Technology Archives - gettectonic.com

12May

Generative AI for Insurance and Financial Services

According to CBInsights, based upon research conducted by analyzing earnings calls, business relationships, and investment activities to assess the AI initiatives of some of the world’s largest companies across various sectors. Generative AI for Insurance and Financial Services is growing rapidly. The latest research report from the CBInsights team highlights the undeniable significance of AI for many of these global giants. Salesforce CEO Marc Benioff, for instance, referred to AI as “the single most important moment in the history of the technology industry” during the company’s recent earnings call. JPMorgan CEO Jamie Dimon echoed this sentiment in his April 2024 letter, expressing strong conviction about the extraordinary consequences of AI. Several companies are strategically focusing on AI to drive efficiencies and innovation. For instance, major pharmaceutical firms are collaborating on AI-powered drug discovery projects to expedite drug development timelines, while payments giants are deploying AI to combat fraud effectively. Despite the hype surrounding recent advancements, the translation of AI innovations into revenue has been limited so far. However, companies remain optimistic about future opportunities, recognizing the imperative of taking proactive steps to reshape industries. Generative AI for Insurance and Financial Services CBInsights’ comprehensive report digs into the AI strategies of various companies across sectors such as financial services, insurance, enterprise tech, pharmaceuticals, and industrials. By leveraging the CB Insights technology intelligence platform, they have analyzed signals like investment, partnerships, executive discussions in earnings transcripts, and patents to gain insights into these efforts. AI and machine learning algorithms are increasingly being utilized to enhance digital identity and regulatory technology (Regtech) services, as well as to improve customer experience through AI chatbots. In the financial services sector, advancements in AI technology are making services more accessible and frictionless, empowering investment platforms to automate tasks and focus on critical product development endeavors. While AI is still evolving, it is expected to play a pivotal role in driving the digital economy forward in the near 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

May 12, 2024in Generative AI

11May

Gen AI Role in Healthcare

Generative AI’s Growing Role in Healthcare: Potential and Challenges The rapid advancements in large language models (LLMs) have introduced generative AI tools into nearly every business sector, including healthcare. As defined by the Government Accountability Office, generative AI is “a technology that can create content, including text, images, audio, or video, when prompted by a user.” These systems learn patterns and relationships from vast datasets, enabling them to generate new content that resembles but is not identical to the original training data. This capability is powered by machine learning algorithms and statistical models. In healthcare, generative AI is being utilized for various applications, including clinical documentation, patient communication, and clinical text summarization. Streamlining Clinical Documentation Excessive documentation is a leading cause of clinician burnout, as highlighted by a 2022 athenahealth survey conducted by the Harris Poll. Generative AI shows promise in easing these documentation burdens, potentially improving clinician satisfaction and reducing burnout. A 2024 study published in NEJM Catalyst explored the use of ambient AI scribes within The Permanente Medical Group (TPMG). This technology employs smartphone microphones and generative AI to transcribe patient encounters in real-time, providing clinicians with draft documentation for review. In October 2023, TPMG deployed this ambient AI technology across various settings, benefiting 10,000 physicians and staff. Physicians who used the ambient AI scribe reported positive outcomes, including more personal and meaningful patient interactions and reduced after-hours electronic health record (EHR) documentation. Early patient feedback was also favorable, with improved provider interactions noted. Additionally, ambient AI produced high-quality clinical documentation for clinician review. However, a 2023 study in the Journal of the American Medical Informatics Association (JAMIA) cautioned that ambient AI might struggle with non-lexical conversational sounds (NLCSes), such as “mm-hm” or “uh-uh,” which can convey clinically relevant information. The study found that while the ambient AI tools had a word error rate of about 12% for all words, the error rate for NLCSes was significantly higher, reaching up to 98.7% for those conveying critical information. Misinterpretation of these sounds could lead to inaccuracies in clinical documentation and potential patient safety issues. Enhancing Patient Communication With the digital transformation in healthcare, patient portal messages have surged. A 2021 study in JAMIA reported a 157% increase in patient portal inbox messages since 2020. In response, some healthcare organizations are exploring the use of generative AI to draft replies to these messages. A 2024 study published in JAMA Network Open evaluated the adoption of AI-generated draft replies to patient messages at an academic medical center. After five weeks, clinicians used the AI-generated drafts 20% of the time, a notable rate considering the LLMs were not fine-tuned for patient communication. Clinicians reported reduced task load and emotional exhaustion, suggesting that AI-generated replies could help alleviate burnout. However, the study found no significant changes in reply time, read time, or write time between the pre-pilot and pilot periods. Despite this, clinicians expressed optimism about time savings, indicating that the cognitive ease of editing drafts rather than writing from scratch might not be fully captured by time metrics. Summarizing Clinical Data Summarizing information within patient records is a time-consuming task for clinicians, and errors in this process can negatively impact clinical decision support. Generative AI has shown potential in this area, with a 2023 study finding that LLM-generated summaries could outperform human expert summaries in terms of conciseness, completeness, and correctness. However, using generative AI for clinical data summarization presents risks. A viewpoint in JAMA argued that LLMs performing summarization tasks might not fall under FDA medical device oversight, as they provide language-based outputs rather than disease predictions or numerical estimates. Without statutory changes, the FDA’s authority to regulate these LLMs remains unclear. The authors also noted that differences in summary length, organization, and tone could influence clinician interpretations and subsequent decision-making. Furthermore, LLMs might exhibit biases, such as sycophancy, where responses are tailored to user expectations. To address these concerns, the authors called for comprehensive standards for LLM-generated summaries, including testing for biases and errors, as well as clinical trials to quantify potential harms and benefits. The Path Forward Generative AI holds significant promise for transforming healthcare and reducing clinician burnout, but realizing this potential requires comprehensive standards and regulatory clarity. A 2024 study published in npj Digital Medicine emphasized the need for defined leadership, adoption incentives, and ongoing regulation to deliver on the promise of generative AI in healthcare. Leadership should focus on establishing guidelines for LLM performance and identifying optimal clinical settings for AI tool trials. The study suggested that a subcommittee within the FDA, comprising physicians, healthcare administrators, developers, and investors, could effectively lead this effort. Additionally, widespread deployment of generative AI will likely require payer incentives, as most providers view these tools as capital expenses. With the right leadership, incentives, and regulatory framework, generative AI can be effectively implemented across the healthcare continuum to streamline clinical workflows and improve patient care. 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

