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Payload and REDA One Launch REDA Pay Embedded Payment Solution Payload has unveiled REDA Pay, an embedded payment solution tailored for Salesforce users. This new offering stems from a strategic partnership between Payload and REDA One, aiming to streamline and enhance payment processes for businesses. “REDA One needed a payment solution that could be deployed quickly, efficiently, and effectively to expand their platform’s capabilities,” said Zach Jacob, Vice President of Partnerships at Payload. “Payload’s robust APIs proved to be the perfect match, seamlessly integrating with REDA One’s existing infrastructure." Jacob emphasized the ease and speed of implementation, noting, “In no time, REDA One was able to activate REDA Pay, demonstrating the simplicity and adaptability of our payment tools. This collaboration underscores Payload’s commitment to delivering powerful, straightforward solutions that enable SaaS platforms like REDA One to provide cutting-edge payment experiences without unnecessary complexity.” The Growing Role of Embedded Payments Highlighting the importance of embedded payments, Jacob stated, “In today’s digital era, embedded payments are not just a feature—they are an essential element of an exceptional user experience.” With REDA Pay, Salesforce users can now process payments seamlessly within their workflows, reducing friction and enhancing efficiency. Jacob outlined three core advantages of REDA Pay: Intuitive Experience: “Users can send and receive payments directly within the platform, boosting productivity and convenience.” Security: “Built to the highest industry standards, our solutions protect every transaction with advanced security measures.” Scalability and Flexibility: “As REDA One’s customers grow, REDA Pay will evolve to meet their changing requirements.” Elevating SaaS Platforms Jacob also highlighted the broader impact of this launch for SaaS providers: “REDA Pay exemplifies how effortlessly SaaS platforms can elevate their offerings by integrating embedded payment solutions. Payload’s APIs are designed for seamless integration, enabling platforms to quickly add enhanced payment capabilities for their users. This not only improves the user experience but also unlocks new opportunities for growth and revenue.” With REDA Pay, Payload and REDA One have set a new standard for embedded payment solutions in Salesforce, driving innovation and efficiency for businesses in the digital age.

Payload and REDA

Payload and REDA One Launch REDA Pay Embedded Payment Solution Payload has unveiled REDA Pay, an embedded payment solution tailored for Salesforce users. This new offering stems from a strategic partnership between Payload and REDA One, aiming to streamline and enhance payment processes for businesses. “REDA One needed a payment solution that could be deployed quickly, efficiently, and effectively to expand their platform’s capabilities,” said Zach Jacob, Vice President of Partnerships at Payload. “Payload’s robust APIs proved to be the perfect match, seamlessly integrating with REDA One’s existing infrastructure.” Jacob emphasized the ease and speed of implementation, noting, “In no time, REDA One was able to activate REDA Pay, demonstrating the simplicity and adaptability of our payment tools. This collaboration underscores Payload’s commitment to delivering powerful, straightforward solutions that enable SaaS platforms like REDA One to provide cutting-edge payment experiences without unnecessary complexity.” The Growing Role of Embedded Payments Highlighting the importance of embedded payments, Jacob stated, “In today’s digital era, embedded payments are not just a feature—they are an essential element of an exceptional user experience.” With REDA Pay, Salesforce users can now process payments seamlessly within their workflows, reducing friction and enhancing efficiency. Jacob outlined three core advantages of REDA Pay: Elevating SaaS Platforms Jacob also highlighted the broader impact of this launch for SaaS providers:“REDA Pay exemplifies how effortlessly SaaS platforms can elevate their offerings by integrating embedded payment solutions. Payload’s APIs are designed for seamless integration, enabling platforms to quickly add enhanced payment capabilities for their users. This not only improves the user experience but also unlocks new opportunities for growth and revenue.” With REDA Pay, Payload and REDA One have set a new standard for embedded payment solutions in Salesforce, driving innovation and efficiency for businesses in the digital age. 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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Speed to Launch of Agentforce

