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AI Productivity Paradox
20Nov

AI Productivity Paradox

The AI Productivity Paradox: Why Aren’t More Workers Using AI Tooks Like ChatGPT?The Real Barrier Isn’t Technical Skills — It’s Time to Think Despite the transformative potential of tools like ChatGPT, most knowledge workers aren’t utilizing them effectively. Those who do tend to use them for basic tasks like summarization. Less than 5% of ChatGPT’s user base subscribes to the paid Plus version, indicating that a small fraction of potential professional users are tapping into AI for more complex, high-value tasks. Having spent over a decade building AI products at companies such as Google Brain and Shopify Ads, the evolution of AI has been clearly evident. With the advent of ChatGPT, AI has transitioned from being an enhancement for tools like photo organizers to becoming a significant productivity booster for all knowledge workers. Most executives are aware that today’s buzz around AI is more than just hype. They’re eager to make their companies AI-forward, recognizing that it’s now more powerful and user-friendly than ever. Yet, despite this potential and enthusiasm, widespread adoption remains slow. The real issue lies in how organizations approach work itself. Systemic problems are hindering the integration of these tools into the daily workflow. Ultimately, the question executives need to ask isn’t, “How can we use AI to work faster? Or can this feature be built with AI?” but rather, “How can we use AI to create more value? What are the questions we should be asking but aren’t?” Real-world ImpactRecently, large language models (LLMs)—the technology behind tools like ChatGPT—were used to tackle a complex data structuring and analysis task. This task would typically require a cross-functional team of data analysts and content designers, taking a month or more to complete. Here’s what was accomplished in just one day using Google AI Studio: However, the process wasn’t just about pressing a button and letting AI do all the work. It required focused effort, detailed instructions, and multiple iterations. Hours were spent crafting precise prompts, providing feedback, and redirecting the AI when it went off course. In this case, the task was compressed from a month-long process to a single day. While it was mentally exhausting, the result wasn’t just a faster process—it was a fundamentally better and different outcome. The LLMs uncovered nuanced patterns and edge cases within the data that traditional analysis would have missed. The Counterintuitive TruthHere lies the key to understanding the AI productivity paradox: The success in using AI was possible because leadership allowed for a full day dedicated to rethinking data processes with AI as a thought partner. This provided the space for deep, strategic thinking, exploring connections and possibilities that would typically take weeks. However, this quality-focused work is often sacrificed under the pressure to meet deadlines. Ironically, most people don’t have time to figure out how they could save time. This lack of dedicated time for exploration is a luxury many product managers (PMs) can’t afford. Under constant pressure to deliver immediate results, many PMs don’t have even an hour for strategic thinking. For many, the only way to carve out time for this work is by pretending to be sick. This continuous pressure also hinders AI adoption. Developing thorough testing plans or proactively addressing AI-related issues is viewed as a luxury, not a necessity. This creates a counterproductive dynamic: Why use AI to spot issues in documentation if fixing them would delay launch? Why conduct further user research when the direction has already been set from above? Charting a New Course — Investing in PeopleProviding employees time to “figure out AI” isn’t enough; most need training to fully understand how to leverage ChatGPT beyond simple tasks like summarization. Yet the training required is often far less than what people expect. While the market is flooded with AI training programs, many aren’t suitable for most employees. These programs are often time-consuming, overly technical, and not tailored to specific job functions. The best results come from working closely with individuals for brief periods—10 to 15 minutes—to audit their current workflows and identify areas where LLMs could be used to streamline processes. Understanding the technical details behind token prediction isn’t necessary to create effective prompts. It’s also a myth that AI adoption is only for those with technical backgrounds under 40. In fact, attention to detail and a passion for quality work are far better indicators of success. By setting aside biases, companies may discover hidden AI enthusiasts within their ranks. For example, a lawyer in his sixties, after just five minutes of explanation, grasped the potential of LLMs. By tailoring examples to his domain, the technology helped him draft a law review article he had been putting off for months. It’s likely that many companies already have AI enthusiasts—individuals who’ve taken the initiative to explore LLMs in their work. These “LLM whisperers” could come from any department: engineering, marketing, data science, product management, or customer service. By identifying these internal innovators, organizations can leverage their expertise. Once these experts are found, they can conduct “AI audits” of current workflows, identify areas for improvement, and provide starter prompts for specific use cases. These internal experts often better understand the company’s systems and goals, making them more capable of spotting relevant opportunities. Ensuring Time for ExplorationBeyond providing training, it’s crucial that employees have the time to explore and experiment with AI tools. Companies can’t simply tell their employees to innovate with AI while demanding that another month’s worth of features be delivered by Friday at 5 p.m. Ensuring teams have a few hours a month for exploration is essential for fostering true AI adoption. Once the initial hurdle of adoption is overcome, employees will be able to identify the most promising areas for AI investment. From there, organizations will be better positioned to assess the need for more specialized training. ConclusionThe AI productivity paradox is not about the complexity of the technology but rather how organizations approach work and innovation. Harnessing AI’s potential is simpler than “AI influencers” often suggest, requiring only

