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The 5G Letdown
05Apr

The 5G Letdown

The 5G Letdown: How Hype Outpaced Reality When 5G first arrived, it wasn’t just sold as an upgrade—it was pitched as the backbone of a futuristic society. Telecom giants promised self-driving car networks, remote robotic surgeries, and hyper-connected smart cities. Five years later, most of those visions remain science fiction. So what happened? The Grand Promises vs. The Reality 1. Remote Surgery? Not So Fast Marketing campaigns showed doctors performing precision operations from miles away using 5G’s “ultra-low latency.” But in reality:✔ Wired connections are still more reliable for critical medical procedures.✔ Regulatory and ethical hurdles (like patient consent and sterile environments) were glossed over.✔ Most hospitals never needed 5G for this in the first place. 2. Autonomous Cars Didn’t Need 5G The vision: A seamless 5G-powered traffic grid where cars communicate to prevent accidents. The truth?✔ Self-driving systems rely on onboard sensors and AI, not constant wireless signals.✔ Network dropouts would be deadly—so engineers designed cars to function independently.✔ 5G’s spotty coverage makes it an unreliable backbone for safety-critical systems. 3. Smart Cities? More Like Slow Rollouts While some cities have deployed IoT sensors (like smart streetlights), most “smart city” projects:✔ Use existing 4G or Wi-Fi instead of 5G.✔ Face budget and bureaucracy issues—not tech limitations.✔ Don’t actually require the speed 5G theoretically offers. Why 5G Fell Short 1. Millimeter Wave Limitations 5G’s fastest frequencies (mmWave) can’t penetrate walls and require antennas every few hundred meters. Carriers skipped the expensive infrastructure, relying instead on:✔ “Non-standalone 5G”—a rebranded 4G/5G hybrid that delivers barely noticeable speed boosts.✔ Misleading coverage maps showing 5G in areas where it barely functions. 2. Consumers Didn’t Notice (or Care) Most people’s daily use—streaming, browsing, social media—works fine on 4G. The average user sees little benefit from 5G, especially when:✔ Real-world speeds often match LTE.✔ Battery drain is worse on 5G phones.✔ Rural areas still lack coverage, despite ads claiming nationwide availability. 3. The Real Winners Were Equipment Makers Carriers spent $100B+ on spectrum licenses and infrastructure, but struggled to monetize 5G. Meanwhile:✔ Ericsson, Nokia, and Qualcomm made billions selling hardware.✔ Lobbyists pushed 5G as a “national priority”—even though the benefits were exaggerated. The Conspiracies & Health Panics The rapid deployment of 5G towers sparked baseless fears over radiation, despite studies showing:✔ 5G emissions are well below safety limits.✔ FM radio waves are stronger than 5G signals.✔ Scam products (like “5G-blocking” stickers) exploited public confusion. Was 5G a Scam? Not entirely—but it was the most overhyped tech of the decade. The truth?✔ Some industries (like factories) benefit from private 5G networks.✔ 6G is already being hyped—will we fall for it again?✔ The lesson? Demand proof, not promises. Final Verdict: 5G delivered incremental upgrades, not a revolution. And with 6G looming, we should ask: Will the next “game-changer” actually change anything? Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 5, 2025in Salesforce
How AI is Transforming Self-Appraisals
04Apr

