. In a recent study published in the Journal of the American Medical Informatics Association, Dr. Fabiana Dos Santos, a post-doctoral research scientist at Columbia University School of Nursing, led a team to explore how a ChatGPT-based framework could assist in generating care plan suggestions for a lung cancer patient. In an interview with Healthtech Analytics, Dr. Santos discussed the potential and challenges of using AI chatbots in nursing. Challenges in Nursing Care Plan Documentation Creating care plans is vital for ensuring patients receive timely, adequate care tailored to their needs. Nurses are central to this process, yet they face significant obstacles when documenting care plans. AI Assisting Nursing and Salesforce as a customer relationship solution addresses those challenges. “Nurses are on the front line of care and spend a considerable amount of time interacting closely with patients, contributing valuable clinical assessments to electronic health records (EHRs),” Dr. Santos explained. “However, many documentation systems are cumbersome, leading to a documentation burden where nurses spend much of their workday interacting with EHRs. This can result in cognitive burden, stress, frustration, and disruptions to direct patient care.” The American Association of Critical-Care Nurses (AACN) highlights that electronic documentation is a significant burden, consuming an average of 40% of a nurse’s shift. Time spent on documentation inversely correlates with time spent on patient care, leading to increased burnout, cognitive load, and decreased job satisfaction. These factors, in turn, contribute to patient-related issues such as a higher risk of medical errors and hospital-acquired infections, which lower patient satisfaction. When combined with the heavy workloads nurses already manage, inefficient documentation tools can make care planning even more challenging. AI Assisting Nursing and Care Plans “The demands of direct patient care and managing multiple administrative tasks simultaneously limit nurses’ time to develop individualized care plans,” Dr. Santos continued. “The non-user-friendly interfaces of many EHR systems exacerbate this challenge, making it difficult to capture all aspects of a patient’s condition, including physical, psychological, social, cultural, and spiritual dimensions.” To address these challenges, Dr. Santos and her team explored the potential of ChatGPT to improve clinical documentation. “These negative impacts on a nurse’s workday underscore the urgency of improving EHR documentation systems to reduce these issues,” she noted. “AI tools, if well designed, can improve the process of developing individualized care plans and reduce the burden of EHR-related documentation.” The Promises and Pitfalls of AI Developing care plans requires nurses to draw from their expertise to address issues like symptom management and comfort care, especially for patients with complex needs. Dr. Santos emphasized that advanced technologies, such as generative AI (GenAI), could streamline this process by enhancing documentation workflows and assisting with administrative tasks. AI tools can rapidly process large amounts of data and generate care plans more quickly than traditional methods, potentially allowing nurses to spend more time on direct and holistic patient care. However, Dr. Santos stressed the importance of carefully validating AI models, ensuring that nurses’ clinical judgment and expertise play a central role in evaluating AI-generated care plans. “New technologies can help nurses improve documentation, leading to better descriptions of patient conditions, more accurate capture of care processes, and ultimately, improved patient outcomes,” she said. “This presents an important opportunity to use novel generative AI solutions to reduce nurses’ workload and act as a supportive documentation tool.” Despite the promise of AI as a support tool, Dr. Santos cautioned that chatbots require further development to be effectively implemented in nursing care plans. AI-generated outputs can contain inaccuracies or irrelevant information, necessitating careful review and validation by nurses. Additionally, AI tools may lack the nuanced understanding of a patient’s unique needs, which only a nurse can provide through personal, empathetic interactions, such as interpreting specific cultural or spiritual needs. Despite these challenges, large language models (LLMs) and other GenAI tools are generating significant interest in the healthcare industry. They are expected to be deployed in various applications, including EHR workflows and nursing efficiency. Dr. Santos’ research contributes to this growing field. To conduct the study, the researchers developed and validated a method for structuring ChatGPT prompts—guidelines that the LLM uses to generate responses—that could produce high-quality nursing care plans. The approach involved providing detailed patient information and specific questions to consider when creating an appropriate care plan. The research team refined the Patient’s Needs Framework over ten rounds using 22 diverse hypothetical patient cases, ensuring that the ChatGPT-generated plans were consistent and aligned with typical nursing care plans. “Our findings revealed that ChatGPT could prioritize critical aspects of care, such as oxygenation, infection prevention, fall risk, and emotional support, while also providing thorough explanations for each suggested intervention, making it a valuable tool for nurses,” Dr. Santos indicated. The Future of AI in Nursing While the study focused on care plans for lung cancer, Dr. Santos emphasized that this research is just the beginning of