Speed to Launch of Agentforce

Agentforce isn’t just another AI platform that requires months of customization. At most customers, they quickly saw its power, launching transformative generative AI experiences in just days—no AI engineers needed. For companies with larger admin teams, the benefits can be even greater. Unlike other platforms, Agentforce places a strong emphasis on data privacy, building on the trust that Salesforce is known for, making these virtual assistants invaluable. We began with employee-facing use cases, saving our team several hours per week. Now, with Agentforce, we’re seeing even more opportunities to drive efficiencies and better serve our customers. “We’re excited to leverage Agentforce to completely overhaul recruitment and enrollment at Unity Environmental University. Instead of traditional forms or chatbots, our students will soon engage with an autonomous recruitment agent directly on our website, offering personalized support throughout the college application process.”– Dr. Melik Khoury, President & CEO, Unity Environmental University “For first-generation college students, the 1:385 coach-to-student ratio makes personalized guidance challenging. By integrating Agentforce into our platform, we’re deploying cutting-edge solutions to better support students. These agents enable our coaches to focus on high-touch, personalized experiences while handling vital tasks like sharing deadlines and answering common questions—24/7.”– Siva Kumari, CEO, College Possible “Agentforce offers organizations a unique opportunity to move beyond incremental improvements and achieve exponential ROI. By automating customer interactions, improving outcomes, and reducing costs, it integrates data, flows, and user interfaces to mitigate risks and accelerate value creation. This agent-based platform approach allows businesses to harness AI’s full potential, revolutionizing customer engagement and paving the way for exponential growth.”– Rebecca Wettemann, CEO and Principal Analyst, Valoir “Autonomous agents powered by Salesforce’s Agentforce are revolutionizing customer experiences by providing fast, accurate, and personalized support around the clock. With advanced AI making decisions and taking actions autonomously, businesses can resolve customer issues more efficiently, fostering deeper interactions and enhancing satisfaction. This innovation enables companies to reallocate human resources to more complex tasks, boosting individual productivity and scaling business growth. Agentforce is setting new standards for seamless sales, service, marketing, and commerce interactions, reinforcing its leadership in customer experience.”– Michael Fauscette, CEO and Chief Analyst, Arion Research LLC “The best way to predict the future is to invent it.” — Alan Kay, Computer Science Pioneer Technology progresses in what biologists call punctuated equilibrium, with new capabilities slowly emerging from labs and tinkerers until a breakthrough shifts the axis of possibility. These pioneering feats create new paradigms, unleashing waves of innovation—much like the Apple Macintosh, the iPhone, and the Salesforce Platform, which revolutionized the enterprise software-as-a-service (SaaS) model and sparked an entire industry. The Age of Agentforce Begins At Dreamforce 2024, Salesforce Futures reflected on the launch of Agentforce, inspired by visions like the Apple Knowledge Navigator. In 2023, we used this inspiration to craft our Salesforce 2030 film, which showcased the collaboration between humans and autonomous AI agents. Now, with Agentforce, we’re witnessing that vision come to life. Agentforce is a suite of customizable AI agents and tools built on the Salesforce Platform, offering an elegant solution to the complexity of AI deployment. It addresses the challenges of integrating data, models, infrastructure, and applications into a unified system. With powerful tools like Agent Builder and Model Builder, organizations can easily create, customize, and deploy AI agents. Salesforce’s Atlas Reasoning Engine empowers these agents to handle both routine and complex tasks autonomously. A New Era of AI Innovation At Dreamforce 2024, over 10,000 attendees raced to build their own agents using the “Agent Builder” experience, turning verbal instructions into fully functioning agents in under 15 minutes. This wasn’t just another chatbot—it’s a new breed of AI that could transform how businesses operate and deliver superior customer experiences. Companies like Saks, OpenTable, and Wiley have quickly embraced this technology. As Mick Costigan and David Berthy of Salesforce Futures explain, “When we see signals like this, it pushes us toward the future. Soon, we’ll see complex, multi-agent systems solving higher-order challenges, both in the enterprise and in consumer devices.” Shaping the Future Agentforce isn’t just a product—it’s a platform for experimentation. With hundreds of thousands of Salesforce customers soon gaining access, the full potential of these tools will unfold in ways we can’t yet imagine. As with every major technological shift, the real magic will lie in how people use it. Every interaction, every agent deployed, and every problem solved will shape the future in unexpected ways. Platform Evolution Adam Evans, Salesforce SVP of Product, notes that Agentforce builds on the company’s transformation over the past four years, following the pattern of Salesforce’s original disruption of enterprise software. Unlike traditional solutions, Agentforce eliminates the need for customers to build their own AI infrastructure, providing a ready-to-use solution. At the core of Agentforce is the Atlas Reasoning Engine, delivering results that are twice as relevant and 33% more accurate than competing solutions. This engine integrates Salesforce Data Cloud, Flow for automation, and the Einstein Trust Layer for governance. Early Customer Results Early Agentforce deployments highlight how organizations are using autonomous agents to enhance, rather than replace, human workers: George Pokorny, Senior VP of Global Customer Success at OpenTable, shared, “Just saving two minutes on a ten-minute call lets our service reps focus on strengthening customer relationships, thanks to seamless integration with Service Cloud, giving us a unified view of diner preferences and history.” 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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Government CRM System

