UX Archives - gettectonic.com
10Mar

Goodbye Skype

Microsoft to Shut Down Skype After 20 Years Microsoft has announced plans to shut down Skype on May 5, marking the end of a 20-year journey for the once-pioneering internet communications platform. This may be the perfect time to re-evaluate your internal comms tools. Launched in 2003, Skype revolutionized online communication by enabling free audio and video calls worldwide. The platform quickly gained popularity, amassing hundreds of millions of users and even becoming a verb — people would often say they would “Skype” someone. The Rise and Fall of Skype Founded by Swede Niklas Zennström and Dane Janus Friis, with software developed by Estonians Ahti Heinla, Priit Kasesalu, Jaan Tallinn, and Toivo Annus, Skype was initially based in Luxembourg. Its innovative approach to online communication made it a household name in the early 2000s. In 2011, Microsoft acquired Skype for $8.5 billion, outbidding tech giants like Google and Facebook. At the time, Skype had around 150 million active users. However, by 2020, the user base had dropped to 23 million, though the platform experienced a temporary resurgence during the pandemic. Decline Amid Growing Competition Microsoft faced challenges integrating Skype into its ecosystem. In 2017, the company launched Teams, a collaboration platform, which gradually overshadowed Skype. Additionally, growing competition from Apple’s FaceTime, Google’s communication apps, Zoom, and Salesforce-owned Slack further diminished Skype’s prominence. Transition to Teams Microsoft confirmed that Skype users will be transitioned to Teams, with all chats and contacts migrating automatically. The company emphasized that there would be no job losses resulting from the shutdown and highlighted Teams’ growing popularity, which currently boasts 320 million monthly active users. While Microsoft did not disclose Skype’s current user count, the company stated that it remains committed to supporting seamless communication through Teams. This shift signifies the end of an era for Skype but reinforces Microsoft’s focus on integrating advanced communication tools into its product suite. The closure of Skype marks the conclusion of a significant chapter in internet communication, as users transition to more modern, collaborative platforms like Slack. There are many alternatives to Skype, including Viber, Zoom, Slack, Microsoft Teams, Jitsi, WhatsA[[, Google Meet, FaceTime, and Google Hangouts. For sending video messages check out Marco Polo.  Features Other considerations Learn how Slack elevates team performance here Learn how Slack integrates with Salesforce here To migrate to Salesforce Slack, or discuss your options, 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 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 10, 2025in Google, Salesforce0 Comments
Shift From AI Agents to AI Agent Tool Use
03Mar