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November 20, 2024in AI Tools, Data, Einstein 1 Platform, Generative AI, Google, Technology0 Comments
How Does Salesforce Use AI
19Nov

How Does Salesforce Use AI

With all the buzz in the news about AI, it may feel like AI is everywhere. In fact, as of 2023, over 80% of global companies report adopting AI to enhance their business operations. This means if your company isn’t yet leveraging AI to strengthen customer relationships, you risk falling behind. The good news is that Salesforce CRM already comes with a suite of AI tools ready for use. In this insight, we’ll explore how combining quality data, AI, and Salesforce can help you build more meaningful, lasting relationships with your customers. How Does Salesforce Use AI? Salesforce offers various built-in functionalities to create customizable, predictive, and generative AI experiences tailored to your business needs. One standout tool is Agentforce, which enables the creation of autonomous AI agents. If you have numerous routine tasks but limited staff, Agentforce could be the solution. For instance, if you lack an in-house customer support agent, Agentforce can build an AI service agent to handle incoming cases, responding intuitively in real-time. Not enough sales reps? No problem—create an AI sales agent to manage records, interact with leads, answer questions, and schedule meetings. Another significant AI feature is generative AI in Salesforce. According to KPMG, 77% of executives believe generative AI will have a more profound societal impact in the next three to five years than any other emerging technology. So, how can it improve your business? Salesforce’s in-house LLM, xGen, helps you generate human-like text and create original visual content from existing data or user input. This capability can enhance user experiences by automating the generation of dynamic and personalized imagery for applications. Generative AI also transforms how users interact with and consume data. Complex datasets can now be converted into easily understandable formats—visualizations, charts, or graphs—generated from natural language prompts. These insights make data accessible, enabling users to share knowledge and drive informed decisions. How Can You Use AI to Improve Customer Relationships? AI is reshaping business models, workflows, and customer engagement. By harnessing quality data, AI, and Salesforce, you can enhance how you connect with customers. Here are key ways to leverage this combination for a smarter customer strategy: Challenges You May Encounter on Your AI Journey Adopting AI in Salesforce, especially Einstein AI, offers many benefits, but it also comes with challenges. Here are some factors to consider for a successful rollout: Importance of Data Quality When Using AI Analytics Data quality is essential for AI accuracy and reliability. Poor data can skew predictions and erode user trust. Key factors that contribute to high data quality include: AI can also enhance data quality by automating data validation and cleansing. Machine learning algorithms can detect and address anomalies, duplicate records, and incomplete datasets, improving the reliability of your data over time. The Future of CRM: AI-Driven Customer Engagement and Business Growth Integrating AI into Salesforce is revolutionizing CRM by enabling businesses to engage with customers more intelligently. From automating routine tasks to enhancing decision-making and delivering personalized communication, AI-driven innovations are empowering businesses to build stronger relationships with customers. As AI continues to evolve, those who embrace it will gain a competitive edge and drive long-term growth. The future of CRM is here—and it’s smarter, faster, and more customer-focused than ever. 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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November 19, 2024in AI Tools, Data, Generative AI, Salesforce, Technology0 Comments
Training Your Own AI Model
19Nov