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Deepfake Detection With New Tool

Deepfake Detection With New Tool

Pindrop Expands Deepfake Detection with New Tool On Thursday, voice authentication vendor Pindrop expanded its deepfake detection capabilities with the preview release of Pindrop Pulse Inspect, a tool designed to detect AI-generated speech in digital audio files. This new tool builds on Pindrop’s earlier launch of Pindrop Pulse at the start of the year. While Pindrop Pulse initially targeted call centers, Pulse Inspect broadens its reach, catering to media organizations, nonprofits, government agencies, and social networks. Pindrop Pulse is already integrated with the company’s fraud protection and authentication platform. The new Pulse Inspect tool allows users to upload audio files to the Pindrop platform to determine if they contain synthetic speech, providing deepfake scores in the process. The introduction of Pulse Inspect is timely, coinciding with heightened concerns over deepfakes as the U.S. general election in November approaches. In recent months, Pindrop has tested its technology on high-profile cases. The company analyzed a deepfake audio clip of presidential candidate Kamala Harris, posted on X by Elon Musk, and discovered partial deepfakes in the audio. Pindrop also examined a deepfake of Elon Musk, released on July 24, identifying voice cloning technology from vendor ElevenLabs as the source. Additionally, Pindrop detected a fake robocall, generated using ElevenLabs’ technology, impersonating President Joe Biden before the January Democratic presidential primary. ElevenLabs has publicly stated its commitment to preventing the misuse of audio AI tools. “The human ear can no longer reliably distinguish between real and synthetically generated audio,” said Rahul Sood, Pindrop’s Chief Product Officer, during a discussion on the risks deepfakes pose for the upcoming election. “It’s almost impossible to have a high level of confidence without assistance.” Fighting AI with AI Analysts emphasize the necessity of tools like Pulse Inspect in the age of generative AI. “They’re fighting AI with AI,” said Lisa Martin, an analyst at the Futurum Group, highlighting the importance of Pindrop’s technology. According to Pindrop, their detection technology is trained on over 350 deepfake generation tools, 20 million unique utterances, and more than 40 languages. “We know how powerful generative AI is—it can be used for good, but it can also be weaponized, as we’re seeing,” Martin noted. She added that with the increasing ease of creating deepfakes, the demand for detection tools like Pulse Inspect will only grow. As deepfakes continue to proliferate, companies like Pindrop and competitors such as Resemble AI are racing to develop these detection solutions. With Pulse Inspect, Pindrop is extending its technology’s application beyond call centers. Pindrop has also partnered with Respeecher, a voice cloning vendor that collaborates with Hollywood. “Respeecher is working with Pindrop to ensure their synthetic voice technology for Hollywood is not misused,” said Martin, stressing the importance of ethical development and use of AI voice cloning technology. Pulse Inspect is positioned to assist media companies, social media networks, nonprofits, and government organizations in navigating the challenges of AI-generated audio. The Challenge of Scaling Deepfake Detection While Pindrop is well-equipped to detect deepfakes, scaling this technology could be costly and complex, according to Forrester Research analyst Mo Allibhai. “Implementing this technology at scale is expensive, even from an integration standpoint,” said Allibhai. “We need to be selective in how we deploy it.” Allibhai suggested that edge AI, such as Apple’s upcoming generative AI system for iPhones, could ease these challenges by reducing the reliance on cloud computing, making solutions like Pulse Inspect more viable in the long term. Pindrop Pulse Inspect offers an API-driven batch-processing platform and user interface, designed to meet the evolving needs of organizations facing the growing threat of deepfake audio. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Copilots in the Workplace

