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Predictive Analytics
09Sep

Predictive Analytics

Industry forecasts predict an annual growth rate of 6% to 7%, fueled by innovations in cloud computing, artificial intelligence (AI), and data engineering. In 2023, the global data analytics market was valued at approximately $41 billion and is expected to surge to $118.5 billion by 2029, with a compound annual growth rate (CAGR) of 27.1%. This significant expansion reflects the growing demand for advanced analytics tools that provide actionable insights. AI has notably enhanced the accuracy of predictive models, enabling marketers to anticipate customer behaviors and preferences with impressive precision. “We’re on the verge of a new era in predictive analytics, with tools like Salesforce Einstein Data Analytics revolutionizing how we harness data-driven insights to transform marketing strategies,” says Koushik Kumar Ganeeb, a Principal Member of Technical Staff at Salesforce Data Cloud and a distinguished Data and AI Architect. Ganeeb’s leadership spans initiatives like AI-powered Salesforce Einstein Data Analytics, Marketing Cloud Connector for Data Cloud, and Intelligence Reporting (Datorama). His expertise includes architecting vast data extraction pipelines that process trillions of transactions daily. These pipelines play a crucial role in the growth strategies of Fortune 500 companies, helping them scale their data operations efficiently by leveraging AI. Ganeeb’s visionary work has propelled Salesforce Einstein Data Analytics into the forefront of business intelligence. Under his guidance, the platform’s advanced capabilities—such as predictive modeling, real-time data analysis, and natural language processing—are now pivotal in transforming how businesses forecast trends, personalize marketing efforts, and make data-driven decisions with unprecedented precision. AI and Machine Learning: The Next Frontier Beginning in 2018, Salesforce Marketing Cloud, a leading engagement platform used by top enterprises, faced challenges in extracting actionable insights and enhancing AI capabilities from rapidly growing data across diverse systems. Ganeeb was tasked with overcoming these hurdles, leading to the development of the Salesforce Einstein Provisioning Process. This process involved the creation of extensive data import jobs and the establishment of standardized patterns based on consumer adoption learning. These automated jobs handle trillions of transactions daily, delivering critical engagement and profile data in real-time to meet the scalability needs of large enterprises. The data flows seamlessly into AI models that generate predictions on a massive scale, such as Engagement Scores and insights into messaging and language usage across the platform. “Integrating AI and machine learning into data analytics through Salesforce Einstein is not just a technological enhancement—it’s a revolutionary shift in how we approach data,” explains Ganeeb. “With our advanced predictive models and real-time data processing, we can analyze vast amounts of data instantly, delivering insights that were previously unimaginable.” This innovative approach empowers organizations to make more informed decisions, driving unprecedented growth and operational efficiency. Real-World Success Stories Under Ganeeb’s technical leadership, Salesforce Einstein Data Analytics has delivered remarkable results across industries by leveraging AI and machine learning to provide actionable insights and enhance business performance. In the past year, leading companies like T-Mobile, Fitbit, and Dell Technologies have reported significant improvements after integrating Einstein. Ganeeb’s proficiency in designing and scaling data engineering solutions has been critical in helping these enterprises optimize performance. “Scalability with Salesforce Einstein Data Analytics goes beyond managing data volumes—it ensures that every data point is converted into actionable insights,” says Ganeeb. His work processing petabytes of data daily underscores his commitment to precision and efficiency in data engineering. Navigating Data Ethics and Quality Despite the rapid growth of predictive analytics, Ganeeb emphasizes the importance of data ethics and quality. “The accuracy of predictive models depends on the integrity of the data,” he notes. Salesforce Einstein Data Analytics addresses this by curating datasets to ensure they are representative and free from bias, maintaining trust while delivering reliable insights. By implementing rigorous data quality checks and ethical considerations, Ganeeb ensures that Einstein Analytics not only delivers actionable insights but also fosters transparency and trust. This balanced approach is key to the responsible use of predictive analytics across various industries. Future Trends in Predictive Analytics The future of predictive analytics looks bright, with AI and machine learning poised to further refine the accuracy and utility of predictive models. “Success lies in embracing technological advancements while maintaining a human touch,” Ganeeb notes. “By combining AI-driven insights with human intuition, businesses can navigate market complexities and uncover new opportunities.” Ganeeb’s contributions to Salesforce Einstein Data Analytics exemplify this balanced approach, integrating cutting-edge technology with human insight to empower businesses to make strategic decisions. His work positions organizations to thrive in a data-driven world, helping them stay agile and competitive in an evolving market. Balancing Benefits and Challenges – Predictive Analytics While predictive analytics offers vast potential, Ganeeb recognizes the challenges. Ensuring data quality, addressing ethical concerns, and maintaining transparency are crucial for its responsible use. “Although challenges remain, the future of AI-based predictive analytics is promising,” Ganeeb asserts. His work with Salesforce Einstein Data Analytics continues to push the boundaries of marketing analytics, enabling businesses to harness the power of AI for transformative 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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September 9, 2024in Salesforce Data Cloud, Salesforce Einstein, Salesforce Marketing Cloud
Salesforce AI Agents Explained
09Sep

