Triforcia

Last February, Salesforce introduced Einstein Copilot, a conversational AI assistant for the enterprise. Natively embedded across Salesforce applications, Einstein Copilot is grounded in a company’s unique data and metadata, enabling it to answer questions, generate content, and dynamically automate actions — all in the service of providing better productivity, deeper customer relationships, and higher margins. Einstein Copilot includes a library of actions, which is a set of jobs the copilot can do. For example, if a user asks a copilot for help with writing an email, the copilot launches an action that drafts and revises the email and grounds it in relevant Salesforce data. For more complex processes, Einstein Copilot could orchestrate numerous actions to autonomously complete a task. For example, if a customer has a problem with a product, they could start a conversation with an Einstein Service Agent that would be able to look at their purchase history and, using a company’s own knowledge articles, automatically suggest a few troubleshooting techniques. If that doesn’t work, it could ask the customer to upload a picture of the error code they’re seeing, analyze the problem, then determine if the item needs to be exchanged. The agent could proactively suggest replacements or upsell the customer to another model, offer a discount for the inconvenience, and connect the customer to a store near them to pick up the item.

Count on them automating routine and complex tasks, such as personalized service, support, recommendations, and resolutions for customers based on detailed analyses of their purchase histories, preferences, and questions or concerns. Look forward to them sifting through company historical records and public information to find and line up top sales prospects in a region, and then crafting talking points the rep can use when getting in a room with the customer. And, expect them to recognize significant market opportunities and come up with creative marketing campaigns for reaching specific demographics at particular points in time. All without human intervention and executing tasks in milliseconds. The possibilities for these fully autonomous AI agents — an advanced form of generative AI that can continuously improve their own performance through self-learning — are really endless. But, before humans start handing over important tasks to these technological marvels, organizations will need to get their employees ready. That’s because, as with any new hire, autonomous AI agents won’t be immediately accepted. They’ll have to prove themselves before being allowed to handle truly important jobs. Moreover, they’ll need to gain the trust of human beings who haven’t worked with the technology.

1. Human involvement is needed to build trust in AI. 63% of global workers say more human involvement would build their trust in AI. 2. Concerns about AI may come from a lack of understanding. Fifty-four percent of global workers say they do not know how AI is implemented or governed in their workplace. Workers who are knowledgeable about how AI is implemented and governed in their workplace are 5x more likely to say they will trust AI to operate autonomously within the next two years than those who are not knowledgeable. 3. Training may be another key to trusted autonomy: 62% of workers say more skill-building and training opportunities would build their trust in AI.

1. Today, 54% of global workers trust humans and AI to do most work tasks together. 2. When asked if these workers trusted AI to do any of these same tasks autonomously, the answer, for a small group, was some. Tasks they felt comfortable with offloading to autonomous AI included: a- Writing code: 15% trust AI to write code autonomously. b- Uncovering data insights: 13% trust AI to uncover data insights on its own. c- Develop communications: 12% trust AI to develop internal and external communications without a human. d- Act as a personal assistant: 12% trust autonomous AI to act as their personal assistant.

Leaders trust AI to do more of their work than employees do — leaders trust AI to do 51% of their work, while rank-and-file workers trust AI to do 40%. 1. Workers today already trust AI to do roughly 43% of their work tasks, indicating a shift among workers to offload tasks to AI. 2. 77% of global workers will eventually trust AI to operate autonomously. This number includes: a- 10% of global workers who trust AI to operate autonomously today. b- 26% of global workers who will trust AI to operate autonomously in less than three years. c- 41% of global workers who will trust AI to operate autonomously in three. or more years.