Copilots in the Workplace

The Rise of AI-Powered Copilots in the Workplace: The New Age of Office Helpers As more businesses embrace AI tools, the tech world is buzzing with a new kind of office assistant: the AI-powered copilot. These digital sidekicks are here to revolutionize how we interact with information—think of them as the high-tech, caffeine-free version of your office buddy who always knows where the stapler is. Copilots in the Workplace are here. AI-powered copilots use large language models (LLMs) to help users wade through vast amounts of data, often with the grace of a caffeinated librarian. By facilitating conversations instead of requiring precise queries, these tools let you ask for help without needing to channel your inner tech wizard. Hugo Sarrazin, Chief Product and Technology Officer at UKG, points out that many of these AI copilots are essentially “search functions dressed up in a snazzy new outfit.” UKG’s own digital assistant, UKG Bryte, made its debut last November—just in time to help you find out why your vacation request hasn’t been approved yet. These AI assistants offer an enhanced chatbot experience by understanding a wide range of queries through generative AI. Imagine asking your chatbot, “Hey, what’s the deadline for open enrollment?” and getting a response that doesn’t involve translating your question into a techie dialect. “Generative AI isn’t stuck on keywords and rigid queries. It’s like a magic eight ball with a PhD,” Sarrazin explains. Traditional systems often force users through pre-set menus and workflows—kind of like a bureaucratic maze—but copilots let you skip the detours and get straight to the point. With AI copilots, you can ask in plain language and receive useful answers without needing to consult a human. Picture this: an HR chatbot that knows exactly what the per diem is for your conference, or which days you’re free for the next company holiday—like having a personal assistant who never needs a coffee break. Salesforce employees, for instance, are getting a taste of this futuristic help with their Einstein copilot. Since the introduction of Einstein, Salesforce has seen an uptick in productivity and a drop in mundane tasks. Nathalie Scardino, Salesforce’s Chief People Officer, says the company has been working to seamlessly integrate AI tools into daily workflows—because nothing says “we care” like a virtual assistant who understands your workload better than you do. After Salesforce acquired Slack in 2020, the Einstein-powered Slack app launched in February. This tool helps with scheduling, document summarization, and general inquiries, effectively turning your to-do list into a “done” list. Research showed that desk workers spend 41% of their time on tasks that aren’t exactly rocket science, and Einstein is here to tackle those chores. Scardino and Salesforce’s CIO, Juan Perez, have been busy ensuring that AI tools fit perfectly into the company’s workflow. Einstein is also making waves in HR by integrating with Basecamp, Salesforce’s hub for employee info. This integration has answered over 88,000 queries and cut resolution times from two days to just 30 minutes—making it the office hero you didn’t know you needed. “The big win here is bringing all those disparate systems together and making information accessible without needing a PhD,” Scardino quips. “No more hopping between six systems just to find out about your healthcare benefits.” In this brave new world of AI-assisted work, copilots like Einstein are proving that getting the right information quickly is no longer a sci-fi dream. They’re here to make our office lives smoother, smarter, and a little less dependent on those old-fashioned human helpers. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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GitHub Copilot Autofix

GitHub Copilot Autofix

On Wednesday, GitHub announced the general availability of Copilot Autofix, an AI-driven tool designed to identify and remediate software vulnerabilities. Originally unveiled in March and tested in public beta, Copilot Autofix integrates GitHub’s CodeQL scanning engine with GPT-4, heuristics, and Copilot APIs to generate code suggestions for developers. The tool provides prompts based on CodeQL analysis and code snippets, allowing users to accept, edit, or reject the suggestions. In a blog post, Mike Hanley, GitHub’s Chief Security Officer and Senior Vice President of Engineering, highlighted the challenges developers and security teams face in addressing existing vulnerabilities. “Code scanning tools can find vulnerabilities, but the real issue is remediation, which requires security expertise and time—both of which are in short supply,” Hanley noted. “The problem isn’t finding vulnerabilities; it’s fixing them.” According to GitHub, the private beta of Copilot Autofix showed that users could respond to a CodeQL alert and automatically remediate a vulnerability in a pull request in just 28 minutes on average, compared to 90 minutes for manual remediation. The tool was even faster for common vulnerabilities like cross-site scripting, with remediation times averaging 22 minutes compared to three hours manually, and SQL injection flaws, which were fixed in 18 minutes on average versus almost four hours manually. Hanley likened the efficiency of Copilot Autofix in fixing vulnerabilities to the speed at which GitHub Copilot, their generative AI coding assistant released in 2022, produces code for developers. However, there have been concerns that GitHub Copilot and similar AI coding assistants could replicate existing vulnerabilities in the codebases they help generate. Industry analyst Katie Norton from IDC noted that while the replication of vulnerabilities is concerning, the rapid pace at which AI coding assistants generate new software could pose a more significant security issue. Chris Wysopal, CTO and co-founder of Veracode, echoed this concern, pointing out that faster coding speeds have led to more software being produced and a larger backlog of vulnerabilities for developers to manage. Norton also emphasized that AI-powered tools like Copilot Autofix could help alleviate the burden on developers by reducing these backlogs and enabling them to fix vulnerabilities without needing to be security experts. Other vendors, including Mobb and Snyk, have also developed AI-powered autoremediation tools. Initially supporting JavaScript, TypeScript, Java, and Python during its public beta, Copilot Autofix now also supports C#, C/C++, Go, Kotlin, Swift, and Ruby. Hanley also highlighted that Copilot Autofix would benefit the open-source software community. GitHub has previously provided open-source maintainers with free access to enterprise security tools for code scanning, secret scanning, and dependency management. Starting in September, Copilot Autofix will also be made available for free to these maintainers. “As the global home of the open-source community, GitHub is uniquely positioned to help maintainers detect and remediate vulnerabilities, making open-source software safer and more reliable for everyone,” Hanley said. Copilot Autofix is now available to all GitHub customers globally. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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The Role of Data to Harness AI