Salesforce Announces Top Secret Gov Cloud

This advanced cloud solution is hosted on Amazon Web Services’ Top Secret cloud infrastructure. According to Salesforce’s press release, Government Cloud Premium is built with an API-first architecture, enabling agencies to leverage other data sources and systems, including proprietary AI applications, to enhance mission-critical operations.

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Digital Transformation and Security Challenges

Digital Transformation and Security Challenges

Agencies Accelerate Digital Transformation Amid Growing Security Demands Federal agencies are ramping up digital transformation initiatives to meet evolving public expectations and comply with mandates like the 21st Century Integrated Digital Experience Act (IDEA). However, securely transitioning to modern platforms like Salesforce requires specialized expertise, as highlighted in a new e-book by Own Company. The push for digital transformation is driven by the need to deliver efficient, modernized citizen services while safeguarding critical data. According to Federal Chief Information Officer Clare Martorana, agencies face a dual challenge: adopting advanced technologies and ensuring compliance with stringent security and regulatory frameworks. Salesforce, a leading SaaS platform, plays a pivotal role in these modernization efforts, offering tools to replace outdated systems and streamline operations. Yet, moving to such platforms involves more than migrating legacy data. Agencies must also address complex security requirements and ensure compliance with government regulations. To support secure transitions, companies like Own Company have emerged as key partners in federal digital transformation. Their solutions focus on secure development, data recovery, and long-term archiving. Tools like “Own Accelerate” enable safe and efficient testing within sandbox environments, while “Own Secure” leverages data classification and zero-trust principles to prevent security vulnerabilities. These measures mitigate risks such as insider threats and configuration errors, ensuring sensitive data remains protected throughout the transition process. Compliance with mandates like the Federal Information Security Management Act (FISMA) and National Institute of Standards and Technology (NIST) protocols remains a top priority. Agencies must safeguard citizen data across services ranging from healthcare to housing assistance while maintaining security and operational efficiency over the data’s lifecycle. Secure backups, compliance audits, and controlled data access are essential for building trust and resilience. As agencies incorporate AI into their operations, robust data strategies are becoming even more critical. AI-driven tools rely on accurate, real-time data for effective training and decision-making. Own’s backup and archiving solutions help agencies unlock data for AI applications while managing compliance and controlling storage costs. Ultimately, successful digital transformation requires more than adopting new technologies — it demands a careful balance of modernization, security, cost-efficiency, and alignment with agency missions. By acting decisively and addressing these challenges, federal agencies can meet rising public expectations while maintaining compliance and security. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI Agents and Digital Transformation

