AI-Driven Archives - gettectonic.com - Page 30
Where Will AI Take Us?
26Mar

Where Will AI Take Us?

Author Jeremy Wagstaff wrote a very thought provoking article on the future of AI, and how much of it we could predict based on the past. This insight expands on that article. Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn. These machines can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Many people think of artificial intelligence in the vein of how they personally use it. Some people don’t even realize when they are using it. Artificial intelligence has long been a concept in human mythology and literature. Our imaginations have been grabbed by the thought of sentient machines constructed by humans, from Talos, the enormous bronze automaton (self-operating machine) that safeguarded the island of Crete in Greek mythology, to the spacecraft-controlling HAL in 2001: A Space Odyssey. Artificial Intelligence comes in a variety of flavors, if you will. Artificial intelligence can be categorized in several ways, including by capability and functionality: You likely weren’t even aware of all of the above categorizations of artificial intelligence. Most of us still would sub set into generative ai, a subset of narrow AI, predictive ai, and reactive ai. Reflect on the AI journey through the Three C’s – Computation, Cognition, and Communication – as the guiding pillars for understanding the transformative potential of AI. Gain insights into how these concepts converge to shape the future of technology. Beyond a definition, what really is artificial intelligence, who makes it, who uses it, what does it do and how. Artificial Intelligence Companies – A Sampling AI and Its Challenges Artificial intelligence (AI) presents a novel and significant challenge to the fundamental ideas underpinning the modern state, affecting governance, social and mental health, the balance between capitalism and individual protection, and international cooperation and commerce. Addressing this amorphous technology, which lacks a clear definition yet pervades increasing facets of life, is complex and daunting. It is essential to recognize what should not be done, drawing lessons from past mistakes that may not be reversible this time. In the 1920s, the concept of a street was fluid. People viewed city streets as public spaces open to anyone not endangering or obstructing others. However, conflicts between ‘joy riders’ and ‘jay walkers’ began to emerge, with judges often siding with pedestrians in lawsuits. Motorist associations and the car industry lobbied to prioritize vehicles, leading to the construction of vehicle-only thoroughfares. The dominance of cars prevailed for a century, but recent efforts have sought to reverse this trend with ‘complete streets,’ bicycle and pedestrian infrastructure, and traffic calming measures. Technology, such as electric micro-mobility and improved VR/AR for street design, plays a role in this transformation. The guy digging out a road bed for chariots and Roman armies likely considered none of this. Addressing new technology is not easy to do, and it’s taken changes to our planet’s climate, a pandemic, and the deaths of tens of millions of people in traffic accidents (3.6 million in the U.S. since 1899). If we had better understood the implications of the first automobile technology, perhaps we could have made better decisions. Similarly, society should avoid repeating past mistakes with AI. The market has driven AI’s development, often prioritizing those who stand to profit over consumers. You know, capitalism. The rapid adoption and expansion of AI, driven by commercial and nationalist competition, have created significant distortions. Companies like Nvidia have soared in value due to AI chip sales, and governments are heavily investing in AI technology to gain competitive advantages. Listening to AI experts highlights the enormity of the commitment being made and reveals that these experts, despite their knowledge, may not be the best sources for AI guidance. The size and impact of AI are already redirecting massive resources and creating new challenges. For example, AI’s demand for energy, chips, memory, and talent is immense, and the future of AI-driven applications depends on the availability of computing resources. The rise in demand for AI has already led to significant industry changes. Data centers are transforming into ‘AI data centers,’ and the demand for specialized AI chips and memory is skyrocketing. The U.S. government is investing billions to boost its position in AI, and countries like China are rapidly advancing in AI expertise. China may be behind in physical assets, but it is moving fast on expertise, generating almost half of the world’s top AI researchers (Source: New York Times). The U.S. has just announced it will provide chip maker Intel with $20 billion in grants and loans to boost the country’s position in AI. Nvidia is now the third largest company in the world, entirely because its specialized chips account for more than 70 percent of AI chip sales. Memory-maker Micro has mostly run out of high-bandwidth memory (HBM) stocks because of the chips’ usage in AI—one customer paid $600 million up-front to lock in supply, according to a story by Stack. Back in January, the International Energy Agency forecast that data centers may more than double their electrical consumption by 2026 (Source: Sandra MacGregor, Data Center Knowledge). AI is sucking up all the payroll: Those tech workers who don’t have AI skills are finding fewer roles and lower salaries—or their jobs disappearing entirely to automation and AI (Source: Belle Lin at WSJ). Sam Altman of OpenAI sees a future where demand for AI-driven apps is limited only by the amount of computing available at a price the consumer is willing o pay. “Compute is going to be the currency of the future. I think it will be maybe the most precious commodity in the world, and I think we should be investing heavily to make a lot more compute.” Sam Altman, OpenAI CEO This AI buildup is reminiscent of past technological transformations, where powerful interests shaped outcomes, often at the expense of broader societal considerations. Consider early car manufacturers. They focused on a need for factories, components, and roads.