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Tableau can’t deploy new AI capabilities to every user without the support of IT administrators who govern the system. Tableau announced a scalability update to its Tableau Cloud platform with Hyperforce, Salesforce’s modern, trusted cloud infrastructure, that allows Tableau to develop faster and meet customer data residency requirements. In addition, Tableau has new licensing and support options with Tableau+, a new premium bundle, and Success Plans, an updated support model. Hyperforce improves the availability and agility of Tableau Cloud by allowing growth into new regions and data centers faster. Tableau Cloud, Tableau’s leading software-as-a-service platform for analytics, is increasingly used in large and complex enterprise implementations as customers deploy Tableau’s AI-driven analytics capabilities to every user. Tableau is accelerating the growth of this platform with Hyperforce. This helps customers whose data must be hosted in their country. It also provides an easier pathway to additional compliance certifications like FedRAMP. Tableau+ provides a simpler buying option for customers who want the ability to provide analytics to everyone in their organization. It includes premium capabilities for large and complex environments: 1.Data Cloud Everywhere – 250,000 credits of Salesforce Data Cloud to improve the experience of working with CRM data. 2. Premier Success Plan – elevated coverage to ensure the customer receives prioritized customer support. 3. Tableau Cloud Manager – providing a single management console for up to 50 sites. 4. Einstein Copilot for Tableau All capabilities of Tableau Enterprise, including Data Management, Advanced Management, extra storage on Tableau Cloud, and eLearning.

As AI makes the experience of working with data more approachable, Tableau is seeing its impact expand from analysts to knowledge workers in lines of business. Tableau Pulse, launched in February, brings data to the masses with personalized, automated insights powered by AI. Tableau is announced new capabilities for Pulse and Einstein Copilot for Tableau, an AI assistant that allows novice analysts to explore and base more decisions on data. AI-assisted data transformation, which can automate a data transformation pipeline with step-by-step suggestions that an analyst can employ with a single click. For example, the user could enter a prompt like “Look through this product’s reviews and help me determine which ones are the most positive.” Einstein Copilot for Tableau will then guide the user through the steps needed to prepare the data for analysis. Using Einstein Copilot for Tableau Catalog, people can automatically generate descriptions of data to make their data sources easier to find and explore. For example, someone working in hospitality can click “Draft with Einstein” for data about travel, and receive a detailed description of the data, using the data source’s metadata and field names to help other analysts easily reference these insights. Tableau Pulse automatically identifies and delivers insights based on a user’s personalized set of KPIs. Users receive these findings in email, chat, and on mobile devices, with the ability to interact, explore, and filter their insights.

Tableau’s analyst fanbase flocks to the annual conference to hear about the latest innovations in the application that they love. Over a dozen new features will be showcased in “Devs on Stage,” where Tableau Developers demo new innovations in a live keynote presentation. 1. Viz Extensions – Tableau’s passionate base of analytics aficionados constantly stretches the boundaries of the application to draw complex diagrams like Sankey Charts and Network Diagrams. Viz Extensions expand the visual libraries Tableau can use to create these graphics faster: a new Sankey extension allows an analyst to build the chart in three clicks, avoiding the complex data preparation or calculations required without Viz Extensions. Viz Extensions are also exposed as an open API that anyone can use to build their own visualization templates. 2. Shared Dimensions and Composable Data Sources – Another frequent challenge for analysts is working with complex data. Data coming from different sources with differing levels of detail can force analysts to spend more time preparing and modeling data than actually generating insights. Shared Dimensions allow analysts to create more complex data models, including those with multiple fact tables. Composable Data Sources expand the capability further, allowing analysts to supplement centrally defined data sources with their own additions without changing the underlying model. Using these capabilities, an analyst or data curator can create a single underlying model that can source dozens or hundreds of data visualizations. 3. Tableau Desktop Public Edition – Tableau is investing in building the next generation of data analysts. Already known for its academic programs, which have enabled 3.2 million students and teachers with free software and learning resources since 2011, Tableau is now expanding its free offering with Tableau Public. Tableau Public is a free platform to explore, create, and publicly share data visualizations online with over 9.5 million published workbooks, where analysts go to hone their skills and express their passion for data.

For years, Tableau has been known for its simple mission statement: Salesorce Helps People See and Understand Data. Today, only 30% of workers say they use data to make business decisions. To help every worker tap into data that helps their businesses grow, analytics must be more approachable and more automated, so workers can follow data-driven recommendations. Tableau sees AI as an opportunity to lower the barrier for entry: according to a 2024 report by Forrester Research, 59% of data and analytics decision makers whose organizations are using AI technologies report significant cost savings from using AI in operations, and 47% say they have AI-based data products that are generating revenue. Tableau’s latest announcements include analytical enhancements that improve usability for data analysts, AI that unlocks data for more people, and scalability improvements that ease IT administration and governance tasks in a comprehensive update to the platform.