May 11, 2024in Einstein 1 Platform, Generative AI, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Implementation Services, Salesforce Optimization

10May

Agentic Era of UX

The Agentic Era of UX The future of digital experience has arrived, but it’s fragmenting into countless micro-applications. The missing piece in AI user experience? The experience itself. It’s been almost a year and a half since generative AI burst onto the scene, heralded as transformative. But what have we actually seen in terms of user experience? Many companies released AI-powered summaries or search features, claimed them as revolutionary, and received applause—until the applause faded. The so-called “next era” of tech hasn’t yet delivered on its promise. We were given “the most profound technology since fire,” yet many implementations feel like candles that barely flicker. Many UX designers continue advocating for AI to solve genuine user needs. Technology must serve users, not just exist for its own sake. The core issue now is broader: AI has often been treated as a quick fix rather than a true UX transformation. Where user experience traditionally supports the entire journey, AI is being wedged into small, isolated tasks, losing the holistic perspective. For most companies, AI feels like a string of individual “use cases” rather than a full, cohesive UX meal. Many consulting firms push companies to prioritize use cases in terms of complexity and value, often resulting in chatbots that address a handful of user needs. There are notable exceptions, though. For example, Loom went beyond simple AI features to enhance the user’s entire workflow, supporting end-to-end functionality for video recording, transcription, editing, and even task management. Welcome to the Agentic Era of AI We’re now on the verge of the “agentic” era of AI. Industry leaders are abuzz with the potential of AI agents. OpenAI’s Sam Altman calls agents AI’s “killer function,” while other leaders predict this future is within reach, possibly within 3–18 months. The agentic promise is profound: AI agents, or “agentic workflows,” break down complex tasks into manageable steps, helping users complete intricate projects with autonomy. As Ezra Klein describes, imagine telling an AI to plan your child’s dragon-themed birthday party in Brooklyn, and the agent handles everything from booking to ordering the cake—transforming a casual AI prompt into tangible results. Today’s general-purpose models can’t handle this level of complexity independently. But agentic workflows make this possible by chaining AI actions, allowing systems to execute tasks step-by-step. A Vision for Agentic UX Design’s role in this era is to bring a vision of agentic UX to life. In traditional digital experiences, we build systems that assist users along their journey, but we still expect users to navigate the journey themselves. With an agentic UX, an AI partner supports the user at every step. This vision means UX will be defined by three pillars: Early examples are emerging, like Adobe’s Gen Studio, Intercom’s Copilot, and Dovetail’s Magic Experience, each taking steps toward a future where AI provides ongoing, meaningful support to users. An agentic UX doesn’t necessarily need to label itself “agent-powered.” Dovetail, for instance, offers a suite of “Magic” features where the AI partner plays a supporting role, from summarizing transcripts to highlighting key points. Over time, as AI evolves, these agents will assume greater responsibility in user journeys, shifting from supportive to proactive. Strategically Reinvent for the Agentic Era Adapting to the agentic era presents an opportunity—and a risk for those who ignore it. Currently, organizations are focused on laying the infrastructure for “AI readiness.” While that’s essential, it can obscure the longer-term vision of what’s possible. Until business leaders fully grasp the agentic UX’s potential, it’s up to design to step into a strategic role and make this vision vivid, relatable, and exciting. This requires more than launching a quick proof of concept; it demands a reimagining of digital experience. Here’s a recommended approach: It’s been a challenging year for design, with layoffs and value debates. But with the agentic era approaching, the strategic potential for UX is immense. Now is the time to rally, to guide organizations into a new era of digital experience where users are truly supported every step of the way. 4ox Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more

May 10, 2024in Generative AI, Technology

09May

Marketing To Generation Alpha

Marketing to Generation Alpha: A Blueprint for Marketers As Generation Alpha emerges onto the consumer landscape, marketers face the challenge of engaging with this digitally native and globally conscious cohort. With the oldest members just 14 years old, they’re already shaping purchasing decisions and are poised to wield significant buying power in the coming years. To understand how to effectively connect with Generation Alpha, we turn to insights from leading researchers in the field. What makes Gen Alpha unique? Unlike prior generations, Gen Alpha is growing up in a digital age that empowers them to make decisions for themselves at a younger age. They have unprecedented access to information, online content, and social networks, allowing them to form opinions and make choices independently. What Defines Generation Alpha? Generation Alpha, born from 2010 onwards, represents the latest demographic wave. Despite their youth, they’re already exerting influence on their parents’ spending habits, setting the stage for their own economic impact, projected to surpass $5.46 trillion by 2029. This generation is characterized by its global outlook, digital fluency, and social connectivity. They are mobile in terms of lifestyle, visual in content consumption, and deeply intertwined with technology and social media. These children are coming of age in a pandemic and post-pandemic world. Face masks are as common as Tik Toks. Why can’t Gen Alpha read? The performance of Gen Alpha in schools is influenced by multiple factors. One key aspect is the evolving educational landscape, with traditional teaching methods sometimes struggling to cater to the unique learning styles and preferences of this generation. A woke generation of teachers is creating an ultra-woke generation of students. Key Insights from Experts Mark McCrindle, who coined the term Generation Alpha, underscores their digital and social nature, highlighting their unique preferences and behaviors. Heather Dretsch, Ph.D., emphasizes the influence of millennial parents on Generation Alpha’s consumer habits, noting a nod to nostalgia in brand preferences. Understanding Gen Alpha’s Values Generation Alpha exhibits a heightened social consciousness, surpassing even their predecessors, Gen Z, in their concern for global issues such as climate change, racism, and equality. They view themselves as stewards of the future, advocating for positive change on a global scale. Even as young as age 14. What is the least parented generation? According to Wikipedia, a 2004 marketing study conducted by Reach Advisors stated that Gen X kids “went through its all-important, formative years as one of the least parented, least nurtured generations in U.S. history.” Marketers need to address the fact that the least parented generation is raising the Gen Alpha generation. What problems will Gen Alpha face? Less development of creativity and imagination. Without questioning the skills that the Alpha generation will acquire thanks to new technologies, it should be stressed that as the use of physical toys is reduced, the development of imagination and creativity will suffer. Reduced ability to achieve happiness. An expectation of all toys being interactive from an electronic and AI perspective is going to develop a different generation than one that played with rolling pins and pie pans or cardboard boxes or outside until the street lights came on. Navigating Marketing Strategies To resonate with Generation Alpha, brands must align with their ethical values authentically. Simply paying lip service won’t suffice; brands must demonstrate genuine commitment through tangible actions, such as donations or sustainable practices. Gen Alpha’s sophistication makes them adept at discerning inauthentic messaging, requiring marketers to build genuine, two-way relationships. Generation Alpha–born from the early 2010s to the mid-2020s–will be the largest and most connected generation in history. Plus, their economic footprint is expected to wield as much spending power as Millennials and Gen Z combined, by the year 2029. Adapting to Gen Alpha’s Preferences Generation Alpha’s digital proficiency and individualistic tendencies necessitate a shift in marketing approaches. Traditional branding methods may fall short, as this generation seeks personal engagement and co-creation opportunities. Brands should prioritize authentic digital relationships over mere consumption, leveraging platforms where Gen Alpha feels most at home. Embracing Nostalgia and Authenticity Millennial parents play a significant role in shaping Gen Alpha’s preferences, often introducing them to brands and content from their own childhoods. Nostalgia can be a powerful tool for marketers, tapping into shared experiences and cultural touchpoints. Moreover, Gen Alpha values authenticity and genuine connections, favoring brands that resonate with their personal identity and values. Numbering 2 billion and counting, Gen Alpha (born 2010-2024) is expected to be the biggest generation in history. And even though its oldest members are only 14 years old, Gen Alpha is already an economic force to be reckoned with. “They’re spending money, and in significant amounts. Not only that, they influence parental purchasing decisions in a significant way,” says social analyst and demographer Mark McCrindle. “We estimate that the global spend of Generation Alpha direct, and in influence, is $5.5 trillion already, so a pretty phenomenal economic footprint to go with their unsurpassed demographic footprint.” Its youngest members will make their appearance this year, but the oldest Alphas were born the same year the iPad came out. We think of kids from the 80’s being born with a joystick in their hands. The 90’s with a keyboard. Imaging coming into a world as connected as with access to an iPad and the internet. As the first entire generation born into the world of smartphones and other connected devices, Alphas have become consumers much earlier than previous generations. That’s thanks, in part, to online forms of payment linked to parental credit cards or other digital currencies. And they’re using that money to buy digital games and accessories. “They’re buying virtual items using virtual currency,” McCrindle says. “So, there’s whole new ways of spending and means of spending for this generation that’s really leading to that increased commercialization.” Looking Ahead As marketers navigate the evolving landscape of Generation Alpha, they must remain agile and responsive to shifting preferences and behaviors. By prioritizing authenticity, ethical values, and meaningful engagement, brands can forge lasting connections with this sophisticated and socially conscious generation. In conclusion,

