17Dec
Is the Future Agentic for ERP?
the success of AI in ERP depends on user adoption. If AI agents continue to make implementation easier and enhance current workflows, it’s clear that the future of ERP could indeed be agentic.
16Dec
AI is Transforming Threat Detection
Artificial Intelligence (AI) is significantly transforming threat detection by enabling faster, more accurate identification of potential security breaches through its ability to analyze vast amounts of data in real-time, detect anomalies and patterns that might indicate a threat, even when those threats are new or previously unknown, thus providing a proactive approach to cybersecurity compared to traditional rule-based systems.
16Dec
Salesforce Prompt Builder
Salesforce Prompt Builder: Field Generation Prompt Template What is a Prompt? A prompt is a set of detailed instructions designed to guide a Large Language Model (LLM) in generating relevant and high-quality output. Just like chefs fine-tune their recipes through testing and adjustments, prompt design involves iterating on instructions to ensure that the LLM delivers accurate, actionable results. Effective prompt design involves “grounding” your prompts with specific data, such as business context, product details, and customer information. By tailoring prompts to your particular needs, you help the LLM provide responses that align with your business goals. Like a well-crafted recipe, an effective prompt consists of both ingredients and instructions that work together to produce optimal results. A great prompt offers clear directions to the LLM, ensuring it generates output that meets your expectations. But what does an ideal prompt template look like? Here’s a breakdown: What is a Field Generation Prompt Template? The Field Generation Prompt Template is a tool that integrates AI-powered workflows directly into fields within Lightning record pages. This template allows users to populate fields with summaries or descriptions generated by an LLM, streamlining interactions and enhancing productivity during customer conversations. Let’s explore how to set up a Field Generation Prompt Template by using an example: generating a summary of case comments to help customer service agents efficiently review a case. Steps to Create a Field Generation Prompt Template 1. Create a New Rich Text Field on the Case Object 2. Enable Einstein Setup 3. Create a Prompt Template with the Field Generation Template Type 4. Configure the Prompt Template Workspace Optional: You can also use Flow or Apex to incorporate additional merge fields. 5. Preview the LLM’s Response Example Prompt: Scenario:You are a customer service representative at a company called ENForce.com, and you need a quick summary of a case’s comments. Record Merge Fields: Instructions: vbnetCopy codeFollow these instructions precisely. Do not add information not provided. – Refer to the “contact” as “client” in the summary. – Use clear, concise, and straightforward language in the active voice with a friendly, informal, and informative tone. – Include an introductory sentence and closing sentence, along with several bullet points. – Use a variety of emojis as bullet points to make the list more engaging. – Limit the summary to no more than seven sentences. – Do not include any reference to missing values or incomplete data. 6. Add the “Case Summary” Field to the Lightning Record Page 7. Generate the Summary By following these steps, you can leverage Salesforce’s Prompt Builder to enhance case management processes and improve the efficiency of customer service interactions through AI-assisted summaries. 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
16Dec
Agentforce 2.0 Unveiled
Salesforce Unveils Agentforce 2.0: Transforming Workflows with Enhanced AI Reasoning and Data Integration Salesforce has launched Agentforce 2.0, the next-generation version of its digital labor platform, offering enterprises new pre-built skills, advanced workflow integrations, and enhanced AI reasoning capabilities. Designed to create a “limitless workforce,” Agentforce 2.0 equips businesses with AI agents capable of executing complex tasks across any department, system, or workflow with improved precision and efficiency. Key Enhancements in Agentforce 2.0 1. Expanded Pre-Built Skills and IntegrationsAgentforce 2.0 introduces a robust library of pre-built agent skills compatible with Salesforce CRM, Slack, Tableau, and partner-developed tools on the AppExchange. Additionally, integrations with MuleSoft allow businesses to extend Agentforce capabilities across any system or workflow. 2. Advanced AI Reasoning and RetrievalPowered by Salesforce’s upgraded Atlas Reasoning Engine and retrieval-augmented generation (RAG) technology, the platform now handles deeply nuanced queries and multi-step tasks, leveraging enriched context from Data Cloud. 3. Enhanced Agent BuilderAgentforce’s updated Agent Builder can interpret natural language instructions—such as “onboard new team members”—to auto-generate agents and workflows. It also pulls from the expanded skill library to streamline agent creation, saving time and improving customizability. 