Salesforce AI Agents Explained

Salesforce’s AI Agents: Revolutionizing Enterprise Sales and Service for the Future In the rapidly evolving landscape of artificial intelligence (AI), Salesforce continues to lead the charge, transforming enterprise operations with cutting-edge AI agents. With the introduction of Agentforce, Salesforce is not just enhancing sales and service departments but reshaping business processes across sectors. This comprehensive exploration highlights how Salesforce’s AI agents are changing the game, offering enterprise-level executives insights into their revolutionary potential. Salesforce AI Agents Explained. AI Agents: Beyond Autonomous Vehicles A fitting analogy to grasp the progression of AI agents is the evolution of autonomous vehicles. Just as self-driving cars advance from basic driver assistance to full autonomy, AI agents evolve from simple automation to more complex decision-making. Salesforce’s Chief Product Officer, David Schmaier, draws this comparison: “In the autonomous driving world, we have levels of autonomy, from level zero to level five. AI agents for enterprises follow a similar path.” At the core of this evolution is what Salesforce defines as the “agentic” phase of AI. Unlike generative AI that follows instructions to create content, agentic AI autonomously determines and takes actions based on broader goals. Schmaier notes, “We’re at the point where AI not only creates content but takes strategic actions. It’s like having an infinite pool of interns handling mundane tasks so human employees can focus on higher-value activities.” Agentforce: Salesforce’s Next-Generation AI Platform Agentforce is the latest addition to Salesforce’s AI arsenal, unveiled during their Q2 ’25 earnings call and now positioned as a significant milestone in AI development. With Agentforce, organizations can build and manage autonomous agents for tasks across various business functions—not just customer service. This versatility is highlighted by Marc Benioff, Salesforce’s CEO, who described the energy around Agentforce during a recent briefing as “palpable.” Agentforce builds on Salesforce’s data management, security, and customization expertise, uniting these capabilities into an AI framework. Schmaier explains, “It’s about creating trusted, enterprise-ready agents, not just deploying a large language model. We’ve developed over 100 out-of-the-box use cases, from sales account summaries to service reply recommendations, all customizable and easy to deploy.” Agentforce “In Every App” A key announcement is the integration of Agentforce in every app across Salesforce’s product suite, including Sales, Service, Marketing, and Commerce Agents. The Atlas reasoning engine, Agent Builder, and a partner network were also introduced to further enhance its capabilities. The Atlas Reasoning Engine acts as the “brain” behind Agentforce, autonomously generating plans and refining them based on actions it needs to perform, such as running business processes or engaging customers through preferred channels. What Makes an AI Agent? Salesforce AI Agents Explained Building an AI agent with Agentforce requires five key elements: These components leverage existing Salesforce infrastructure, making it easier for businesses to deploy agents through Agent Builder, which is part of the new Agentforce Studio. Agents vs. Chatbots Unlike traditional chatbots, which provide pre-programmed responses, Salesforce’s AI agents use large language models (LLMs) and generative AI to interpret and autonomously execute customer requests based on CRM data. This distinction allows AI agents to perform tasks that go beyond simple queries, driving efficiency in customer service, sales, and other business areas. Practical Applications: Sales, Service, and Marketing Salesforce’s AI agents offer tangible business benefits. For instance, Sales Agent, available as both a Sales Development Representative (SDR) and Sales Coach, automates lead nurturing and inquiry management. It utilizes CRM data to deliver personalized pitches, handle objections, and even suggest meeting times—freeing sales teams to focus on more strategic tasks. In customer service, AI agents manage routine inquiries, allowing human representatives to address more complex customer needs. In marketing, AI agents generate data-driven insights to personalize campaigns, improving customer engagement and conversion rates. The Security and Trust Foundation Security and trust remain core to Salesforce’s approach to AI. The Einstein Trust Layer ensures that data protection, privacy, and ethical guidelines are maintained throughout AI interactions. Schmaier emphasizes, “Our platform defines what data agents can access and how they use it, adhering to strict data integrity standards.” The Trust Layer also prevents AI from training on customer data without consent, ensuring transparency and security. A Partnership Between Humans and AI-Salesforce AI Agents Explained Salesforce’s vision emphasizes the synergy between human employees and AI agents. As Schmaier points out, “AI agents handle routine tasks and deliver insights, allowing employees to focus on more creative and strategic work.” This human-AI partnership boosts productivity and innovation, ultimately improving business outcomes. The Future of AI in Business As AI technology advances, Salesforce is already working on next-generation capabilities for Agentforce, including predictive analytics and more sophisticated autonomous agents. Schmaier forecasts, “These agents will handle a wider range of tasks and provide deeper insights and recommendations.” With Agentforce launching in October 2024, businesses can expect significant returns on investment, thanks to its cost-efficient model starting at $2 per conversation. In summary, Salesforce’s Agentforce is a game-changing innovation, blending AI and human intelligence to transform sales, service, and marketing. As more details unfold, it’s clear that Agentforce will redefine the future of business operations—driving efficiency, personalization, and strategic success. 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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September 9, 2024in Agentforce Platform, Generative AI, Technology
Salesforce and Qatalog
09Sep

Salesforce and Qatalog

Conversational AI for Salesforce Supercharge your Salesforce workflows with the power of AI. Whether you’re tracking deals, reviewing pipeline performance, or uncovering insights, Qatalog’s AI assistant simplifies it all with natural language queries. Designed to understand the intent behind your questions, it delivers accurate, context-rich answers—no manual reporting required. Whether you’re a Salesforce novice or a seasoned pro, Salesforce and Qatalog redefine how you engage with your CRM data. Key Features Salesforce and Qatalog Conversational Search Say goodbye to navigating complex dashboards and reports. Just ask straightforward questions like: Get instant, actionable answers powered by AI, saving time and effort. No Technical Expertise Needed Qatalog’s intuitive AI chat interface is designed for everyone. Non-technical users can quickly access insights without needing Salesforce expertise, freeing up technical teams to focus on higher-value tasks. Seamless Integrations Connect Salesforce with your favorite business tools, including Outlook, Google Drive, Slack, and more. Access Salesforce CRM data in context across your apps, streamlining workflows and collaboration. Enterprise-Grade Data Security Your data’s privacy is paramount. Qatalog processes Salesforce data securely in real-time and discards it immediately after use, ensuring sensitive information stays protected. Transform the way you work with Salesforce—ask, explore, and act with confidence using Qatalog’s Conversational AI. Salesforce and Qatalog. 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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September 9, 2024in Data, Enterprise, Google, Salesforce
US Comprehensive AI Legislation
09Sep