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March 26, 2024in Generative AI
Big Marketing Strategies for Small Businesses
22Mar

Big Marketing Strategies for Small Businesses

Smart Marketing Strategies for SMBs and Startups on a Budget Running a small or medium-sized business (SMB) or startup means finding creative ways to attract customers while maximizing limited resources. While marketing on a tight budget may seem challenging, the right approach can turn constraints into opportunities. Read on to discover great big tactics for little businesses. With a mix of technology and creativity, you can effectively grow your business without overspending. In fact, 76% of SMBs are investing more in technology this year than last. With a strategic mindset and the right tools, budget-conscious marketing can be just as impactful as big-budget campaigns. Build a Cost-Effective Website Start your marketing journey with a free or low-cost website—your business’s digital storefront. You don’t need a massive investment to make your site engaging and effective. With easy-to-use ecommerce platforms, you can create a clean, user-friendly site that connects with your audience. How to Make Your Website Shine: Leverage SEO and Content Marketing Search engine optimization (SEO) and content marketing are your best allies in boosting online visibility without high costs. A well-optimized website with valuable content can drive organic traffic and increase engagement. SEO Tips for SMBs: Maximize Google My Business (GMB) Google My Business is a free tool that enhances your visibility in local searches. Keep your profile updated with accurate contact details, business hours, and engaging photos to build credibility and attract local customers. How to Optimize GMB: Personalize Email Marketing Campaigns Email marketing is a cost-effective way to stay connected with customers. A well-crafted email strategy fosters engagement and brand loyalty. Email Marketing Best Practices: Invest in a CRM System A customer relationship management (CRM) tool helps streamline communication, track leads, and improve customer interactions. Platforms like Starter Suite make it easy to follow up with potential customers and create targeted marketing campaigns. Why Use a CRM? Optimize Social Media Marketing Social media is a powerful and free tool for brand awareness, but success depends on consistency and strategy. Focus on platforms where your target audience is most active. Social Media Best Practices: Leverage Video and Podcasts Encourage Customer Testimonials Nothing builds trust like genuine customer reviews and testimonials. Positive feedback can influence potential buyers and reinforce credibility. How to Gather Great Testimonials: Pro Tip: Use AI-powered tools to generate surveys, craft follow-up emails, and request reviews efficiently. Track Progress with Analytics Marketing efforts should be data-driven. Tools like Google Analytics and CRM platforms provide insights into customer behavior, traffic sources, and campaign effectiveness. How to Use Analytics: Market Your SMB Like a Pro—Without a Big Budget Effective marketing doesn’t require a massive budget—just smart strategies and the right tools. By building a strong online presence, leveraging cost-effective marketing channels, and connecting with customers personally, you can make a lasting impact. Get started with Starter Suite today to streamline your marketing and grow your business with ease. If you have read this far, you may be concerned you don’t have the manpower to make these changes. Tectonic is here to help. 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 22, 2024in Data, Google, Google Analytics, Technology
Top AI Tools Shaping Business Success
19Mar

