Technology Archives - gettectonic.com - Page 2

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salesforce end to end
24Feb

Salesforce and Google Announcement

Salesforce (NYSE:CRM) has entered into a deal with Google (NASDAQ:GOOGL) to offer its customer relations management software, Agentforce artificial intelligence assistants, and Data Cloud offerings through Google Cloud, the companies announced today. Google and Salesforce already have many of the same clients, and this new deal will allow for more product integration between Google Workspace and Salesforce’s customer relationship management and AI offerings. Salesforce already uses Amazon (AMZN) Web Services for much of its cloud computing. “Our mutual customers have asked us to be able to work more seamlessly across Salesforce and Google Cloud, and this expanded partnership will help them accelerate their AI transformations with agentic AI, state-of-the-art AI models, data analytics, and more,” said Thomas Kurian, CEO of Google Cloud. The deal is expected to total $2.5B over the next seven years, according to a report by Bloomberg. Salesforce and Google today announced a major expansion of their strategic partnership, delivering choice in the models and capabilities businesses use to build and deploy AI-powered agents. In today’s constantly evolving AI landscape, innovations like autonomous agents are emerging so quickly that businesses struggle to keep pace. This expanded partnership provides crucial flexibility, empowering customers to develop tailored AI solutions that meet their specific needs, rather than being locked into a single model provider. Google Cloud is at the forefront of enterprise AI innovation with millions of developers building with Google’s cutting-edge Gemini models and on Google Cloud’s AI-optimized infrastructure. This expanded partnership will empower Salesforce customers to build Agentforce agents using Gemini and to deploy Salesforce on Google Cloud. This is an expansion of the existing partnership that allows customers to use data from Data Cloud and Google BigQuery bi-directionally via zero-copy technology—further equipping customers with the data, AI, trust, and actions they need to bring autonomous agents into their businesses. Additionally, this integration empowers Agentforce agents with the ability to reference up-to-the-minute data, news, current events, and credible citations, substantially enhancing their contextual awareness and ability to deliver accurate, evidence-backed responses. For example, in supply chain management and logistics, an agent built with Agentforce could track shipments and monitor inventory levels in Salesforce Commerce Cloud and proactively identify potential disruptions using real-time data from Google Search, including weather conditions, port congestion, and geopolitical events. Availability is expected in the coming months. AI: Unlocking the Power of Choice and Flexibility with Gemini and Agentforce Businesses need the freedom to choose the best models for their needs rather than be locked into one vendor. In 2025, Google’s Gemini models will also be available for prompt building and reasoning directly within Agentforce. With Gemini and Agentforce, businesses will benefit from: For example, an insurance customer can submit a claim with photos of the damage and an audio voicemail from a witness. Agentforce, using Gemini, can then help the insurance provider deliver better customer experiences by processing all these inputs, assessing the claim’s validity, and even using text-to-speech to contact the customer with a resolution, streamlining the traditionally lengthy claims process. Availability is expected this year. Trust: Salesforce Platform deployed on Google Cloud Customers will be able to use Salesforce’s unified platform (Agentforce, Data Cloud, Customer 360) on Google Cloud’s highly secure, AI-optimized infrastructure, benefiting from features like dynamic grounding, zero data retention, and toxicity detection provided by the Einstein Trust Layer. Once Salesforce products are available on Google Cloud, customers will also have the ability to procure Salesforce offerings through the Google Cloud Marketplace, opening up new possibilities for global businesses to optimize their investments across Salesforce and Google Cloud and benefiting thousands of existing joint customers. Action: Enhanced Employee Productivity and Customer Service with AI-Powered Integrations Millions use Salesforce and Google Cloud daily. This partnership prioritizes choice and flexibility, enabling seamless cross-platform work. New and deeper connections between platforms like Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite, as well as Slack and Google Workspace, will empower AI agents and service representatives with unified data access, streamlined workflows, and advanced AI capabilities, regardless of platform. Salesforce and Google Cloud are deeply integrating their customer service platforms—Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite—to create a seamless and intelligent support experience. Expected later this year, this unified approach empowers AI agents in Service Cloud with: Salesforce and Google Cloud are also exploring deeper integrations between Slack and Google Workspace, boosting productivity and creating a more cohesive digital workspace for teams and organizations. The companies are currently exploring use cases such as: Expanding Partnership Capabilities and Integrations This partnership goes beyond core product integrations to deliver a more connected and intelligent data foundation for businesses. Expected availability throughout 2025: This landmark partnership between Salesforce and Google represents a strategic paradigm shift in enterprise AI deployment, emphasizing infrastructure innovation, AI capability enhancement, and enterprise value. The integration of Google Search grounding provides a unique competitive advantage, offering real-time, factual responses backed by the world’s most comprehensive search engine. The companies are committed to ongoing innovation and deeper collaboration to empower businesses with even more powerful solutions. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 24, 2025in Agentic AI, Artificial Intelligence, Data, Enterprise, Google, Salesforce, Salesforce Commerce Cloud, Salesforce Service Cloud, Technology0 Comments