4. Slack IntegrationSlack Actions are now embedded into Agentforce, enabling AI agents to interact directly within Slack. For example, agents can send direct messages summarizing project updates or modify Slack Canvas documents in response to customer feedback. Industry Impact and Adoption Marc Benioff, Chair and CEO of Salesforce, highlighted the transformative potential of Agentforce 2.0:“This launch takes our digital labor platform to the next level, blending AI, data, apps, and automation to reshape how businesses operate. Agentforce 2.0 empowers organizations to build a limitless workforce, delivering unprecedented levels of intelligence, customization, and efficiency.” Leading enterprises like Accenture, The Adecco Group, IBM, Finnair, and Indeed are already leveraging Agentforce to augment operations. A Growing Market for Digital Labor The release of Agentforce 2.0 responds to surging demand for agentic AI, with Salesforce closing 200 platform deals within a week and adding thousands more to its pipeline. According to CEO Marc Benioff, Salesforce plans to expand its salesforce by 2,000 workers to support adoption. “Digital labor is the new horizon for businesses,” Benioff remarked. “The way we architect, run, and staff our organizations is undergoing a fundamental transformation.” Challenges and Opportunities While the platform promises significant productivity gains, analysts warn of potential governance and security concerns. By 2028, Gartner predicts AI agent misuse could account for 25% of enterprise breaches. Salesforce emphasizes the importance of robust security measures to support adoption and mitigate risks. With over 80% of executives planning to deploy AI agents within three years (according to Capgemini), Agentforce 2.0 positions Salesforce as a leader in the evolving digital workforce space. Agentforce 2.0 is now available globally, with early adopters reporting improved scalability, efficiency, and customer satisfaction. For more information, visit the Salesforce Agentforce product page. About SalesforceSalesforce is a global leader in customer relationship management (CRM), enabling companies to connect with customers in new and innovative ways. With cutting-edge AI, data, and automation solutions, Salesforce empowers businesses to drive productivity, efficiency, and growth. For more details, visit www.salesforce.com. About TectonicWe are a niche, high quality, service-oriented US based technology services provider.We specialize in helping companies take advantage of the cross section between CRM, marketing, the use of data and analytics to shape behaviors and drive desired financial performance results. We have industry leading delivery capabilities addressing some of the most complex technology services, integrations and Salesforce implementation. Our delivery teams have over 200 certifications across a wide variety of technology services and products, including products, services and solutions serving sales, services, marketing, communities, customers, clients, operations, call centers, loyalty programs, just to name a few. In addition, we have highly skilled, cost effective off-shore delivery capabilities that allow us to provide our services at competitive, value added pricing levels. Please reach out and let us see how we can help you and your company. Tectonic is your Salesforce implementation partner. For more details, visit www.gettectonic.com. 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
16Dec
AI and UX Design
This insight comprehensively covers how AI is transforming UX design, presenting both opportunities and challenges while emphasizing the importance of maintaining a human-centric approach. Here’s a polished and slightly condensed version, retaining the core points for better clarity and engagement: AI in UX Design: Transforming Experiences in 2024 and Beyond In 2024, artificial intelligence (AI) is redefining user experience (UX) design and research. From streamlining processes to elevating personalization, UX professionals are integrating AI into their workflows to create experiences that are more intuitive and efficient. This insight explores how AI is reshaping UX and how designers can leverage it while preserving the human touch. How AI is Revolutionizing UX Design 1. Advanced AI Technologies in UXAI technologies like machine learning (ML), natural language processing (NLP), and computer vision are empowering designers with tools to understand user behavior better, build conversational interfaces, and create accessible, adaptable designs. These innovations provide deeper insights into user preferences and help refine interfaces to align with evolving needs. 