May 9, 2024in Salesforce

08May

Reddit Acquires Memorable AI

Reddit Acquires Memorable AI to Enhance Ad Campaign Performance Reddit has acquired Memorable AI, an ad creative optimization platform, in a strategic move to enhance ad campaign performance and impact for its advertisers. This acquisition will integrate Memorable AI’s advanced tools into Reddit’s ad stack, offering benefits such as creative insights, improved effectiveness, and automation to maximize ad performance and return on ad spend. “Memorable AI has a proven ability to optimize ad creative for the best possible results before an ad even runs,” said Reddit Chief Operating Officer Jen Wong. “By incorporating Memorable AI’s capabilities, Reddit will advance its efforts in optimizing, generating, and selecting ad creatives to deliver superior results for our advertisers. We are excited to welcome the Memorable AI team to Reddit.” Recently recognized as one of Gartner’s Cool Vendors in Generative AI for Marketing 2024, Memorable AI specializes in estimating the impact of ad creatives across metrics like click-through, engagement, view-through rates, brand lift, and conversion rates. This acquisition follows Reddit’s recent purchase of audience contextualization company Spiketrap. Reddit Acquires Memorable AI Sebastian Acevedo, Co-Founder of Memorable AI, commented, “Over the past three years, we have focused on developing cutting-edge creative intelligence products. Our state-of-the-art machine learning models help top global advertisers analyze their creatives, predict their impact, and achieve double-digit improvements with actionable insights. We are thrilled to elevate this technology with Reddit’s extensive customer base. This acquisition positions Reddit as a leader in creative effectiveness AI, and its advertisers will greatly benefit from AI-driven creative pretests and recommendations.” The Memorable AI team has joined Reddit and will lead projects across Reddit’s ads business, driving forward innovative solutions for ad performance. 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 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 Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more

May 8, 2024in Generative AI

07May

Why AI Keeps Salesforce Co-Founder Up At Night

Parker Harris holds conflicting views on artificial intelligence (AI). As the co-founder of Salesforce, he has urged the company’s leaders to swiftly integrate AI into their products. However, he grapples with concerns about maintaining the balance between speed and the company’s reputation for delivering high-quality solutions to clients. This dilemma has even led him to lose sleep. Expressing his anxiety at Salesforce’s World Tour event in New York City, Harris emphasized the unprecedented pace of AI development. He feels a sense of urgency to accelerate the adoption of AI technologies, driven by the need to meet customer expectations. Yet, he recognizes the importance of caution, knowing that customers rely on Salesforce to provide reliable solutions. Harris acknowledges the challenge of navigating this balance, pondering how to move quickly without making critical mistakes. Transitioning to his role as chief technology officer at Slack, a subsidiary of Salesforce, Harris reflected on AI’s potential, particularly its ability to generate images and videos from simple prompts. However, he tempered the enthusiasm by noting that what may seem like “magic tricks” on social media platforms may not necessarily translate effectively in workplace contexts. Harris also acknowledged the pervasive fear among entrepreneurs of missing out on the AI revolution, especially after a significant milestone in February when OpenAI, a market leader, was valued at $80 billion. This realization, coupled with the partnership between Salesforce rival Microsoft and OpenAI, prompted Harris and Salesforce co-founder Marc Benioff to acknowledge their need to catch up in the AI race. Salesforce’s main AI offering, Einstein, enables businesses to create predictive AI models using proprietary customer data. In Slack, enterprises can access Slack AI, a tool that summarizes conversations and provides answers to questions, for a monthly fee of $10 per person. Despite the promise of AI, Harris highlighted a critical issue: trust. He expressed concerns about AI occasionally providing inaccurate information or omitting key details, which could erode user trust in the technology. Maintaining trust is crucial, as users are unlikely to continue using AI tools if they encounter such troubling issues. 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