Amadeus and Salesforce Expand Partnership

Amadeus and Salesforce Expand Partnership to Transform Hotel Service Centers Amadeus is deepening its collaboration with Salesforce to develop a next-generation hotel service center, designed to tackle key challenges in hospitality reservations and customer service. Currently in development, this innovative solution integrates Salesforce Service Cloud with Amadeus’ Central Reservations Systems and Guest Interaction solutions, targeting the global hospitality market. Enhancing the Guest Experience and Driving Revenue At its core, the new service center will elevate the Amadeus Central Reservations System (ACRS™) and iHotelier® by streamlining booking experiences and transforming how call center agents assist travelers. Key benefits include: By leveraging intelligent automation and real-time guest insights, hotels can enhance customer interactions, drive incremental revenue, and deliver more tailored experiences. A Flexible, Scalable Solution for All Hotel Operators The new service center is designed for maximum adaptability, enabling hoteliers to seamlessly integrate with Salesforce Service Cloud while scaling from entry-level solutions to advanced implementations. Capabilities range from basic booking and guest profile management to advanced features such as: ✔ Agent task automation for improved efficiency.✔ Ongoing case management to ensure seamless guest support.✔ Omnichannel communications for a unified guest experience. From boutique hotels to global chains, operators can now access enterprise-grade technology tailored to their needs, boosting both service quality and operational efficiency. Leveraging AI and Automation to Empower Hotel Agents Recognizing the potential of Agentforce to enhance productivity, Amadeus is exploring AI-driven automation and intelligent case management to further streamline workflows and optimize customer service operations. Brian Landsman, EVP, Global Business Development and Partnerships at Salesforce, stated: “Building on the success of Amadeus Delphi® on Salesforce, Amadeus has chosen the Salesforce Platform and Agentforce to scale its new Service Center offering. This collaboration empowers customer service representatives with the combined power of Salesforce Service Cloud and Amadeus’ ACRS and iHotelier solutions. We see incredible potential in continuing to bring innovations to our mutual customers.” Peter Waters, Executive Vice President, Hotel IT Solutions at Amadeus, added: “We’re thrilled to expand our partnership with Salesforce to deliver an end-to-end solution that enhances hotel guest services while driving bookings and revenue. By optimizing guest management and service workflows, this next-generation service center will redefine hospitality operations.” Tectonic has additional implemented Salesforce Marketing Cloud Engagement with Amadeus for marketing automation. About Amadeus Amadeus powers personalized, seamless travel experiences, helping hospitality providers attract, serve, and retain guests. With over 30 years of expertise, Amadeus develops cutting-edge, open software solutions that drive operational efficiency and customer satisfaction. With a presence in 175+ countries, Amadeus is committed to enabling hotels to create unforgettable guest experiences while maximizing revenue opportunities. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 21, 2025in Data, Enterprise, Salesforce, Salesforce Service Cloud, Technology0 Comments
$15 Million to AI Training for U.S. Government Workforce
19Feb

AI Adoption in the Federal Government

AI Adoption in the Federal Government: A New Era Under the Trump Administration With a new administration in Washington and a $500 billion AI infrastructure initiative underway, the U.S. federal government may be entering a phase of accelerated AI adoption. Federal AI Expansion AI adoption grew under the Biden administration, with agencies leveraging it for fraud detection, workflow automation, and data analysis. However, experts predict that the Trump administration will further expand federal AI use. “Trump and his advisers have spoken about ‘unleashing AI,’ signaling a push for broader adoption within government agencies,” said Darrell West, a senior fellow at the Brookings Institution’s Center for Technology Innovation. As the administration scales back AI safety regulations and deepens ties with major tech firms, federal AI usage is expected to rise. However, ensuring transparency and educating the public remain crucial for building trust in government AI applications. AI Governance Framework The foundation for federal AI governance was established under Trump’s first term, with executive orders EO 13859 (2019) and EO 13960 (2020). EO 13960 mandated an annual AI use case inventory, significantly expanding under Biden—from 710 cases in 2023 to 2,133 in 2024. Reggie Townsend, VP of Data Ethics at SAS and a National AI Advisory Committee (NAIAC) member, emphasized the importance of this transparency: “The inventory was a crucial first step in building public trust.” Biden’s EO 14110 (2023) introduced stronger AI guardrails, requiring agencies to designate chief AI officers, disclose safety-related AI use cases, and implement risk management guidelines. However, on his first day in office, Trump rescinded EO 14110, signaling a shift toward deregulation. AI Applications in Government The 2024 federal AI inventory reported 2,133 AI use cases across 41 agencies. The Department of Health and Human Services (HHS) led with 271 cases, reflecting a 66% increase from the previous year. Key applications include: Harvard Kennedy School adjunct lecturer Bruce Schneier anticipates even broader AI integration in government, from automating reports to drafting legislation and conducting audits. Despite growing interest, the federal government lags behind the private sector in AI adoption, especially for generative AI, due to concerns over bias, reliability, and transparency. AI Under a Second Trump Term Trump’s return to office in 2025 signals an AI policy shift favoring reduced oversight and enhanced global AI leadership. “Federal AI adoption will accelerate under Trump,” West said, citing efforts to integrate major tech figures into federal initiatives. Notably, Trump appointed xAI owner Elon Musk to lead the newly rebranded Department of Government Efficiency, formerly the U.S. Digital Service. This agency is tasked with modernizing federal technology, reducing costs, and driving deregulation. With EO 14110 rescinded, the scope of AI governance under Trump remains uncertain. “Will he eliminate all guardrails, or keep some protections? That’s something to watch,” West noted. Big Tech’s Role in Federal AI Trump’s inauguration underscored tech industry influence, with Elon Musk, Mark Zuckerberg, Jeff Bezos, and Sundar Pichai in attendance. Major tech firms, including Amazon, Google, and Microsoft, each contributed $1 million to the event, while OpenAI CEO Sam Altman made a personal $1 million donation. Some companies are aligning with the administration’s stance on AI and content moderation. Meta, for instance, has replaced its fact-checking services with a community-driven model similar to X’s Community Notes and relaxed its moderation policies. A deregulated AI landscape could benefit big tech, particularly in areas like AI safety standards and data copyright issues, while advancing the administration’s vision for U.S. AI dominance. AI’s Future in Government On his second day in office, Trump announced a $500 billion AI infrastructure investment, forming Stargate—a coalition of OpenAI, SoftBank, MGX, and Oracle—to expand AI infrastructure nationwide. “This will be the largest AI infrastructure project in history,” Trump declared, emphasizing the need for AI leadership against global competitors like China. However, West warned that accelerated adoption must be managed carefully: “It’s critical that AI is implemented fairly, with privacy and security safeguards in place.” Building AI Literacy Effective AI deployment requires education within federal agencies. “Many government workers lack AI expertise, making it difficult to procure and implement AI solutions effectively,” West said. NAIAC’s Townsend advocates for structured AI training, tailored to different federal roles. Public AI literacy is also crucial, with initiatives like the National AI Research Resource (NAIRR) promoting equitable access to AI education and development. “The public must be informed enough to hold the government accountable on AI issues,” Townsend concluded. As AI adoption accelerates, striking a balance between innovation, oversight, and public trust will define the next phase of federal AI policy. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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February 19, 2025in Data, Generative AI, Google, Public Sector Solutions, Technology0 Comments
ai trust layer
18Feb