AI Agent Dilemma

The AI Agent Dilemma: Hype, Confusion, and Competing Definitions Silicon Valley is all in on AI agents. OpenAI CEO Sam Altman predicts they will “join the workforce” this year. Microsoft CEO Satya Nadella envisions them replacing certain knowledge work. Meanwhile, Salesforce CEO Marc Benioff has set an ambitious goal: making Salesforce the “number one provider of digital labor in the world” through its suite of AI-driven agentic services. But despite the enthusiasm, there’s little consensus on what an AI agent actually is. In recent years, tech leaders have hailed AI agents as transformative—just as AI chatbots like OpenAI’s ChatGPT redefined information retrieval, agents, they claim, will revolutionize work. That may be true. But the problem lies in defining what an “agent” really is. Much like AI buzzwords such as “multimodal,” “AGI,” or even “AI” itself, the term “agent” is becoming so broad that it risks losing all meaning. This ambiguity puts companies like OpenAI, Microsoft, Salesforce, Amazon, and Google in a tricky spot. Each is investing heavily in AI agents, but their definitions—and implementations—differ wildly. An Amazon agent is not the same as a Google agent, leading to confusion and, increasingly, customer frustration. Even industry insiders are growing weary of the term. Ryan Salva, senior director of product at Google and former GitHub Copilot leader, openly criticizes the overuse of “agents.” “I think our industry has stretched the term ‘agent’ to the point where it’s almost nonsensical,” Salva told TechCrunch. “[It is] one of my pet peeves.” A Definition in Flux The struggle to define AI agents isn’t new. Former TechCrunch reporter Ron Miller raised the question last year: What exactly is an AI agent? The challenge is that every company building them has a different answer. That confusion only deepened this past week. OpenAI published a blog post defining agents as “automated systems that can independently accomplish tasks on behalf of users.” Yet in its developer documentation, it described agents as “LLMs equipped with instructions and tools.” Adding to the inconsistency, OpenAI’s API product marketing lead, Leher Pathak, stated on X (formerly Twitter) that she sees “assistants” and “agents” as interchangeable—further muddying the waters. Microsoft attempts to make a distinction, describing agents as “the new apps” for an AI-powered world, while reserving “assistant” for more general task helpers like email drafting tools. Anthropic takes a broader approach, stating that agents can be “fully autonomous systems that operate independently over extended periods” or simply “prescriptive implementations that follow predefined workflows.” Salesforce, meanwhile, has perhaps the widest-ranging definition, describing agents as AI-driven systems that can “understand and respond to customer inquiries without human intervention.” It categorizes them into six types, from “simple reflex agents” to “utility-based agents.” Why the Confusion? The nebulous nature of AI agents is part of the problem. These systems are still evolving, and major players like OpenAI, Google, and Perplexity have only just begun rolling out their first versions—each with vastly different capabilities. But history also plays a role. Rich Villars, GVP of worldwide research at IDC, points out that tech companies have “a long history” of using flexible definitions for emerging technologies. “They care more about what they are trying to accomplish on a technical level,” Villars told TechCrunch, “especially in fast-evolving markets.” Marketing is another culprit. Andrew Ng, founder of DeepLearning.ai, argues that the term “agent” once had a clear technical meaning—until marketers and a few major companies co-opted it. The Double-Edged Sword of Ambiguity The lack of a standardized definition presents both opportunities and challenges. Jim Rowan, head of AI at Deloitte, notes that while the ambiguity allows companies to tailor agents to specific needs, it also leads to “misaligned expectations” and difficulty in measuring value and ROI. “Without a standardized definition, at least within an organization, it becomes challenging to benchmark performance and ensure consistent outcomes,” Rowan explains. “This can result in varied interpretations of what AI agents should deliver, potentially complicating project goals and results.” While a clearer framework for AI agents would help businesses maximize their investments, history suggests that the industry is unlikely to agree on a single definition—just as it never fully defined “AI” itself. For now, AI agents remain both a promising innovation and a marketing-driven enigma. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 3, 2025in AI Chatbots, Google, Salesforce0 Comments
Agentforce Unveiled
21Feb