May 7, 2024in Salesforce, Salesforce Einstein

04May

Salesforce to Power Loyalty and Personalization for IHG

IHG Hotels & Resorts has teamed up with Salesforce to elevate guest loyalty and meet the evolving expectations of customers. Through its One Rewards program, IHG aims to foster guest loyalty by enhancing efficiency and delivering personalized experiences across its expansive network of over 6,000 hotels spanning 19 IHG brands. Salesforce to Power Loyalty and Personalization for IHG Research indicates that 65% of consumers express a preference for brands that prioritize personalized experiences. In response to these consumer preferences, IHG is embarking on a journey to standardize its CRM infrastructure using the Einstein 1 Platform. This platform seamlessly integrates CRM and data to create comprehensive customer profiles and tailor guest experiences, thereby driving loyalty. Leveraging generative AI, Salesforce and its technology partners are also assisting IHG in guest management endeavors. Heather Balsley, Global Chief Commercial & Marketing Officer at IHG Hotels & Resorts, emphasized, “As we strive to enhance the IHG One Rewards loyalty program, our foremost goal is to provide guests with booking and stay experiences that are customized to their unique travel requirements. Our partnership with Salesforce will empower us to further refine the technology, tools, teams, and solutions underpinning our loyalty program, enabling us to offer personalized content and services that forge deeper connections with our most valued guests.” Salesforce to Power Loyalty and Personalization for IHG By harnessing the capabilities of Service Cloud, IHG gains a comprehensive 360-degree view of guests, enabling prompt and accurate resolution of guest inquiries and thereby elevating overall guest satisfaction. Additionally, IHG’s adoption of Marketing Cloud facilitates targeted customer engagement through preferred communication channels, including email, SMS, and push notifications. IHG One Rewards members exhibit a strong inclination to book directly through IHG websites and its One Rewards mobile app, demonstrating a significant increase in spending compared to non-members. Through the predictive AI technology offered by the Einstein 1 Platform, IHG aims to expand its loyalty membership base and further enhance guest engagement. For more information about the Einstein 1 Platform, visit: Salesforce – Einstein 1 Platform 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

May 4, 2024in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Einstein, Salesforce Hospitality Travel and Transportation

29Apr

Blockers to IT Success and Salesforce Implementation Solutions

The CIO’s website recently delved into the primary obstacles to achieving success in IT. Tectonic echoes these concerns and offers insights and remedies based on our Salesforce Implementation Solutions. Issues such as data challenges, technical debt, and talent shortages can significantly hinder the progress of IT organizations and departments in executing high-value projects. Several CIOs have shared their approaches to tackling these challenges. Tectonic poses solutions based upon the Salesforce ecosystem. Carm Taglienti, Chief Data Officer and Distinguished Engineer at Insight, reflects on the dual nature of the recent surge in artificial intelligence (AI). While AI advancements have undoubtedly enhanced efficiency and productivity across technology departments, lines of business, and business units, the rapid proliferation of AI technologies, particularly generative AI, has disrupted numerous IT plans. Taglienti emphasizes the need for organizations to adapt swiftly to these technological shifts to avoid derailing critical projects. Tectonic recently looked at challenges the public sector face in regards to AI. Read more here. The rapid evolution of technology poses a continuous challenge for IT leaders. The relentless pace of technological advancements, exemplified by the rise of AI, demands proactive resource allocation to stay competitive. Ryan Downing, CIO of Principal Financial Group, underscores the necessity of adopting a strategic approach to navigate the complexities of multicloud environments effectively. Tectonic echoes the multicloud challenge. We address this for our clients with Salesforce implementation, optimization, consulting, and ongoing managed services. Salesforce remains the world’s number one CRM solution for a reason. Cloud solutions for marketing, personalization, patient data privacy, manufacturing, feedback management, and more are just a small sampling of the IT solutions Salesforce and Tectonic present. Unaddressed data issues pose a significant impediment to realizing the full potential of analytics, automation, and AI. Many organizations are grappling with legacy systems and inadequate data management practices, hindering their progress in succesfully deploying advanced technologies. Working with a Salesforce partner can address this challenge. The scarcity of skilled talent remains a pressing concern for CIOs, as highlighted in the State of the CIO Study by Foundry. Despite efforts to train internal staff and leverage contractors, filling critical tech positions remains challenging, impeding transformation initiatives. Managed services providers help address this skill gap. Technical debt and legacy systems present additional hurdles for IT departments. The maintenance of outdated infrastructure drains resources and limits innovation, forcing CIOs to strike a delicate balance between modernization efforts and operational demands. Addressing cybersecurity threats and compliance with evolving regulations further strains IT resources, necessitating proactive measures to safeguard organizational assets and maintain regulatory compliance. Striking the right balance between sustaining existing operations, fostering growth, and driving transformative initiatives is another challenge facing CIOs. Scott Saccal of Cambrex emphasizes the importance of aligning resource allocation with strategic objectives to avoid market displacement. The allure of new technologies, coupled with executive pressure to explore shiny objects, can divert focus from core priorities, hampering strategic execution. Shadow IT and the lack of organizational agility pose additional barriers to IT success, highlighting the need for CIOs to foster collaboration, align IT initiatives with business goals, and cultivate a culture of adaptability within their departments. ‘Shadow IT’ refers to the unsanctioned use of software, hardware, or other systems and services within an organization, often without the knowledge of that organization’s information technology (IT) department. CIOs must navigate a myriad of challenges, from technological disruptions to talent shortages, while maintaining a laser focus on strategic objectives to drive organizational success in an ever-evolving digital landscape. Tectonic is here to consult and achieve your IT challenges. Contact us today. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