US Comprehensive AI Legislation

U.S. policymakers have yet to pass comprehensive AI legislation through Congress, but several AI-related bills are now making their way to the Senate floor, presenting new opportunities for regulation. In late July, the U.S. Senate Committee on Commerce, Science, and Transportation advanced eight AI-focused bills aimed at enhancing the transparency and safety of AI systems. These bills also target AI-generated deepfakes—false images, audio, and videos. Since the launch of OpenAI’s ChatGPT in late 2022, regulating AI has become a key issue at both federal and state levels. This week, California lawmakers advanced SB 1047, a bill requiring safety testing for AI models, which is awaiting Governor Gavin Newsom’s signature. Most of the bills before the Senate center on innovation, research, and safety, with only one— the Artificial Intelligence Research, Innovation, and Accountability Act—introducing penalties for non-compliance. “Voluntary guidance and standards can help companies develop safer, more responsible AI, but without binding requirements, the real impact is unlikely,” said Enza Iannopollo, an analyst at Forrester Research. However, Hodan Omaar, a senior policy manager at the Center for Data Innovation, praised the Senate’s emphasis on AI research and innovation, expressing optimism about the progress being made. Here’s a look at the key AI bills up for consideration after Congress returns from summer recess: 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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September 9, 2024in Salesforce
Slack Expands AI Features
08Sep

Slack Expands AI Features

Slack is introducing several new AI-driven features, including the integration of AI-powered agents from Salesforce and other leading partners across the platform. The Big Picture: As part of its evolution, the Salesforce-owned company aims to position Slack as a hub where humans collaborate seamlessly with an increasing number of bots and AI agents. Key Updates: Ahead of Salesforce’s Dreamforce conference, Slack announced its support for agents from partners such as Adobe, Anthropic, Cohere, Perplexity, Writer, and more, alongside Salesforce’s own Agentforce. Additionally, Slack is enhancing its AI capabilities, expanding its AI-driven transcription features to include informal video chat sessions, known as “huddles.” Why It Matters: This move aligns with Salesforce’s broader strategy of leveraging generative AI to power autonomous agents that can take independent action, moving beyond the traditional role of AI as a co-pilot merely assisting humans. What They’re Saying: “Slack’s vision of becoming an AI-powered work operating system fits perfectly with the growing role of agents in the workplace,” said Slack CEO Denise Dresser in a statement to Axios. While Dresser didn’t disclose how many paying customers have adopted Slack’s AI features, it’s worth noting that these features require a separate monthly fee. Initially, Slack planned to require companies to pay for AI features for all users or none, but the company later shifted this approach following customer feedback. And Slack Expands AI Features with New Agent Integrations Slack is introducing several new AI-driven features, including the integration of AI-powered agents from Salesforce and other leading partners across the platform. The Big Picture: As part of its evolution, the Salesforce-owned company aims to position Slack as a hub where humans collaborate seamlessly with an increasing number of bots and AI agents. Key Updates: Ahead of Salesforce’s Dreamforce conference, Slack announced its support for agents from partners such as Adobe, Anthropic, Cohere, Perplexity, Writer, and more, alongside Salesforce’s own Agentforce. Additionally, Slack is enhancing its AI capabilities, expanding its AI-driven transcription features to include informal video chat sessions, known as “huddles.” Why It Matters: This move aligns with Salesforce’s broader strategy of leveraging generative AI to power autonomous agents that can take independent action, moving beyond the traditional role of AI as a co-pilot merely assisting humans. What They’re Saying: “Slack’s vision of becoming an AI-powered work operating system fits perfectly with the growing role of agents in the workplace,” said Slack CEO Denise Dresser in a statement to Axios. While Dresser didn’t disclose how many paying customers have adopted Slack’s AI features, it’s worth noting that these features require a separate monthly fee. Initially, Slack planned to require companies to pay for AI features for all users or none, but the company later shifted this approach following customer feedback. 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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September 8, 2024in Generative AI
AI in Performance Management
08Sep