Training Your Own AI Model May Not Win Customers – But Leveraging Data Will

While AI plays a crucial role in delivering personalized customer experiences, the real game-changer lies in data connectivity. It’s not about having the flashiest AI model but about how data is managed across every interaction. Imagine a global retail brand with a network of physical stores, an e-commerce site, and active social media. An in-store shopper “likes” a product on Instagram, triggering an autonomous agent to send a personalized discount code. This leads them to a tailored shopping page based on their preferences, with items in their size, style, and budget. After the purchase, the agent follows up to ensure satisfaction and offers discounts on complementary items, creating a VIP-like experience. While AI can automate these touchpoints, the real enabler is a robust data platform that brings each data point into a cohesive, connected system. Without this, AI’s effectiveness is limited; Gartner predicts that 30% of generative AI projects will be abandoned by 2025 due to poor data quality. Why Data – Not a Custom AI Model – Drives Results Many companies think they need a custom-trained language model (LLM) to achieve superior customer insights. However, training an LLM is costly, requires specialized expertise, and lacks built-in permission controls. And because LLMs require constant updates to stay relevant, it’s a significant commitment with diminishing returns. Instead, a more practical approach is to integrate a pre-trained LLM with a data platform that aggregates data from diverse systems in real time. By providing AI with current, connected data, companies can enhance accuracy, identify trends, and respond to customer needs quickly. The Power of Integrated Data Platforms Consider the shopper who “liked” a social media post and then interacted with an autonomous agent. Alone, these interactions may not signify much, but together they reveal a clear buying intent. Scaling this approach allows brands to spot valuable opportunities faster. Autonomous agents can help sales teams prioritize prospects, resolve service cases, and drive sales – all in real time. This isn’t limited to retail. In healthcare, agents can streamline patient benefits verification, summarize insurance details, and assist with pharmacy coverage. From finance to manufacturing, data-enabled AI agents have endless applications. Metadata: The Secret to Seamless AI For AI to deliver tailored, high-value interactions, it needs organized data – and metadata is key. By categorizing and tagging data, metadata enables AI to find the right information, whether drafting a customer message or identifying top sales prospects. A unified data platform that harmonizes data and metadata yields sharper predictions and more personalized outputs, outperforming siloed data systems. Data-Driven Precision in Customer Experience An effective data platform is the backbone of an agile, customer-centric business, making AI far more than guesswork. By using data to understand customer needs in real time, businesses can deliver targeted, timely experiences that build loyalty and growth. A comprehensive data strategy is essential to unlocking AI’s potential. This data strategy guide provides best practices for aligning data with business goals, unearthing insights, and enhancing customer engagement. A unified data platform connects your organization around the customer – transforming a simple “like” into a sale, and a sale into loyalty. Without it, your AI is just guessing. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more

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November 19, 2024in Data, Generative AI0 Comments
AI Agent Trends
19Nov

AI Agent Trends

AI Agents: Key Statistics and Trends for 2025 “The agent revolution is real and as exciting as the cloud, social, and mobile revolutions,” remarked Salesforce Chair and CEO Marc Benioff. “It will provide a level of transformation that we’ve never seen.” With the general availability of Agentforce, the era of AI-powered agents is officially here. These intelligent software agents, designed to perform tasks autonomously or in collaboration with humans, are already transforming businesses by driving efficiency and improving customer outcomes. AI Agents in Action Companies across the globe are leveraging AI agents to achieve remarkable results. For example, Wiley has seen a 40% boost in case resolution rates with Agentforce, far surpassing their previous bot’s performance. Other success stories from Saks and Opentable reinforce the ROI potential of this groundbreaking technology. Salesforce research highlights data from consumers, employees, and business leaders worldwide, demonstrating how AI agents address key pain points while unlocking significant opportunities for enterprises and individuals alike. Why Consumers Need AI Agents Traditional customer service processes often frustrate consumers, leading to inefficiency and dissatisfaction: AI agents are transforming this landscape with immediate, personalized assistance that minimizes wait times and eliminates repeated explanations. Consumer sentiment indicates a growing acceptance of this technology: Why Enterprises Need AI Agents For enterprises, inefficiency is a persistent challenge. Time-consuming administrative tasks often prevent workers from focusing on strategic, customer-centric activities: AI adoption is increasingly a priority for revenue-generating teams, with measurable benefits: Salesforce experts emphasize that while AI has already proven its value in service, sales, marketing, and commerce, the surface of its potential has only just been scratched. The Agent-First Future As organizations adopt an agent-first approach, they unlock opportunities to redefine operations, increase efficiency, and drive innovation: AI agents are not just the future—they’re the present solution to enduring challenges, empowering businesses to meet the demands of a rapidly evolving digital economy. 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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November 19, 2024in Agentforce Platform, Data, Enterprise, Salesforce, Technology0 Comments
Generative AI Energy Consumption Rises
19Nov