Inventing the Future of Agents

“The best way to predict the future is to invent it.” – Alan Kay, Computer Science PioneerOr, to channel Buzz Lightyear: “To infinity and beyond.” Inventing the Future of Agents The history of computing has always advanced in fits and starts, a pattern biologists call punctuated equilibrium. Revolutionary technologies emerge slowly—nurtured in research labs, garages, and the minds of visionaries—until the moment comes when a breakthrough shifts the axis of possibility. From there, a new paradigm takes shape, unleashing waves of innovation. Think of the Apple Macintosh, the iPhone, and Salesforce’s own Platform, which pioneered enterprise software-as-a-service (SaaS) and sparked an entirely new industry. Each of these milestones reshaped the way we live and work, setting the stage for even greater advances to come. Alan Kay: A Visionary for Computing’s Future One such paradigm-shifter was Alan Kay. In 1971, while working at Xerox PARC, Kay was immersed in an era when computers were room-sized behemoths. At the time, only four of these machines were connected to the fledgling ARPAnet, a precursor to today’s internet. Kay, a skilled musician with a deep appreciation for human-centered design, brought an empathetic and humanistic approach to innovation. In 1972, he introduced the Dynabook—a radical vision for personal computing that was decades ahead of its time. The Dynabook concept featured a battery-powered laptop with a touchscreen, wireless access to global information, and an interface so simple even children could use it. Kay and his team at PARC went on to develop many of the foundational elements of modern personal computing: overlapping windows, graphical user interfaces, and object-oriented programming. Later, while at Apple, Kay helped shape the vision for the groundbreaking 1987 Apple Knowledge Navigator video, which anticipated today’s iPad and iPhone. Agents and Humans: Driving Success Together Fast-forward to today, and we are on the cusp of another technological leap forward: AI agents. Much like Kay’s vision of personal computing, the emergence of intelligent, autonomous agents signals a new chapter in how humans and technology work together. Agentforce: Bringing the Future to the Present This interplay between visionary ideas and emerging technologies was on full display with the launch of Agentforce at Dreamforce 2024. A year earlier, at Dreamforce 2023, Salesforce Futures debuted its Salesforce 2030 film, drawing inspiration from Apple’s Knowledge Navigator. The film offered a glimpse into a world where humans collaborate seamlessly with autonomous AI agents—an aspirational vision of business transformed. Since then, the imagination gap between fiction and reality has narrowed. Salesforce’s work in Agentforce and publications like Personal AI Agents and Agents at Work have explored how agents are already changing business as we know it. These tools are bringing science fiction to life, enabling businesses to achieve unprecedented levels of efficiency, creativity, and success. A New Paradigm in Progress Like the Macintosh, the iPhone, or the Salesforce Platform, the rise of AI agents represents another transformative moment in computing history. By combining vision with technological breakthroughs, we are witnessing the dawn of a new era—one where humans and AI agents work together to push the boundaries of what’s possible. Alan Kay’s timeless wisdom rings true: the future isn’t something we wait for—it’s something we invent. With Agentforce, that future is already here. Inventing the Future of Agents. Are you ready to start Inventing the Future of Agents? 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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NetSuite Salesforce Collaboration

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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AI FOMO

AI FOMO

Enterprise interest in artificial intelligence has surged in the past two years, with boardroom discussions centered on how to capitalize on AI advancements before competitors do. Generative AI has been a particular focus for executives since the launch of ChatGPT in November 2022, followed by other major product releases like Amazon’s Bedrock, Google’s Gemini, Meta’s Llama, and a host of SaaS tools incorporating the technology. However, the initial rush driven by fear of missing out (FOMO) is beginning to fade. Business and tech leaders are now shifting their attention from experimentation to more practical concerns: How can AI generate revenue? This question will grow in importance as pilot AI projects move into production, raising expectations for financial returns. Using AI to Increase Revenue AI’s potential to drive revenue will be a critical factor in determining how quickly organizations adopt the technology and how willing they are to invest further. Here are 10 ways businesses can harness AI to boost revenue: 1. Boost Sales AI-powered virtual assistants and chatbots can help increase sales. For example, Ikea’s generative AI tool assists customers in designing their living spaces while shopping for furniture. Similarly, jewelry insurance company BriteCo launched a GenAI chatbot that reduced chat abandonment rates, leading to more successful customer interactions and potentially higher sales. A TechTarget survey revealed that AI-powered customer-facing tools like chatbots are among the top investments for IT leaders. 2. Reduce Customer Churn AI helps businesses retain clients, reducing revenue loss and improving customer lifetime value. By analyzing historical data, AI can profile customer attributes and identify accounts at risk of leaving. AI can then assist in personalizing customer experiences, decreasing churn and fostering loyalty. 3. Enhance Recommendation Engines AI algorithms can analyze customer data to offer personalized product recommendations. This drives cross-selling and upselling opportunities, boosting revenue. For instance, Meta’s AI-powered recommendation engine has increased user engagement across its platforms, attracting more advertisers. 4. Accelerate Marketing Strategies While marketing doesn’t directly generate revenue, it fuels the sales pipeline. Generative AI can quickly produce personalized content, such as newsletters and ads, tailored to customer interests. Gartner predicts that by 2025, 30% of outbound marketing messages will be AI-generated, up from less than 2% in 2022. 5. Detect Fraud AI is instrumental in detecting fraudulent activities, helping businesses preserve revenue. Financial firms like Capital One use machine learning to detect anomalies and prevent credit card fraud, while e-commerce companies leverage AI to flag fraudulent orders. 6. Reinvent Business Processes AI can transform entire business processes, unlocking new revenue streams. For example, Accenture’s 2024 report highlighted an insurance company that expects a 10% revenue boost after retooling its underwriting workflow with AI. In healthcare, AI could streamline revenue cycle management, speeding up reimbursement processes. 7. Develop New Products and Services AI accelerates product development, particularly in industries like pharmaceuticals, where it assists in drug discovery. AI tools also speed up the delivery of digital products, as seen with companies like Ally Financial and ServiceNow, which have reduced software development times by 20% or more. 8. Provide Predictive Maintenance AI-driven predictive maintenance helps prevent costly equipment downtime in industries like manufacturing and fleet management. By identifying equipment on the brink of failure, AI allows companies to schedule repairs and avoid revenue loss from operational disruptions. 9. Improve Forecasting AI’s predictive capabilities enhance planning and forecasting. By analyzing historical and real-time data, AI can predict product demand and customer behavior, enabling businesses to optimize inventory levels and ensure product availability for ready-to-buy customers. 10. Optimize Pricing AI can dynamically adjust prices based on factors like demand shifts and competitor pricing. Reinforcement learning algorithms allow businesses to optimize pricing in real time, ensuring they maximize revenue even as market conditions change. Keeping ROI in Focus While AI offers numerous ways to generate new revenue streams, it also introduces costs in development, infrastructure, and operations—some of which may not be immediately apparent. For instance, research from McKinsey & Company shows that GenAI models account for only 15% of a project’s total cost, with additional expenses related to change management and data preparation often overlooked. To make the most of AI, organizations should prioritize use cases with a clear return on investment (ROI) and postpone those that don’t justify the expense. A focus on ROI ensures that AI deployments align with business goals and contribute to sustainable revenue growth. 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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What Should Enterprises Build with Agentic AI?