2. Automating Routine Design TasksAI is taking over repetitive tasks such as rapid prototyping, A/B testing, and user data analysis, allowing designers to focus on creative, strategic challenges. For example: 3. Enhanced PersonalizationAI-driven systems offer dynamic content delivery, adaptive interfaces, and predictive behavior modeling to craft uniquely tailored experiences. These enhancements not only engage users but also foster loyalty by addressing individual preferences in real time. Balancing AI and Human-Centric Design While AI accelerates UX processes, maintaining a human-centered approach is essential. Successful integration requires: Best Practices for AI-Driven UX Design Ethical Considerations in AI-Enhanced UX Ethics remain at the forefront of AI in UX. Key concerns include: Learning from Case Studies These examples highlight how thoughtful AI integration can transform UX into a seamless, user-friendly journey. Preparing for Future Trends Looking ahead to 2025 and beyond, AI will continue to introduce innovations like emotional recognition and generative design, enabling even more intuitive user experiences. However, challenges such as data privacy concerns and high implementation costs will persist. UX professionals must adapt by blending AI-driven insights with human creativity, ensuring that designs remain empathetic and accessible. Conclusion AI is revolutionizing UX design, offering tools to enhance efficiency, personalization, and user engagement. The key to success lies in using AI as a complement to creativity rather than a replacement. By balancing automation with human-centered principles and committing to ethical practices, businesses can harness AI to create transformative, user-focused designs that truly resonate. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more
16Dec
Innovate Vacation Ownership with Salesforce
As the vacation ownership industry grows, focus on innovation, personalization, and partnerships sets Salesforce apart. By leveraging Salesforce and Tableau, the company ensures its systems, teams, and customer experiences evolve to meet the expectations of modern travelers, delivering on its promise of unforgettable vacations.
15Dec
MOIRAI-MoE
MOIRAI-MoE represents a groundbreaking advancement in time series forecasting by introducing a flexible, data-driven approach that addresses the limitations of traditional models. Its sparse mixture of experts architecture achieves token-level specialization, offering significant performance improvements and computational efficiency. By dynamically adapting to the unique characteristics of time series data, MOIRAI-MoE sets a new standard for foundation models, paving the way for future innovations and expanding the potential of zero-shot forecasting across diverse industries.
15Dec
Transforming the Role of Data Science Teams
GenAI: Transforming the Role of Data Science Teams Challenges, Opportunities, and the Evolving Responsibilities of Data Scientists Generative AI (GenAI) is revolutionizing the AI landscape, offering faster development cycles, reduced technical overhead, and enabling groundbreaking use cases that once seemed unattainable. However, it also introduces new challenges, including the risks of hallucinations and reliance on third-party APIs. For Data Scientists and Machine Learning (ML) teams, this shift directly impacts their roles. GenAI-driven projects, often powered by external providers like OpenAI, Anthropic, or Meta, blur traditional lines. AI solutions are increasingly accessible to non-technical teams, but this accessibility raises fundamental questions about the role and responsibilities of data science teams in ensuring effective, ethical, and future-proof AI systems. Let’s explore how this evolution is reshaping the field. Expanding Possibilities Without Losing Focus While GenAI unlocks opportunities to solve a broader range of challenges, not every problem warrants an AI solution. Data Scientists remain vital in assessing when and where AI is appropriate, selecting the right approaches—whether GenAI, traditional ML, or hybrid solutions—and designing reliable systems. Although GenAI broadens the toolkit, two factors shape its application: For example, incorporating features that enable user oversight of AI outputs may prove more strategic than attempting full automation with extensive fine-tuning. Differentiation will not come from simply using LLMs, which are widely accessible, but from the unique value and functionality they enable. Traditional ML Is Far from Dead—It’s Evolving with GenAI While GenAI is transformative, traditional ML continues to play a critical role. Many use cases, especially those unrelated to text or images, are best addressed with ML. GenAI often complements traditional ML, enabling faster prototyping, enhanced experimentation, and hybrid systems that blend the strengths of both approaches. For instance, traditional ML workflows—requiring extensive data preparation, training, and maintenance—contrast with GenAI’s simplified process: prompt engineering, offline evaluation, and API integration. This allows rapid proof of concept for new ideas. Once proven, teams can refine solutions using traditional ML to optimize costs or latency, or transition to Small Language Models (SMLs) for greater control and performance. Hybrid systems are increasingly common. For example, DoorDash combines LLMs with ML models for product classification. LLMs handle cases the ML model cannot