AI for the Ho-Ho-Holidays

The Holiday Rush and AI’s Growing Role in Retail The holiday season is approaching quickly, with fewer days between Thanksgiving and Christmas this year than at any time since 2019. This condensed timeline makes Salesforce’s latest State of the Connected Customer report—this year titled State of the AI Connected Customer—particularly timely. The report, based on insights from over 15,000 consumers worldwide, focuses on the growing role of artificial intelligence (AI), specifically AI agents, in transforming customer experiences. With Salesforce’s recent launch of Agentforce, AI agents have taken center stage. According to Michael Affronti, SVP and General Manager of Commerce Cloud at Salesforce, the retail sector is already exploring this technology: “Retailers that we talk to are starting to implement AI agents. Unlike chatbots, AI agents can analyze customer data to make proactive recommendations and even take action. For consumers, AI agents create smoother checkout experiences, streamline returns, and deliver personalized shopping that feels like working with an incredible in-store associate. For retailers, AI agents drive higher margins and customer retention by delivering exceptional service. As we like to say, ‘There’s an agent for that.’” Rebuilding Trust with AI One of the most compelling use cases for AI agents, according to Affronti, lies in addressing declining consumer trust. Salesforce’s research highlights alarming trends: AI agents present an opportunity to rebuild trust by delivering reliable and transparent experiences. While consumer expectations for personalized service remain high, Salesforce data suggests that 30% of consumers would work with AI agents if it meant faster service. However, skepticism persists—curiosity is the top emotion associated with AI, followed closely by suspicion and anxiety. Transparency is crucial, as 40% of consumers are more likely to trust AI agents when their logic is explained, and there’s an option to escalate to a human. “Most people just want to know it’s AI, and then they’ll be comfortable,” Affronti notes. “Clarity about what the agent is doing, combined with the ability to talk to a real person, builds trust.” Three Opportunities for Retailers Affronti outlines three key strategies for retailers to embrace AI agents effectively this holiday season: Experimentation and Preparing for the Future For retailers not yet leveraging AI, Affronti advises starting small but experimenting now. For example, large brands like Saks are already piloting AI agents such as “Sophie,” which handles tasks like order management and learns new capabilities based on customer feedback. However, smaller businesses can also benefit from AI tools, such as generative AI for writing product descriptions or automating promotions, regardless of scale. “One of the great things about AI today is how democratized it has become,” Affronti explains. “Small businesses using Salesforce’s Commerce Cloud can leverage AI for tasks like creating product descriptions or automating translations, even if their catalog is limited.” Looking Ahead While this holiday season may not see a widespread rollout of AI-driven retail solutions, early adopters are already showcasing what’s possible. Retailers that embrace experimentation and lay the groundwork for AI-powered experiences today will likely see significant results by the 2025 holiday season. The key takeaway: now is the time to build the foundation for the future of AI in retail. 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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November 19, 2024in AI Tools, Artificial Intelligence, Data, Generative AI, Technology0 Comments
DHS Introduces AI Framework to Protect Critical Infrastructure
19Nov

DHS Introduces AI Framework to Protect Critical Infrastructure

The Department of Homeland Security (DHS) has unveiled the Roles and Responsibilities Framework for Artificial Intelligence in Critical Infrastructure, a voluntary set of guidelines designed to ensure the safe and secure deployment of AI across the systems that power daily life. From energy grids to water systems, transportation, and communications, critical infrastructure increasingly relies on AI for enhanced efficiency and resilience. While AI offers transformative potential—such as detecting earthquakes, optimizing energy usage, and streamlining logistics—it also introduces new vulnerabilities. Framework Overview The framework, developed with input from cloud providers, AI developers, critical infrastructure operators, civil society, and public sector organizations, builds on DHS’s broader policies from 2023, which align with White House directives. It aims to provide a shared roadmap for balancing AI’s benefits with its risks. AI Vulnerabilities in Critical Infrastructure The DHS framework categorizes vulnerabilities into three key areas: The guidelines also address sector-specific vulnerabilities and offer strategies to ensure AI strengthens resilience while minimizing misuse risks. Industry and Government Support Arvind Krishna, Chairman and CEO of IBM, lauded the framework as a “powerful tool” for fostering responsible AI development. “We look forward to working with DHS to promote shared and individual responsibilities in advancing trusted AI systems.” Marc Benioff, CEO of Salesforce, emphasized the framework’s role in fostering collaboration among stakeholders while prioritizing trust and accountability. “Salesforce is committed to humans and AI working together to advance critical infrastructure industries in the U.S. We support this framework as a vital step toward shaping the future of AI in a safe and sustainable manner.” DHS Secretary Alejandro N. Mayorkas highlighted the urgency of proactive action. “AI offers a once-in-a-generation opportunity to improve the strength and resilience of U.S. critical infrastructure, and we must seize it while minimizing its potential harms. The framework, if widely adopted, will help ensure the safety and security of critical services.” DHS Recommendations for Stakeholders A Call to Action DHS encourages widespread adoption of the framework to build safer, more resilient critical infrastructure. By prioritizing trust, transparency, and collaboration, this initiative aims to guide the responsible integration of AI into essential systems, ensuring they remain secure and effective as technology continues to evolve. 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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November 19, 2024in Artificial Intelligence, Data, Laws, Salesforce, Technology0 Comments
Salesforce Data Migration Tools
18Nov