The Role of Data to Harness AI

Harnessing AI for Enhanced Sales and Service: The Role of Data Organizations are racing to leverage AI to enhance their sales and service experiences. The Role of Data to Harness AI cannot be underestimated. However, great AI solutions rely on quality data. Traditionally, companies have managed structured data—neatly organized into rows and columns, such as customer engagement data from CRM systems. But businesses also hold a wealth of unstructured data in formats like documents, images, audio, and video recordings. This unstructured data can be highly valuable, offering deeper AI insights that are more accurate and comprehensive, grounded in real customer interactions. Yet, many organizations struggle to effectively access, integrate, and utilize their unstructured data to gain a holistic customer view. With advancements in large language models (LLMs) and generative AI, organizations can now bridge this gap. To succeed in the AI era, companies need to develop integrated, federated, intelligent, and actionable solutions across all customer touchpoints while managing complexity. Leveraging Unstructured Data for Superior AI Performance For instance, when a customer seeks help with a recent purchase, they typically start with a company’s chatbot. To ensure a relevant and positive experience, the chatbot must be informed by comprehensive customer data, including recent purchases, warranty details, and past interactions. Additionally, the chatbot should draw on broader company data, such as insights from other customers and internal knowledge base articles. This data can be spread across structured databases and unstructured files, like warranty contracts or knowledge articles. Accessing and utilizing both types of data is crucial for a satisfying interaction. The key to accurate AI responses is augmenting LLMs with both real-time structured and unstructured data from within a company’s systems. An effective approach is Retrieval Augmented Generation (RAG), which combines proprietary data with generative AI to enhance contextuality, timeliness, and relevance. Ensuring Relevance Across Scenarios A unified view of customer data—both structured and unstructured—provides the most relevant information for any situation. For example, financial institutions can leverage this comprehensive data to offer real-time market insights tailored to individual banking needs, providing actionable advice based on current information. Companies are increasingly exploring RAG technology to improve internal processes and deliver precise, up-to-date information to employees. This approach enhances contextual assistance, personalized support, and decision-making efficiency across the organization. The Role of Data to Harness AI Preparing Data for AI: Key Steps By addressing these areas, organizations can harness the full potential of AI, transforming customer interactions and enhancing service efficiency. Talk to Tectonic today if your data is ina disarray. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Qwary Salesforce Integration