classify confidently, retraining the ML system with new insights—a powerful feedback loop. GenAI Solves New Problems—But Still Needs Expertise The AI landscape is shifting from bespoke in-house models to fewer, large multi-task models provided by external vendors. While this simplifies some aspects of AI implementation, it requires teams to remain vigilant about GenAI’s probabilistic nature and inherent risks. Key challenges unique to GenAI include: Data Scientists must ensure robust evaluations, including statistical and model-based metrics, before deployment. Monitoring tools like Datadog now offer LLM-specific observability, enabling teams to track system performance in real-world environments. Teams must also address ethical concerns, applying frameworks like ComplAI to benchmark models and incorporating guardrails to align outputs with organizational and societal values. Building AI Literacy Across Organizations AI literacy is becoming a critical competency for organizations. Beyond technical implementation, competitive advantage now depends on how effectively the entire workforce understands and leverages AI. Data Scientists are uniquely positioned to champion this literacy by leading initiatives such as internal training, workshops, and hackathons. These efforts can: The New Role of Data Scientists: A Strategic Pivot The role of Data Scientists is not diminishing but evolving. Their expertise remains essential to ensure AI solutions are reliable, ethical, and impactful. Key responsibilities now include: By adapting to this new landscape, Data Scientists will continue to play a pivotal role in guiding organizations to harness AI effectively and responsibly. GenAI is not replacing them; it’s expanding their impact. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more
14Dec
Why Tracking Business Metrics Matters More Than You Think
Without measurement, a business is flying by the seat of its pants. In business, as in many areas of life, tracking progress is essential for growth. For example, one individual has been tracking cycling times on the same routes for over five years, and while performance has slowed, improvements in other areas, like taking more time off with family and building stronger client relationships, have been evident. Despite this, many businesses still fail to measure enough, particularly when it comes to understanding key performance indicators. A recent Salesforce survey found that 60% of small businesses rely primarily on cash flow as their key metric, often neglecting other important indicators of business health. For many, the primary measure of success is simply how much money is in the bank account, which, while important, is only a small part of the larger picture. The importance of measurement and metrics for business success and growth cannot be over emphasized. By tracking the right indicators, businesses gain a competitive edge and the ability to adapt and thrive in an ever-changing market. The Importance of Measurement Today, measuring business performance is more critical than ever for several reasons: Key Metrics to Measure While industry-specific metrics are important, there are several universal indicators that every management team should focus on. Thanks to new digital tools, gathering and analyzing these metrics is easier than ever, offering a comprehensive view of a business’s health. The Consequences of Not Measuring Without measurement, businesses are essentially operating without road signs. Small businesses, in particular, may not measure enough, while larger organizations may suffer from “analysis paralysis” by over-measuring and becoming overwhelmed by data. Measurement makes a difference. Just as an individual may track cycling times without measuring other variables like weight or diet, businesses must decide which metrics are most relevant to their success. While some aspects of business may be left unmeasured, others—such as sales, margins, and marketing performance—are vital for growth and strategic decision-making. In conclusion, businesses that embrace measurement are better equipped to navigate challenges, seize opportunities, and ultimately, thrive in a competitive market. 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
13Dec
AI Agents Next AI Evolution
AI agents are being hailed as the next big leap in artificial intelligence, but there’s no universally accepted definition of what they are—or what they should do. Even within the tech community, there’s debate about what constitutes an AI agent. At its core, an AI agent can be described as software powered by artificial intelligence that performs tasks once handled by human roles, such as customer service agents, HR representatives, or IT help desk staff. However, their potential spans much further. These agents don’t just answer questions—they take action, often working across multiple systems. For example, Perplexity recently launched an AI agent to assist with holiday shopping, while Google introduced Project Mariner, an agent that helps users book flights, find recipes, and shop for household items. While