Scale Your Marketing with Agentforce

Scale Your Marketing with Agentforce: AI-Powered Automation for Modern Campaigns Traditional marketing systems struggle to keep pace with today’s demand for precision, personalization, and scale. With marketing teams managing complex, multi-platform campaigns, repetitive work quickly becomes a challenge—41% of employee time is spent on low-impact tasks, and 65% of desk workers believe AI will help them focus on more strategic work. Enter Agentforce for Marketers, built with the Atlas Reasoning Engine. These AI-powered agents help businesses scale their workforces on demand, analyzing data, making decisions, and taking proactive action on tasks like answering customer inquiries and qualifying leads. If you’re ready to embrace a new level of efficiency, this Tectonic insight explores how Agentforce can revolutionize your marketing efforts. What is Agentforce for Marketing? Introduced at Dreamforce 2024, Agentforce represents Salesforce’s next evolution in AI. Powered by the Atlas Reasoning Engine, it enhances automation with retrieval-augmented generation (RAG) and contextual decision-making. Salesforce CEO Marc Benioff calls Agentforce “the third wave of AI—moving beyond copilots to highly accurate, low-hallucination customer service agents that actively drive success.” For marketers, this means automation that analyzes vast datasets, connects customer interactions across teams, and provides real-time insights—all while optimizing campaigns, streamlining workflows, and generating personalized content. The Core of Agentforce: Agentforce combines Agent Builder, Model Builder, and Prompt Builder, allowing marketers to: These tools enable seamless, personalized experiences while reducing manual effort. Key Autonomous AI Agents in Agentforce Agentforce’s AI-powered agents cover a wide range of marketing and sales functions, including: Core Features of Agentforce for Marketing Agentforce transforms marketing by delivering AI-driven insights, automating workflows, and personalizing customer experiences at scale. 1. AI-Driven Campaign Insights Agentforce integrates Salesforce Data Cloud and Marketing Cloud Intelligence to analyze customer behavior patterns, optimize targeting strategies, and improve campaign performance. 💡 Only 32% of marketers say they effectively use customer data for personalization. Agentforce closes this gap by providing real-time, actionable insights. 2. Real-Time Data Integration By consolidating insights from CRM records, external platforms, and unstructured sources, Agentforce ensures AI-driven recommendations power marketing automation and personalization. ✅ Example: OpenTable used Agentforce’s data-driven insights to boost customer engagement and increase case resolution rates. 3. Automated Campaign Workflows Agentforce eliminates repetitive tasks like email follow-ups, social media posts, and ad placements, allowing teams to focus on strategy. 💡 Marketers can set up automated email sequences that trigger based on customer behavior—without manual intervention. Use Cases: How Marketers Leverage Agentforce 1. Personalized Email Campaigns Agentforce analyzes customer interactions to send hyper-targeted emails based on past purchases, browsing history, and engagement. ✅ Example: An online retailer sends tailored product recommendations based on recent searches, increasing conversion rates. 2. Omnichannel Campaign Management Agentforce synchronizes messaging across email, social media, and ads, ensuring consistency across platforms like Marketing Cloud and Facebook Ads Manager. ✅ Example: A product launch campaign can automatically schedule email announcements, social media posts, and search ads—all aligned in messaging. 3. Advanced Audience Segmentation Using AI-powered behavioral analysis, Agentforce creates refined audience segments to deliver hyper-personalized marketing. ✅ Example: A luxury retailer identifies VIP customers likely to attend exclusive events and sends personalized invitations. 4. Performance Tracking & Optimization Agentforce continuously monitors engagement metrics, offering AI-driven recommendations for campaign improvements. 💡 This allows marketers to adjust strategies in real time, maximizing impact. Challenges & Considerations 1. Adapting to AI-Powered Marketing Many professionals feel unprepared for AI-driven tools. Organizations should invest in training programs to ease adoption and leverage Salesforce’s low-code tools for a smoother transition. 2. Ethical & Sustainable AI Implementation Responsible AI use is critical. Agentforce includes features to:✅ Mitigate bias in AI-driven processes.✅ Reduce environmental impact by optimizing hardware usage.✅ Ensure accuracy with real-time, dynamic data. 💡 Salesforce’s AI Red Teaming and Ethical AI Maturity Model help businesses implement AI responsibly. The Future of Marketing with Agentforce Agentforce is redefining marketing automation, eliminating repetitive tasks, enhancing personalization, and driving smarter decision-making. If you’re ready to scale your marketing with AI-powered efficiency, Agentforce is your next competitive advantage. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 21, 2025in Data, Marketing Automation, Salesforce, Salesforce Data Cloud0 Comments
Unlocking the Future of AI with Phidata
05Feb

Unlocking the Future of AI with Phidata

Unlocking the Future of AI with Phidata: Build Smarter, Faster, and Better In a world where artificial intelligence is at the core of innovation, developing intelligent systems that can understand, reason, and act is no longer a luxury—it’s a necessity. Yet, creating these systems from the ground up can feel daunting, even for experienced developers. Enter Phidata, a revolutionary platform that simplifies the process of building intelligent multi-modal agents and workflows. Phidata isn’t just a framework—it’s a transformative toolkit for crafting AI systems that think critically, collaborate effectively, and solve complex problems. Whether you’re a developer, data scientist, or AI enthusiast, Phidata empowers you to create agents with memory, knowledge, and advanced reasoning capabilities, all while seamlessly integrating cutting-edge tools. Here’s your guide to this groundbreaking platform. Why Phidata Stands Out Phidata reimagines how developers design and deploy AI agents by blending simplicity with robust functionality. Here’s what makes it a game-changer: Elegantly Simple Development Phidata’s intuitive design enables you to create powerful agents with minimal code. Clean, concise, and efficient, it’s as simple as writing a “Hello World!” script to set up an agent capable of performing tasks like web searches or data analysis. Unmatched Flexibility From integrating diverse tools to customizing agent instructions, Phidata equips your AI to tackle complex, real-world challenges effortlessly. Whether you’re building agents for financial forecasting, content creation, or automated research, Phidata has you covered. Multi-Modal Intelligence Phidata agents can seamlessly interact with multiple data types, including text, images, audio, and video. This multi-modal capability ensures adaptability across industries and use cases, from visual data analysis to language translation. Collaborative Multi-Agent Workflows Why settle for a single-agent approach when you can create teams of intelligent agents? Phidata enables collaborative multi-agent workflows, where agents work together to achieve shared objectives—like a team of digital coworkers, each bringing their unique expertise to the table. Intuitive User Interface Phidata’s sleek, user-friendly interface makes interacting with your agents effortless. Say goodbye to frustrating debugging and focus on what matters: building innovative solutions. Built-In Reasoning and Knowledge (RAG) Phidata integrates structured reasoning and knowledge retrieval directly into its framework. This ensures your agents deliver organized, insightful responses tailored to your needs—whether for decision-making or customer engagement. Real-Time Monitoring and Debugging Track your agents’ performance with Phidata’s built-in monitoring and debugging tools. Fine-tune their behavior, optimize workflows, and ensure peak performance at all times. Transform Possibilities Into Reality Phidata opens the door to limitless possibilities, empowering you to: Whether you’re automating workflows, analyzing data, or designing innovative applications, Phidata redefines what’s possible with AI. Take the leap into the future of intelligent systems and start building smarter today with Phidata. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 5, 2025in Salesforce
AI Agents and Digital Transformation
30Jan