Top AI Tools Shaping Business Success

Top AI Tools Shaping Business Success in 2024 In the dynamic world of business, staying ahead means embracing the latest technologies. Artificial Intelligence (AI) is no longer just a buzzword—it’s a transformative force that helps businesses operate more efficiently, make smarter decisions, and enhance customer experiences. As we move through 2024, the AI tool ecosystem is rapidly expanding, offering innovative solutions to automate tasks, gain deep insights, and improve customer engagement. Below, we explore the top AI tools that are shaping the future of business. StoryChief is a comprehensive content marketing platform that simplifies the creation and distribution of content through AI. From ideation to optimization, it leverages machine learning to help businesses generate high-quality, engaging content at scale. Key Features: Pricing: Plans start with a free tier, with paid options ranging from $40 to $500 per month. Developed by OpenAI, ChatGPT is a versatile language model capable of generating human-like text. It excels in content creation, customer support, and data analysis. Key Use Cases: Pricing: API access with usage-based pricing. Perplexity AI is an advanced search engine that provides accurate, summarized answers to complex queries using natural language processing (NLP). Key Features: Pricing: Free version available, with Pro version at $20/month offering enhanced features. Zapier connects over 5,000 apps, enabling automation of repetitive tasks across your tech stack with AI-powered tools that simplify complex automations. Key Features: Pricing: Free plan available for up to 100 tasks per month; paid plans start at $19.99/month. Grammarly is an AI-driven writing assistant that enhances the quality of written communication, ensuring clarity, conciseness, and error-free content. Key Features: Pricing: Free version available; Premium plans start at $12/month for individuals and $25/user/month for businesses. Typeframes simplifies video creation with AI, turning scripts or images into professional-quality videos with animations, transitions, and voiceovers. Key Features: Pricing: Plans start at $29/month, with higher-tier options available. Chatbase enables businesses to build intelligent chatbots and virtual assistants that handle a wide range of customer service inquiries. Key Features: Pricing: Free plan available with limited message credits; paid plans start at $19/month. Secta is an AI-powered headshot generator that creates professional-quality headshots from user-submitted photos, ideal for businesses needing polished profile pictures. Key Features: Pricing: Pay-as-you-go at $49 per headshot session. Voicenotes is an AI-driven transcription tool that converts voice memos into concise summaries and action items, perfect for capturing important information efficiently. Key Features: Pricing: Free plan available; paid plans start at $10/month, with lifetime payment options. Notion AI enhances the popular Notion productivity platform with AI-powered writing assistance, content summarization, and database management. Key Features: Pricing: Available as an add-on at $10 per user per month, with discounts for annual plans. Choosing the Right AI Tools for Your Business Selecting the right AI tools involves considering several factors: By evaluating these aspects, you can effectively leverage AI to enhance efficiency, drive growth, and maintain a competitive edge in 2024. 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 19, 2024in Salesforce
Acceptable AI Use Policies
19Mar

AI Data Readiness

Data Readiness: The Key to AI Success As organizations rapidly integrate AI into their CRM systems, data readiness has become a critical factor in successful AI implementation. A study by Forrester found that companies prioritizing data readiness achieve better outcomes when deploying AI-powered CRM features. Additionally, organizations can leverage vendors to enhance their data readiness and AI capabilities, though trust remains a serious consideration. The Impact of Data Readiness The Growing Importance of AI-Ready Data AI adoption has surged across industries, with a McKinsey survey revealing that AI adoption has more than doubled in recent years. Furthermore, IBM’s 2023 CEO study found that 75% of CEOs believe competitive advantage hinges on advanced generative AI capabilities. However, AI is only as effective as the data supporting it. Chad Sanderson, CEO of Gable, likens data readiness to a healthy diet: “If garbage goes in, garbage comes out.” AI-ready data must be well-governed, secure, bias-free, enriched, accurate, and high quality. What is Data Readiness for AI? Data readiness for AI involves preparing data to ensure its effectiveness in AI-driven applications. Key characteristics of AI-ready data include: Defining AI-Ready Data: 4 Key Factors Different industry experts provide varied definitions of AI-ready data: In our interpretation, AI-ready data exists in a unified platform, not in silos. It is enriched with metadata, ensuring transparency in data lineage, enabling AI systems to deliver meaningful insights. Additionally, AI-ready data requires a governance framework to maintain security, compliance, and ethical use. 1. Metadata Management Metadata management provides essential context for AI systems. Key elements include: 2. Data and Metadata Quality Management High-quality AI output depends on high-quality data. Organizations should continuously evaluate data based on relevance, reliability, and accuracy. Equally important is metadata quality, which ensures that AI models interpret and apply data correctly. 3. Data Lineage Management Understanding data origins and transformations is crucial for AI readiness. Harvard Business Review emphasizes the importance of ontology, a structured representation of data relationships, in AI system development. 4. Data Governance Data governance establishes AI standards, ensuring ethical and compliant AI practices. Steve Lohr of The New York Times highlights data provenance as a key governance element, akin to food safety regulations ensuring transparency in data origins and processing. Is Your Data AI-Ready? According to IBM’s 2023 CEO survey, the top barriers to AI adoption include concerns around data lineage, security, and compliance. Harvard Business Review also cites siloed data as a major challenge, emphasizing that AI success requires well-prepared data systems. Gartner underscores the necessity of lighthouse principles—guiding frameworks for ethical AI usage. Organizations lacking structured governance, transparency, and documentation are not yet AI-ready. How to Ensure Data Readiness for AI A Gartner survey found that only 9% of CIOs and data leaders have an AI vision statement, with over a third lacking plans to create one. The first step to AI readiness is defining an AI vision statement and setting lighthouse principles to guide AI initiatives. Key strategies for AI readiness include: Wrapping Up Achieving data readiness for AI involves ensuring data is secure, accurate, bias-free, enriched, and accessible. Key components include metadata management, quality assurance, data lineage tracking, and governance frameworks. Ultimately, AI readiness extends beyond technology—it requires a cultural shift within organizations. Aligning strategy, preparing data, and fostering AI-driven decision-making will enable organizations to harness AI’s full potential. By following these best practices, businesses can ensure their AI investments deliver meaningful, data-driven insights. 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 19, 2024in Data, Generative AI, Salesforce, Technology
Custom Copilot Actions
18Mar