the idea seems straightforward, it’s muddied by inconsistent definitions. For Google, AI agents are task-based assistants tailored to specific roles, like coding help for developers or troubleshooting issues for IT professionals. In contrast, Asana views agents as digital co-workers that take on assigned tasks, and Sierra—a startup led by former Salesforce co-CEO Bret Taylor—envisions agents as sophisticated customer experience tools that surpass traditional chatbots by tackling complex problems. This lack of consensus adds to the uncertainty around what AI agents can truly achieve. Rudina Seseri, founder and managing partner at Glasswing Ventures, explains this ambiguity stems from the technology’s infancy. She describes AI agents as intelligent systems capable of perceiving their environment, reasoning, making decisions, and taking actions to achieve specific goals autonomously. These agents rely on a mix of AI technologies, including natural language processing, machine learning, and computer vision, to operate in dynamic environments. Optimists, like Box CEO Aaron Levie, believe AI agents will improve rapidly as advancements in GPU performance, model efficiency, and AI frameworks create a self-reinforcing cycle of innovation. However, skeptics like MIT robotics pioneer Rodney Brooks caution against overestimating progress, noting that solving real-world problems—especially those involving legacy systems with limited API access—can be far more challenging than anticipated. David Cushman of HFS Research likens current AI agents to assistants rather than fully autonomous entities, with their capabilities limited to helping users complete specific tasks within pre-defined boundaries. True autonomy, where AI agents handle contingencies and perform at scale without human oversight, remains a distant goal. Jon Turow, a partner at Madrona Ventures, emphasizes the need for dedicated infrastructure to support the development of AI agents. He envisions a tech stack that allows developers to focus on product differentiation while leaving scalability and reliability to the platform. This infrastructure would likely involve multiple specialized models working together under a routing layer, rather than relying on a single large language model (LLM). Fred Havemeyer of Macquarie US Equity Research agrees, noting that the most effective AI agents will combine various models to handle complex tasks. He imagines a future where agents act like autonomous supervisors, delegating tasks and reasoning through multi-step processes to achieve abstract goals. While this vision is compelling, the current state of AI agents suggests we’re still in a transitional phase. The progress so far is promising, but several breakthroughs are needed before agents can operate as envisioned—truly autonomous, multi-functional, and capable of seamless collaboration across diverse systems. This story, originally published on July 13, 2024, has been updated to reflect new developments from Perplexity and Google. 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
13Dec
UK Leading AI’s Third Wave
The UK Leading AI’s Third Wave: Insights from Salesforce’s AI Readiness Index Salesforce’s latest UK AI Readiness Index positions the UK as a frontrunner in the third wave of AI innovation, particularly in agentic AI—autonomous systems capable of decision-making and action. This comes as nations globally compete for leadership in AI development, with significant implications for economic growth, national security, and technological sovereignty. UK’s AI Readiness Exceeds G7 Averages The index reveals that the UK’s overall readiness score is 65.5, outpacing the G7 average of 61.2. Both government and business sectors outperform their peers, reflecting a robust environment for innovation. Zahra Bahrololoumi, CBE, UKI CEO of Salesforce, highlights the transformative potential of this technology, stating: “Agentic AI is revolutionising enterprise software by enabling seamless collaboration between humans and AI agents, driving customer success. The UK AI Readiness Index affirms the UK’s vision and infrastructure to lead globally in this new wave of innovation.” Driving Forces Behind UK’s Leadership The UK’s strength lies in its holistic approach to AI development, integrating: Minister for AI and Digital Government, Feryal Clark, notes: “These findings are proof that the UK is primed to leverage AI’s potential, showcasing our strength in fostering innovation, investment, and collaboration across sectors.” AI in Action: Transforming UK Businesses Salesforce’s Agentforce platform is helping UK organisations capitalise on AI’s potential. Leading companies such as Capita, Heathrow Airport, and Bionic have reported significant productivity gains: The Road Ahead: Maintaining Leadership The report outlines key priorities for sustaining the UK’s position: Salesforce’s commitment to the UK includes a $4 billion investment over five years and the opening of its AI Centre in London, aimed at training developers and administrators in cutting-edge AI technologies. What the Experts Say Antony