Gen AI Trust Layers

Addressing the Generative AI Production Gap with Trust Layers Despite the growing excitement around generative AI, only a small percentage of projects have successfully moved into production. A key barrier is the persistent concern over large language models (LLMs) generating hallucinations—responses that are inconsistent or completely disconnected from reality. To address these issues, organizations are increasingly adopting AI trust layers to enhance reliability and mitigate risk. Understanding the Challenge Generative AI models, like LLMs, are powerful tools trained on vast amounts of unstructured data, enabling them to answer questions and complete tasks based on text, documents, recordings, images, and videos. This capability has revolutionized the creation of chatbots, co-pilots, and even semi-autonomous agents. However, these models are inherently non-deterministic, meaning they don’t always produce consistent outputs. This lack of predictability leads to the infamous phenomenon of hallucination—what the National Institute of Standards and Technology (NIST) terms “confabulation.” While hallucination is a byproduct of how generative models function, its risks in mission-critical applications cannot be ignored. Implementing AI Trust Layers To address these challenges, organizations are turning to AI trust layers—frameworks designed to monitor and control generative AI behavior. These trust layers vary in implementation: Galileo: Building AI Trust from the Ground Up Galileo, founded in 2021 by Yash Sheth, Atindriyo Sanyal, and Vikram Chatterji, has emerged as a leader in developing AI trust solutions. Drawing on his decade of experience at Google building LLMs for speech recognition, Sheth recognized early on that non-deterministic AI systems needed robust trust frameworks to achieve widespread adoption in enterprise settings. The Need for Trust in Mission-Critical AI “Sheth explained: ‘Generative AI doesn’t give you the same answer every time. To mitigate risk in mission-critical tasks, you need a trust framework to ensure these models behave as expected in production.’ Enterprises, which prioritize privacy, security, and reputation, require this level of assurance before deploying LLMs at scale. Galileo’s Approach to Trust Layers Galileo’s AI trust layer is built on its proprietary foundation model, which evaluates the behavior of target LLMs. This approach is bolstered by metrics and real-time guardrails to block undesirable outcomes, such as hallucinations, data leaks, or harmful outputs. Key Products in Galileo’s Suite Sheth described the underlying technology: “Our evaluation foundation models are dependable, reliable, and scalable. They run continuously in production, ensuring bad outcomes are blocked in real time.” By combining these components, Galileo provides enterprises with a trust layer that gives them confidence in their generative AI applications, mirroring the reliability of traditional software systems. From Research to Real-World Impact Unlike vendors who quickly adapted traditional machine learning frameworks for generative AI, Galileo spent two years conducting research and developing its Generative AI Studio, launched in August 2023. This thorough approach has started to pay off: A Crucial Moment for AI Trust Layers As enterprises prepare to move generative AI experiments into production, trust layers are becoming essential. These frameworks address lingering concerns about the unpredictable nature of LLMs, allowing organizations to scale AI while minimizing risk. Sheth emphasized the stakes: “When mission-critical software starts becoming infused with AI, trust layers will define whether we progress or regress to the stone ages of software. That’s what’s holding back proof-of-concepts from reaching production.” With Galileo’s innovative approach, enterprises now have a path to unlock the full potential of generative AI—responsibly, securely, and at scale. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 18, 2025in Data, Enterprise, Generative AI, Google, Salesforce, Technology0 Comments
Salesforce Life Sciences Cloud and Honeywell
15Feb