AI Agents Help Streamline Customer Service

AI Agents Help Fisher & Paykel Streamline Customer Service Through Expanded Salesforce Partnership Fisher & Paykel, the New Zealand-based luxury appliance manufacturer, is leveraging AI agents to automate customer service tasks, such as answering frequently asked questions and scheduling service appointments. This initiative is designed to free up employee time for more value-added tasks, enhancing the overall customer service experience. In collaboration with Salesforce, Fisher & Paykel is using autonomous agents that integrate seamlessly with its CRM system, providing agents with greater visibility into customers’ interaction histories. This enables more efficient, data-driven interactions and allows the company to proactively resolve issues, such as freezer temperature irregularities, by automatically notifying customers and helping them schedule necessary appointments. For instance, AI agents can diagnose appliance issues, alert the service team, and assist customers in scheduling repair appointments. These agents also support on-site technicians by providing critical information, such as appointment locations and appliance age, while offering helpful articles and generating post-service summaries. Additionally, the integration of AI agents will enhance collaboration with Fisher & Paykel’s retail, builder, and designer partners. These partners will benefit from more efficient access to inventory information, accurate quotes for multiple products, and streamlined order placement and tracking. Enhancing Automation-Ready Environments This initiative builds on existing capabilities from the partnership, combining AI, data, and CRM functions such as subscription management and consolidated customer engagement data. The results have been impressive: Fisher & Paykel saw a 206% increase in unique email opens and a 112% rise in unique clicks in 2023. They also reduced manual effort by 30 minutes per order and saved up to 3,300 hours through automation in the B2B side of their business, according to Salesforce. In addition to service automation, Fisher & Paykel is tapping into AI-driven automated journeys based on consumer buying signals and cloud-based customer service support that automates appointment confirmations. Rudi Khoury, Chief Digital Officer at Fisher & Paykel, emphasized that customer expectations for efficiency and personalized service align perfectly with the brand’s luxury offerings, highlighting the importance of AI in meeting these demands. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 30, 2025in Salesforce
03Jan