Walker, Deputy CEO of techUK, remarks: “The Salesforce UK AI Readiness Index highlights the UK’s strong position to lead the next wave of AI innovation. By supporting SMEs, investing in skills, and ensuring flexible regulation, the UK can solidify its global AI leadership.” Paul O’Sullivan, UKI CTO and SVP Solution Engineering at Salesforce, reinforces the urgency: “We are in the third wave of AI—an autonomous age moving at unprecedented speed. The UK has a unique opportunity to lead, but this requires sustained focus on skills, innovation, and collaboration.” Conclusion As the AI revolution accelerates, the UK’s leadership in agentic AI positions it as a global AI powerhouse. By balancing innovation with responsibility and investing in infrastructure and talent, the UK is not just adapting to AI’s future but shaping it. Salesforce’s AI initiatives, including its Agentforce platform and London AI Centre, ensure the UK remains at the forefront of this transformational journey. 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
13Dec
AI-Driven Care Coordination Software
Can AI-Driven Care Coordination Software Improve Workflows? University Hospitals is leveraging AI to enhance care coordination across its network of 13 hospitals and numerous outpatient settings. This effort highlights the transformative potential of AI-driven platforms in streamlining workflows, improving patient outcomes, and addressing clinician burnout. The Role of AI in Care Coordination Care coordination ensures seamless collaboration between healthcare providers, aiming for safe, appropriate, and effective treatment. Effective information-sharing can: According to the U.S. Centers for Medicare & Medicaid Services (CMS), poor care coordination can lead to: The Agency for Healthcare Research and Quality (AHRQ) advocates for a mix of technology adoption and care-specific strategies, such as proactive care plans tailored to patient needs. While electronic health records (EHRs) aid in these efforts, AI’s ability to analyze vast data sets positions it as the next evolution in care coordination. University Hospitals’ AI Initiative University Hospitals has partnered with Aidoc to deploy its AI-powered platform, aiOS, to improve radiology and care coordination workflows. Chair of Radiology Donna Plecha shared insights on how AI is already assisting in their operations: Best Practices for Implementing AI 1. Identify High-Value Use Cases: 2. Conduct Architectural Reviews: 3. Monitor ROI and Metrics: 4. Gain Clinician Buy-In: Looking Ahead AI is proving to be a valuable tool in care coordination, but its adoption requires realistic expectations and a thoughtful approach. Plecha underscores that AI won’t replace radiologists but will empower those who embrace it. As healthcare faces increasing patient volumes and clinician shortages, leveraging AI to reduce workloads and enhance care quality is becoming a necessity. With ongoing evaluations and phased implementations, University Hospitals is setting a precedent for how AI can drive innovation in care coordination while maintaining clinician oversight and patient trust. 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
13Dec
Leveraging Agentforce
At Dreamforce 2024, Salesforce customers showcased the power of Agentforce by creating over 10,000 autonomous agents, each designed to address specific business challenges. The message was clear: “If you can describe it, Agentforce can do it.” By leveraging Agentforce, customers are able to create a flexible, on-demand digital workforce that operates without limitations, making it easy to build and deploy agents using familiar Salesforce tools and language. Why This Matters: Recent Salesforce research reveals that U.S. consumers often spend up to nine hours interacting with customer service to resolve a single issue. Moreover, 67% of consumers are frustrated when their issues aren’t resolved immediately and may abandon one-third of customer service interactions. This presents a massive opportunity to enhance the customer experience with AI-powered agents. “Piloting Agentforce made a noticeable difference during our busiest period — back-to-school season. We saw a 40% increase in case resolution, surpassing the performance of our old bot. Agentforce helps manage routine tasks, allowing our service teams to focus on more complex cases.” – Kevin Quigley, Director of Process Improvement, Wiley What’s New: Several new solutions are now available to all customers: Going Deeper: Agentforce is fully integrated into the Salesforce Platform, combining powerful data, AI, and the Salesforce Customer 360 ecosystem. This integration unlocks infinite agent capacity and proactive actions across all roles and channels, with full context on every customer interaction. Industry-Specific Examples: Agentforce’s flexibility allows it to serve various industries with tailored solutions: Customer & Analyst Quotes: “Agentforce is enhancing Saks’ ability to provide personalized customer support, automating routine tasks like order tracking, which allows our teams to focus on delivering a high-touch