How AI is Transforming Self-Appraisals

How AI is Transforming Self-Appraisals—Making Them Easier and Fairer for Employees and Managers Performance reviews are often dreaded—evaluating a year’s worth of your hard work can feel overwhelming, and many struggle to articulate their achievements objectively. But AI is changing that, making self-assessments more efficient, balanced, and even empowering—especially for groups like women, who often face biases in traditional reviews. The Rise of AI in Performance Reviews AI-powered tools are increasingly being used to streamline self-appraisals, helping employees structure their evaluations and align them with company goals. According to Microsoft’s 2024 Work Trend Index, 75% of knowledge workers—including engineers, scientists, and lawyers—already use AI in some capacity. The demand is clear: When Oracle introduced an AI-driven performance review system in 2023, 89% of employees said they were willing to be early adopters. “That shows how much people believe in this technology and how much they need it,” said Triparna de Vreede, a professor at the University of South Florida who studies AI and workplace well-being. Why Traditional Reviews Fall Short Conventional performance evaluations are often subjective, influenced by recency bias (where recent mistakes overshadow past successes) and workplace power dynamics. Employees may not always understand how their work contributes to broader business goals, while managers can struggle to provide unbiased feedback. “If you did great things all year but made one mistake last month, that can overshadow everything,” de Vreede explained. “AI helps standardize feedback so employees don’t feel like favoritism is at play.” How AI Improves the Process The Gender Gap in Self-Assessments Women frequently face challenges in performance reviews. A Textio study found that 38% of feedback for high-performing women contained exaggerated or clichéd language, and 75% were called “emotional”—compared to just 11% of men. Additionally, women tend to undersell their achievements. A 2022 National Bureau of Economic Research study found that women rated their performance at 46 out of 100, while men gave themselves 61. “AI can help women confidently showcase their impact without imposter syndrome getting in the way,” said de Vreede. The Human Touch Still Matters Despite AI’s benefits, human oversight remains crucial. Privacy concerns, transparency about data usage, and ensuring softer skills (like communication and teamwork) are evaluated fairly all require human judgment. “AI can’t fully understand human nuances, but it can prompt employees to reflect on them,” de Vreede noted. “The best reviews come from a collaboration between AI and the employee—not just AI doing all the work.” The Future of AI in Performance Reviews Companies like Oracle and Textio (used by 25% of Fortune 500 firms) are already refining AI-powered evaluations. However, de Vreede cautions against over-reliance: employees must still self-refect rather than letting AI do all the thinking. “AI can draft your review, but you need to refine it,” she said. “Otherwise, the evaluation loses its meaning.” As AI continues to evolve, it promises to make performance reviews less stressful, more accurate, and fairer for everyone—finally turning a dreaded process into one that actually helps employees grow. Salesforce AI can significantly enhance performance reviews by automating tasks, analyzing data, and providing actionable insights. AI tools can help streamline the review process, generate clearer and more unbiased feedback, and even predict future performance trends. Salesforce Einstein, for example, can analyze vast amounts of employee data to identify patterns and generate insights that inform performance reviews.  Here’s how Salesforce AI can be used in performance reviews: 1. Automating and Streamlining the Process: 2. Enhancing Accuracy and Objectivity: 3. Providing Actionable Insights: Examples of Salesforce AI Tools for Performance Reviews: Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 4, 2025in AI Tools, Data, Salesforce, Salesforce Einstein, Technology
Salesforce Field Service
30Mar

Field Service Mobile Data Capture

Field Service Mobile Data Capture Using Discovery Framework Offline-Capable Dynamic Forms for Field Teams Transform field service operations with intelligent, structured data collection powered by Salesforce’s Discovery Framework. This solution enables: ✔ Offline functionality – Capture data without internet connectivity✔ Dynamic forms – Build responsive question flows in Flow Builder✔ Centralized question bank – Reuse and version assessment questions✔ Full audit trail – Track all form submissions and revisions Solution Capabilities Key Features Implementation Guide Prerequisites Setup Process Technical Considerations Supported Data Types Discovery Framework Type Flow Component Use Case Example Single-Select Picklist Radio Buttons Equipment Condition Multi-Select Picklist Checkbox Group Required Repairs Number Input Field Measurement Reading Date Date Picker Service Completion Text Text Area Customer Feedback Error Handling Mobile User Experience Field technicians can: Best Practices “Since implementing Discovery Framework forms, our first-time fix rate improved by 28% because technicians now capture complete information upfront,” reports Jessica Tan, Field Ops Director at Contoso Industrial. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 30, 2025in Data, Enterprise, Salesforce
Dementia Care and Telemedicine
21Mar