Digital Marketing for Casinos

Unveiling the Casino Experience: Harnessing the Power of Digital Marketing In the exciting world of casinos—where entertainment meets sophistication—the influence of digital marketing is undeniable. A strategic approach is packed with actionable insights designed to boost online presence, engage audiences, and drive sustained success. Discover how to craft compelling content, wield social media’s dynamic power, utilize a customer relationship platform, and optimize visibility to ensure your casino stands out in an increasingly competitive digital arena. Tectonic has a successful, winning track record in Salesforce implementation for casinos. Whether you’re promoting exclusive guest events, captivating diverse demographics, or showcasing the unique experience of your casino, this insight equips you to master the digital space with Salesforce. With these strategies, casinos can create a ever-growing online presence that not only strengthens bonds with existing patrons but also entices new guests. Generating New and Repeat Guest Traffic with Salesforce Key Takeaways Why Digital Marketing is a Critical Component for Casinos Digital marketing serves as a critical driver of customer engagement, loyalty, and revenue growth in the casino industry. Strategies such as SEO, email marketing, and social media engagement empower casinos to connect with target audiences and continuously refine their efforts to remain competitive. In today’s crowded and competitive gaming world, leveraging data-driven marketing offers the competitive edge needed to captivate and retain customers. Winning Strategies for Casino Marketing 1. Search Engine Optimization (SEO):Ensure your casino is easy to find with these tactics: 2. Pay-Per-Click Advertising (PPC):Drive traffic with targeted PPC campaigns by: 3. Social Media Marketing:Create buzz with engaging social media campaigns: 4. Email Marketing:Maintain direct communication with: 5. Salesforce 360 Degree Guest View:Maintain personalized communication with: Reaching the Right Audience with Precision Audience Segmentation:Segmenting your audience by behavior, demographics, and preferences ensures more effective marketing. Navigating Legal and Ethical Challenges in Casino Marketing Compliance is essential in maintaining trust and navigating complex regulations. Measuring Success: Metrics and Optimization Key Metrics to Monitor: Campaign Optimization: Addressing Industry Challenges with Marketing 1. Rising Competition:Stand out by delivering unmatched gaming experiences and innovative promotions. 2. High Player Churn:Combat churn with data-driven marketing and personalized offerings to boost player lifetime value. 3. ROI Challenges:Optimize your mix of games and services to balance player satisfaction and profitability. The Road Ahead: Commitment to Digital Transformation With the global online gaming market projected to grow at a significant pace, casinos must embrace a future grounded in digital and data-driven marketing. Investments in technology, analytics, and talent will be pivotal in securing long-term profitability and differentiation. In an industry where chance often rules, success lies in a deliberate, strategic approach to digital marketing. This insight equips you with the tools to not only compete but thrive in this dynamic landscape. Contact Tectonic today to explore Salesforce tools to better reach, engage, and serve your guests. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 3, 2025in Agentforce Platform, Data, Einstein 1 Platform, Einstein Insights, Enterprise, Laws, Marketing Automation, Salesforce, Salesforce Data Cloud, Salesforce Development Services, Salesforce Experience Cloud, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Technology
AI Captivates the World
01Jan

AI Captivates the World

In the late 1990s, a transformative moment unfolded that expanded the world to enquiring minds—the screeching of a dial-up modem, followed by a pixelated “Welcome” screen that connected users to a vast, invisible network spanning the globe. The internet revolution redefined how people interacted with information and one another, permanently reshaping digital communication. Fast forward to 2024, and a similar wave of innovation is underway. Artificial intelligence is captivating the world with its ability to understand, create, and process information. Massive datasets can now be uploaded to AI tools, which instantly distill complex insights—tasks that once took teams of analysts weeks to complete are now executed in seconds. Just as the internet linked people and information, AI is deepening connectivity across all aspects of life, from healthcare and finance to workplaces and homes. In this evolving digital divide, designers hold a critical role—not only in making AI usable but in ensuring it remains understandable, trustworthy, and human-centered. As Fei-Fei Li, Co-Director of Stanford’s Human-Centered AI Institute, states, “If we want machines to think, we need to teach them to see.” The traditional linear process of problem ideation, design, prototyping, and delivery is no longer sufficient for AI design. Instead, designers find themselves on an “AI design rollercoaster”—a dynamic cycle of constant iteration. One day, a seemingly impossible feature is prototyped, and the next, the entire approach pivots due to breakthroughs in large language model (LLM) capabilities. Many teams develop working prototypes before even defining their target audience. It is akin to painting a landscape from a moving train—compelling, challenging, and occasionally bewildering. However, this state of flux is where innovation thrives. Strategies for Designers: Understanding AI’s Capabilities and Limitations Designing for AI requires an understanding of its strengths and weaknesses. While designers do not need to become machine learning engineers, they must grasp AI fundamentals to communicate effectively with technical teams. For example, neural networks excel at recognizing patterns in unstructured data but often struggle with logical reasoning. Recognizing these limitations prevents the development of features that sound promising in theory but fail in practice. Strategies for Designers: Designing for Data Scalability Data is the lifeblood of AI systems, yet its quality and availability fluctuate over time. Designers must create interfaces that can adapt to changing data landscapes. For instance, an AI-powered personal finance app may initially rely on basic transaction data but later incorporate richer datasets for advanced investment recommendations. Interfaces should be modular and scalable, capable of accommodating evolving AI functionalities. Strategies for Designers: The Role of Prototyping in AI Design Static wireframes and basic mockups are insufficient for AI-driven products. AI prototypes must capture the responsive, dynamic nature of intelligent systems. Interactive prototypes offer stakeholders a tangible preview of AI’s potential, highlighting both opportunities and challenges early in the design process. Strategies for Designers: Developing AI Design Intuition To navigate AI design effectively, professionals must cultivate an “AI design sixth sense”—an intuitive understanding of what works well in AI-driven interactions. Immersing in AI experiences, exploring different tools, and analyzing emerging design patterns help build this expertise. Strategies for Designers: Pushing Boundaries in AI Design There are no established rulebooks for AI design—only a vast frontier waiting to be explored. The absence of rigid norms offers designers the freedom to experiment and push boundaries. Some of the most groundbreaking innovations stem from unconventional ideas once deemed impractical. Strategies for Designers: Strengthening Collaboration Between Design and Engineering In AI product design, the traditional “design then handoff” model is giving way to a more integrated approach. Designers and engineers increasingly work in tandem, refining AI experiences through continuous iteration. Some of the most effective design solutions emerge from close collaboration with technical teams. Strategies for Designers: The Next Frontier of Design As AI design continues to evolve, the parallels to the early days of the internet are striking. The excitement, potential, and magnitude of change are reminiscent of Web 1.0, yet amplified in scope. Looking ahead, the field must address profound questions: Will AI become indistinguishable from human intelligence? Will designers craft interfaces for AI-human hybrids yet to be imagined? Designers play an essential role in shaping this future—not as passive observers, but as architects of the next digital revolution. The experiences they create will define humanity’s interactions with artificial intelligence. This responsibility should inspire innovation, challenge conventions, and push the boundaries of what is possible. Call to Action Begin the AI design journey today. Choose an AI tool, explore its interface, and analyze its capabilities. Identify strengths, weaknesses, and opportunities for improvement. Share insights with fellow designers and contribute to the evolving conversation on AI design. The next breakthrough may arise from a single moment of curiosity. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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January 1, 2025in AI Tools, Artificial Intelligence, Data
AI and UX Design
16Dec