What Should Enterprises Build with Agentic AI?

The rise of agentic AI has dominated recent discussions in enterprise technology, sparking debates over its transformative potential and practical applications. Just weeks ago, few had heard of the term. Now, every tech vendor is racing to stake their claim in this emerging space, positioning agentic AI as the successor to AI co-pilots. While co-pilots assist users with tasks, agentic AI represents the next step: delegating tasks to intelligent agents capable of independent execution, akin to assigning work to a junior colleague. But beyond the buzz, the pressing questions remain: Cutting Through the Hype Recent launches provide a snapshot of how enterprises are beginning to deploy agentic AI. Salesforce’s Agentforce, Asana’s AI Studio, and Atlassian’s Rovo AI Assistant all emphasize the ability of these agents to streamline workflows by interpreting unstructured data and automating complex tasks. These tools promise flexibility over previous rigid, rule-based systems. For example, instead of painstakingly scripting every step, users can instruct an agent to “follow documented policies, analyze data, and propose actions,” reserving human approval for final execution. However, the performance of these agents hinges on data quality and system robustness. Salesforce’s Marc Benioff, for instance, critiques Microsoft’s Copilot for lacking a robust data model, emphasizing Salesforce’s own structured approach as a competitive edge. Similarly, Asana and Atlassian highlight the structured work graphs underpinning their platforms as critical for accurate and reliable outputs. Key Challenges Despite the promise, there are significant challenges to deploying agentic AI effectively: Early Wins and Future Potential Early adopters are seeing value in high-volume, repetitive scenarios such as customer service. For example: However, these successes represent low-hanging fruit. The true promise lies in rethinking how enterprises work. As one panelist at Atlassian’s event noted: “We shouldn’t just use this AI to enhance existing processes. We should ask whether these are the processes we want for the future.” The Path Forward The transformative potential of agentic AI will depend on broader process standardization. Just as standardized shipping containers revolutionized logistics, and virtual containers transformed IT operations, similar breakthroughs in process design could unlock exponential gains for AI-driven workflows. For now, enterprises should: Conclusion Agentic AI holds immense potential, but its real power lies in enabling enterprises to question and redesign how work gets done. While it may still be in its early days, businesses that align their AI investments with strategic goals—and not just immediate fixes—will be best positioned to thrive in this new era of intelligent automation. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Scaling Generative AI

Scaling Generative AI

Many organizations follow a hybrid approach to AI infrastructure, combining public clouds, colocation facilities, and on-prem solutions. Specialized GPU-as-a-service vendors, for instance, are becoming popular for handling high-demand AI computations, helping businesses manage costs without compromising performance. Business process outsourcing company TaskUs, for example, focuses on optimizing compute and data flows as it scales its gen AI deployments, while Cognizant advises that companies distinguish between training and inference needs, each with different latency requirements.