Salesforce Life Sciences Cloud and Honeywell

Honeywell’s TrackWise® Quality solution suite, in combination with Salesforce Life Sciences Cloud, will provide a comprehensive software platform for pharmaceutical and medical technology companies. Honeywell has expanded its strategic partnership with Salesforce, Inc. to introduce an integrated software platform designed for the life sciences industry. This platform, which includes Honeywell’s TrackWise Quality, Salesforce Life Sciences Cloud, Agentforce, and other solutions, aims to help pharmaceutical and medical technology companies accelerate the delivery of critical medications and healthcare devices with enhanced safety and cost efficiency. By digitizing and automating quality and compliance processes, Honeywell’s TrackWise Quality enables companies to manufacture products more efficiently, mitigate risks, reduce production costs, and bring safer products to market faster. Salesforce Life Sciences Cloud consolidates diverse data sources—such as clinical test results and medical records—to optimize interactions between pharmaceutical and medtech organizations, healthcare professionals, partners, and patients. This collaboration underscores the shared commitment of Honeywell and Salesforce to advancing automation and efficiency in the life sciences sector. “Our ongoing commitment to providing innovative software to manufacturers of critical life-supporting treatments centers around fostering trust between providers and patients,” said Frank Defesche, SVP & GM, Life Sciences at Salesforce. “The long-standing collaboration between Salesforce and Honeywell strengthens the life sciences industry by enhancing quality interactions and products, ultimately leading to improved patient outcomes.” “Partnering with Salesforce allows us to leverage our combined expertise in life sciences to drive operational efficiency, improve quality, and enhance patient-centric solutions through technology,” said Sunil Pandita, Vice President & General Manager of Honeywell Life Sciences. “From assisting patients in finding life-changing clinical trials to detecting anomalies in pharmaceutical manufacturing, Honeywell and Salesforce technologies are enabling better patient care.” Honeywell’s TrackWise Quality fosters a proactive approach to quality management by integrating industry best practices, advanced tracking and analytics, and artificial intelligence (AI) capabilities. This empowers life sciences companies to harness data more effectively, optimize performance, and enhance decision-making processes. Salesforce Life Sciences Cloud serves as a comprehensive, AI-powered engagement platform for pharmaceutical and medtech companies. Built on Sales Cloud and Service Cloud, it streamlines processes such as automating pharmacy benefit verification and expediting the screening of clinical trial candidates. These enhancements improve patient access, medication adherence, and accelerate diverse patient recruitment while reducing trial attrition. Additional Salesforce solutions within the platform include Agentforce, Data Cloud, and Analytics. As part of its continued commitment to life sciences customers, Honeywell has joined the Salesforce Agentforce Partner Network, a global ecosystem of partners developing solutions for regulatory-compliant training materials for life sciences professionals. To learn more about Honeywell’s industry-leading technologies for life sciences, visit: www.honeywell.com/us/en/industries/life-sciences. Salesforce, Salesforce Life Sciences Cloud, Agentforce, Data Cloud, and other names are trademarks of Salesforce, Inc. About Honeywell Honeywell is a diversified operating company serving a wide range of industries worldwide. Its business aligns with three key megatrends—automation, the future of aviation, and energy transition—supported by the Honeywell Accelerator operating system and Honeywell Forge IoT platform. As a trusted partner, Honeywell helps organizations address complex global challenges, delivering innovative solutions through its Aerospace Technologies, Industrial Automation, Building Automation, and Energy and Sustainability Solutions segments. For more news and updates on Honeywell, visit www.honeywell.com/newsroom. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 15, 2025in Artificial Intelligence, Data, Life Sciences Cloud, Salesforce, Technology0 Comments
The Hidden Risks of Over-Reliance on AI
14Feb

The Hidden Risks of Over-Reliance on AI

Are Marketers Trusting AI Too Much? How to Avoid Losing Your Strategic Edge AI tools have revolutionized how marketers approach research, content creation, and decision-making. However, an overreliance on these tools could undermine critical thinking and strategic planning, leaving marketers vulnerable in a fast-evolving landscape. Here’s how to balance the power of automation with human insight. The Rise of AI in Search and Marketing In late December, SEO consultancy Previsible shared a striking report: Google’s search dominance has plateaued and is now being challenged by AI-assisted search tools. These tools, such as ChatGPT, Claude, and Google’s own AI-enhanced search, are growing in popularity due to their ability to deliver contextually relevant and personalized results. Unlike traditional search, which relies on keyword matching, AI-driven search processes intent and context. This shift is reshaping how users find information and make decisions. How AI Is Changing User Behavior The increasing sophistication of AI tools brings both opportunities and risks. Users often trust AI-generated outputs without question, assuming they’re accurate and complete. Traditional search, by contrast, forces users to critically analyze and filter multiple sources. This blind trust in AI mirrors the concept of “System 1 thinking,” as described by Nobel Prize-winning psychologist Daniel Kahneman in Thinking, Fast and Slow. As AI models like ChatGPT operate primarily as “System 1 thinkers,” users risk adopting a similar approach, bypassing critical analysis in favor of convenience. The Hidden Risks of Over-Reliance on AI Younger marketers may be especially at risk of falling into this trap. Many are using AI tools like ChatGPT to summarize information or generate ideas, often without questioning the accuracy of the outputs. For B2B marketers, the allure of AI lies in its speed and perceived accuracy. However, this reliance on automation could lead to a generation of marketers who lack the ability—or inclination—to think strategically. The danger is clear: unchecked dependence on AI tools could foster a “groupthink” mentality, where creativity and critical thinking are sidelined. Without intervention, marketing departments risk becoming overly reliant on tools that were designed to enhance human efforts, not replace them. How Marketing Leaders Can Address This Threat To counter this trend, marketing leaders must actively promote the development of strategic skills. Here’s how: In a world increasingly driven by AI, marketers who can blend automation with strategic thinking will be best positioned for success. Using AI to Enhance, Not Replace, Strategic Thinking AI should empower marketers to make better decisions—not serve as the sole decision-maker. As one professor aptly put it, “Use AI to become a better student, not to be the student.” The key is balance. By combining the intuitive capabilities of AI with the deliberate, analytical approach of System 2 thinking, marketers can leverage technology without sacrificing creativity or strategy. In short, AI is a tool—not a replacement for human ingenuity. Those who recognize this distinction will thrive in an increasingly automated world. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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February 14, 2025in AI Tools, Google, Technology0 Comments
Rethinking Technology in Local Government
10Feb