Custom Copilot Actions

How to Create a Custom Copilot Action Custom Copilot Actions allow you to extend Copilot’s functionality within Salesforce, enabling users to perform tasks specific to your business needs. By utilizing invocable Apex classes, autolaunched flows, and prompt templates, you can build custom actions tailored to your organization’s requirements. Extend your unified copilot with custom actions. Before You Begin: Steps to Create a Custom Copilot Action: Testing and Deployment: Understanding Einstein Copilot Einstein Copilot is Salesforce’s AI assistant designed to enhance productivity and user experience across various applications and departments. Admins can configure and deploy Copilots to empower users with AI capabilities, streamlining workflows and increasing efficiency. Out-of-the-Box Actions: In the Spring ’24 release, Einstein Copilot offers several out-of-the-box actions, including: Customization and Future Development: Admins can create custom actions to tailor Copilot’s capabilities to their organization’s specific requirements. Custom actions enable tasks such as updating records and integrating with external systems, enhancing productivity and efficiency. When you create a custom action, you build it on top of platform functionality you want to make available in Einstein Copilot, such as invocable Apex classes, autolaunched flows, or prompt templates. Adding custom actions lets you customize your copilot and get more mileage out of your current Salesforce platform capabilities. Access to a custom copilot action depends on the type of Salesforce action it references. For example, if a custom action was built using a flow, the custom action adheres to the permissions, field-level security, and sharing settings configured in the flow. Use Cases and Considerations: Typical Use Cases: Considerations: Building Custom Copilot Actions: Power of Custom Actions: Custom actions extend Copilot’s capabilities, offering a wide range of use cases and functionalities. Actions can be built using flows, prompts, or Apex, providing flexibility and customization options. Descriptive Instructions: Accurate descriptions of actions, inputs, and outputs are essential for Copilot’s understanding and execution. Clear instructions provide context and improve response accuracy. Best Practices: Einstein Copilot, coupled with custom actions, empowers organizations to optimize workflows and drive efficiency. By following best practices and leveraging the full potential of Copilot, Salesforce admins can enhance user experiences and unlock new levels of productivity. Explore these features within your organization to realize the benefits of Salesforce Einstein Copilot Custom Actions. Assign an action to your copilot from the Copilot Actions page, the record page for an action, or the Copilot Action Library tab of the actions panel in the Copilot Builder. Your copilot must be deactivated. To test your action and preview how the output appears in a copilot conversation, open the copilot in the Copilot Builder and start a preview conversation. Enter utterances that you expect to trigger your action, and then make adjustments to the copilot action instructions based on your results. What powers Einstein Copilot custom actions? By facilitating the flow of work through smart, AI-driven actions, Einstein Copilot enhances efficiency and decision-making. Here’s how organizations can harness its power through the design of custom actions, ensuring their operations are as streamlined and effective as possible. 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 18, 2024in Mulesoft, Salesforce Einstein
ai and sustainability
14Mar