AI in Performance Management

AI in Performance Management: Benefits and Use Cases AI is making its way into all aspects of the workplace, and performance management is no exception. While the technology can streamline performance reviews and enhance feedback quality, HR leaders should be mindful of potential drawbacks, such as impersonal or overly generic feedback. Here’s a look at how AI can be used in performance management, along with its advantages and some challenges to consider. 4 Benefits of Using AI in Performance Management AI can offer several advantages for companies in terms of improving employee feedback and overall performance. Here are four key benefits: 1. Faster Employee Feedback Creation AI can help managers draft initial feedback for employees, saving time and effort. By setting parameters like years in the role or specific job metrics, AI-generated feedback can be more accurate. However, managers should review and personalize the feedback to ensure it feels relevant and human. 2. Enhanced Feedback Quality AI tools can analyze performance review drafts, identifying issues like repetitive wording, biased language, or inappropriate tone. By refining the text, AI helps managers deliver more thoughtful and effective feedback. 3. Better Reporting and Dashboards AI can analyze performance data and generate reports or dashboards, providing senior leaders and HR teams with a clear overview of employee performance. This capability is especially useful for large companies with substantial data, helping decision-makers track progress and identify trends. 4. Boosted Employee Performance By simplifying the review process, AI can encourage managers to provide feedback more frequently. Regular, timely feedback keeps employees focused, motivated, and aligned with company goals, enhancing their development and overall experience. 4 Use Cases for AI in Performance Management AI’s role in performance management goes beyond feedback creation. Here are four specific ways AI can streamline the process: 1. Employee Data Analysis AI can aggregate and analyze various employee data sources—such as past performance reviews or internal communications—summarizing key insights for managers. This saves time spent on manual data gathering, though managers should still verify the data and focus on the most relevant information. 2. Generating Discussion Topics AI can generate discussion prompts for managers to use in one-on-one meetings with employees, such as future career goals or project challenges. While this saves time, managers should tailor the AI suggestions to the individual employee to ensure relevance. 3. Career Path Generation AI can suggest potential career paths for employees, pointing out skills or training required for advancement. While helpful, managers should rely on company-specific career progression frameworks when available, as these tend to be more tailored to the organization’s needs. 4. Feedback Reminders AI can automatically remind managers to provide feedback to their direct reports, helping maintain a regular cadence of performance reviews. Additionally, AI can flag anomalies in feedback frequency, ensuring that employees receive consistent input throughout the year. Key Takeaways for HR Leaders While AI can significantly enhance the efficiency and effectiveness of performance management, it’s essential to remember that human oversight is critical. AI can automate processes and improve feedback, but managers should always review AI-generated content for accuracy and appropriateness to maintain a personal connection with their employees. By leveraging AI thoughtfully, companies can improve performance management processes, offer more frequent feedback, and drive better employee outcomes. 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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September 8, 2024in Salesforce
Product Cultural Relevance
08Sep

Product Cultural Relevance

Technology discussions often center around quantifiable metrics such as daily or monthly active users, impressions, and click-through rates. However, one area that tends to be underrepresented is the cultural relevance of a product. The most impactful products are not necessarily those with the largest reach or the most polished features. Instead, they often represent a snapshot of a specific moment in time—messy, unpolished, and even unworkable by today’s standards—but they capture the essence of what a platform was, is, or could be. For instance, 4Chan attracts individuals with poor social skills, while MySpace nostalgically signals that its users are over 25. TikTok Shop has become synonymous with scams, and transactions conducted exclusively in Bitcoin often carry a dubious connotation. These products, while varied, share a common thread: culture imbues them with modern-day context, enabling them to spread rapidly throughout society. The hallmark of a culturally successful platform is its ability to transcend its original design. Content from the platform often becomes representative of the app itself, with even a screenshot of the user interface communicating context to someone who has never used the app. Take Pinterest, for example. Users frequently save screenshots from other platforms, and Pinterest itself pushes users to create videos that can be shared on TikTok. There’s a cultural interchange between platforms—TikTok-branded posts on Pinterest, tweets used in memes, and BeReal’s demand for authenticity all reinforce this idea. BeReal memes, in particular, have gained traction because they capture not just the bizarre moments within the app but also the cultural expectation of authenticity. Cultural relevance extends to past platforms as well. MySpace’s “Top 10 Friends” feature still resonates today, demonstrating that some features become lasting cultural markers, even after the platform itself fades. This phenomenon even applies to non-social media platforms like Cash App and Venmo, both of which have earned reputations that transcend their functional purpose. Cash App became known for enabling questionable activities, such as buying drugs, while Venmo was linked to political scandals, simply because of how its features were used. The platforms themselves could be replaced, but the cultural legacies they’ve created are irreplaceable. Consider apps like Ask.fm or After School, which became infamous for promoting bullying. These apps, though damaging, also became cultural markers of growing up in an interconnected world. They reflect how young people learned about others’ brutal opinions, often anonymously. There’s an interesting emotion tied to the revival of old products. Many times, new apps are merely nostalgic reconceptualizations of software long past its prime, like MySpace knock-offs or iPhone Tamagotchis. While they may elicit some emotional response, they often fail to carry the same cultural weight as the originals. This brings us to the ongoing battle between Threads and X (formerly Twitter). Both platforms aim to recreate the scale of Twitter but through their own cultural lenses. However, neither can replace the original Twitter. The identity of Twitter was never about its features, but the chaotic, real-time unfolding of events—something that cannot be easily replicated by Threads or X. People don’t join platforms for features; they join for cultural relevance. Twitter succeeded because it was the place to witness things happening in real time, from fights to breaking news. That kind of relevance isn’t easily replicated, and while Truth Social managed to carve out its own cultural niche (albeit for a specific political party), both Threads and X are still struggling to find a similar resonance. Cultural relevance in app development goes beyond features. It encompasses the product’s philosophy, the people involved, the features maintained, and the moderation policies in place. Building cultural relevance means creating a product that becomes an integral part of its community’s identity. Take Superfan, a young app built on the premise of a weekly Spotify Wrapped experience. It has pivoted toward monetizing fan-artist interactions, recognizing that people who closely identify with artists are likely to embrace deeper connections with them. Superfan’s model leverages cultural relevance by enabling users to share their listening habits and tag artists, creating a cycle of engagement that benefits both fans and artists. For Superfan to fully succeed, it must make its artist-fan content as culturally significant as the music statistics it started with. If it can create a visually compelling, shareable form of content that resonates with users, it will have cemented its cultural relevance. Success in the tech world is often defined by metrics like DAUs and revenue. However, there is immense value in products that eschew traditional metrics and prioritize cultural impact, which is emotional rather than numerical. Ultimately, cultural impact may be the only way to humanize software in a world where software increasingly defines the human experience. The apps and websites we encounter leave emotional imprints, and their cultural significance shapes how we remember them, long after the code itself fades from view. 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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September 8, 2024in Salesforce
Adopting Salesforce Security Policies
07Sep