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AI Risk Management

AI Risk Management

Organizations must acknowledge the risks associated with implementing AI systems to use the technology ethically and minimize liability. Throughout history, companies have had to manage the risks associated with adopting new technologies, and AI is no exception. Some AI risks are similar to those encountered when deploying any new technology or tool, such as poor strategic alignment with business goals, a lack of necessary skills to support initiatives, and failure to secure buy-in across the organization. For these challenges, executives should rely on best practices that have guided the successful adoption of other technologies. In the case of AI, this includes: However, AI introduces unique risks that must be addressed head-on. Here are 15 areas of concern that can arise as organizations implement and use AI technologies in the enterprise: Managing AI Risks While AI risks cannot be eliminated, they can be managed. Organizations must first recognize and understand these risks and then implement policies to minimize their negative impact. These policies should ensure the use of high-quality data, require testing and validation to eliminate biases, and mandate ongoing monitoring to identify and address unexpected consequences. Furthermore, ethical considerations should be embedded in AI systems, with frameworks in place to ensure AI produces transparent, fair, and unbiased results. Human oversight is essential to confirm these systems meet established standards. For successful risk management, the involvement of the board and the C-suite is crucial. As noted, “This is not just an IT problem, so all executives need to get involved in this.” 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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salesforce ai pitchfield

Salesforce AI Pitchfield

AI Pitchfield is more than a showcase of entrepreneurial talent—it’s a launchpad for the next generation of AI pioneers. By fostering connections and providing critical investment opportunities, Salesforce and its partners are driving the evolution of AI across India and Southeast Asia. This initiative reflects Salesforce’s commitment to advancing technology, empowering startups, and shaping a future where AI continues to transform industries and unlock untapped potential.

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Salesforce Government Cloud Premium

Salesforce Government Cloud Premium

Software company Salesforce announced on Monday that it has rolled out a new version of its government cloud that has Top Secret authorization and is geared toward U.S. national security agencies and intelligence organizations.

The new offering, called Government Cloud Premium, is hosted on Amazon Web Services’ Top Secret cloud.

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Cohesity Data Explore

Cohesity has introduced Data Explore, a new feature in its Gaia generative AI platform, aimed at simplifying data search within backups for any employee. The update, launched this week, adds keyword search capabilities and data visualization through topic word clouds, enhancing user access to valuable information. Previously, users could interact with Gaia’s conversational AI interface to ask questions about stored data. Data Explore now extends this by enabling users to browse frequent keywords within data sets and receive search suggestions to help refine their queries. This addition is particularly valuable for users who may not know exactly what to ask when exploring backup data. As part of the update, Gaia’s support for file storage systems has also expanded. Gaia now integrates with both on-premises and cloud-based file servers, such as Dell Technologies’ PowerScale and NetApp systems, in addition to existing support for Microsoft 365 services like Outlook, SharePoint, and OneDrive. This enhanced search functionality reflects a broader trend among backup vendors to deliver greater utility from stored data, according to Simon Robinson of TechTarget’s Enterprise Strategy Group. He noted that tools making data accessible to non-experts bring businesses closer to the goal of actionable insights. “You don’t need to be a corporate librarian to use this stuff,” Robinson said. Data Explore’s semantic indexing, similar to internet search engines, aids users by automatically surfacing keywords, questions, and suggestions, making backup data more searchable and actionable. According to Krista Case, an analyst at Futurum Group, this helps reduce AI hype by grounding Gaia in practical use cases, facilitating faster insights for end users. Since Gaia’s launch as a SaaS add-on for Cohesity Data Cloud, its features have evolved to offer deeper insights beyond simple chatbot interactions. Greg Statton, Cohesity’s VP of AI solutions, shared that the platform aims to be more than a support agent for backup queries. The vision is to provide advanced AI tools that enhance data discovery, flag abnormal events, and reduce alert fatigue, giving IT administrators actionable intelligence that is more contextually aware of their tasks. Ultimately, Cohesity’s Data Explore feature exemplifies generative AI’s potential in unlocking business value from backup data. By making this data accessible and understandable, Cohesity is helping organizations achieve the long-awaited promise of deriving value from stored data – a milestone Robinson believes backup vendors are now on the verge of realizing. 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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Generative AI Energy Consumption Rises