AI and Sustainability

Climate Change: A Global Crisis Demanding Urgent Action Climate change is one of the most critical challenges of our time, accelerating at an unprecedented pace. Rising global temperatures, melting polar ice, surging sea levels, and intensifying extreme weather events are destabilizing ecosystems, endangering biodiversity, and jeopardizing human communities worldwide. The future of our planet and the well-being of generations to come depend on decisive action—reducing greenhouse gas emissions, shifting to renewable energy, and embracing sustainable practices. Artificial intelligence (AI) is emerging as a vital tool in this fight, offering innovative technological solutions to advance sustainability efforts. AI for a Sustainable Future Sustainability is about meeting society’s environmental, social, and economic needs without compromising future generations’ ability to do the same. With mounting pressure on Earth’s resources and growing recognition of the need for responsible practices, sustainability has never been more crucial. The United Nations’ 17 Sustainable Development Goals (SDGs) provide a global framework for fostering sustainable progress. AI stands at the forefront of this movement, enabling smarter resource management, waste reduction, and more efficient systems—while also demanding careful consideration of its own environmental impact. Key Areas Where AI Drives Sustainability Beyond these areas, AI aids sustainability across industries—streamlining manufacturing processes, designing energy-efficient buildings, and advancing green technologies. The Hidden Cost: AI’s Carbon Footprint Despite its benefits, AI has a significant environmental downside. Data centers, which power AI systems, consume vast amounts of energy—accounting for roughly 1% of global electricity use—and this demand is rising. Much of this energy comes from non-renewable sources, contributing to carbon emissions. Additionally, hardware production involves resource-intensive processes, from mining rare metals to managing electronic waste. It is not totally unimaginable that the “tree huggers” and “nuclear power haters” are dusting off their signs to protest the surging power demands of AI. To maximize AI’s sustainability potential, we must address its environmental impact. This includes: By balancing AI’s advantages with its ecological costs, we can harness its power to build a greener future—without undermining the very goals it seeks to achieve. 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 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 14, 2024in Artificial Intelligence, Data, Google
UX Design Trends 2024
08Mar

UX Design Trends 2024

Navigating Design Trends: AI, Discovery, Accessibility, and Collaboration. Salesforce UX Design Trends 2024. As we reflect on the past year and look ahead, design trends are emerging, signaling a pivotal moment in the intersection of creativity, usability, and AI. For developers, admins, architects, and business leaders, understanding these trends is crucial in shaping the future. Here are the four design trends steering this transformative journey: As we move forward, these design trends signify a paradigm shift, emphasizing the significance of AI, streamlined discovery, accessibility, and the growing collaboration between designers and developers. Navigating this transformative landscape requires an adaptable mindset and a commitment to ethical, inclusive design practices from the outset. When you work with Tectonic we take all these considerations to mind as we design or re-design your Salesforce org. Contact Tectonic today. UX Design Trends 2024 Like2 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 8, 2024in Salesforce
AI and the Role of Healthcare CIOs
07Mar