Dementia Care and Telemedicine

How 3 Health Systems Are Leveraging Telemedicine for Dementia Care Telemedicine is expanding access to dementia care, particularly for rural and elderly patients, though challenges like technology barriers and sustainability remain. Dementia—an umbrella term for cognitive and memory disorders—affects millions of Americans directly and indirectly. By 2060, nearly 1 million people in the U.S. are projected to develop dementia. While no cure exists, the growing prevalence underscores the need for accessible and effective care solutions. Telehealth has emerged as a critical tool in meeting this demand. The rapid adoption of virtual care during the COVID-19 pandemic transformed dementia care delivery. A 2024 study found that telehealth use surged among dementia patients, particularly those with long travel distances to clinics and the oldest age groups. For health systems like the University of Mississippi Medical Center (UMMC), telemedicine has been a game-changer. “COVID-19 changed things almost overnight,” said Dr. Kim Tarver, associate professor of medicine and director of clinical services at UMMC’s MIND Center. “We have patients who travel three hours to see us. Being able to communicate without requiring a clinic visit every time is incredibly helpful.” UMMC is among several health systems integrating telehealth into dementia care, though challenges like technology access and financial sustainability persist. Telehealth’s Role in Dementia Care: Benefits and Applications Dementia care is uniquely suited for telehealth. Virtual visits allow for evaluations, treatment adjustments, and follow-ups while offering privacy and flexibility that in-person visits cannot. At UMMC, clinicians conduct cognitive assessments like the Montreal Cognitive Assessment (MoCA) remotely. A nurse guides patients through the test via screen-sharing, while caregivers assist with physical exam components when needed. “I’ll ask the caregiver to perform parts of the exam, like cerebellar function tests, while I observe via video,” Tarver explained. Though in-person visits are still used for verification, virtual assessments have proven comparably accurate. Telemedicine also enables family members to discuss concerns privately—especially valuable when patients are unaware of or resistant to acknowledging their condition. Extending Dementia Care Through Virtual Workforce Solutions Health systems are also using telehealth to expand their dementia care workforce. At the University of California, San Francisco (UCSF), unlicensed but trained care navigators support families, handling routine assessments and triaging complex cases to specialists. “Navigators manage caseloads of families, consulting licensed experts only when needed,” said Dr. Katherine Possin, a neurology professor at UCSF. “This extends the reach of our limited dementia specialist workforce.” Similarly, Banner Health’s Dementia Care Partners program employs health coaches (Certified Nursing Assistants) to conduct initial assessments and provide ongoing support, reducing clinician workload. “If I train 30 people who each support 3,000 patients, the impact multiplies rapidly,” said Dr. Ganesh Gopalakrishna of Banner Alzheimer’s Institute. Banner also uses Project ECHO, a telehealth-based training model, to educate community providers—from physicians to elder care attorneys—on dementia care best practices. Overcoming Telehealth Challenges in Dementia Care Despite its benefits, implementing telehealth in dementia care presents hurdles: The Future of Telehealth in Dementia Care Despite obstacles, providers see immense value in virtual dementia care—reducing caregiver burden, preventing unnecessary hospitalizations, and improving patients’ quality of life. “I hope telehealth becomes the standard of care,” Possin said. As health systems refine their approaches, telemedicine promises to play an increasingly vital role in dementia care—bridging gaps in access and delivering support to patients and families when they need it most. Tectonic can help you transform telehealth in your organization. Contact us today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 21, 2025in Life Sciences Cloud, Salesforce, Salesforce Development Services, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Implementation Services, Technology
AI Captivates the World
17Mar

AI vs Human Intelligence

Artificial Intelligence vs. Human Intelligence: Key Differences Explained Artificial intelligence (AI) often mimics human-like capabilities, but there are fundamental differences between natural human intelligence and artificial systems. While AI has made remarkable strides in replicating certain aspects of human cognition, it operates in ways that are distinct from how humans think, learn, and solve problems. Below, we explore three key areas where AI and human intelligence diverge. Defining Intelligence Human IntelligenceHuman intelligence is often described using terms like smartness, understanding, brainpower, reasoning, sharpness, and wisdom. These concepts reflect the complexity of human cognition, which has been debated for thousands of years. At its core, human intelligence is a biopsychological capacity to acquire, apply, and adapt knowledge and skills. It encompasses not only logical reasoning but also emotional understanding, creativity, and social interaction. Artificial IntelligenceAI refers to machines designed to perform tasks traditionally associated with human intelligence, such as learning, problem-solving, and decision-making. Over the past few decades, AI has advanced rapidly, particularly in areas like machine learning and generative AI. However, AI lacks the depth and breadth of human intelligence, operating instead through algorithms and data processing. Human Intelligence: What Humans Do Better Humans excel in areas that require empathy, judgment, intuition, and creativity. These qualities are deeply rooted in our evolution as social beings. For example: These capabilities make human intelligence uniquely suited for tasks that involve emotional connection, ethical decision-making, and creative thinking. Artificial Intelligence: What AI Does Better AI outperforms humans in several areas, particularly those involving data processing, pattern recognition, and speed: However, AI’s strengths are limited to the data it is trained on and the algorithms it uses, lacking the adaptability and contextual understanding of human intelligence. 3 Key Differences Between AI and Human Intelligence AI and Human Intelligence: Working Together The future lies in human-AI collaboration, where the strengths of both are leveraged to address complex challenges. For example: While some may find the idea of integrating AI into decision-making unsettling, the scale of global challenges—from climate change to healthcare—demands the combined power of human and artificial intelligence. By working together, humans and AI can amplify each other’s strengths while mitigating weaknesses. Conclusion AI and human intelligence are fundamentally different, each excelling in areas where the other falls short. Human intelligence is unparalleled in creativity, empathy, and ethical reasoning, while AI dominates in data processing, pattern recognition, and speed. The key to unlocking the full potential of AI lies in human-AI collaboration, where the unique strengths of both are harnessed to solve the world’s most pressing problems. As we move forward, this partnership will likely become not just beneficial but essential. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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March 17, 2025in Artificial Intelligence, Data, Generative AI
Financial Services Sector
14Mar