Salesforce Data Migration Tools

In the current age of digital transformation, effective data migration is essential, especially as cloud adoption accelerates. Research from Foundry reveals that 63% of IT leaders have increased their cloud migrations, but 90% face challenges—primarily budgetary constraints. This highlights the importance of thoughtful planning and strategic execution. In this context, we’ll explore the significance of successful Salesforce data migration and present a nine-step roadmap to ensure a seamless transition. Additionally, we’ll cover solutions for data preparation and the top five Salesforce data migration tools that can help turn migration challenges into growth opportunities. Salesforce Data Migration ChecklistDownload our e-book to quickly and efficiently migrate data from Excel spreadsheets and CRM systems to Salesforce. Why is Data Migration Important?In 2010, I bought my first smartphone and struggled to transfer data from my outdated phone. My contacts were vital, but the old phone lacked proper data transfer options. Determined not to re-enter everything manually, I searched for a solution. Eventually, I found a method to extract data into a CSV file, which I converted to vCard format to transfer successfully. This experience reinforced how essential data migration is—not only for businesses but also for everyday situations. For organizations looking to modernize, data migration is a crucial step in upgrading IT infrastructure. It enables smooth transitions from legacy systems to modern platforms like Salesforce, enhancing efficiency, scalability, and data accessibility. Effective data migration improves data management, reduces costs tied to outdated systems, and supports better decision-making through improved analytics. It also ensures data integrity and security, aligning IT capabilities with evolving business needs, fostering innovation, and keeping a competitive edge. What is Data Migration in Salesforce?Whether you are already using Salesforce or considering adoption, one common question arises: “How do I migrate my data to Salesforce?” Salesforce data migration involves moving information from external systems like legacy CRMs or local databases into Salesforce. This process is critical not only for protecting data integrity but also for enabling better decision-making, improving customer service, and promoting organizational growth. A well-planned data migration strategy ensures a smooth transition to Salesforce, maximizing its potential and enhancing business efficiency. 9-Step Salesforce Data Migration PlanPreparing for a Salesforce data migration? Follow these nine essential steps for a seamless process: Need Help with Data Migration to Salesforce?We offer consulting services to guide you through the data migration process, from auditing data sources to executing the migration strategy. Tectonic is here to help. Top 5 Salesforce Data Migration ToolsHere’s a quick comparison of five Salesforce data migration tools to help you choose the right solution: For hassle-free data migration, reach out to Tectonic for a tailored plan that minimizes downtime and maximizes operational efficiency. 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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November 18, 2024in Data, Salesforce0 Comments
AI platform for automated task management
18Nov

AI platform for automated task management

Salesforce Doubles Down on AI Innovation with Agentforce Salesforce, renowned for its CRM software used by over 150,000 businesses, including Amazon and Walmart, continues to push the boundaries of innovation. Beyond its flagship CRM, Salesforce also owns Slack, the popular workplace communication app. Now, the company is taking its AI capabilities to the next level with Agentforce—a platform that empowers businesses to build and deploy AI-powered digital agents for automating tasks such as creating sales reports and summarizing Slack conversations. What Problem Does Agentforce Solve? Salesforce has been leveraging AI for years, starting with the launch of Einstein in 2016. Einstein’s initial capabilities were limited to basic, scriptable tasks. However, the rise of generative AI created an opportunity to tackle more complex challenges, enabling tools to make smarter decisions and interpret natural language. This evolution led to a series of innovations—Einstein GPT, Einstein Copilot, and now Agentforce—a flexible platform offering prebuilt and customizable agents designed to meet diverse business needs. “Our customers wanted more. Some wanted to tweak the agents we offer, while others wanted to create their own,” said Tyler Carlson, Salesforce’s VP of Business Development. The Technology Behind Agentforce Agentforce is powered by Salesforce’s Atlas Reasoning Engine, developed in-house to drive smarter decision-making. The platform integrates with AI models from leading providers like OpenAI, Anthropic, Amazon, and Google, offering businesses a variety of tools to choose from. Slack, which Salesforce acquired in 2021, plays a pivotal role as a testing ground for these AI agents. Currently in beta, Agentforce’s Slack integration allows businesses to implement automations directly where employees work, enhancing usability. “Slack makes these tools easy to use and accessible,” Carlson noted. How Agentforce Stands Out Customizing AI for Business Needs With tools like Agentbuilder, businesses can create AI agents tailored to specific tasks. For instance, an agent could prioritize and sort incoming emails, respond to HR inquiries, or handle customer support using internal data. One standout example is Salesforce’s partnership with Workday to develop an AI-powered service agent for employee questions. Driving Results and Adoption Salesforce has already seen promising results from early trials, with Agentforce resolving 90% of customer inquiries autonomously. The company aims to expand adoption and functionality, allowing these agents to handle even larger workloads. “We’re building a bigger ecosystem of partners and skills,” Carlson emphasized. “By next year, we want Agentforce to be a must-have for businesses.” With Agentforce, Salesforce continues to cement its role as a leader in AI innovation, helping businesses work smarter, faster, and more effectively. 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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November 18, 2024in Agentforce Platform, Data, Generative AI, Google, Salesforce, Technology0 Comments
Redefining Autonomous AI for the Enterprise
18Nov