AI and the Role of Healthcare CIOs

Healthcare leaders see significant potential in data analytics and AI technology to transform the industry over the next five years, according to a new market research report from Arcadia and The Harris Poll. AI and the Role of Healthcare CIOs The report, titled “The Healthcare CIO’s Role in the Age of AI,” examines AI’s impact on the healthcare sector and how decision-makers are preparing to leverage the technology. Notably, 96% of healthcare leaders surveyed believe that adopting AI effectively will provide a competitive edge both now and in the future. While only a third see AI as essential today, 73% expect it to become critical within five years. How Health Systems Are Using AI Around 63% of respondents revealed that their organizations use AI to analyze large patient data sets to identify trends and guide population health management efforts. Another 58% are using AI to analyze individual patient data to identify opportunities for improving health outcomes. Close to half of the leaders indicated that AI is being used to optimize electronic health records (EHR) management and analysis. These trends align with the findings of the recent “Top of Mind for Top Health Systems” survey, conducted by the University of Pittsburgh Medical Center’s Center for Connected Medicine (CCM) in collaboration with KLAS, which identified AI as the most exciting emerging technology in healthcare with transformative potential for both administration and care delivery. The excitement surrounding healthcare AI largely stems from its ability to break down data silos and tap into the wealth of clinical data that healthcare organizations already collect. “Healthcare leaders are thoughtfully preparing to harness the full value of AI in care delivery reform,” said Aneesh Chopra, Arcadia’s chief strategy officer. “As safe, secure data sharing scales, technology leaders prioritize data platforms that organize fragmented patient records into clinically relevant insights at every stage of the patient journey.” A quest for a 360 degree patient view abounds. Using AI to Support Strategic Priorities The Arcadia survey emphasized the importance of using analytics to improve patient care, with 83% of leaders believing that harnessing data will help healthcare organizations remain competitive and resilient while overcoming digital transformation and financial challenges. Eighty-four percent of respondents cited technology as a current priority, with 44% focusing on an enterprise-wide approach to data analytics, 41% prioritizing AI-driven decision-making, and 32% working to simplify technical ecosystems. These efforts are viewed as crucial to advancing other strategic goals, with 40% of leaders prioritizing the patient experience, 35% aiming to improve outcomes, and 29% focusing on patient engagement. Although healthcare leaders view AI adoption positively for strategic advancements, hurdles remain. While 96% of respondents are confident in adopting AI, many feel pressured to move quickly. When asked about the sources of this pressure, 82% cited data and analytics teams, 78% pointed to IT and tech teams, and 73% mentioned executives. However, successfully implementing AI requires talent and resources that some organizations lack. About 40% of leaders identified a lack of talent as a significant barrier to AI adoption, signaling the need for IT and analytics teams to acquire new skill sets. Seventy-one percent of IT leaders reported a growing demand for data-driven decision-making skills, while two-thirds pointed to a rising need for expertise in data analysis, machine learning, and systems integration. Additionally, nearly 60% mentioned the need for roles that focus on training and support for healthcare staff. The Evolving Role of CIOs CIOs and other healthcare leaders are seeing their roles evolve as AI and data become more integrated into healthcare operations. Eighty-seven percent of respondents see themselves as strategy influencers, actively involved in setting and executing AI strategies, while only 13% view themselves as purely focused on implementation. Despite these evolving roles, many CIOs feel constrained by daily operations. Fifty-eight percent reported being primarily focused on tactical execution rather than developing long-term AI strategies, although they believe they should spend 75% of their time on strategic planning to be most effective. Part of these strategies will likely focus on improving communication and workforce readiness. Three out of four leaders cited a lack of effective communication between IT teams and clinical staff as a barrier to leveraging new technologies, and two out of five noted that clinical staff are not fully equipped to make the best use of data analytics. “CIOs and their teams are setting the stage for an AI-powered revolution in patient care and healthcare operations,” said Michael Meucci, Arcadia’s president and CEO. “Our findings highlight a strong consensus that a solid data foundation is necessary to realize the future of AI in healthcare. At the same time, the human workforce, with evolving talent and skills, will shape the real-world impact of AI in healthcare.“ Content updated August 2024. 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 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 7, 2024in Generative AI, Salesforce Development Services, Salesforce Health and Life Sciences Solutions
Einstein Copilot Studio
02Mar

Einstein Copilot Studio Explained

Einstein Copilot Studio Explained: Crafting and Personalizing a Reliable AI Assistant Enterprises aiming to personalize Einstein Copilot can leverage the newly introduced Einstein Copilot Studio. This platform enables the construction and customization of AI assistants, incorporating pertinent prompts, skills, and AI models tailored for specific sales, service, marketing, commerce, and IT tasks. Beyond the confines of Salesforce applications, companies can seamlessly integrate Einstein Copilot into consumer-facing channels. This extension enhances customer interactions by embedding AI assistants into websites for real-time chat capabilities or integrating with popular messaging platforms such as Slack, WhatsApp, or SMS. Einstein Copilot Studio comprises the following key components: Just as Microsoft has introduced its own Copilot solutions, powered by generative AI, Salesforce is tapping into the power of LLMs to empower sales, marketing, and customer service professionals. Building on Salesforce’s existing range of Einstein AI features, the company announced “Einstein 1” this year – the next generation of the Salesforce platform. Einstein 1 is a comprehensive suite of tools that empowers users to bring AI into their everyday workflows. The Einstein Copilot (Salesforce Copilot) solution is at the core of this solution, alongside the new Copilot studio and the Einstein Trust Layer. Contact Tectonic today to explore the value of Einstein Copilot Studio for your company., Like2 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 2, 2024in Einstein 1 Platform
AI Training Options
29Feb