Rethinking Technology in Local Government

Rethinking Technology in Local Government: A Call to Action By Richard Young, Head of Local Government, Salesforce The latest survey from Salesforce and LGC underscores an urgent need for a technology transformation in local government. Legacy systems and fragmented infrastructure remain significant roadblocks to digital progress, with nearly half of respondents identifying them as barriers to adoption. Outdated, disconnected systems limit efficiency, frustrate staff and residents, and prevent seamless data sharing—ultimately hindering councils from delivering modern, responsive services. Breaking Down Silos: A Unified Approach To move beyond fragmented solutions, councils must embrace a connected digital ecosystem that integrates systems, data, and stakeholders. Salesforce enables this shift through: ✅ MuleSoft – Seamlessly integrates legacy and modern systems, allowing for real-time data sharing and eliminating silos.✅ Salesforce Customer 360 – Provides a single, unified view of residents, enabling personalized, consistent service delivery across all touchpoints. By adopting a resident-first approach, councils can streamline operations, enhance engagement, and deliver services more effectively. Overcoming Barriers to Digital Transformation While the benefits of modern technology are clear, our survey reveals significant challenges to implementation, including: Salesforce supports councils through these challenges by providing: 🎓 Comprehensive training programs – Equipping staff with the skills to confidently adopt new technology.🤝 Shared service models – Encouraging collaboration across councils to pool resources and scale best practices.🚀 The Government Innovators Network – A knowledge-sharing platform connecting public sector leaders and private technology partners to drive innovation. By focusing on incremental modernization and ROI-driven deployments, councils can maximize value while staying within budget constraints. Empowering Councils for the Future To truly future-proof local government, technology must be: ✔ User-friendly – Intuitive systems reduce friction, enabling both staff and residents to self-service with ease.✔ Scalable and secure – Protecting against cyber threats and evolving challenges.✔ Designed for impact – Fostering collaboration between public and private sectors to drive long-term innovation. Salesforce has already made a measurable impact: 🏛 A UK council integrated over 30 legacy systems, reducing administrative overhead by 40% and increasing resident satisfaction by 25%.🇦🇺 An Australian local authority centralized resident engagement, cutting service request response times by 50%. Across the globe, we are transforming council operations, governance, and resident experiences. A Connected Future Starts Now Now is the time for councils to rethink their approach to technology. By embracing scalable, integrated solutions, they can deliver better services, empower staff, and put residents at the heart of every decision. Together, we can reimagine local government—creating a more connected, efficient, and empowered future. Richard Young, Head of Local Government, Salesforce Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 10, 2025in Data, Mulesoft, Salesforce, Technology0 Comments
Salesforce’s AI Energy Score
08Feb

Salesforce’s AI Energy Score

Salesforce’s AI Energy Score: Setting a New Standard for AI Sustainability Understanding AI’s Environmental Impact As AI adoption accelerates globally, concerns about its environmental footprint have grown. Due to AI’s reliance on power-intensive data centers, the technology consumes vast amounts of energy and water, raising sustainability challenges. To address this, Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, has introduced the AI Energy Score—a pioneering tool designed to measure and compare AI models’ energy efficiency. The AI Energy Score Launch The AI Energy Score will debut at the AI Action Summit on February 10, 2025, where leaders from over 100 countries, along with private sector and civil society representatives, will convene to discuss AI’s role in sustainability. Recognized by the French Government and the Paris Peace Forum, this initiative marks a significant step toward transparent and accountable AI development. “We are at a critical moment where the rapid acceleration of both the climate crisis and AI innovation intersect,” says Boris Gamazaychikov, Head of AI Sustainability at Salesforce.“AI’s environmental impact has remained largely opaque, with little transparency around its energy consumption. The AI Energy Score provides a standardized framework to disclose and compare these impacts, removing a key blocker to making sustainable AI the norm.” What Is the AI Energy Score? Developed in partnership with Hugging Face, Cohere, and Carnegie Mellon University, the AI Energy Score aims to establish clear and standardized energy consumption metrics for AI models. “The AI Energy Score is a major milestone for sustainable AI,” says Dr. Sasha Luccioni, AI & Climate Lead at Hugging Face. “By creating a transparent rating system, we address a key blocker for reducing AI’s environmental impact. We’re excited to launch this initiative and drive industry-wide adoption.” Key features of the AI Energy Score include: ✅ Standardized energy ratings – A framework for evaluating AI models’ energy efficiency✅ Public leaderboard – A ranking of 200+ AI models across 10 common tasks (e.g., text and image generation)✅ Benchmarking portal – A platform for submitting and assessing AI models, both open and proprietary✅ Recognizable energy use label – A 1–5 star system for easy identification of energy-efficient models✅ Label generator – A tool for AI developers to create and share standardized energy labels The Impact of the AI Energy Score The introduction of this score is expected to have far-reaching implications for the AI industry: 🔹 Driving market preference – Transparency will push demand for more energy-efficient AI models🔹 Incentivizing sustainable development – Public disclosure will encourage AI developers to prioritize efficiency🔹 Empowering informed decisions – AI users and businesses can make better choices based on energy efficiency data Salesforce’s Commitment to Sustainable AI Salesforce is leading by example, becoming the first AI model developer to disclose energy efficiency data for its proprietary models under this framework. This aligns with the company’s broader sustainability goals and ethical AI approach. Agentforce: AI Efficiency at Scale Salesforce’s Agentforce platform, introduced in 2024, is designed to deploy autonomous AI agents across business functions while maintaining energy efficiency. “Agentforce is built with sustainability at its core, delivering high performance while minimizing environmental impact,” explains Boris Gamazaychikov.“Unlike DIY AI approaches that require energy-intensive model training for each customer, Agentforce is optimized out of the box, reducing costly and carbon-heavy training.” Organizations are already leveraging Agentforce for impact-driven efficiencies: ✅ Good360 uses Agentforce to allocate donated goods more efficiently, cutting waste and emissions while saving 1,000+ employee hours annually✅ Businesses can reduce operational costs by optimizing AI model energy consumption “Reducing AI energy use isn’t just good for the environment—it lowers costs, optimizes infrastructure, and improves long-term profitability,” says Suzanne DiBianca, EVP & Chief Impact Officer at Salesforce.“We’re proud to work with industry leaders to build a more transparent AI ecosystem.” Addressing the AI Energy Challenge With AI-driven data center power usage projected to double by 2026, the AI Energy Score is a timely solution to help organizations manage and reduce their AI-related environmental impact. “The AI Energy Score isn’t just an energy-use metric—it’s a strategic business advantage,” adds Boris Gamazaychikov. “By helping organizations assess and optimize AI model energy consumption, it supports lower costs, better infrastructure efficiency, and long-term profitability.” As AI continues to evolve, sustainability must be part of the equation. The AI Energy Score is a major step in ensuring that the AI industry moves toward a more responsible, energy-efficient future.: Setting a New Standard for AI Sustainability Understanding AI’s Environmental Impact As AI adoption accelerates globally, concerns about its environmental footprint have grown. Due to AI’s reliance on power-intensive data centers, the technology consumes vast amounts of energy and water, raising sustainability challenges. To address this, Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, has introduced the AI Energy Score—a pioneering tool designed to measure and compare AI models’ energy efficiency. The AI Energy Score Launch The AI Energy Score will debut at the AI Action Summit on February 10, 2025, where leaders from over 100 countries, along with private sector and civil society representatives, will convene to discuss AI’s role in sustainability. Recognized by the French Government and the Paris Peace Forum, this initiative marks a significant step toward transparent and accountable AI development. “We are at a critical moment where the rapid acceleration of both the climate crisis and AI innovation intersect,” says Boris Gamazaychikov, Head of AI Sustainability at Salesforce.“AI’s environmental impact has remained largely opaque, with little transparency around its energy consumption. The AI Energy Score provides a standardized framework to disclose and compare these impacts, removing a key blocker to making sustainable AI the norm.” What Is the AI Energy Score? Developed in partnership with Hugging Face, Cohere, and Carnegie Mellon University, the AI Energy Score aims to establish clear and standardized energy consumption metrics for AI models. “The AI Energy Score is a major milestone for sustainable AI,” says Dr. Sasha Luccioni, AI & Climate Lead at Hugging Face. “By creating a transparent rating system, we address a key blocker for reducing AI’s