Adopting Salesforce Security Policies

Data breaches reached an all-time high in 2023, affecting more than 234 million individuals, and there’s no sign of the trend slowing down. At the center of this challenge is how organizations allocate resources to safeguard customer data. One of the most critical systems for managing this data is CRM platforms like Salesforce, used by over 150,000 U.S. businesses. However, security blind spots within Salesforce continue to pose significant risks. To address these concerns, the National Institute of Standards and Technology (NIST) offers a strategic framework for Salesforce security teams. In February 2024, NIST released Version 2.0 of its Cybersecurity Framework (CSF), marking the first major update in a decade. Key improvements include the introduction of a new “Govern” function, streamlining of categories to simplify usability, and updates to the “Respond” function to enhance incident management. This framework now applies across all industries, not just critical infrastructure. For Salesforce security leaders, these changes will significantly affect how they manage security, from aligning Salesforce practices with enterprise risk strategies to strengthening oversight of third-party apps. Here’s how these updates will influence Salesforce security going forward. What is the NIST Cybersecurity Framework 2.0? The NIST Cybersecurity Framework, first launched in 2014, was developed after an executive order by President Obama, aiming to provide a standardized set of guidelines to improve cybersecurity across critical infrastructure. The framework’s objectives include: The newly updated NIST CSF 2.0, released in 2024, expands on the original framework, providing organizations with structured, yet flexible, guidance for managing cybersecurity risks. It revolves around three core components: the CSF Core, CSF Profiles, and CSF Tiers. Key Components of NIST Cybersecurity Framework 2.0 These components help organizations understand, assess, and improve their cybersecurity posture, forming the basis for risk-informed strategies that align with organizational needs and the evolving threat landscape. Key Updates in the NIST Cybersecurity Framework 2.0 and Their Impact on Salesforce Security The 2024 updates to NIST CSF offer insights that Salesforce security leaders can use to align their strategies with evolving cybersecurity risks. Implementation Strategies for Salesforce Security Leaders To incorporate CSF 2.0 into Salesforce security operations, leaders should: Conclusion: Embracing NIST CSF 2.0 to Strengthen Salesforce Security The 2024 NIST Cybersecurity Framework updates offer crucial insights for Salesforce security leaders. By adopting these practices, organizations can enhance data protection, strengthen incident response capabilities, and ensure business continuity—critical for those relying on Salesforce for managing sensitive customer data. 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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September 7, 2024in Data, Enterprise, Salesforce, Salesforce Shield, Technology
Salesforce Validation Rules
07Sep

Salesforce Validation Rules Explained

When to Use (and Avoid) Salesforce Validation Rules Ensuring quality data in Salesforce is crucial, but finding the right balance between enforcing data integrity and maintaining a smooth user experience can be challenging. Both Flows and validation rules play important roles in this process. The Role of Validation Rules and Flows in Data Management Salesforce administrators must carefully consider the impact of data validation methods. Some approaches prevent records from being saved if certain conditions aren’t met, while others allow the process to continue and address issues later. Sales teams, in particular, may find it frustrating to be slowed down by data entry requirements, but there are situations where enforcing specific data formats or ranges is essential. This is where Salesforce validation rules come into play. For more complex processes, especially those managed by automation, Flows offer a solution that allows records to be corrected without interrupting the workflow. The Purpose of Validation Rules Validation rules in Salesforce are used to enforce specific data requirements by preventing the record from being saved if certain conditions are not met. For instance, a simple validation rule might require a field value to be between 10 and 100: scssCopy codeOR( Your_Field__c < 10, Your_Field__c > 100 ) Validation rules are typically applied to a single field or a combination of fields, and they are especially useful when a user must enter specific information, such as a description for a unique discount type. How Flows Offer Flexibility Salesforce Flows have evolved into a robust alternative to validation rules, providing more flexibility in how data is managed. Flows can be configured to check conditions before or after a record is saved, allowing for automatic corrections without blocking the save. For example, a Flow could assign a default value if the user fails to enter one or perform a lookup to populate a field. Flows also allow records to be saved even if they would otherwise trigger a validation rule. This capability is particularly valuable for automated processes, as it prevents errors from halting updates made by tools like Fivetran, Hightouch, or Zapier. Balancing User Experience with Data Validation Validation rules are designed with the user in mind, serving as reminders to ensure that necessary information is entered. However, if these rules are too restrictive or unclear, they can hinder productivity. One common challenge arises when trying to enforce constraints on date fields, such as ensuring a follow-up task is scheduled within a certain time frame. While a validation rule can prevent a date field from being left blank, Salesforce does not allow a rule to simultaneously enforce non-blankness and a specific date calculation. To address this, a combination of validation rules and Flows can be used: Key Takeaway Balancing the use of validation rules and Flows is essential for effective data management in Salesforce. Validation rules are useful for enforcing critical data entry requirements, while Flows offer the flexibility to correct issues automatically. By focusing on the user experience, administrators can determine the optimal combination of these features to maintain data integrity without disrupting workflow. 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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September 7, 2024in Salesforce
Salesforce and Ortoo Integration
06Sep