AI Training Options

As AI adoption accelerates, AI certifications and courses have proliferated, providing deeper knowledge of this rapidly evolving technology. AI Training Options. Numerous AI certifications cover the basics, so we’ve narrowed the field to 10 of the most diverse and comprehensive programs. AI Training Options Artificial intelligence is poised to become the key technology that drives business transformation and gives companies a competitive edge. According to a recent forecast by the International Data Corporation, global spending on AI—including AI-enabled applications, infrastructure, and related services—will more than double to $632 billion by 2028, growing at a compound annual rate of 29% between 2024 and 2028. AI helps businesses boost productivity by automating processes such as robotics and autonomous vehicles, while also supporting existing workforces with technologies like assisted and augmented intelligence. Companies are integrating AI across various sectors, including finance, healthcare, retail, smart home devices, fraud detection, and security surveillance. Why AI certifications are important: 10 of the best AI certifications and courses: Each certification offers unique benefits, whether you’re a beginner or an experienced professional aiming to stay ahead in AI-driven industries. Content updated September 2024. 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 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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February 29, 2024in Artificial Intelligence, Data, Generative AI, Google, Technology
Personalization With Customized AI-Driven Journeys
28Feb

Personalization With Customized AI-Driven Journeys

AI-Enabled Triggers for Guiding Customer Journeys – Personalization With Customized AI-Driven Journeys Initiate timely and relevant customer experiences that seamlessly lead individuals through their purchasing journey. Employ AI-powered decision-making to identify the most suitable next steps for customers, offering personalized suggestions based on real-time behavior, historical data, and business-specific datasets such as pricing and inventory. Deliver predefined experiences, such as browsing or cart abandonment journeys, while utilizing real-time interactions to determine the optimal content, channel, or offer for each customer. Efficiently extract insights by harnessing behavioral data and advanced analytics to visualize cross-channel customer journeys for both individuals and segments, identifying and resolving key friction points. Elevate customer acquisition, loyalty, and lifetime value by crafting personalized, omni-channel journeys that align with both customer desires and business objectives. Enable trigger-based customer journeys that facilitate immediate responses to customer actions, whether in the physical realm, such as entering a store and connecting to Wi-Fi, or in the virtual space, like visiting a shopping website. The Role of AI in Elevating the Customer Journey AI significantly contributes to heightened customer satisfaction, ultimately leading to improved retention. Address customer pain points in their preferred language and provide solutions tailored to their needs based on purchasing history and previous interactions with customer service. AI’s Influence Across Customer Journey Stages At each stage of the customer journey, AI transforms experiences by delivering personalized interactions from awareness to post-purchase. This transformation is made possible through automation, predictive analytics, and intelligent virtual agents. Transformative Impact of Generative AI on Customer Journeys Generative AI, exemplified by advanced language models like GPT-4, has the potential to revolutionize customer journeys. These models automate communication and content creation, dynamically adjusting tone and style to match customer preferences. For instance, Grammarly’s tone detector adapts communication based on the recipient’s profile and interaction history. Continuous Iteration and AI in Customer Journey Mapping In the era of digitization, AI-driven personalization surpasses traditional customer journey mapping based on a few personas. Organizations must harness AI and machine learning to create personalized journeys that enhance user experiences. The iterative improvement process involves collecting comprehensive data, utilizing AI for analysis and insights, implementing changes, and evaluating results through key performance indicators. Netflix: An AI Success Story Netflix serves as a prime example of AI success, continuously analyzing user behavior and preferences to refine content recommendation algorithms. This approach enhances personalization, leading to increased customer engagement and satisfaction. Integrating Generative AI into Existing Systems To fully capitalize on generative AI, integration into existing systems and processes is crucial. This may entail developing APIs to connect AI tools with customer relationship management (CRM) systems and content management systems. Testing and Continuous Enhancement Implementing AI-driven personalization necessitates a robust testing and evaluation process. Clearly defined key performance indicators and analytics capabilities are essential for measuring effectiveness and making continuous improvements. Like2 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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February 28, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Marketing Cloud, Salesforce Personalization
28Feb