Redefining Autonomous AI for the Enterprise

Salesforce Agentforce: Redefining Autonomous AI for the Enterprise Salesforce has unveiled Agentforce, a groundbreaking addition to its platform that enables businesses to create and deploy autonomous AI agents capable of performing tasks across any business function. Unlike traditional chatbots or copilots, Agentforce leverages advanced reasoning capabilities to independently resolve customer cases, qualify sales leads, optimize marketing campaigns, and more. By automating actions triggered by data changes, business rules, pre-built automations, or API signals, Agentforce empowers companies like OpenTable, Saks, and Wiley to scale their workforce and enhance customer experiences. “Agentforce is redefining what’s possible in business and beyond,” said Marc Benioff, Chair and CEO of Salesforce. “This technology is ushering in an era of AI abundance and limitless workforces, augmenting employees, building deeper customer relationships, and driving unprecedented growth and profitability.” Built on a Metadata-Driven Architecture Agentforce builds on Salesforce’s metadata-driven platform, ensuring rapid deployment and customization without extensive manual effort. “Agentforce taps into the trusted Salesforce platform, seamlessly integrating enterprise data, workflows, and AI models to deliver actionable intelligence,” said Srini Tallapragada, President and Chief Engineering Officer at Salesforce. Addressing Market Inefficiencies Salesforce research identified significant inefficiencies Agentforce is designed to address: Marc Benioff emphasized, “The agent revolution is as transformative as the cloud, social, and mobile revolutions, setting a new standard for operational efficiency.” Rapid Adoption and Industry Use Cases At Dreamforce 2024, customers created over 10,000 autonomous agents in three days, with adoption accelerating to 20,000 agents globally through Salesforce World Tour events. The platform’s natural language interface enables business users—not just IT teams—to build and customize agents. Industry Applications: Ecosystem and Partner Support The launch is bolstered by partnerships with global systems integrators, including Accenture, Deloitte, IBM, PwC, and Slalom. These collaborations have accelerated emerging technology rollouts by 31%, according to Salesforce. Additionally, the new Agentblazer Community provides a hub for knowledge sharing and integrations via the Salesforce AppExchange. Pricing and Future Development Agentforce is now generally available, with pricing starting at $2 per conversation, including volume discounts. Customers can explore the platform through the Salesforce Foundations trial, offering 1,000 conversation credits for free. Future development plans focus on enabling multi-agent scenarios for complex workflows and expanding autonomous capabilities across business processes. “This is just the first chapter,” said Clara Shih, CEO of Salesforce AI. “The innovation we’ll see from this technology will transform businesses in ways we’ve only begun to imagine.” What This Means for Businesses Agentforce represents Salesforce’s most ambitious platform expansion since Einstein AI’s debut in 2016. Its consumption-based pricing model aligns with Salesforce’s broader shift toward pay-as-you-use services, mirroring strategies with Data Cloud and Einstein GPT. For enterprises, the platform offers a low-risk trial to assess its potential for driving operational improvements. The challenge will be transitioning from pilot projects to large-scale deployments while maintaining the claimed accuracy and efficiency advantages. With over 20,000 agents created and a robust partner ecosystem, Salesforce is well-positioned to lead the autonomous AI revolution. However, the ultimate success of Agentforce will depend on its ability to consistently deliver measurable business value beyond the initial wave of adoption. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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November 18, 2024in Agentforce Platform, Data, Enterprise, Mulesoft, Salesforce Foundations, Technology0 Comments
NetSuite Salesforce Collaboration
17Nov