Salesforce and Ortoo Integration

Ortoo Launches Smart Actions: A Revolutionary Salesforce-Native App for AI Automation Ortoo, a leading provider of Salesforce productivity solutions, has unveiled its latest innovation, Smart Actions, now available on the Salesforce AppExchange. This groundbreaking Salesforce-native app allows businesses to seamlessly integrate AI automation into their Salesforce workflows, dramatically boosting efficiency and simplifying complex processes with a single click. Salesforce and Ortoo integration for Smart Actions. How do I sync Ortto activities to Salesforce? In your Ortto account, navigate to Data sources > Salesforce > Sync Ortto activities to Salesforce. Choose up to 5 activities. At Sync settings, select whether you wish to sync these Ortto activities as activities and/or as tasks. If you are syncing the Salesforce Task object to Ortto (selected at Salesforce fields): Smart Actions empowers companies to deploy AI and GPT-powered automations across sales, service, and support functions within Salesforce, eliminating the traditionally high costs associated with advanced AI tools. By integrating smoothly into the Salesforce ecosystem, Smart Actions enables businesses to automate manual tasks, personalize communications, and optimize workflows with unparalleled ease. Track and manage email conversations within Salesforce. AI-powered actions to streamline sales workflows. SEAMLESS SALESFORCE INTEGRATION “With Smart Actions, we’re making AI automation accessible to businesses of all sizes,” said Amy Grenham, Head of Marketing at Ortoo. “If you’ve ever built a custom GPT using OpenAI, creating a Smart Action will feel very familiar. Ortoo’s prompt builder allows you to set the context, specify the Salesforce fields to analyze, and determine where the output should go. This simplicity makes it incredibly easy to deploy AI-driven processes and transform operations within Salesforce.” Key Features and Practical Applications Real-World Applications of Smart Actions Get Started with Smart Actions Today Smart Actions is now available on the Salesforce AppExchange. Businesses can start using the app for free, with additional features available through a premium version. SmartActions is a 5 star product on the Salesforce AppExchange. 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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September 6, 2024in Salesforce Implementation Services
Citizen Development
06Sep

Citizen Development

As we progress through the era of digital transformation, citizen development has emerged as a key trend in the business landscape. This approach empowers end-users to create their applications, streamlining workflows and reshaping corporate operations. However, like any innovation, citizen development presents both advantages and challenges. In this article, we will explore the benefits, pros and cons of citizen development, and strategies to effectively leverage it within your organization. 1. The Rise of Citizen Development The popularity of citizen development is on the rise, as reflected by Statista, which reports a remarkable 24.6% growth in this sector since 2020. The increasing demand for software solutions in the corporate environment has made the traditional model of IT departments solely managing application development unsustainable. By enabling non-technical personnel to develop their applications, businesses can relieve pressure on IT teams, speed up solution delivery, and cultivate a more agile business model. Furthermore, investing in citizen development platforms fosters an inclusive and innovative workplace, allowing diverse perspectives to generate unique applications that meet specific workflow needs. 2. Benefits of Citizen Development for Companies 2.1 Accelerated Pace and Flexibility Citizen development tools facilitate rapid prototyping and quicker application rollouts. Non-technical personnel can design, modify, and launch applications according to immediate needs, enhancing agility and responsiveness. 2.2 Boosted Creativity Empowering your staff to create applications unlocks a wealth of untapped potential. Citizen development nurtures a culture of innovation, leading to tailored solutions that address specific business challenges. 2.3 Tailored App Design Citizen developers, as end-users, possess an in-depth understanding of their workflow requirements. This perspective enables them to develop applications that align closely with user needs, improving adoption and utility. 2.4 Heightened Productivity By reducing the back-and-forth between IT departments and end-users, citizen development streamlines operations, leading to enhanced efficiency. 2.5 Cost-Effectiveness Citizen development significantly cuts costs associated with traditional application development, such as hiring professional developers or outsourcing tasks. Rapid application rollouts also help seize business opportunities quickly, optimizing ROI. 2.6 Reduced Workload for IT Staff Enabling non-technical personnel to handle minor application development tasks lightens the load on IT teams, allowing them to focus on high-priority projects. 2.7 Enhanced Visibility and Accountability Many citizen development platforms include built-in analytics and reporting features, offering insights into application usage and performance. This transparency helps businesses track initiatives, make data-driven decisions, and continuously improve processes. 3. Implementing Citizen Development with Salesforce Solutions Given its extensive benefits, citizen development is a strategy many businesses are eager to adopt. Salesforce provides a powerful platform to effectively harness citizen development. Salesforce’s platform caters to both professional and citizen developers, offering a comprehensive suite of user-friendly tools for building applications and managing workflows. With built-in safeguards for data security and regulatory compliance, Salesforce for Public Sector and Tribal Governments ensures a smooth and secure citizen development process. Their clear deployment roadmap and thorough training programs equip businesses for success in their citizen development journey. 4. Partnering with Tectonic for Public Sector and Tribal Government Solutions Consider Tectonic as your trusted partner for PSS solutions. Tectonic is a distinguished provider of technology solutions with extensive expertise in Salesforce and process management. With a proven track record of successful projects, Tectonic has earned the trust of clients globally. Tectonic maintains a close partnership with Salesforce, ensuring a deep understanding of its advanced features, including process automation. As a Salesforce partner, Tectonic keeps clients updated on the latest advancements, delivering cutting-edge solutions tailored to their specific needs. By selecting Tectonic as your implementation partner for public sector Salesforce, you benefit from their vast experience and specialized knowledge. Tectonic provides a dedicated public sector team that excels in implementing secure and efficient solutions, working closely with our clients to address their unique challenges. Tectonic offers a comprehensive range of services, from initial implementation to ongoing support and maintenance. Their offerings include process modeling, application design, automation implementation, and roles management. With Tectonic’s expertise, you can ensure seamless integration of automation into your pss projects. To learn more about Tectonic’s public sector services, visit our services page, where you can explore their offerings, including Salesforce Managed Services. Tectonic’s Managed Services provide full support to ensure your public sector environment runs smoothly, covering automation management, data governance, and performance optimization. 5. Final Thoughts While citizen development presents both advantages and challenges, the benefits largely outweigh the potential drawbacks. Although there are concerns about data security and the need for proper governance, the positive impact of citizen development makes it a vital component of the digital transformation narrative. Successful implementation hinges on selecting the right platform and tools that align with your business model and workflow needs. Salesforce Public Sector Solution excels in this regard, offering a user-friendly suite of tools with a clear roadmap for deployment and top-notch support. Brining your public sector tech into the 21st century is an imperative. To fully realize the benefits of citizen development, businesses must strike a balance between empowerment and control. Establishing an environment that fosters innovation and efficiency, while also implementing a governance structure to mitigate risks, is essential. With careful planning, the right tools, and a culture of collaboration, the rewards of citizen development can be substantial. Whether you’re looking to enhance speed and agility, optimize costs, or cultivate a culture of innovation, citizen development offers a promising pathway forward. Embrace citizen development in Salesforce PSS, and set your business on the road to success. If you have any questions about implementing Salesforce Public Sector Solutions and its benefits, feel free to contact us to discuss your project. 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