April 29, 2024in Generative AI, Salesforce, Salesforce Einstein

24Apr

Impact of AI Agents Across Key Sectors in 2024

Sophisticated autonomous digital entities are already transforming our lives, industries, and the way we engage with technology. What will be the Impact of AI Agents Across Key Sectors in 2024? While much attention has been given to Generative AI (Gen AI), the next major leap forward comes from AI Agents. This emerging technology is set to revolutionize how we work and interact with the world. How AI Agents Will Shape Daily Life AI Agents: An OverviewAI Agents, also called digital assistants or AI-driven entities, are advanced systems designed to perform tasks and provide services autonomously. They use machine learning, natural language processing, and other AI technologies to understand user needs, solve problems, and complete tasks without direct human intervention. The Impact of AI Agents Across Key Sectors in 2024 Personalization and AssistanceAI Agents are increasingly embedded in our personal and professional routines. By learning our preferences, habits, and needs, they offer personalized recommendations, such as curating music playlists, suggesting films, or creating custom workout plans. Their ability to deliver tailored assistance makes everyday life more seamless and enjoyable. Healthcare AdvancementsIn healthcare, AI Agents are making a significant impact. They can analyze medical records, provide diagnostic insights, and assist with treatment planning. Multi-modal agents even process medical imaging to aid in diagnoses, marking a groundbreaking advancement for both healthcare professionals and patients. Efficiency in BusinessAI Agents are transforming business operations by improving customer service through 24/7 automated chatbots and streamlining processes in supply chain management, human resources, and data analysis. These systems help optimize operations and support more informed decision-making. Education and LearningIn education, AI Agents offer personalized learning experiences tailored to each student’s needs, helping them learn at their own pace. Teachers also benefit, as AI Agents provide insights to customize instruction and track student progress. Enhanced CybersecurityAs cybersecurity threats evolve, AI Agents play a key role in identifying and mitigating risks. They detect anomalies in real-time, helping organizations protect their data and systems from breaches and attacks. Environmental ImpactAI Agents are contributing to sustainability by optimizing energy consumption in buildings, improving waste management, and monitoring environmental changes. Their role in addressing climate change is increasingly critical. Research and InnovationIn fields like drug discovery and climate modeling, AI Agents accelerate research by processing and analyzing vast amounts of data. Their involvement speeds up discoveries and innovation across multiple domains. Impact of AI Agents Across Key Sectors in 2024 In 2024, AI Agents have become much more than just digital assistants; they are driving transformative change across industries and daily life. Their ability to understand, adapt, and respond to human needs makes technology more efficient, personalized, and accessible. However, as AI Agents continue to evolve, it is crucial to consider ethical concerns and promote responsible use. With mindful integration, AI Agents hold the promise of a more connected, sustainable, and innovative future. If you are ready to explore AI Agents in your business, contact Tectonic today. 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

April 24, 2024in Generative AI

22Apr

More Sustainable and Equitable Future Through AI

Salesforce has unveiled a series of initiatives aimed at fostering a more sustainable and equitable future through AI. The company has introduced its Sustainable AI Policy Principles, a framework designed to guide AI regulation with a focus on minimizing environmental impact and promoting climate innovation. Additionally, Salesforce has selected five new nonprofits for its Salesforce Accelerator – AI for Impact, which targets climate action. This initiative will enable these purpose-driven organizations to harness AI solutions to tackle the pressing challenges of climate change. Why It Matters Prioritizing responsible AI development is crucial for leveraging technology to make a positive impact while ensuring that equity and sustainability remain central. Salesforce Sustainable AI Policy PrinciplesRead Them Here Key Aspects of the Principles The Sustainable AI Policy Principles extend Salesforce’s commitment to advocating for science-based policies that support a just and equitable transition to a 1.5-degree future. These principles offer best practices for lawmakers and regulators on: Salesforce is also the first tech company to support the Transformational AI to Modernize the Economy (TAME) legislation, which aims to enhance AI’s role in predicting and responding to extreme weather events. The AI for Impact Accelerator The AI for Impact cohort will support climate-focused nonprofits with technology, investments, and philanthropy to develop AI solutions that benefit the environment. Alongside product donations and $2 million in funding, these organizations will work on AI-powered initiatives in three crucial areas: Participants will also receive a year of pro bono consulting from Salesforce experts in strategy, planning, responsible AI use, data strategy, and technical architecture. Accelerator Participants Include: Moving Forward Suzanne DiBianca, EVP and Chief Impact Officer at Salesforce, emphasizes the importance of developing equitable and sustainable AI technology. “With AI transforming our lives and work, it is vital to ensure the technology is developed responsibly. We are excited to support climate nonprofits committed to sustainable AI innovation and advocate for clear policies that guide responsible AI development.” Quotes from Participants: Together, these efforts aim to accelerate the positive impact of technology, ensuring it benefits everyone and supports a sustainable 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

April 22, 2024in Salesforce

21Apr

Harnessing Zero Copy Integration

Streamlining Data Management: Harnessing Zero Copy Integration for Efficient Customer Insights Zero copy integration offers a revolutionary approach to accessing and utilizing customer data without the need for burdensome data transfers. By seamlessly linking disparate databases, this innovative technique eliminates the complexities associated with moving, copying, or reformatting data. Let’s explore how zero copy integration can optimize data management processes and enhance the efficiency of customer data platforms (CDPs) alongside traditional data warehouses. Understanding Zero Copy Integration: Zero copy integration, also known as zero ETL (extract-transform-load), facilitates the sharing of data across multiple databases without physically relocating it. This method enables real-time access to data, significantly reducing costs and mitigating the risks of errors inherent in data movement processes. Unlike traditional data replication methods, zero copy integration ensures that data remains in its original location, eliminating the need for redundant storage and synchronization efforts. Good technology standards can actually bring order to the chaos and allow products from different companies to work together, fostering healthy competition and enhancing productivity. That is precisely what Zero-Copy Integration does. Zero-Copy Integration is a framework that eliminates the need for data copies and integration, making it easier to work with applications, analytics, artificial intelligence, and machine learning. Canada’s Digital Governance Council recently announced that Zero-Copy Integration has been published for open access by the public, setting a new standard for data collaboration. Moreover, Zero-Copy Integration prioritizes data-centricity and active metadata over complex code and solution modularity over monolithic design. It also facilitates data governance through data products and federated stewardship, eliminating the need for centralized teams. In addition to boosting the development and deployment of new technologies, Zero-Copy Integration also addresses the growing number of data privacy regulations. By putting data at the center of the process, Zero-Copy Integration ensures greater collaboration and control, positively affecting industries like healthcare, research, banking, and public services. Benefits of Zero-Data Integration Proponents of zero-copy integration and dataware say the framework will lower data storage costs, improve performance of IT teams, improve privacy and security of data, and drive innovation in systems for public health, social research, open banking and sustainability through innovations in: Comparing Traditional vs. Zero Copy Integration: Aspect Traditional Zero Copy Replication Requires copying data to target Data remains in original location Updates Data accuracy dependent on synchronization Real-time access to data Cost Involves data movement expenses No additional data movement costs Regulatory Compliance Complex governance due to data duplication Simplified compliance with source data only Errors Data movement introduces potential errors Minimized risk of errors with no data movement Maintenance Increases complexity with copying and synchronization Streamlined management with no data relocation Implementing Zero Copy Integration: The implementation of zero copy integration varies depending on the platform and direction of data access. Let’s explore how it works in scenarios involving Salesforce Data Cloud and Snowflake data warehouse: Case Study: Buyers Edge’s Zero Copy Success Story: Buyers Edge, a procurement optimization company, leveraged zero copy integration to unify customer profiles in a CDP while accessing purchase data from their data warehouse. By seamlessly integrating Salesforce Data Cloud with their warehouse, Buyers Edge enhanced predictive modeling capabilities, resulting in tailored sales and marketing strategies. Zero copy integration revolutionizes data management practices by enabling seamless data access and eliminating the need for data duplication or relocation. As businesses navigate the evolving data landscape, leveraging zero copy integration can streamline operations, enhance insights, and empower organizations to unlock the full potential of their data assets. MILESTONES / TIMELINE Second half 2023 – Internationalization February 21, 2023 – Information Session (watch above ☝ or via YouTube) February 15, 2023 – ‘Zero-copy’ applications published by DCA February 08, 2023 – Published by Digital Governance Council (Press release) December 15, 2022 – Approved by Standards Council of Canada June-Nov 2022 – Public consultation period 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