Future of Financial Services

The Future of Financial Services: AI Agents, Consumer Trust, and Digital Transformation Fewer than half of consumers are fully satisfied with the service they receive from banks, insurance providers, and wealth management advisors. This underscores the urgent need for financial service institutions (FSIs) to prioritize standout customer experiences—both human and digital—leveraging AI agents to enhance personalization, efficiency, and responsiveness. Why Customer Experience is Key Consumer loyalty has long been driven by competitive pricing, fees, and interest rates. However, with declining rates making promotional incentives less feasible, FSIs are refocusing on customer service as a key differentiator. AI-powered digital experiences provide an opportunity to exceed customer expectations, offering speed, convenience, and hyper-personalization at scale. A significant portion of consumers are willing to stay with an institution that offers an exceptional experience, even if it raises its rates or fees. For instance, 46% of consumers—and 55% of high earners in the U.S. (households making over $100,000 per year)—value experience over pricing alone. Digital self-service is a primary component of this enhanced experience, with many consumers preferring to complete tasks online rather than through traditional phone or in-branch interactions. Institutions like Credit Unions are already meeting this demand by deploying self-service tools that provide instant resolutions, 24/7. AI Agents: Transforming the FSI Landscape AI agents represent a major leap forward in customer service, automating interactions and resolving issues without human intervention. However, trust in these AI-driven systems remains a work in progress. Only 41% of wealth management clients report being fully satisfied with their institution’s speed and effectiveness, and satisfaction levels are even lower among banking and insurance customers. Despite some skepticism, AI adoption is accelerating. Half of consumers expect AI to significantly impact their financial relationships, a belief even more pronounced among Millennials and Gen Z. The percentage of customers anticipating AI-driven transaction speed improvements has risen from 46% in 2023 to 65% today. Yet, consumer education on AI’s capabilities remains a challenge. AI agents have the potential to act as financial advisors, enhancing financial literacy, optimizing savings, and even increasing earnings. Salesforce’s Agentforce aims to bridge this gap, offering digital financial assistants that can answer questions like, “Am I saving enough for retirement?” or “Can I afford this vacation?”—delivering expert insights instantly and at scale. Building Trust in AI-Powered Finance Despite AI’s promise, trust issues persist. While 54% of consumers express confidence in AI agents, only 10% fully trust them. This skepticism is fueled by concerns over data privacy, security, and transparency. Many consumers are wary of how FSIs handle their personal information and are seeking greater clarity on AI’s role in financial decision-making. A Salesforce study revealed that 73% of consumers want to know when they’re interacting with AI, highlighting the importance of transparency in AI implementation. “For AI to succeed in financial services, trust and compliance must be built into the foundation,” said Eran Agrios, SVP & GM of Financial Services at Salesforce. “FSIs need to ensure their AI strategies are not only effective but also worthy of customer confidence.” AI in Action: Case Studies in Financial Services Financial institutions leveraging Agentforce are already seeing tangible benefits: Integrating Agentforce with ERP for Maximum Impact To maximize the potential of AI agents, FSIs must integrate them seamlessly into their broader enterprise ecosystems. Best practices for integration include: The Next Two Years: Defining the Future of AI in Finance As AI continues to disrupt the financial sector, FSIs that embrace AI-first strategies will outperform competitors in efficiency, security, and customer experience. Here’s what the future holds: The Takeaway Financial institutions that invest in AI-driven experiences today will define the future of finance. By adopting transparent, compliant, and consumer-centric AI strategies, FSIs can build trust, drive efficiency, and deliver exceptional customer experiences that set them apart in an increasingly AI-powered world. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 14, 2025in Data, Enterprise, Mulesoft, Salesforce, Salesforce Data Cloud
Scaling AI Systems
11Mar