Qwary Salesforce Integration

Qwary Enhances Customer Insights with New Salesforce Integration HERNDON, Va., Aug. 13, 2024 /PRNewswire/ — While surveys have long been a staple for gathering customer feedback, data entry often poses a challenge in obtaining comprehensive insights. Qwary’s new Salesforce integration aims to resolve this issue by enabling seamless data transfer and synchronization between the two platforms. This integration allows teams to consolidate customer information into a single hub, providing real-time visibility and enhancing strategic planning and collaboration. Key features include creating email campaigns, importing contacts, mapping survey results, and automating event-based workflows. What Is Qwary’s Salesforce Integration? Qwary’s Salesforce integration is designed to streamline the analysis of Salesforce survey data, offering a more efficient way to understand customer interactions with your brand. By integrating survey feedback with CRM data, this tool helps you quickly adapt your products and services to meet evolving customer needs. It tracks customer journeys, collects feedback, and reveals pain points, enabling you to deliver tailored solutions. Benefits of Using Qwary’s Salesforce Integration Qwary’s integration offers several notable benefits: Automate Feedback Collection The integration automates the feedback collection process by triggering surveys at strategic points in the customer lifecycle. This allows your team to act swiftly to foster engagement and generate leads. Gain Actionable Insights Seamlessly integrating with Salesforce CRM, Qwary scores, analyzes, and enriches customer data, helping your team identify emerging trends and seize opportunities for personalization and customer development. Synchronize Data Automatically With Qwary’s integration, your contact data is consolidated into a single, reliable source of truth. Whether you’re using Salesforce or Qwary, automated data synchronization ensures consistency and provides real-time updates. Collaborate Effectively The integration promotes effective teamwork by sharing data between Salesforce and Qwary, enabling your team to solve problems collaboratively and refine strategies to boost customer retention. Key Capabilities Qwary’s Salesforce integration excels in managing customer feedback, automating workflows, and consolidating contact data: Salesforce Workflow Automation The integration simplifies scheduling and automating survey triggers, eliminating manual processes. Surveys can be initiated via email or following significant events, with responses seamlessly mapped into Salesforce. This creates a comprehensive view of customer behavior, helping your team act on insights, strengthen connections, and enhance satisfaction. Contact Data Importation Qwary facilitates quick access to Salesforce contacts, providing a holistic view of your customer base. The integration streamlines contact data importation and updates, eliminating manual data entry and speeding up data management. Potential Business Impacts By combining automation, synchronization, and data consolidation with a user-friendly interface, Qwary’s Salesforce integration enhances your sales team’s ability to collect and leverage customer feedback. Immediate access to comprehensive consumer insights allows your business to respond promptly to customer needs, improving satisfaction and loyalty. Real-time data aggregation helps your company adapt quickly and refine offerings to exceed customer expectations. Stay Ahead with Qwary’s Salesforce Integration Qwary continuously updates its solutions to meet the evolving needs of businesses focused on customer engagement. Leveraging automation, synchronization, and advanced analytics through an accessible platform, Qwary’s Salesforce integration empowers your team to enhance offerings and connect with customers efficiently. By optimizing the use of survey data and Salesforce feedback, Qwary keeps your business at the forefront of market trends, enabling you to consistently delight your customers. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Everyone Is Implementing AI

Everyone Is Implementing AI

AI is undoubtedly a generational change in software, with its full trajectory still unpredictable. There is a perceived divide between the “Haves” and “Have Nots.” Companies like OpenAI, Microsoft, and Databricks are seen as understanding AI’s potential, with Nvidia providing the necessary hardware support. Many hot start-ups are Gen AI native, continuing to attract unicorn valuations. Meanwhile, several SaaS leaders appear to be lagging behind. We say, Everyone Is Implementing AI. Marc Benioff stated in their latest quarterly call: “Now, we’re working with thousands of customers to power generative AI use cases with our Einstein Copilot, our prompt builder, our Einstein Studio, all of which went live in the first quarter. And we’ve closed hundreds of copilot deals since this incredible technology has gone GA. And in just the last few months, we’re seeing Einstein Copilot develop higher levels of capability. We are absolutely delighted and cannot be more excited about the success that we’re seeing with our customers with this great new capability.” Everyone Is Implementing AI However, it remains unclear whether simply adding AI to classic B2B SaaS products accelerates growth. Despite significant investments in AI, companies like Salesforce, Asana, and ZoomInfo are growing at less than 10% annually. The main point is that while “AI Washing” might impress some investors, AI must significantly accelerate revenue growth to achieve more than market parity. It is essential to see how AI can add real value and integrate it effectively. But AI alone may not be a growth accelerant. Everyone Is Implementing AI Recent data from Emergence Capital shows that 60% of VC-backed SaaS companies have already released GenAI features, with another 24% planning to do so. Achieving “AI Parity” is crucial, but simply adding GenAI features may not be disruptive in the B2B space. Companies must go further to stand out, despite the 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 The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI Adoption Rates