April 21, 2024in Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake

18Apr

Who Calls AI Ethical

Background – Who Calls AI Ethical On March 13, 2024, the European Union (EU) enacted the EU AI Act, a move that some argue has hindered its position in the global AI race. This legislation aims to ‘unify’ the development and implementation of AI within the EU, but it is seen as more restrictive than progressive. Rather than fostering innovation, the act focuses on governance, which may not be sufficient for maintaining a competitive edge. The EU AI Act embodies the EU’s stance on Ethical AI, a concept that has been met with skepticism. Critics argue that Ethical AI is often misinterpreted and, at worst, a monetizable construct. In contrast, Responsible AI, which emphasizes ensuring products perform as intended without causing harm, is seen as a more practical approach. This involves methodologies such as red-teaming and penetration testing to stress-test products. This critique of Ethical AI forms the basis of this insight,and Eric Sandosham article here. The EU AI Act To understand the implications of the EU AI Act, it is essential to summarize its key components and address the broader issues with the concept of Ethical AI. The EU defines AI as “a machine-based system designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment. It infers from the input it receives to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.” Based on this definition, the EU AI Act can be summarized into several key points: Fear of AI The EU AI Act appears to be driven by concerns about AI being weaponized or becoming uncontrollable. Questions arise about whether the act aims to prevent job disruptions or protect against potential risks. However, AI is essentially automating and enhancing tasks that humans already perform, such as social scoring, predictive policing, and background checks. AI’s implementation is more consistent, reliable, and faster than human efforts. Existing regulations already cover vehicular safety, healthcare safety, and infrastructure safety, raising the question of why AI-specific regulations are necessary. AI solutions automate decision-making, but the parameters and outcomes are still human-designed. The fear of AI becoming uncontrollable lacks evidence, and the path to artificial general intelligence (AGI) remains distant. Ethical AI as a Red Herring In AI research and development, the terms Ethical AI and Responsible AI are often used interchangeably, but they are distinct. Ethics involve systematized rules of right and wrong, often with legal implications. Morality is informed by cultural and religious beliefs, while responsibility is about accountability and obligation. These constructs are continuously evolving, and so must the ethics and rights related to technology and AI. Promoting AI development and broad adoption can naturally improve governance through market forces, transparency, and competition. Profit-driven organizations are incentivized to enhance AI’s positive utility. The focus should be on defining responsible use of AI, especially for non-profit and government agencies. Towards Responsible AI Responsible AI emphasizes accountability and obligation. It involves defining safeguards against misuse rather than prohibiting use cases out of fear. This aligns with responsible product development, where existing legal frameworks ensure products work as intended and minimize misuse risks. AI can improve processes such as recruitment by reducing errors compared to human solutions. AI’s role is to make distinctions based on data attributes, striving for accuracy. The concern is erroneous discrimination, which can be mitigated through rigorous testing for bias as part of product quality assurance. Conclusion The EU AI Act is unlikely to become a global standard. It may slow AI research, development, and implementation within the EU, hindering AI adoption in the region and causing long-term harm. Humanity has an obligation to push the boundaries of AI innovation. As a species facing eventual extinction from various potential threats, AI could represent a means of survival and advancement beyond our biological limitations. 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