AI and UX Design

This insight comprehensively covers how AI is transforming UX design, presenting both opportunities and challenges while emphasizing the importance of maintaining a human-centric approach. Here’s a polished and slightly condensed version, retaining the core points for better clarity and engagement: AI in UX Design: Transforming Experiences in 2024 and Beyond In 2024, artificial intelligence (AI) is redefining user experience (UX) design and research. From streamlining processes to elevating personalization, UX professionals are integrating AI into their workflows to create experiences that are more intuitive and efficient. This insight explores how AI is reshaping UX and how designers can leverage it while preserving the human touch. How AI is Revolutionizing UX Design 1. Advanced AI Technologies in UXAI technologies like machine learning (ML), natural language processing (NLP), and computer vision are empowering designers with tools to understand user behavior better, build conversational interfaces, and create accessible, adaptable designs. These innovations provide deeper insights into user preferences and help refine interfaces to align with evolving needs. 2. Automating Routine Design TasksAI is taking over repetitive tasks such as rapid prototyping, A/B testing, and user data analysis, allowing designers to focus on creative, strategic challenges. For example: 3. Enhanced PersonalizationAI-driven systems offer dynamic content delivery, adaptive interfaces, and predictive behavior modeling to craft uniquely tailored experiences. These enhancements not only engage users but also foster loyalty by addressing individual preferences in real time. Balancing AI and Human-Centric Design While AI accelerates UX processes, maintaining a human-centered approach is essential. Successful integration requires: Best Practices for AI-Driven UX Design Ethical Considerations in AI-Enhanced UX Ethics remain at the forefront of AI in UX. Key concerns include: Learning from Case Studies These examples highlight how thoughtful AI integration can transform UX into a seamless, user-friendly journey. Preparing for Future Trends Looking ahead to 2025 and beyond, AI will continue to introduce innovations like emotional recognition and generative design, enabling even more intuitive user experiences. However, challenges such as data privacy concerns and high implementation costs will persist. UX professionals must adapt by blending AI-driven insights with human creativity, ensuring that designs remain empathetic and accessible. Conclusion AI is revolutionizing UX design, offering tools to enhance efficiency, personalization, and user engagement. The key to success lies in using AI as a complement to creativity rather than a replacement. By balancing automation with human-centered principles and committing to ethical practices, businesses can harness AI to create transformative, user-focused designs that truly resonate. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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December 16, 2024in Artificial Intelligence, Data, Google
Salesforce is Powering the Future of Digital Careers
12Dec