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February 8, 2025in Agentforce Platform, Data, Salesforce, Technology0 Comments
06Feb

Decision Domain Management

Roger’s first week in the office felt like a wilder than 8 second ride on a raging rodeo bull. Armed with top-notch academic achievements, he hoped to breeze through operational routines and impress his new managers. What he didn’t expect was to land in a whirlwind of half-documented processes, half-baked ideas, and near-constant firefighting. While the organization had detailed SOPs for simple, routine tasks—approving invoices, updating customer records, and shipping standard orders—Roger quickly realized that behind the structured facade, there was a deeper level of uncertainty. Every day, he heard colleagues discuss “strategic pivots” or “risky product bets.” There were whispers about AI-based initiatives that promised to automate entire workflows. Yet, when the conversation shifted to major decisions—like selecting the right AI use cases—leaders often seemed to rely more on intuition than any structured methodology. One afternoon, Roger was invited to a cross-functional meeting about the company’s AI roadmap. Expecting an opportunity to showcase his knowledge, he instead found himself in a room filled with brilliant minds pulling in different directions. Some argued that AI should focus on automating repetitive tasks aligned with existing SOPs. Others insisted that AI’s real value lay in predictive modeling—helping forecast new market opportunities. The debate went in circles, with no consensus on where or how to allocate AI resources. After an hour of heated discussion, the group dispersed, each manager still convinced of the merit of their own perspective but no closer to a resolution. That evening, as Roger stood near the coffee machine, he muttered to himself, “We have SOPs for simple tasks, but nothing for big decisions. How do we even begin selecting which AI models or agents to develop first?” His frustration led him to a conversation with a coworker who had been with the company for years. “We’re missing something fundamental here,” Roger said. “We’re rushing to onboard AI agents that can mimic our SOPs—like some large language model trained to follow rote instructions—but that’s not where the real value lies. We don’t even have a framework for weighing one AI initiative against another. Everything feels like guesswork.” His coworker shrugged. “That’s just how it’s always been. The big decisions happen behind closed doors, mostly based on experience and intuition. If you’re waiting for a blueprint, you might be waiting a long time.” That was Roger’s ;ight bulb moment. Despite all his academic training, he realized the organization lacked a structured approach to high-level decision-making. Sure, they had polished SOPs for operational tasks, but when it came to determining which AI initiatives to prioritize, there were no formal criteria, classifications, or scoring mechanisms in place. Frustrated but determined, Roger decided he needed answers. Two days later, he approached a coworker known for their deep understanding of business strategy and technology. After a quick greeting, he outlined his concerns—the disorganized AI roadmap meeting, the disconnect between SOP-driven automation and strategic AI modeling, and his growing suspicion that even senior leaders were making decisions without a clear framework. His coworker listened, then gestured for him to take a seat. “Take a breath,” they said. “You’re not the first to notice this gap. Let me explain what’s really missing.” Why SOPs Aren’t Enough The coworker acknowledged that the organization was strong in SOPs. “We’re great at detailing exactly how to handle repetitive, rules-based tasks—like verifying invoices or updating inventory. In those areas, we can plug in AI agents pretty easily. They follow a well-defined script and execute tasks efficiently. But that’s just the tip of the iceberg.” They leaned forward and continued, “Where we struggle, as you’ve discovered, is in decision-making at deeper levels—strategic decisions like which new product lines to pursue, or tactical decisions like selecting the right vendor partnerships. There’s no documented methodology for these. It’s all in people’s heads.” Roger tilted his head, intrigued. “So how do we fix something as basic but great impact as that?” “That’s where Decision Domain Management comes in,” he explained. In the context of data governance and management, data domains are the high-level blocks that data professionals use to define master data. Simply put, data domains help data teams logically group data that is of interest to their business or stakeholders. “Think of it as the equivalent of SOPs—but for decision-making. Instead of prescribing exact steps for routine tasks, it helps classify decisions, assess their importance, and determine whether AI can support them—and if so, in what capacity.” They broke it down further. The Decision Types “First, we categorize decisions into three broad types: Once we correctly classify a decision, we get a clearer picture of how critical it is and whether it requires an AI agent (good at routine tasks) or an AI model (good at predictive and analytical tasks).” The Cynefin Framework The coworker then introduced the Cynefin Framework, explaining how it helps categorize decision contexts: By combining Decision Types with the Cynefin Framework, organizations can determine exactly where AI projects will be most beneficial. Putting It into Practice Seeing the spark of understanding in Roger’s eyes, the coworker provided some real-world examples: ✅ AI agents are ideal for simple SOP-based tasks like invoice validation or shipping notifications. ✅ AI models can support complicated decisions, like vendor negotiations, by analyzing performance metrics. ✅ Strategic AI modeling can help navigate complex decisions, such as predicting new market trends, but human judgment is still required. “Once we classify decisions,” the coworker continued, “we can score and prioritize AI investments based on impact and feasibility. Instead of throwing AI at random problems, we make informed choices.” The Lightbulb Moment Roger exhaled, visibly relieved. “So the problem isn’t just that we lack a single best AI approach—it’s that we don’t have a shared structure for decision-making in the first place,” he said. “If we build that structure, we’ll know which AI investments matter most, and we won’t keep debating in circles.” The coworker nodded. “Exactly. Decision Domain Management is the missing blueprint. We can’t expect AI to handle what even humans haven’t clearly defined. By categorizing