April 18, 2024in Salesforce

14Apr

Paradox of Writing With AI

It seems like some people honestly believe they can spot AI-generated content immediately, but that’s not always the case. Well-written content isn’t inherently AI-generated, and if it is AI-generated, that doesn’t necessarily mean it’s well-written. The quality of writing often depends more on the writer’s skill than the tools they use. Paradox of Writing With AI is that it will make a good writer better. And it will make a bad writer worse. The real difference in human versus AI content lies in the accessibility of writing tools and the lack of proper ethical regulation for their use. This ease of access makes it simple for people to feel entitled to judge written content. True, if you publish your writing – online or elsewhere – you open it up for judgement. But imagine if UX design or data applications were graded as indiscriminately—those discussions would likely be confined to experts rather than becoming public debates on social media condemning all well-written content. Good writing requires creativity, flair, and uniqueness, among other skills, to truly impress readers. Good writing is well-organized and flows well with consistent style or voice from beginning to end. Good writing is also free from mistakes and errors in spelling, punctuation and grammar. But that alone doesn’t make it engaging or meaningful. A good writer will brainstorm for great ideas and follow them up with research. A good writer can think of fresh angles to view a topic. A good writer is sure to re-write and self-edit to make a better draft. AI has been integrated into various tools and applications long before ChatGPT was launched. Search engines use it to provide relevant results; social media algorithms keep your favorite content visible; Siri and Alexa rely on natural language processing and speech recognition; Netflix and Spotify use AI recommendation systems to cater to your tastes, and so on. AI enhances human ideas, not just in writing, but across many fields. Writing With AI is Inevitable For instance, Chinese Nobel laureate Mo Yan surprised everyone at the 65th-anniversary celebration of Shouhuo magazine by revealing he uses ChatGPT. During his speech praising fellow author Yu Hua, he mentioned that he struggled to write a commendation and asked a doctoral student to use ChatGPT for help. This revelation caused quite a stir, as it was unexpected for a Nobel Prize winner to use AI for writing. Why shouldn’t he? If AI makes a good writer better, then most of us should be employing it. Mo Yan isn’t alone. Rie Kudan, the 17th winner of Japan’s Akutagawa Prize, admitted to using ChatGPT for her novel, Tokyo-to Dojo-to. She stated that about 5% of the book consists of AI-generated sentences. Kudan, who is introverted, shared that frequent interactions with the AI tool allowed her to express personal thoughts she couldn’t comfortably discuss with others. ChatGPT’s responses often sparked dialogue in her novel, adding a unique dimension to her writing process. Grammarly, another AI tool, is why some people’s writing doesn’t reflect their irritation when discussing AI-generated content online. Grammarly has been widely used for editing and proofreading, ensuring users’ writing maintains a promotional tone and corrects errors without sounding sarcastic or bored. The Problem with Sounding Alike & The Uniqueness of a Writer’s Voice A significant issue with AI-generated content is that many written works sound similar. Writers need to develop unique voices. While Jane Austen, Mary Shelley, and the Brontë sisters are admirable, emulating their ornate language can interfere with communication’s primary purpose. Excessive fanciness can make speech overly flamboyant, akin to Oscar Wilde’s works. However asking AI to work through your content and put it in the voice of a known writer, add humor, or change the tense is time saving. The problem isn’t that AI enables people to produce well-crafted content. Many individuals have exceptional writing skills and huge vocabularies. The real issue is the uniformity in everyone’s writing, a lack of diversity that AI can perpetuate. Yet, you only have to Google any topic and you will find many blog posts and articles that share the same view, and perhaps the same voice. Some discussions about AI resemble early 2000s conspiracy theories about cell phones. While the context has changed, the tone remains similar. The Importance of Creativity in Writing & Our Language Creativity is essential in writing. Even AI relies on human creativity. Without our input, machines would repeatedly generate the same content. Machine learning in AI is about learning from people. Our role is crucial, demonstrating the value of our unique voices. Developing a unique voice takes time and effort, which is why creatives like Kelly McKernan, Nicki Minaj, Elin Hilderbrand, and Jonathan Franzen are suing AI companies for copyright infringement. These unique voices significantly impact language evolution, and it’s vital for us to continue growing creatively. Writers play a crucial role in language evolution by creating new words or phrases that captivate readers. Over time, these innovations can enrich the language. A writer’s distinctive style can set trends, leading to significant changes in language use. This power must be used wisely. Famous writers’ narrative structures and dialogue usage can inspire others. For example, Dr. Seuss coined “nerd,” J.R.R. Tolkien introduced “tween,” Milton created “pandemonium”, novelist William Gibson first used “cyberspace”, Johnathon Swift gave us “yahoo” in Gulliver’s Travels, and Charles Dickens gave us “boredom.” The core of a good piece of writing is a great idea. With a strong core idea, the writer can easily layer the content around it. Content even can build the framework from which comes a whole new word. Content includes interesting examples to which the reader can relate. That content needs to be well-organized and clear in form so that the reader can easily see the message or find the intended meaning. In addition, the writing should have style and the right voice that matches its topic and theme while also reflecting what the author believes. Writing Through the Centuries Writing has evolved over centuries, influencing language development. During

April 14, 2024in Salesforce Einstein

13Apr

Gen AI Depends on Good Data

Accelerate Your Generative AI Journey: A Call to Action for Data Leaders Generative AI is generating immense excitement across organizations, with boards of directors conducting educational workshops and senior management teams brainstorming potential use cases. They need to keep in mind, Gen AI Depends on Good Data. Individuals and departments are already experimenting with the technology to enhance productivity and effectiveness. There needs to be as much effort into data quality as to the technology. The critical work required for generative AI success falls to chief data officers (CDOs), data engineers, and knowledge curators. Unfortunately, many have yet to begin the necessary preparations. A survey in late 2023 of 334 CDOs and data leaders, sponsored by Amazon Web Services and the MIT Chief Data Officer/Information Quality Symposium, coupled with interviews, reveals a gap between enthusiasm and readiness. While there’s a shared excitement about generative AI, much work remains to get organizations ready for it. The Current State of Data Preparedness Most companies have yet to develop new data strategies or manage their data to effectively leverage generative AI. This insight outlines the survey results and suggests next steps for data readiness. Maximizing Value with Generative AI Historically, AI has worked with structured data like numbers in rows and columns. Generative AI, however, utilizes unstructured data—text, images, and video—to generate new content. This technology offers both assistance and competition for human content creators. Survey findings show that 80% of data leaders believe generative AI will transform their business environment, and 62% plan to increase spending on it. Yet, many are not yet realizing substantial economic value from generative AI. Only 6% of respondents have a generative AI application in production deployment. A significant 16% have banned employee use, though this is decreasing as companies address data privacy issues with enterprise versions of generative AI models. Focus on Core Business Areas Experiments with generative AI should target core business areas. Universal Music, for instance, is aggressively experimenting with generative AI for R&D, exploring how it can create music, write lyrics, and imitate artists’ voices while protecting intellectual property rights. Gen AI Depends on Good Data For generative AI to be truly valuable, organizations need to customize vendors’ models with their own data and prepare their data for integration. Generative AI relies on well-curated data to ensure accuracy, recency, uniqueness, and other quality attributes. Poor-quality data yields poor-quality AI responses. Data leaders in our survey cited data quality as the greatest challenge to realizing generative AI’s potential, with 46% highlighting this issue. Jeff McMillan, Chief Data, Analytics, and Innovation Officer at Morgan Stanley Wealth Management, emphasizes the importance of high-quality training content and the need to address disparate data sources for successful generative AI implementation. Current Efforts and Challenges Most data leaders have not yet made significant changes to their data strategies. While 93% agree that a data strategy is critical for generative AI, 57% have made no changes, and only 11% strongly agree their organizations have the right data foundation. Organizations making progress are focusing on specific tasks like data integration, cleaning datasets, surveying data, and curating documents for domain-specific AI models. Walid Mehanna, Group Chief Data and AI Officer at Merck Group, and Raj Nimmagadda, Chief Data Officer for R&D at Sanofi, stress the importance of robust data foundations, governance, and standards for generative AI success. Focus on High-Value Data Domains Given the monumental effort required to curate, clean, and integrate all unstructured data for generative AI, organizations should focus on specific data domains where they plan to implement the technology. The most common business areas prioritizing generative AI development include customer operations, software engineering, marketing and sales, and R&D. The Time to Start is Now While other important data projects exist, including improving transaction data and supporting traditional analytics, the preparation for generative AI should not be delayed. Despite some slow pivoting from structured to unstructured data management, and competition among CDOs, CIOs, CTOs, and chief digital officers for leadership in generative AI, the consensus is clear: generative AI is a transformative capability. Preparing a large organization’s data for AI could take several years, and the time to start is now. 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

April 13, 2024in Generative AI

09Apr

What is Salesforce Einstein 1?