AI Adoption Rates

Businesses Eager to Embrace AI, Yet Concerned About Trust, Data, and Ethics in AI Adoption Rates As AI adoption rates are projected to surge, only 10% of people currently have full trust in AI for making informed decisions. According to Salesforce’s latest research, nearly half of customer service teams, over 40% of salespeople, and a third of marketers have fully integrated AI to enhance their work. However, 77% of business leaders express concerns about trusted data and ethics that could potentially stall their AI initiatives. The “Trends in AI for CRM” report highlights that companies fear missing out on the benefits of generative AI if the data supporting large language models (LLMs) is not based on their own reliable customer records. Additionally, respondents are worried about the lack of clear company policies governing the ethical use of AI and the complex landscape of LLM vendors, with 80% of companies currently using multiple models. Data Trust Issues Stymie AI Progress Despite expectations for a dramatic increase in AI adoption, only 10% of individuals fully trust AI to make informed decisions. The report reveals that 59% of organizations lack unified data strategies essential for ensuring AI reliability and accuracy. While 80% of employees using AI at work report increased productivity—a key driver for rapid AI adoption—only 21% of surveyed workers said their company has established clear policies on approved AI tools and use cases. Many employees, undeterred by the absence of formal policies, continue to use unapproved (55%) or explicitly banned (40%) tools. Furthermore, 69% of respondents noted that their employers have not provided training on AI usage. Critical Focus Areas: Trust, Data Security, and Transparency The report also underscores that 74% of the general public is concerned about the unethical use of AI. Companies that emphasize end-user control are better positioned to build customer trust in their AI strategies, with 56% of survey respondents expressing openness to AI under these conditions. Key factors for deepening trust in AI include increased visibility into AI use, human validation of outputs, and enhanced user control. “This is a pivotal moment as business leaders across various industries look to AI to drive growth, efficiency, and customer loyalty,” said Clara Shih, CEO of Salesforce AI. “Success with AI requires more than just deploying LLMs. It demands trusted data, user access control, vector search capabilities, audit trails, citations, data masking, low-code builders, and seamless UI integration to truly succeed,” Shih added. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI All Grown Up

Generative AI Tools

One of the most significant use cases for generative AI in business is customer service and support. Most of us have likely experienced the frustration of dealing with traditional automated systems. However, today’s advanced AI, powered by large language models and natural language chatbots, is rapidly improving these interactions. While many still prefer human agents for complex or sensitive issues, AI is proving highly capable of handling routine inquiries efficiently. Here’s an overview of some of the top AI-powered tools for automating customer service. Although the human element will always be essential in customer experience, these tools free up human agents from repetitive tasks, allowing them to focus on more complex challenges requiring empathy and creativity. Cognigy Cognigy is an AI platform designed to automate customer service voice and chat channels. It goes beyond simply reading FAQ responses by delivering personalized, context-sensitive answers in multiple languages. Cognigy’s AI Copilot feature enhances human contact center workers by offering real-time AI assistance during interactions, making both fully automated and human-augmented support possible. IBM WatsonX Assistant IBM’s WatsonX Assistant helps businesses create AI-powered personal assistants to streamline tasks, including customer support. With its drag-and-drop configuration, companies can set up seamless self-service experiences. The platform uses retrieval-augmented generation (RAG) to ensure that responses are accurate and up-to-date, continuously improving as it learns from customer interactions. Salesforce Einstein Service Cloud Einstein Service Cloud, part of the Salesforce platform, automates routine and complex customer service tasks. Its AI-powered Agentforce bots manage “low-touch” interactions, while “high-touch” cases are overseen by human agents supported by AI. Fully customizable, Einstein ensures that responses align with your brand’s tone and voice, all while leveraging enterprise data securely. Zendesk AI Zendesk, a leader in customer support, integrates generative AI to boost its service offerings. By using machine learning and natural language processing, Zendesk understands customer sentiment and intent, generates personalized responses, and automatically routes inquiries to the most suitable agent—be it human or machine. It also provides human agents with real-time guidance on resolving issues efficiently. Ada Ada is a conversational AI platform built for large-scale customer service automation. Its no-code interface allows businesses to create custom bots, reducing the cost of handling inquiries by up to 78% per ticket. By integrating domain-specific data, Ada helps improve both support efficiency and customer experience across omnichannel support environments. More AI Tools for Customer Service There are numerous other AI tools designed to enhance automated customer support: While AI tools are transforming customer service, the key lies in using them to complement human agents, allowing for a balance of efficiency and personalized care. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Small Language Models