experience.” – Mike Hite, Chief Technology Officer, Saks Global “With Agentforce, OpenTable is automating routine tasks, saving time for our reps to focus on strengthening customer relationships and providing exceptional service to diners and restaurants worldwide.” – George Pokorny, Senior VP of Global Customer Success, OpenTable “By integrating Agentforce with Data Cloud and MuleSoft, we’re unlocking the full potential of our data, driving faster decisions and reimagining how we serve clients.” – Caroline Basyn, Chief Digital & IT Officer, The Adecco Group “Agentforce will revolutionize ezCater’s food management services, blending AI and human interaction to ensure seamless, personalized experiences for every customer.” – Erin DeCesare, CTO, ezCater 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
12Dec
Why the ‘SaaS-ification’ of Networks is the Future of IT
By adopting a NaaS model, businesses can optimize their networks for the future while focusing on what matters most—their core mission. The era of “hands-free” networking has arrived, and it’s redefining the IT landscape
11Dec
The Nature Tech Revolution
The Nature Tech Revolution: From “Do No Harm” to “Nature-Positive” In January, ERM, Salesforce, Planet, and NatureMetrics launched the NatureTech Alliance at the World Economic Forum in Davos. The Alliance’s mission is clear: empower companies to leverage advanced data and technology to address pressing nature-related challenges. This integrated effort focuses on: After engaging with clients in early 2024, the Alliance identified recurring challenges across value chains. Through interviews with industry leaders, it uncovered actionable insights into corporate efforts to overcome these hurdles. Seven key takeaways highlight the obstacles and opportunities for effective nature-positive strategies. Seven Key Insights for Corporate Nature Action 1. Nature Risk is Both Global and Highly Local Nature-related risks, such as water scarcity or biodiversity loss, vary significantly by region. However, many companies rely on coarse, global data that overlooks critical local nuances like community-level resource usage or ecosystem dynamics. This mismatch creates blind spots that can hinder decision-making, disrupt operations, or lead to regulatory non-compliance. 2. Nature Risk Lacks Integration with Enterprise Strategy Nature-related risks often remain siloed from broader enterprise risk frameworks, despite deep ties to issues like climate change. For instance, deforestation exacerbates biodiversity loss and water stress while releasing carbon into the atmosphere. Integrating nature data into strategic planning is essential for resilience and sustainable performance. 3. Gaps in Understanding Hinder Progress Corporate decision-makers and investors frequently struggle to interpret complex nature-related data, slowing the adoption of nature-positive strategies. Bridging this gap with accessible tools and clear communication is critical to driving meaningful action. 4. A Shift from “Do No Harm” to “Net Positive” Businesses are evolving from mitigating harm (e.g., reducing deforestation) to pursuing net-positive outcomes, such as reforestation or ecosystem restoration. While promising, many of these efforts remain in pilot phases due to challenges in site-level data and measuring impacts. 5. Financial Institutions Lag but Hold Scaling Potential The financial sector trails industries like agriculture in incorporating nature-related data into decision-making. However, as institutions recognize risks like biodiversity loss and soil degradation, they are poised to influence capital flows and set new standards for nature-positive investments. 6. The Future Lies in Outcome-Based Metrics Companies are shifting from input-based metrics (e.g., reduced fertilizer use) to measuring real-world outcomes for biodiversity and ecosystem health. Outcome-based metrics offer better clarity on environmental impacts and link corporate actions to business value. However, challenges like standardized methodologies and reliable data collection persist. 7. Data Fragmentation, Not Technology, is the Biggest Barrier Although technologies like AI and remote sensing are widely available, fragmented and inconsistent data remains a significant hurdle. Many organizations collect localized data but struggle to integrate it across supply chains and operations. Advanced platforms that consolidate disparate datasets are critical for actionable insights. A Shared Vision for Nature-Positive Solutions The NatureTech Alliance envisions a transformative approach to addressing these challenges, built on five pillars: Achieving a Nature-Positive Future By aligning corporate strategies with these principles, businesses can move beyond “do no harm” to actively restoring ecosystems and driving nature-positive outcomes. This transition requires advanced tools, collaboration, and a commitment to measurable impact—paving the way for a more sustainable and resilient future. 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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