The bold new future of enterprise AI requires a new type of platform. What is Salesforce Einstein 1? One platform that can handle terabytes of disconnected data, gives you the freedom to choose your AI models, and connects directly into the flow of work, all while maintaining customer trust. The Einstein 1 Platform unifies your data, AI, CRM, development, and security into a single, comprehensive platform. It empowers IT, admins, and developers with an extensible AI platform, facilitating fast development of generative apps and automation. What is Salesforce Einstein 1 Einstein 1 has a mixture of artificial intelligence tools on the platform, and it kind of mirrors the way the core Salesforce platform is built, standardized and custom. We have out of the box AI features such as sales email generation in Sales Cloud, and service replies in Service Cloud. What is Einstein One? Einstein One seamlessly integrates our robust data platform with Data Cloud, offering a comprehensive AI and data-driven solution within our CRM service. As the leading comprehensive AI for CRM, Salesforce Einstein transforms the Customer Success Platform by incorporating a suite of integrated AI technologies, making it more intelligent and accessible to innovators worldwide. Introducing the Einstein One Platform The future of enterprise AI demands a groundbreaking platform capable of managing terabytes of diverse data, providing the flexibility to select AI models, and seamlessly integrating into daily workflows while maintaining customer trust. The Einstein One Platform consolidates data, AI, CRM, development, and security into a singular, comprehensive platform. It empowers IT, administrators, and developers with an extensible AI platform, facilitating rapid development of generative apps and automation. Salesforce has made significant investments in enhancing the Einstein One platform by introducing two prompt engineering features – a testing center and prompt engineering suggestions, demonstrating the company’s commitment to advancing AI capabilities. Data-driven and AI-driven customer experiences are vital in constructing Data Cloud. Salesforce’s predictive AI, Einstein, has been operational since 2016, conducting over a trillion predictions per week. The company continuously evolves its capabilities, introducing generative AI products like Einstein GPT, discussed at Dreamforce [2023]. ‘Customer 360′ now represents Salesforce customers’ ability to transform into customer-centric entities, delivering integrated and cohesive experiences across sales, marketing, service, and commerce. Leveraging Data Cloud, structured and unstructured engagement data comes alive, offering a personalized perspective of customer interactions. Einstein is accessible through various Salesforce products, including Sales Cloud, Service Cloud, Marketing Cloud, Salesforce Platform, Analytics Cloud, and Community Cloud. What is the Einstein One platform? Salesforce’s Einstein One is a transformative platform that securely integrates data, connects multiple Salesforce products, and empowers customer-centric businesses to create AI-driven apps, revolutionizing CRM interactions. What applications are connected with the Einstein One platform? Einstein Trust Layer: Ensuring the security of generative AI applications within Salesforce, this application acts as a safeguard for data, preventing unauthorized access. Data Cloud: Unifying structured and unstructured data, Data Cloud completes the customer 360 profile, integrating seamlessly with the Einstein One platform and making data actionable. Einstein Copilot: A built-in conversational assistant, Einstein Copilot enables users to ask questions in Natural Language and receive intelligent answers, actions, and more. Copilot Studio: An essential component of Einstein One, Copilot Studio manages Einstein One and Einstein Copilot, allowing businesses to control user access and use generative AI in their workspace. Prompt Builder, Skill Builder, Model Builder: Tools within Copilot Studio, these components empower businesses to create trusted AI prompts, add skills to user access, and choose AI models. What is Data Cloud for Einstein One? Data Cloud, combined with the Einstein Trust Layer, provides secure access to a unified data repository, forming a reliable resource for complete customer profiles and supporting AI assistants. Data Cloud facilitates valuable visualizations through reports, dashboards, and tools like Tableau, offering insights to enhance understanding of customers and business operations. What will Einstein One do for businesses? Einstein One aims to: Increase productivity Reduce operational costs Enhance the delivery of exceptional customer experiences The debut of Einstein One marks a significant stride for Salesforce and businesses, offering a secure path to boost productivity through AI technologies, ensuring continuous access to cutting-edge technologies for businesses. Where can generative AI impact businesses today? Generative AI has the potential to impact businesses by enhancing repetitive processes, making them faster. Exploring text-based processes, such as repetitive emails or form filling, is a great starting point for businesses looking to enhance capabilities. What can generative AI do for sales, service, field service teams? Generative AI can positively impact teams by automating processes, offering intelligent insights, and improving overall efficiency. Specific use cases for generative AI in sales, service, and field service teams can be explored through Salesforce’s 101 video series. What does Einstein One Tableau do? Einstein One Data Cloud, formerly known as Genie, serves as a metadata management tool connecting data from various sources. It makes data usable for AI and analysis, integrating with Einstein One, Tableau, and Salesforce’s CRM applications. Is Salesforce Einstein the same as Tableau? Formerly known as Einstein Analytics, Tableau CRM is Salesforce’s premium analytic platform, offering a powerful way to explore data, especially for current Salesforce users. Salesforce has renamed Einstein Analytics to Tableau CRM, reflecting its commitment to empowering users to make better decisions faster. In essence, the Einstein One platform combines Salesforce Data Cloud, Einstein Copilot, and the Einstein Trust Layer, providing a comprehensive solution for secure and connected data, facilitating generative AI on a comprehensive platform. Salesforce’s Einstein One Platform & the Data-Driven Revolution This innovation has the potential to revolutionize the way businesses interact with their customers. In this insight, we delve deeper into this transformative development, offering valuable insights, considerations for implementation, and the indispensable expertise of Tectonic as a data-oriented technology partner. Salesforce Data Cloud and Einstein AI are now seamlessly integrated into the Einstein One Platform. This integration empowers companies to effortlessly connect their diverse data sources, enabling the creation of AI-driven applications with minimal coding effort. Moreover, it forges a cohesive view of your data across

April 9, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Einstein Insights, Enterprise, Generative AI, Google, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Salesforce Sales Cloud, Technology

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