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September 6, 2024in Data, Salesforce Development Services, Salesforce Public Sector Solutions, Technology
Strong AI Scalability
06Sep

Strong AI Scalability

The rapid pace of digital transformation has made scalability essential for any business looking to remain competitive. The stakes are high—without the ability to scale, businesses risk falling behind as customer demands and market conditions shift. So, what does it take to build a scalable business that can grow without compromising performance or customer satisfaction? In this Tectonic insight, we’ll cover key steps to future-proof your operations, avoid common pitfalls, and ensure your business doesn’t just keep pace with the market, but leads it. Master Scalability with Scale Center Scalability doesn’t have to be overwhelming. Salesforce’s Scale Center, available on Trailhead, provides a comprehensive learning path to help you optimize your scalability strategy. Why Scalability Is a Must-Have Scalability is critical to long-term success. As your business grows, so will the demands on your applications, infrastructure, and resources. If your systems aren’t prepared, you risk performance issues, outages, lost revenue, and dissatisfied customers. Unexpected spikes in demand—from increased customer activity or internal changes like onboarding large numbers of employees—can push systems to their limits, leading to overloads or downtime. A strong scalability plan helps prevent these issues. Here are three best practices to help scale your operations smoothly and sustainably. 1. Prioritize Proactive Scale Testing Scale testing should be a key part of your application lifecycle. Many businesses wait until performance issues arise before addressing them, which can result in maintenance headaches, poor user experiences, and challenges in supporting growth. Proactive steps to take: 2. Use the Right Tools for Seamless Scalability Choosing the right technology is crucial when scaling your business. Equip your team with tools that support growth management, and follow these tips for success: By integrating the right tools and technologies, you’ll not only stay ahead of the curve but also build a culture ready to scale. 3. Focus on Sustainable Growth Strategies Scaling requires a long-term approach. From development to deployment, a strategy that emphasizes scalability from the outset can help you avoid costly fixes down the road. Key practices include: DevOps Done Right Building secure, scalable AI applications and agents requires bridging the gap between tools and skills. Focus on crafting a thoughtful DevOps strategy that supports scalability. Scalability: A Marathon, Not a Sprint Scaling effectively is an ongoing process. Customer needs and market conditions will continue to change, so your strategies should evolve as well. Scalability is about more than just handling increased demand—it’s about ensuring stability and performance across the board. Consider these steps to enhance your approach: Committing to Scalability Scalability isn’t a one-time achievement—it’s a continuous commitment to growing smarter and stronger across all areas of your business. By embedding best practices into your day-to-day operations, you’ll ensure that your systems meet demand and prepare your business for future breakthroughs. As you develop your scalability strategy, remember that customer experience and trust should always guide your decisions. Tackling scalability proactively ensures your business can thrive no matter how market conditions change. It’s more than just a bonus feature—it’s a critical element of a smoother user experience, reduced costs, and the flexibility to pivot when necessary. By embracing these strategies, you’ll not only avoid potential challenges but also build lasting trust with your customers. In a world where loyalty is earned through exceptional experiences, a strong scalability plan is your key to long-term success. 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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September 6, 2024in Data, Hyperforce, Salesforce, Technology
Salesforce to Acquire Own
06Sep

Salesforce to Acquire Own

Salesforce is set to acquire data protection and management vendor Own Co. for approximately $1.9 billion in cash. This move aligns with Salesforce’s ongoing investment in artificial intelligence (AI) and its efforts to bolster cybersecurity amidst rising data security concerns.  The San Francisco-based CRM giant expects to finalize the acquisition of Own by the fourth quarter of its fiscal year 2025, according to a company statement. Own, formerly known as OwnBackup, touts itself as the leading cloud data protection platform for Salesforce, serving around 7,000 customers with services such as data archiving, security, and analytics. He highlighted that Own’s expertise would enhance Salesforce’s data protection and management capabilities, reinforcing the company’s commitment to secure, end-to-end solutions. Sam Gutmann, CEO of Own, echoed the sentiment, stating that the acquisition would allow Own and Salesforce to drive innovation and secure data, particularly in highly regulated industries. Gutmann, who previously founded Intronis, has led Own’s growth since its establishment in 2015, with backing from investors like BlackRock and Salesforce Ventures. The acquisition is expected to strengthen Salesforce’s existing offerings, such as Backup, Shield, and Data Mask. Own, known for its data resilience platform, has raised over 0 million in funding and partnered with major tech players like ServiceNow and Microsoft Dynamics 365. The deal comes shortly after Salesforce announced plans to acquire Tenyx, an AI-powered voice agent startup, as part of its broader AI-driven strategy. Salesforce has shifted focus from larger acquisitions in recent years, prioritizing shareholder returns. However, this purchase reflects the company’s strategic shift towards enhancing its AI and data security solutions to maintain growth momentum. Salesforce anticipates that the Own deal will be accretive to free cash flow starting in the second year after the transaction closes, without affecting its current capital return program. This acquisition underscores Salesforce’s evolving focus on data protection, especially as AI adoption grows and data security becomes increasingly important. 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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September 6, 2024in Einstein 1 Platform
AI Senate Bill 1047
06Sep