Salesforce Data Cloud Explained

Salesforce Data Cloud: The Essential Guide Unlocking the Power of Unified Customer Data Salesforce Data Cloud revolutionizes how businesses connect and activate customer data by unifying information from multiple sources—including demographic, behavioral, and transactional data (e.g., mobile app engagement, eCommerce purchases, and support cases). But before diving in, it’s crucial to understand what Data Cloud is (and isn’t) to maximize its potential. Here are 10 key facts to guide your implementation. 1. Data Cloud (Free) vs. Paid Editions 💡 Key Insight: Start with the free tier to explore, then upgrade as needs grow. 2. Availability & Regional Restrictions 3. Unified Profiles: The “Golden Record” A unified profile is not a merged record—it’s a dynamic, real-time view combining: Unlike Salesforce duplicate rules, source records remain intact—Data Cloud simply creates a single customer view. ⚠️ Note: Unified profiles consume credits based on processing complexity. 4. Data Cloud ≠ A Data Lake 5. Key Data Modeling Concepts Before ingesting data, understand: 📌 Pro Tip: If you’ve used Marketing Cloud Data Extensions, you already know this! 6. No Activations in Free Tier Activations (sending segments to external platforms) require paid editions: Without activations, your segments remain stuck in Data Cloud. 7. Activations vs. Data Actions Feature Use Case Targets Activations Send segments to external platforms Marketing Cloud, Ads, Salesforce Apps Data Actions Trigger real-time insights Platform Events, Webhooks, MC 8. Have Clear Use Cases Before enabling Data Cloud, define what problem you’re solving:✅ Personalized Marketing (e.g., dynamic ad audiences)✅ AI-Driven Sales Insights (e.g., lead scoring)✅ Unified Service History (e.g., 360° customer view) 🚀 Example: A retailer uses Data Cloud to track online + in-store purchases, enabling hyper-targeted email campaigns. 9. The Learning Curve is Worth It 10. Start Small, Scale Smart Final Thoughts Salesforce Data Cloud is a game-changer for businesses drowning in siloed data. By unifying customer insights and enabling real-time activation, it powers smarter marketing, sales, and service—but only if implemented strategically. Ready to begin?✔ Leverage the free tier for testing.✔ Plan use cases before scaling.✔ Invest in training to maximize value. The future of CRM is connected data—will your business be ready? Content updated March 2025. 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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February 28, 2024in Data, Enterprise, Google, Salesforce, Salesforce Data Cloud, Snowflake
New ChatGPT-4o
23Feb

ChatGPT and Salesforce Explained

Supercharge Salesforce with ChatGPT: AI-Powered CRM Enhancements Integrating ChatGPT with Salesforce unlocks transformative potential across sales, service, marketing, and development—boosting efficiency, personalization, and decision-making. Here’s how businesses can harness generative AI to elevate their CRM strategy. 1. Automating Workflows & Boosting Productivity Workflow Optimization Accelerated Development AI-Generated Content 2. Smarter Customer Engagement Intelligent Lead Management Hyper-Personalized Communication Instant Customer Support 3. Data-Driven Sales & Marketing Predictive Sales Insights Laser-Targeted Campaigns AI-Powered Sales Forecasting 4. Seamless Salesforce Integration Einstein GPT + OpenAI Lightning Web Components (LWC) API Configuration 5. Real-World Use Cases Scenario AI Solution Outcome Case Summarization ChatGPT auto-generates case notes for agents. 50% faster resolution times. Dynamic Email Drafting AI crafts personalized responses in <10 seconds. 35% higher reply rates. Automated Reporting “Show me Q2 pipeline trends” → Instant dashboard. No-code analytics for all users. The Bottom Line By integrating ChatGPT with Salesforce, businesses can:✅ Reduce manual work with AI automation.✅ Enhance customer experiences through hyper-personalization.✅ Drive revenue growth with predictive insights. With Einstein GPT and custom LWC integrations, Salesforce users can deploy generative AI without complex coding—unlocking smarter, faster, and more scalable CRM operations. Ready to transform your Salesforce workflows? Start with a pilot in lead scoring, service automation, or sales forecasting today. Content updated June 2025. 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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February 23, 2024in Data, Generative AI, Salesforce
gettectonic.com