NetSuite Salesforce Collaboration

NetSuite Bets on Strategic Growth and Embraces Collaboration with Salesforce Growing on All Fronts At SuiteWorld 2024, the theme, “All Systems Grow,” reflected a pivotal moment for NetSuite. While the event lacked groundbreaking announcements, it showcased a fulfillment of past promises and a notable strategic shift toward openness and collaboration. Oracle and NetSuite are now welcoming competitors as partners, signaling a move toward interoperability that could redefine their market positioning. With over 40,000 customers, NetSuite continues its strong growth in the ERP space, particularly among SMBs. The company’s Q3 sales surged 20% year-over-year, underlining its momentum in the mid-market. Beyond traditional ERP capabilities, NetSuite’s expanded suite of solutions positions it as more than just an ERP provider. Delivering on AI Innovations While there were no splashy acquisitions, NetSuite made significant strides by rolling out 170 new modules and features, many leveraging AI. These enhancements blend predictive AI and generative AI to increase accuracy and user productivity. These updates aim to elevate both the platform’s quality and the efficiency of its users. Redwood Design: A Transformative User Experience NetSuite is adopting Oracle’s Redwood design language, promising a more intuitive and user-friendly interface. While Redwood is not new, its phased rollout within NetSuite is a significant step forward. Notable Additions: SuiteProcurement and Salesforce Integration SuiteProcurement: NetSuite’s new procurement automation solution integrates directly with Amazon Business and Staples Business Advantage, automating ordering, invoicing, approvals, and deliveries. Plans are underway to expand vendor support, offering broader applicability in the future. Salesforce Partnership: NetSuite’s most significant announcement was its strategic partnership with Salesforce, enabling real-time data exchange between the platforms. Evan Goldberg, NetSuite’s founder and EVP, explained the rationale:“It’s up to the customer to decide what software they want to use.” The partnership reflects NetSuite’s commitment to addressing customer needs, with more SaaS integrations expected in the future. Expanding Field Service Management (FSM) NetSuite’s Field Service Management (FSM) capabilities, acquired last year, are now better integrated into its platform. While development progress has been slower than anticipated, significant enhancements are expected in the coming year, leveraging Oracle technology to extend FSM’s functionality across industries. And Field Service Management is available in Salesforce, as well. Positioned for Continued SMB Growth NetSuite’s investments are yielding results, as demonstrated by its rapid growth and deeper integration of Oracle technology. The NetSuite Analytics Data Warehouse and Enterprise Performance Management are driving adoption among existing users, showcasing the platform’s scalability. NetSuite’s ability to quickly integrate Oracle updates into its infrastructure gives it a competitive edge, ensuring customers benefit from the latest innovations without delays. With its robust feature set, AI-powered tools, and strategic partnerships like the one with Salesforce, NetSuite has strengthened its position as a go-to ERP platform for SMBs. Its consistent 20% year-over-year growth indicates a bright future, making it an increasingly attractive option for mid-market businesses. 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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November 17, 2024in Data, Enterprise, Generative AI, Salesforce, Technology0 Comments
Liquid Neural Networks
16Nov

Liquid Neural Networks

LNNs mark a significant departure from traditional, rigid AI structures, drawing deeply from the adaptable nature of biological neural systems. MIT researchers explored how organisms manage complex decision-making and dynamic responses with minimal neurons, translating these principles into the design of LNNs

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November 16, 2024in Artificial Intelligence, Data0 Comments
AI Agent Rivalry
16Nov

AI Agent Rivalry

Microsoft and Salesforce’s AI Agent Rivalry Heats Up The battle for dominance in the AI agent space has escalated, with Salesforce CEO Marc Benioff intensifying his criticism of Microsoft’s AI solutions. Following remarks at Dreamforce 2024, Benioff took to X (formerly Twitter) to call out Microsoft for what he called “rebranding Copilot as ‘agents’ in panic mode.” The AI Agent rivalry winner may be determined not by flashy features but by delivering tangible, transformative outcomes for businesses navigating the complexities of AI adoption. AI Agent Rivalry. Benioff didn’t hold back, labeling Microsoft’s Copilot as “a flop”, citing issues like data leaks, inaccuracies, and requiring customers to build their own large language models (LLMs). In contrast, he touted Salesforce’s Agentforce as a solution that autonomously drives sales, service, marketing, analytics, and commerce without the complications he attributes to Microsoft’s offerings. Microsoft’s Copilot: A New UI for AI Microsoft recently unveiled new autonomous agent capabilities for Copilot Studio and Dynamics 365, positioning these agents as tools to enhance productivity across teams and functions. CEO Satya Nadella described Copilot as “the UI for AI” and emphasized its flexibility, allowing businesses to create, manage, and integrate agents seamlessly. Despite the fanfare, Benioff dismissed Copilot’s updates, likening it to “Clippy 2.0” and claiming it fails to deliver accuracy or transformational impact. Salesforce Expands Agentforce with Strategic Partnerships At Dreamforce 2024, Salesforce unveiled its Agentforce Partner Network, a global ecosystem featuring collaborators like AWS, Google Cloud, IBM, and Workday. The move aims to bolster the capabilities of Agentforce, Salesforce’s AI-driven platform that delivers tailored, autonomous business solutions. Agentforce allows businesses to deploy customizable agents without complex coding. With features like the Agent Builder, users can craft workflows and instructions in natural language, making the platform accessible to both technical and non-technical teams. Flexibility and Customization: Salesforce vs. Microsoft Both Salesforce and Microsoft emphasize AI’s transformative potential, but their approaches differ: Generative AI vs. Predictive AI Salesforce has doubled down on generative AI, with Einstein GPT producing personalized content using CRM data while also providing predictive analytics to forecast customer behavior and sales outcomes. Microsoft, on the other hand, combines generative and predictive AI across its ecosystem. Copilot not only generates content but also performs autonomous decision-making in Dynamics 365 and Azure, positioning itself as a comprehensive enterprise solution. The Rise of Multi-Agent AI Systems The competition between Microsoft and Salesforce reflects a broader trend in AI-driven automation. Companies like OpenAI are experimenting with frameworks like Swarm, which simplifies the creation of interconnected AI agents for tasks such as lead generation and marketing campaign development. Similarly, startups like DevRev are introducing conversational AI builders to design custom agents, offering enterprises up to 95% task accuracy without the need for coding. What Lies Ahead in the AI Agent Landscape? As Salesforce and Microsoft push the boundaries of AI integration, businesses are evaluating these tools for their flexibility, customization, and impact on operations. While Salesforce leads in CRM-focused AI, Microsoft’s integrated approach appeals to enterprises seeking cross-functional AI solutions. In the end, the winner may be determined not by flashy features but by delivering tangible, transformative outcomes for businesses navigating the complexities of AI adoption. AI Agent Rivalry. 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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November 16, 2024in Agentforce Platform, Data, Enterprise, Generative AI, Google, Salesforce0 Comments
RAGate
14Nov