Scaling AI Systems

Scaling AI Systems: How Salesforce Manages 100,000+ AI Requests Per Minute AI adoption is accelerating, but scaling AI systems to handle massive workloads is a challenge few have mastered. At Salesforce, AI infrastructure supports over 100,000 training and metadata requests per minute—a feat that requires precision engineering, robust orchestration, and resilient architecture. So, how does Salesforce achieve this scale? Key Strategies for Scaling AI Systems 1. Intelligent Orchestration to Manage Demand Handling 100,000+ requests per minute means prioritizing workloads efficiently. Salesforce uses intelligent job orchestration to balance AI training and inference tasks across distributed environments. This ensures resources are allocated optimally without overwhelming systems. 2. Scalable and Fault-Tolerant Infrastructure AI workloads are unpredictable. Salesforce has built a fault-tolerant infrastructure that automatically scales up or down based on demand. This dynamic scaling prevents bottlenecks while ensuring high availability. 3. Metadata-Driven AI Pipelines AI models require continuous updates, and metadata management is key. Salesforce’s AI systems track metadata across training pipelines, enabling seamless model updates and performance monitoring. 4. Distributed Compute for Speed and Efficiency Instead of relying on a single processing hub, Salesforce distributes AI workloads across multiple compute nodes. This reduces latency, improves processing speed, and optimizes resource usage across cloud environments. 5. Robust Monitoring and Automation Scaling AI isn’t just about computing power—it requires proactive monitoring. Salesforce leverages automated observability tools to detect anomalies, optimize processing efficiency, and maintain system health in real time. The Future of AI Scalability As enterprises embrace AI-driven automation, the need for scalable, resilient AI infrastructure will only grow. Salesforce’s approach—combining intelligent orchestration, metadata-driven workflows, and distributed computing—sets a blueprint for managing high-volume AI workloads at scale. For organizations looking to scale AI, the lesson is clear: invest in automation, resilience, and intelligent resource management to unlock AI’s full potential. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 11, 2025in Data, Enterprise, Salesforce
Prioritize Data Quality
11Mar