AI Senate Bill 1047

California’s new AI bill has sparked intense debate, with proponents viewing it as necessary regulation and critics warning it could stifle innovation, particularly for small businesses. Senate Bill 1047, known as the Safe and Secure Innovation for Frontier Artificial Intelligence Models Act, mandates that developers of advanced AI systems costing at least $100 million to train must test their models for potential harm and put safeguards in place. It also offers whistleblower protections for employees at large AI firms and establishes CalCompute, a public cloud computing resource aimed at startups and researchers. The bill is awaiting Governor Gavin Newsom’s signature by Sept. 30 to become law. Prominent AI experts, including Geoffrey Hinton and Yoshua Bengio, support the bill. However, it has met resistance from various quarters, including Rep. Nancy Pelosi and OpenAI, who argue it could hinder innovation and the startup ecosystem. Pelosi and others have expressed concerns that the bill’s requirements might burden smaller businesses and harm California’s leadership in tech innovation. Gartner analyst Avivah Litan acknowledged the dilemma, stating that while regulation is critical for AI, the bill’s requirements might negatively impact small businesses. “Some regulation is better than none,” she said, but added that thresholds could be challenging for smaller firms. Steve Carlin, CEO of AiFi, criticized the bill for its vague language and complex demands on AI developers, including unclear guidance on enforcing the rules. He suggested that instead of focusing on AI models, legislation should address the risks and applications of AI, as seen with the EU AI Act. Despite concerns, some experts like Forrester Research’s Alla Valente support the bill’s safety testing and whistleblower protections. Valente argued that safeguarding AI models is essential across industries, though she acknowledged that the costs of compliance could be higher for small businesses. Still, she emphasized that the long-term costs of not implementing safeguards could be greater, with risks including customer lawsuits and regulatory penalties. California’s approach to AI regulation adds to the growing patchwork of state-level AI laws in the U.S. Colorado and Connecticut have also introduced AI legislation, and cities like New York have tackled issues like algorithmic bias. Carlin warned that a fragmented state-by-state regulatory framework could create a costly and complex environment for developers, calling for a unified federal standard instead. While federal legislation has been proposed, none has passed, and Valente pointed out that relying on Congress for action is a slow process. In the meantime, states like California are pushing ahead with their own AI regulations, creating both opportunities and challenges for the AI industry. 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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September 6, 2024in Salesforce
Data Quality Critical
06Sep

Data Quality Critical

Data quality has never been more critical, and it’s only set to grow in importance with each passing year. The reason? The rise of AI—particularly generative AI. Generative AI offers transformative benefits, from vastly improved efficiency to the broader application of data in decision-making. But these advllucantages hinge on the quality of data feeding the AI. For enterprises to fully capitalize on generative AI, the data driving models and applications must be accurate. If the data is flawed, so are the AI’s outputs. Generative AI models require vast amounts of data to produce accurate responses. Their outputs aren’t based on isolated data points but on aggregated data. Even if the data is high-quality, an insufficient volume could result in an incorrect output, known as an AI hallucination. With so much data needed, automating data pipelines is essential. However, with automation comes the challenge: humans can’t monitor every data point along the pipeline. That makes it imperative to ensure data quality from the outset and to implement output checks along the way, as noted by David Menninger, an analyst at ISG’s Ventana Research. Ignoring data quality when deploying generative AI can lead to not just inaccuracies but biased or even offensive outcomes. “As we’re deploying more and more generative AI, if you’re not paying attention to data quality, you run the risks of toxicity, of bias,” Menninger warns. “You’ve got to curate your data before training the models and do some post-processing to ensure the quality of the results.” Enterprises are increasingly recognizing this, with leaders like Saurabh Abhyankar, chief product officer at MicroStrategy, and Madhukar Kumar, chief marketing officer at SingleStore, noting the heightened emphasis on data quality, not just in terms of accuracy but also security and transparency. The rise of generative AI is driving this urgency. Generative AI’s potential to lower barriers to analytics and broaden access to data has made it a game-changer. Traditional analytics tools have been difficult to master, often requiring coding skills and data literacy training. Despite efforts to simplify these tools, widespread adoption has been limited. Generative AI, however, changes the game by enabling natural language interactions, making it easier for employees to engage with data and derive insights. With AI-powered tools, the efficiency gains are undeniable. Generative AI can take on repetitive tasks, generate code, create data pipelines, and even document processes, allowing human workers to focus on higher-level tasks. Abhyankar notes that this could be as transformational for knowledge workers as the industrial revolution was for manual labor. However, this potential is only achievable with high-quality data. Without it, AI-driven decision-making at scale could lead to ethical issues, misinformed actions, and significant consequences, especially when it comes to individual-level decisions like credit approvals or healthcare outcomes. Ensuring data quality is challenging, but necessary. Organizations can use AI-powered tools to monitor data quality, detect irregularities, and alert users to potential issues. However, as advanced as AI becomes, human oversight remains critical. A hybrid approach, where technology augments human expertise, is essential for ensuring that AI models and applications deliver reliable outputs. As Kumar of SingleStore emphasizes, “Hybrid means human plus AI. There are things AI is really good at, like repetition and automation, but when it comes to quality, humans are still better because they have more context.” Ultimately, while AI offers unprecedented opportunities, it’s clear that data quality is the foundation. Without it, the risks are too great, and the potential benefits could turn into unintended consequences. 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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September 6, 2024in Data, Enterprise, Generative AI, Salesforce, Technology

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