Small Language Models

Large language models (LLMs) like OpenAI’s GPT-4 have gained acclaim for their versatility across various tasks, but they come with significant resource demands. In response, the AI industry is shifting focus towards smaller, task-specific models designed to be more efficient. Microsoft, alongside other tech giants, is investing in these smaller models. Science often involves breaking complex systems down into their simplest forms to understand their behavior. This reductionist approach is now being applied to AI, with the goal of creating smaller models tailored for specific functions. Sébastien Bubeck, Microsoft’s VP of generative AI, highlights this trend: “You have this miraculous object, but what exactly was needed for this miracle to happen; what are the basic ingredients that are necessary?” In recent years, the proliferation of LLMs like ChatGPT, Gemini, and Claude has been remarkable. However, smaller language models (SLMs) are gaining traction as a more resource-efficient alternative. Despite their smaller size, SLMs promise substantial benefits to businesses. Microsoft introduced Phi-1 in June last year, a smaller model aimed at aiding Python coding. This was followed by Phi-2 and Phi-3, which, though larger than Phi-1, are still much smaller than leading LLMs. For comparison, Phi-3-medium has 14 billion parameters, while GPT-4 is estimated to have 1.76 trillion parameters—about 125 times more. Microsoft touts the Phi-3 models as “the most capable and cost-effective small language models available.” Microsoft’s shift towards SLMs reflects a belief that the dominance of a few large models will give way to a more diverse ecosystem of smaller, specialized models. For instance, an SLM designed specifically for analyzing consumer behavior might be more effective for targeted advertising than a broad, general-purpose model trained on the entire internet. SLMs excel in their focused training on specific domains. “The whole fine-tuning process … is highly specialized for specific use-cases,” explains Silvio Savarese, Chief Scientist at Salesforce, another company advancing SLMs. To illustrate, using a specialized screwdriver for a home repair project is more practical than a multifunction tool that’s more expensive and less focused. This trend towards SLMs reflects a broader shift in the AI industry from hype to practical application. As Brian Yamada of VLM notes, “As we move into the operationalization phase of this AI era, small will be the new big.” Smaller, specialized models or combinations of models will address specific needs, saving time and resources. Some voices express concern over the dominance of a few large models, with figures like Jack Dorsey advocating for a diverse marketplace of algorithms. Philippe Krakowski of IPG also worries that relying on the same models might stifle creativity. SLMs offer the advantage of lower costs, both in development and operation. Microsoft’s Bubeck emphasizes that SLMs are “several orders of magnitude cheaper” than larger models. Typically, SLMs operate with around three to four billion parameters, making them feasible for deployment on devices like smartphones. However, smaller models come with trade-offs. Fewer parameters mean reduced capabilities. “You have to find the right balance between the intelligence that you need versus the cost,” Bubeck acknowledges. Salesforce’s Savarese views SLMs as a step towards a new form of AI, characterized by “agents” capable of performing specific tasks and executing plans autonomously. This vision of AI agents goes beyond today’s chatbots, which can generate travel itineraries but not take action on your behalf. Salesforce recently introduced a 1 billion-parameter SLM that reportedly outperforms some LLMs on targeted tasks. Salesforce CEO Mark Benioff celebrated this advancement, proclaiming, “On-device agentic AI is here!” 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 Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more

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Chatbots in Healthcare

Chatbots in Healthcare

Not all medical chatbots are created equal, as a recent JAMA Network Open study reveals. The study found that some chatbots are better at tailoring health information to patient health literacy than others. Chatbots in Healthcare may not be ready for prime time. The report compared the free and paid versions of ChatGPT, showing that while the paid version initially provided more readable health information, the difference was minimal once researchers asked the chatbots to explain things at a sixth-grade reading level. The findings suggest that both versions of ChatGPT could potentially widen health disparities in terms of information access and literacy. Chatbots like ChatGPT are becoming increasingly prominent in healthcare, showing potential in improving patient access to health information. However, their quality can vary. The study evaluated the free and paid versions of ChatGPT using the Flesch Reading Ease score for readability and the DISCERN instrument for consumer health information quality. Researchers tested both versions using the five most popular cancer-related queries from 2021 to 2023. They found that while the paid version had slightly higher readability scores (52.6) compared to the free version (62.48) on a 100-point scale, both scores were deemed suboptimal. The study revealed that prompting the free version of ChatGPT to explain concepts at a sixth-grade reading level improved its readability score to 71.55, outperforming the paid version under similar conditions. Even so, when both versions were asked to simplify answers to a sixth-grade reading level, the paid version scored slightly higher at 75.64. Despite these improvements, the overall readability of responses was still problematic. Without the simplification prompt, responses were roughly at a 12th-grade reading level. Even with the prompt, they remained closer to an eighth- or tenth-grade level, possibly due to chatbot confusion about the request. The study raises concerns about health equity. If the paid version of ChatGPT provides more accessible information, individuals with the means to purchase it might have a clear advantage. This disparity could exacerbate existing health inequities, especially for those using the free version. The researchers concluded that until chatbots consistently provide information at a lower reading level, clinicians should guide patients on how to effectively use these tools and encourage them to request information at simpler reading levels. Like Related Posts Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more 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