Prioritize Data Quality

Prioritize Data Quality: Strengthening Governance for AI and Business Success 86% of analytics and IT leaders agree: AI’s effectiveness depends on the quality of its data inputs. High data quality brings organizations closer to data maturity and AI success—and it all starts with strong data governance. 🔹 92% of analytics and IT leaders say there’s never been a greater need for trustworthy data.📊 The State of Data and Analytics Report, 2023 Building a Strong Data Governance Strategy Data governance is more than compliance—it’s a structured approach to managing data quality, security, and usability. With the right governance in place, teams gain confidence in their data, leading to smarter decision-making and a culture of trust. Follow these six steps to lay the foundation for a successful governance strategy: 1. Align Governance Policies with Business Needs Meet with stakeholders to understand how data is used across teams. Ensure governance policies cover every critical workflow and use case, helping teams get the data they need—accurately and securely. 2. Define What ‘Data Quality’ Means for Your Organization Create a clear framework using these key data quality dimensions: ✅ Completeness: Are all necessary data fields populated?✅ Timeliness: Is data up to date and aligned with business goals?✅ Validity: Does data comply with governance rules and constraints?✅ Usage: How frequently is the data used for reporting and decision-making?✅ Accuracy: Does the data reflect reality, and is it sourced from trusted origins?✅ Consistency: Are data formatting and structure standardized across sources?✅ Reliability: Has data maintained quality and consistency over time? 3. Implement a Robust Quality Control Process Standardized processes—data entry validation, deduplication, cleansing, and archiving—are essential for governance. Leverage AI-powered tools like Tableau CRM Analytics to automate these tasks with built-in data profiling and enrichment features. 4. Schedule Regular Governance Reviews Your business evolves—your governance strategy should too. Establish a review cadence to assess policies, update processes, and address new data challenges. 5. Train Teams on Data Security and Compliance Education is key. Assign role-based security permissions, ensure regulatory compliance, and provide a clear process for reporting data issues (e.g., a dedicated Slack channel or help desk). 6. Define Success with Data Governance KPIs Tracking governance effectiveness is essential. Use these key metrics to measure impact: Metric Example of Smart KPI How to Track Data Quality Improve overall data quality by 4% per quarter. Assign values to frequency, error rates, and data usage. Data Usage Increase customer data-driven decision-making by 30% in 12 months. Measure employee logins, reports accessed, and data utilization. Time-to-Insight Reduce time from customer action → dashboard update to 10 minutes by next quarter. Track time-to-insight vs. benchmarks. Moving Up the Data Maturity Curve A well-governed data strategy leads to: 📈 Higher efficiency in decision-making🚀 More successful AI and analytics initiatives🏆 Competitive advantage through trustworthy data 🔍 “Ascending the data maturity curve unlocks new efficiencies and a competitive edge.”— Funke Bishi, Associate Director, Data and Business Analysis, RBC Capital Markets Take Action: Strengthen Your Data Governance ✅ Define what ‘quality data’ means for your business.✅ Align governance policies with team needs.✅ Use AI-powered tools like Tableau Data Prep for automated cleansing.✅ Train leaders on data best practices and compliance. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 11, 2025in Data, Salesforce
The Rise of AI Agents
07Mar

The Rise of AI Agents

The Rise of AI Agents: Salesforce’s Vision for a New Era of Business In just three months, more than 1,000 companies have deployed Salesforce AI agents, unlocking capabilities “they’ve never seen before” and setting the stage for game-changing business outcomes, according to CEO Marc Benioff. That’s a bold prediction—even for a visionary like Benioff, whose track record speaks for itself. But throughout our recent 25-minute conversation for the Cloud Wars CEO Outlook 2025 series, Benioff remained unwavering in his optimism about the AI-powered future. Agentic AI: The Force Driving Business Transformation According to Benioff, AI agents represent the next wave of business transformation, redefining how companies operate, innovate, and compete. “I’ve never been more excited about technology—this is an incredible moment in time,” Benioff said. He described AI agents as the bridge to a future where businesses engage with customers in ways previously thought possible only in science fiction. These AI-driven systems will help organizations operate at lower costs while improving customer relationships and key performance metrics. But Salesforce isn’t just selling this vision to customers—it’s living it. Benioff shared firsthand insights into how the company is leveraging AI to optimize its own operations, revealing lessons that could reshape how enterprises think about productivity and workforce planning. Digital Labor: A Multi-Trillion-Dollar Opportunity One of the most striking takeaways from our conversation was Salesforce’s approach to what Benioff calls “digital labor.” “For 25 years, Salesforce has helped businesses manage data. Now, we’re creating digital workers—AI agents that unlock entirely new ways to operate,” he said. This shift is already making an impact. Salesforce’s Agentforce AI now handles the bulk of the company’s customer support, transforming how its 9,000 service agents manage 36,000 weekly support inquiries: As a result, Salesforce is reallocating 2,000 support professionals to other roles—just one example of how AI is reshaping workforce dynamics. A Radical Rethink: No New Developers in 2025 Perhaps the most surprising revelation? Salesforce is pausing hiring for software engineers in 2025. Benioff explained that despite doubling its engineering team over the past five years, AI has driven a 30% increase in productivity. Rather than hiring more developers, Salesforce is leaning into AI-powered automation to accelerate software development. This shift raises fundamental questions about the future of work: Salesforce vs. Microsoft: Competing Visions for AI Agents AI agents are reshaping enterprise technology, but vendors have differing approaches. Benioff made it clear that Salesforce is taking a unique path—one he believes will ultimately lead the industry. Unlike Microsoft, which is deeply integrating AI within its core applications, Salesforce sees agents as an evolution of its CRM foundation, leveraging the vast 230-petabyte data ecosystem it manages for customers. “The businesses that are closest to their data will win,” Benioff said. “And we’re going to deliver capabilities that our customers have never seen before—ones that will thrill them out of their minds.” The Future: A Billion AI Agents As enterprises race to adopt AI, Benioff predicts an explosion in AI agent deployment. “In the next 12 months, we’ll see thousands of companies deploying up to a billion AI agents. And Salesforce will be the absolute leader in agentic technology for the enterprise,” he said. Benioff’s vision is clear: AI agents aren’t just an enhancement—they are the next frontier of business. And companies that embrace them will lead the way into a new era of efficiency, innovation, and growth. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 7, 2025in Agentic AI, Data, Enterprise, Salesforce, Technology
07Mar