RAGate

RAGate: Revolutionizing Conversational AI with Adaptive Retrieval-Augmented Generation Building Conversational AI systems is challenging.It’s not just feasible; it’s complex, resource-intensive, and time-consuming. The difficulty lies in creating systems that can not only understand and generate human-like responses but also adapt effectively to conversational nuances, ensuring meaningful engagement with users. Retrieval-Augmented Generation (RAG) has already transformed Conversational AI by combining the internal knowledge of large language models (LLMs) with external knowledge sources. By leveraging RAG with business data, organizations empower their customers to ask natural language questions and receive insightful, data-driven answers. The challenge?Not every query requires external knowledge. Over-reliance on external sources can disrupt conversational flow, much like consulting a book for every question during a conversation—even when internal knowledge is sufficient. Worse, if no external knowledge is available, the system may respond with “I don’t know,” despite having relevant internal knowledge to answer. The solution?RAGate — an adaptive mechanism that dynamically determines when to use external knowledge and when to rely on internal insights. Developed by Xi Wang, Procheta Sen, Ruizhe Li, and Emine Yilmaz and introduced in their July 2024 paper on Adaptive Retrieval-Augmented Generation for Conversational Systems, RAGate addresses this balance with precision. What Is Conversational AI? At its core, conversation involves exchanging thoughts, emotions, and information, guided by tone, context, and subtle cues. Humans excel at this due to emotional intelligence, socialization, and cultural exposure. Conversational AI aims to replicate these human-like interactions by leveraging technology to generate natural, contextually appropriate, and engaging responses. These systems adapt fluidly to user inputs, making the interaction dynamic—like conversing with a human. Internal vs. External Knowledge in AI Systems To understand RAGate’s value, we need to differentiate between two key concepts: Limitations of Traditional RAG Systems RAG integrates LLMs’ natural language capabilities with external knowledge retrieval, often guided by “guardrails” to ensure responsible, domain-specific responses. However, strict reliance on external knowledge can lead to: How RAGate Enhances Conversational AI RAGate, or Retrieval-Augmented Generation Gate, adapts dynamically to determine when external knowledge retrieval is necessary. It enhances response quality by intelligently balancing internal and external knowledge, ensuring conversational relevance and efficiency. The mechanism: Traditional RAG vs. RAGate: An Example Scenario: A healthcare chatbot offers advice based on general wellness principles and up-to-date medical research. This adaptive approach improves response accuracy, reduces latency, and enhances the overall conversational experience. RAGate Variants RAGate offers three implementation methods, each tailored to optimize performance: Variant Approach Key Feature RAGate-Prompt Uses natural language prompts to decide when external augmentation is needed. Lightweight and simple to implement. RAGate-PEFT Employs parameter-efficient fine-tuning (e.g., QLoRA) for better decision-making. Fine-tunes the model with minimal resource requirements. RAGate-MHA Leverages multi-head attention to interactively assess context and retrieve external knowledge. Optimized for complex conversational scenarios. RAGate Varients How to Implement RAGate Key Takeaways RAGate represents a breakthrough in Conversational AI, delivering adaptive, contextually relevant, and efficient responses by balancing internal and external knowledge. Its potential spans industries like healthcare, education, finance, and customer support, enhancing decision-making and user engagement. By intelligently combining retrieval-augmented generation with nuanced adaptability, RAGate is set to redefine the way businesses and individuals interact with AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more We Are All Cloud Users My old company and several others are concerned about security, and feel more secure with being able to walk down Read more

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November 14, 2024in Data, Technology0 Comments

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