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Salesforce Enhances Nonprofit Cloud

Salesforce Enhances Nonprofit Cloud

Salesforce Enhances Nonprofit Cloud with AI and Data Tools Salesforce has introduced new artificial intelligence (AI) and data capabilities to its Nonprofit Cloud, aimed at helping organizations boost efficiency, personalize donor engagement, and increase funding. Learn how Salesforce Enhances Nonprofit Cloud. Among the new features are AI tools that generate personalized gift proposals and concise summaries of program success, grant details, donor histories, and more. Additionally, Salesforce announced the launch of Data Cloud for Nonprofits, which unifies and harmonizes data to provide a comprehensive view of donors, volunteers, and program participants. Key new features include: “Every nonprofit strives to deliver the best experience for donors, volunteers, board members, staff, and, most importantly, the people and causes they serve. However, they often face the challenge of doing more with limited resources,” said Lori Freeman, Vice President and Global General Manager of Nonprofit at Salesforce. “With industry-specific AI and data tools, Salesforce empowers nonprofits to enhance productivity by augmenting staff with AI, use data more effectively to build deeper relationships with stakeholders, and ultimately raise the funds needed to fulfill their mission.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Autonomous AI Service Agents

Autonomous AI Service Agents

Salesforce Set to Launch Autonomous AI Service Agents. Considering Tectonic only first wrote about Agentic AI in late June, its like Christmas in July! Salesforce is gearing up to introduce a new generation of customer service chatbots that leverage advanced AI tools to autonomously navigate through various actions and workflows. These bots, termed “autonomous AI agents,” are currently in pilot testing and are expected to be released later this year. Autonomous AI Service Agents Named Einstein Service Agent, these autonomous AI bots aim to utilize generative AI to understand customer intent, trigger workflows, and initiate actions within a user’s Salesforce environment, according to Ryan Nichols, Service Cloud’s chief product officer. By integrating natural language processing, predictive analytics, and generative AI, Einstein Service Agents will identify scenarios and resolve customer inquiries more efficiently. Traditional bots require programming with rules-based logic to handle specific customer service tasks, such as processing returns, issuing refunds, changing passwords, and renewing subscriptions. In contrast, the new autonomous bots, enhanced by generative AI, can better comprehend customer issues (e.g., interpreting “send back” as “return”) and summarize the steps to resolve them. Einstein Service Agent will operate across platforms like WhatsApp, Apple Messages for Business, Facebook Messenger, and SMS text, and will also process text, images, video, and audio that customers provide. Despite the promise of these new bots, their effectiveness is crucial, emphasized Liz Miller, an analyst at Constellation Research. If these bots fail to perform as expected, they risk wasting even more customer time than current technologies and damaging customer relationships. Miller also noted that successful implementation of autonomous AI agents requires human oversight for instances when the bots encounter confusion or errors. Customers, whether in B2C or B2B contexts, are often frustrated with the limitations of rules-based bots and prefer direct human interaction. It is annoying enough to be on the telephone repeating “live person” over and over again. It would be trafic to have to do it online, too. “It’s essential that these bots can handle complex questions,” Miller stated. “Advancements like this are critical, as they can prevent the bot from malfunctioning when faced with unprogrammed scenarios. However, with significant technological advancements like GenAI, it’s important to remember that human language and thought processes are intricate and challenging to map.” Nichols highlighted that the forthcoming Einstein Service Agent will be simpler to set up, as it reduces the need to manually program thousands of potential customer requests into a conversational decision tree. This new technology, which can understand multiple word permutations behind a service request, could potentially lower the need for extensive developer and data scientist involvement for Salesforce users. The pricing details for the autonomous Einstein Service Agent will be announced at its release. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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