Cloud-Based Housing Repairs with Salesforce

Bernicia Leads the Way in Cloud-Based Housing Repairs with Salesforce Bernicia has become the first housing association in the UK to deliver end-to-end repairs services through Salesforce’s cloud-based, nonprofit solution—setting a new industry benchmark for streamlined, automated housing repairs. Transforming Repairs with Salesforce Field Services All electrical repairs at tenants’ homes are now managed through Salesforce Field Services, enhancing the customer experience with seamless, automated processes. By this summer, all responsive repairs will transition into the system, delivering key benefits such as: A Customer-Centric Digital Transformation In 2023, Bernicia reinforced its commitment to tenants by launching a multi-year cultural development program, supported by a £4 million investment in world-class technology. By listening to customer feedback and leveraging data-driven insights, Bernicia has aligned its new digital repairs service with tenant expectations and evolving habits. Andrea Malcolm, Deputy Chief Executive at Bernicia and project sponsor, stated: “The introduction of Field Services marks a major milestone in our journey to customer service excellence. The dedication and expertise of our team have been outstanding, creating an incredible momentum across the business. We’re excited to see the real difference this will make for both customers and colleagues.” Jude Comber, Account Executive at Salesforce Nonprofits, praised the project team, saying: “The level of skill and attention to detail in this project is outstanding. Bernicia’s customer-first approach is a model for how to successfully implement a digital transformation.” Strategic Collaboration with Alscient Achieving this milestone was made possible through Bernicia’s partnership with Alscient, a multi-cloud specialist. Their expertise in Salesforce integration and digital transformation played a key role in designing and implementing the Field Services solution. Salesforce: A Game-Changer for Housing Associations Salesforce offers housing associations a single, integrated platform to streamline operations, enhance tenant relationships, and eliminate inefficiencies caused by data silos. By embracing cloud-based, automated solutions, housing providers can transform service delivery and drive long-term tenant satisfaction. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 7, 2025in Data, Salesforce, Technology
Autonomous AI Service Agents
06Mar

Developing AI Agents

Developing AI Agents: A Practical Guide Why AI Agent Development is Different Building AI agents requires an iterative, hands-on approach rather than traditional waterfall planning. Unlike conventional software projects, you can’t fully design an agent in documents before building – you need to prototype, test, and refine continuously. Key Principles: Designing the User Experience Take a user-centered approach to ensure your agent delivers value: Protip: Test different UX approaches in sandbox before finalizing channel configurations. Technical Implementation Guide 1. Data Strategy 2. Channel & Routing Configuration 3. Security Framework For Employee-Facing Agents: For Customer-Facing Agents: Agent User Permissions: Testing Tip: Always debug flows running as the agent user to catch permission issues. Salesforce Environment Considerations Requirements Checklist Integration Planning Implementation Best Practices Remember: Successful AI agent development balances careful planning with agile experimentation. The most effective agents evolve through real-world testing and refinement. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 6, 2025in Agentforce Platform, Data, Generative AI, Salesforce
spring 25
06Mar