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February 6, 2025in Data, Enterprise, Technology0 Comments
copilots and agentic ai
03Feb

Transforming Industries and Redefining Workflows

The Rise of Agentic AI: Transforming Industries and Redefining Workflows Artificial Intelligence (AI) is evolving faster than we anticipated. No longer limited to predicting outcomes or generating content, AI systems are now capable of handling complex tasks and making autonomous decisions. This new era—driven by Agentic AI—is set to redefine the workplace and transform industries. From Prediction to Autonomy: The Three Waves of AI To understand where we’re headed, it’s important to see how far AI has come. Arun Parameswaran, SVP & MD of Salesforce India, describes it as a fundamental shift: “What has changed with agents is their ability to handle complex reasoning… and, most importantly, to take action.” Unlike previous AI models that recommend or predict, Agentic AI executes tasks, reshaping customer experiences and operational workflows. Agentic AI in Action: Industry Applications At a recent Mint x Salesforce India deep-dive event on AI, industry leaders explored how Agentic AI is driving transformation across sectors. The panel featured: Here’s how Agentic AI is already making an impact: 1. Revolutionizing Customer Support Traditional chatbots have limited capabilities. Agentic AI, however, understands urgency and context. 2. Accelerating Business Decisions In finance and supply chain management, AI agents analyze vast amounts of data and execute decisions autonomously. 3. Transforming Travel & Aviation Airlines are leveraging AI to optimize booking systems, reduce costs, and enhance efficiency. 4. Automating Wealth Management AI agents in financial services monitor markets, adjust strategies, and offer personalized investment recommendations in real time. The Risks & Responsibilities of Agentic AI With great autonomy comes great responsibility. The potential of Agentic AI is vast—but so are the challenges: The Future of Work: AI as a Partner, Not a Replacement Despite concerns about job displacement, AI is more likely to reshape rather than replace roles. What Are AI Agents? AI agents go beyond traditional models like ChatGPT or Gemini. They are proactive, self-learning systems that: They fall into two categories: “AI agents don’t just wait for commands; they anticipate needs and act,” says Dr. Tomer Simon, Chief Scientist at Microsoft Research Israel. AI Agents in the Workplace: A Shift in Roles AI agents streamline processes, but they don’t eliminate the need for human oversight. Salesforce’s Agentforce is a prime example: “Companies need to integrate AI, not fear it. Those who fail to adopt AI tools risk drowning in tasks AI can handle,” warns Dr. Omri Allouche, Chief Scientist at Gong. The Road Ahead: AI-Driven Business Growth Agentic AI is not about replacing people—it’s about empowering them. As organizations re-evaluate workflows and embrace AI collaboration, the companies that act early will gain a competitive edge in efficiency and innovation. Final Thought The AI revolution is here, and Agentic AI is at its forefront. The key question isn’t whether AI will transform industries—it’s how organizations will adapt and thrive in this new era. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 3, 2025in Agentic AI, AI Tools, Artificial Intelligence, Data, Generative AI, Google, Laws, Salesforce, Technology0 Comments
Basejump on AI Analytics
01Feb