Generative AI Energy Consumption Rises

Generative AI Energy Consumption Rises, but Impact on ROI Unclear The energy costs associated with generative AI (GenAI) are often overlooked in enterprise financial planning. However, industry experts suggest that IT leaders should account for the power consumption that comes with adopting this technology. When building a business case for generative AI, some costs are evident, like large language model (LLM) fees and SaaS subscriptions. Other costs, such as preparing data, upgrading cloud infrastructure, and managing organizational changes, are less visible but significant. Generative AI Energy Consumption Rises One often overlooked cost is the energy consumption of generative AI. Training LLMs and responding to user requests—whether answering questions or generating images—demands considerable computing power. These tasks generate heat and necessitate sophisticated cooling systems in data centers, which, in turn, consume additional energy. Despite this, most enterprises have not focused on the energy requirements of GenAI. However, the issue is gaining more attention at a broader level. The International Energy Agency (IEA), for instance, has forecasted that electricity consumption from data centers, AI, and cryptocurrency could double by 2026. By that time, data centers’ electricity use could exceed 1,000 terawatt-hours, equivalent to Japan’s total electricity consumption. Goldman Sachs also flagged the growing energy demand, attributing it partly to AI. The firm projects that global data center electricity use could more than double by 2030, fueled by AI and other factors. ROI Implications of Energy Costs The extent to which rising energy consumption will affect GenAI’s return on investment (ROI) remains unclear. For now, the perceived benefits of GenAI seem to outweigh concerns about energy costs. Most businesses have not been directly impacted, as these costs tend to affect hyperscalers more. For instance, Google reported a 13% increase in greenhouse gas emissions in 2023, largely due to AI-related energy demands in its data centers. Scott Likens, PwC’s global chief AI engineering officer, noted that while energy consumption isn’t a barrier to adoption, it should still be factored into long-term strategies. “You don’t take it for granted. There’s a cost somewhere for the enterprise,” he said. Energy Costs: Hidden but Present Although energy expenses may not appear on an enterprise’s invoice, they are still present. Generative AI’s energy consumption is tied to both model training and inference—each time a user makes a query, the system expends energy to generate a response. While the energy used for individual queries is minor, the cumulative effect across millions of users can add up. How these costs are passed to customers is somewhat opaque. Licensing fees for enterprise versions of GenAI products likely include energy costs, spread across the user base. According to PwC’s Likens, the costs associated with training models are shared among many users, reducing the burden on individual enterprises. On the inference side, GenAI vendors charge for tokens, which correspond to computational power. Although increased token usage signals higher energy consumption, the financial impact on enterprises has so far been minimal, especially as token costs have decreased. This may be similar to buying an EV to save on gas but spending hundreds and losing hours at charging stations. Energy as an Indirect Concern While energy costs haven’t been top-of-mind for GenAI adopters, they could indirectly address the issue by focusing on other deployment challenges, such as reducing latency and improving cost efficiency. Newer models, such as OpenAI’s GPT-4o mini, are more economical and have helped organizations scale GenAI without prohibitive costs. Organizations may also use smaller, fine-tuned models to decrease latency and energy consumption. By adopting multimodel approaches, enterprises can choose models based on the complexity of a task, optimizing for both speed and energy efficiency. The Data Center Dilemma As enterprises consider GenAI’s energy demands, data centers face the challenge head-on, investing in more sophisticated cooling systems to handle the heat generated by AI workloads. According to the Dell’Oro Group, the data center physical infrastructure market grew in the second quarter of 2024, signaling the start of the “AI growth cycle” for infrastructure sales, particularly thermal management systems. Liquid cooling, more efficient than air cooling, is gaining traction as a way to manage the heat from high-performance computing. This method is expected to see rapid growth in the coming years as demand for AI workloads continues to increase. Nuclear Power and AI Energy Demands To meet AI’s growing energy demands, some hyperscalers are exploring nuclear energy for their data centers. AWS, Google, and Microsoft are among the companies exploring this option, with AWS acquiring a nuclear-powered data center campus earlier this year. Nuclear power could help these tech giants keep pace with AI’s energy requirements while also meeting sustainability goals. I don’t know. It seems like if you akin AI accessibility to more nuclear power plants you would lose a lot of fans. As GenAI continues to evolve, both energy costs and efficiency are likely to play a greater role in decision-making. PwC has already begun including carbon impact as part of its GenAI value framework, which assesses the full scope of generative AI deployments. “The cost of carbon is in there, so we shouldn’t ignore it,” Likens said. Generative AI Energy Consumption Rises 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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