Spring 25 Revealed

Spring ’25 Salesforce Release: What’s New and How to Prepare As winter lingers, the Salesforce Ohana is already embracing the promise of spring—a season of renewal, growth, and transformation. The Salesforce Spring ’25 Release brings fresh innovations designed to enhance productivity, streamline integrations, and optimize your CRM experience. With powerful AI enhancements, security updates, and UI improvements, this release is set to elevate the way you work. Let’s explore the key updates and how you can prepare to make the most of these enhancements. 1. Changes to Einstein Activity Capture Permissions What’s New?Salesforce is refining access to Einstein Activity Capture (EAC), ensuring more controlled and secure usage. Sales Engagement Basic Users will no longer have default access to EAC and must be assigned the Standard Einstein Activity Capture permission set to continue using the feature. Why It Matters:This update enhances security by limiting access to users with the appropriate permissions, improving governance over activity data. How to Prepare: 2. Transition to ICU Locale Formats What’s New?Salesforce is shifting from Oracle’s JDK Locale formats to ICU Locale Formats for handling date, currency, and numeric data. Why It Matters:ICU formats provide better internationalization and localization, improving accuracy and consistency across different regions. How to Prepare: 3. Introduction of LWC Stacked Modals What’s New?Lightning Web Components (LWC) now support stacked modals, allowing multiple modal windows to remain open simultaneously. Why It Matters:This improves the user experience by enabling seamless navigation between modal windows without losing context. How to Prepare: 4. Secure Redirection for Flows What’s New?Salesforce now requires that retURL parameters used in Flow redirections be explicitly added to the trusted URLs list. Why It Matters:This security enhancement mitigates risks associated with unauthorized redirections, protecting user data. How to Prepare: 5. Rollbacks for Apex Action Exceptions in REST API What’s New?Salesforce now enforces automatic rollbacks for exceptions occurring during Apex actions invoked via REST API. Why It Matters:This update ensures data integrity by preventing incomplete or failed operations from saving partial updates. How to Prepare: Final Thoughts The Spring ’25 release brings vital enhancements to permissions, security, UI, and API reliability. By proactively testing and preparing, you can ensure a seamless transition while unlocking the full potential of these updates. Stay ahead of the curve and leverage these improvements to create a more efficient, secure, and innovative Salesforce environment. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 6, 2025in Data
AI Data Cloud and Integration
03Mar

It is Time to Implement Data Cloud

With Salesforce Data Cloud you can: With incomplete data your 360-degree customer view is limited and often leads to multiple sales reps working on the same lead. Slow access to the right leads at the right time leads to missed opportunties and delayed closings. If your team cannot trust the data due to siloes and inaccuracies, they avoid using it. It is Time to Implement Data Cloud. Unified Connect and harmonize data from all your Salesforce applications and external data systems. Then activate your data with insights and automation across every customer touchpoint. Powerful With Data Cloud and Agentforce, you can create the most intelligent agents possible, giving them access to the exact data they need to deliver any employee or customer experience. Secure Securely connect your data to any large language model (LLM) without sacrificing data governance and security thanks to the Einstein 1 trust layer. Open Data Cloud is fully open and extensible – bring your own data lake or model to reduce complexity and leverage what’s already been built. Plus, share out to popular destinations like Snowflake, Google Ads, or Meta Ads. Salesforce Data Cloud is the only hyperscale data engine native to Salesforce. It is more than a CDP. It goes beyond a data lake. You can do more with Data Cloud. Your Agentforce journey begins with Data Cloud. Agents need the right data to work. With Data Cloud, you can create the most intelligent agents possible, giving them access to the exact data they need to deliver any employee or customer experience. Use any data in your organization with Agentforce in a safe and secure manner thanks to the Einstein 1 Trust Layer. Datablazers are Salesforce community members who are passionate about driving business growth with data and AI powered by Data Cloud. Sign up to join a growing group of members to learn, connect, and grow with Data Cloud. Join today. The path to AI success begins and ends with quality data. Business, IT, and analytics decision makers with high data maturity were 2x more likely than low-maturity leaders to have the quality data needed to use AI effectively, according to our State of Data and Analytics report. “What’s data maturity?” you might wonder. Hang tight, we’ll explain in chapter 1 of this guide. Data-leading companies also experience: Your data strategy isn’t just important, it’s critical in getting you to the head of the market with new AI technology by your side. That’s why this Salesforce guide is based on recent industry findings and provides best practices to help your company get the most from your data. Tectonic will be sharing a focus on the 360 degree customer view with Salesforce Data Cloud in our insights. Stay tuned. It is Time to Implement Data Cloud Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 3, 2025in Data, Einstein 1 Platform, Einstein Insights, Google, Salesforce, Salesforce Data Cloud, Salesforce Implementation Services, Snowflake, Technology
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