Basejump on AI Analytics

The Evolution of Data and AI: A New Frontier Once considered the new oil, data is no longer the sole focus of business transformation. The emergence of artificial intelligence (AI) has shifted the conversation toward compute power as the fundamental resource driving innovation. Sequoia Capital emphasizes AI’s transformative impact, stating: “The fields that generative AI addresses — knowledge work and creative work — comprise billions of workers. [If] Generative AI can make these workers at least 10% more efficient and/or creative: they become not only faster and more efficient, but more capable than before. Therefore, Generative AI has the potential to generate trillions of dollars of economic value.”— Sonya Huang, Pat Grady, Generative AI: A Creative New World Whether this vision materializes remains to be seen, but the comparisons to past technological revolutions—such as the internet and mobile computing—are hard to ignore. The Role of AI in Knowledge Work and Data Analytics Data analytics has seen unprecedented growth, prompting businesses to reassess its value. With a projected compound annual growth rate (CAGR) of 27.3% through 2030, the market’s rapid expansion has led to a push for better tools and standards. Data analytics has evolved from a discipline primarily rooted in physics, mathematics, accounting, and economics to a more structured academic field. This shift is evident in the surge of data science degrees. The National Center for Education Statistics reported a 968% increase in data science bachelor’s degrees awarded from 2020 to 2022, highlighting growing demand. Modern Data Analytics: From ETL to ELTL Traditional extract-transform-load (ETL) processes have struggled to keep up with modern analytical demands. The introduction of extract-load-transform (ELT) architectures, championed by tools like dbt, empowered data teams by shifting transformation ownership from data architects to analysts. However, this speed came at a cost: fragmented data governance and inconsistencies in reporting. A more refined approach—ELTL (extract-load-transform-load)—adds a critical governance step, ensuring structured data models before visualization and reporting. Data Governance, the Semantic Layer, and AI Unstructured data delivery has led to discrepancies across dashboards and reports. To address this, solutions such as dbt’s semantic layer and SQLMesh provide standardized testing, metadata management, and auditing mechanisms. AI plays a crucial role here, offering: AI-Driven Precision Analytics AI is set to revolutionize data querying by replacing cumbersome dashboards with precise, real-time insights. Borrowing from the concept of precision medicine, “precision analytics” ensures that businesses receive tailored data transformations instantly. This shift reduces reliance on static filters and rigid dashboards, allowing AI to dynamically generate and refine queries. The Rise of Data Objects AI-generated SQL queries—what we term “data objects”—are distinct from traditional dashboards in that they are: AI Solutions: Retrieving and Querying Data AI-powered data analytics falls into two broad categories: Building Trust in AI-Driven Analytics AI-generated analytics must be trustworthy, requiring: The Future of AI in Data Analytics AI will not replace data teams but will enhance their efficiency by reducing bottlenecks and accelerating insights. Organizations that integrate AI with strong data governance will achieve a competitive edge, enabling faster, more accurate, and more relevant analytics. The shift toward AI-driven data analytics is inevitable. The question is: will organizations embrace the change and refine their strategies, or will they be left behind in the wake of innovation? Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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February 1, 2025in Artificial Intelligence, Data, Enterprise, Generative AI, Technology0 Comments

Einstein Service Agent

It’s been a little over a year since the global surge in GenAI chatbots, sparked by the excitement around ChatGPT. Since then, numerous vendors, both large and mid-sized, have invested heavily in the technology, and many users have already adopted AI-powered chatbots. The competition is intensifying, with CRM giant Salesforce releasing its own GenAI chatbot software, Einstein Service Agent. Einstein Service Agent, built on the Einstein 1 Platform, is Salesforce’s first fully autonomous AI agent. It interacts with large language models (LLMs) by analyzing the context of customer messages to determine the next actions. Utilizing GenAI, the agent generates conversational responses grounded in a company’s trusted business data, including Salesforce CRM data. Salesforce claims that service organizations can now significantly reduce the number of tedious inquiries that hinder productivity, allowing human agents to focus on more complex tasks. For customers, this means getting answers faster without waiting for human agents. Additionally, the service promises 24/7 availability for customer communication in natural language, with an easy handoff to human agents for more complicated issues. Businesses are increasingly turning to AI-based chatbots because, unlike traditional chatbots, they don’t rely on specific programmed queries and can understand context and nuance. Alongside Salesforce, other tech leaders like AWS and Google Cloud have released their own chatbots, such as Amazon Lex and Vertex AI, continuously enhancing their software. Recently, AWS updated its chatbot with the QnAIntent capability in Amazon Lex, allowing integration with a knowledge base in Amazon Bedrock. Similarly, Google released Vertex AI Agent Builder earlier this year, enabling organizations to build AI agents with no code, which can function together with one main agent and subagents. The AI arms race is just beginning, with more vendors developing software to meet market demands. For users, this means that while AI takes over many manual and tedious tasks, the primary challenge will be choosing the right vendor that best suits the needs and resources of their business. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 31, 2025in Data, Einstein 1 Platform, Google, Salesforce, Technology
AI Agents in Government
30Jan

AI Agents in Government

AI Agents: A Key to Rebuilding Public Trust in Government Public trust in government services has been in decline for years, but new research from Salesforce suggests that AI agents could play a crucial role in reversing this trend. Citizens worldwide recognize the need for improved government interactions, with 40% reporting difficulties when seeking assistance and over a third unsure of the programs available to them. However, there is strong public support for AI-driven solutions—90% of global respondents indicated they would use an AI agent to engage with their government. AI Agents: A Game-Changer for Public Services The introduction of AI-powered agents presents a transformative opportunity for governments to enhance service delivery, improve response times, and build stronger constituent relationships. With budget constraints making it difficult to expand government workforces, AI agents can augment public servants, allowing them to operate more efficiently without increasing headcount. Imagine a trip to the AI Agent DMV! “It is clear from our research that AI solutions like Salesforce’s Agentforce can help governments streamline and scale services to better meet the needs of their constituents,” says Nasi Jazayeri, Executive Vice President and GM of Public Sector at Salesforce. “As global leaders convene in Davos, we have a tremendous opportunity for the public and private sectors to collaborate and explore how advancements in AI can improve how governments serve their citizens.” Key Findings from Salesforce’s Research Citizens Call for Improved Government Services Growing Public Interest in AI Agents Top Priorities for AI-Driven Government Services When considering AI adoption in public services, global respondents prioritize: The Future of AI in Government As AI technology continues to evolve, its important role in the public sector is becoming increasingly significant. By enhancing accessibility, streamlining processes, and providing real-time assistance, AI-powered agents can help bridge the trust gap between governments and their constituents. With strong public support, governments have a unique opportunity to leverage AI to build more responsive, efficient, and citizen-friendly services—ushering in a new era of digital governance. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 30, 2025in Agentforce Platform, Agentic AI, Generative AI, Public Sector Solutions, Salesforce, Technology
AI Agents as Tools of Trust
29Jan

Reviving Cold Leads with AI Agents

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

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January 29, 2025in Data, Technology

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