Salesforce is Powering the Future of Digital Careers

The Remote Work Revolution: How Salesforce is Powering the Future of Digital Careers The way we work has undergone a fundamental shift. Remote work has reshaped traditional workplace dynamics, allowing professionals to connect, collaborate, and thrive from anywhere. This transformation, driven by technological advancements, shifting workplace expectations, and global events, has made flexibility the new standard. At the heart of this change is Salesforce, a platform that is redefining how businesses operate in a digital-first world. Salesforce: The Foundation of Remote Work Success As the leading CRM and cloud platform, Salesforce has become indispensable for companies navigating the modern workforce. Its cloud-based solutions provide businesses with the agility to adopt remote work models without sacrificing productivity, collaboration, or efficiency. From customer engagement and workflow automation to data-driven decision-making, Salesforce empowers organizations to build robust digital infrastructures that support distributed teams. Building a Remote-First Culture What was once a luxury or temporary solution has now become the standard. Remote work not only empowers employees but also enables companies to tap into top talent globally. With Salesforce, businesses can create seamless digital work experiences—regardless of location. Salesforce’s cloud-first architecture ensures employees can securely access critical business applications and data from any device, anytime. This fosters a remote-first culture where teams can collaborate in real-time, track progress, and communicate effectively with clients—all while maintaining enterprise-grade security. Driving Productivity & Seamless Collaboration One of the biggest challenges of remote work is maintaining productivity and efficiency across different time zones. Salesforce tackles this with powerful collaboration and automation tools: With platforms like Crossover, Salesforce professionals can tap into global job opportunities and build flexible, remote-first careers in industries like finance, healthcare, retail, and technology. Enhancing Business Agility & Scalability In today’s digital economy, agility and scalability are key to staying competitive. Businesses must be able to adapt quickly, scale operations, and respond to market changes with ease. Salesforce provides:✔ Cloud scalability – No reliance on physical infrastructure, allowing businesses to scale up or down effortlessly.✔ AI-driven analytics & forecasting – Tools like Salesforce Einstein deliver real-time insights to inform strategy and optimize operations.✔ Seamless integrations – Businesses can connect Salesforce with collaboration tools, marketing automation, and financial software for a unified digital ecosystem. Adapting to the Evolving Workforce Today’s workforce values flexibility, work-life balance, and career growth. Companies must rethink hiring strategies to attract and retain top talent. Salesforce helps businesses manage remote teams effectively through: ✅ AI-powered recruitment – Simplifies hiring, onboarding, and performance tracking to ensure businesses attract the right talent.✅ HR automation – Streamlines employee engagement and performance monitoring for data-driven workforce management. For professionals, this means digital careers are more accessible than ever. As demand for Salesforce expertise grows, opportunities in remote work are expanding across every industry. The Future of Remote Work with Salesforce As technology continues to evolve, so will remote work. Salesforce is pushing the boundaries with advancements in AI, machine learning, and automation to enhance productivity, decision-making, and customer experiences. With Salesforce Einstein, businesses can:🔹 Analyze trends and personalize customer experiences🔹 Automate processes for smarter, more efficient workflows🔹 Empower remote teams with AI-driven recommendations Beyond technology, Salesforce is also committed to building an inclusive, sustainable future—reducing reliance on office spaces and fostering well-being-focused remote work cultures. Conclusion: A Future Built on Flexibility & Growth The remote work revolution is here to stay, and Salesforce is powering the transformation. With scalable solutions, advanced automation, and AI-driven insights, businesses can operate seamlessly in a digital-first world. For professionals, a Salesforce-powered career opens doors to global opportunities—offering flexibility, growth, and limitless potential. Whether you’re an experienced Salesforce expert or transitioning into the field, now is the time to embrace the future of work. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 12, 2024in Data, Enterprise, Marketing Automation, Salesforce, Salesforce Einstein, Technology
AI-Checking Agents
02Dec

AI-Checking Agents

Introducing AI-Checking Agents: The Next Frontier in Software Quality Assurance The software industry has continually evolved in its pursuit of better quality assurance (QA) methods. While traditional approaches like unit testing and manual QA offer foundational tools, they often fail to meet the growing complexity of modern software. Automated testing and DevOps practices have helped, but these methods are still time-intensive, costly, and limited in scope. AI-Checking Agents. Enter AI-Checking Agents — an innovative solution leveraging generative AI to revolutionize software testing and quality assurance. These agents promise unprecedented coverage, speed, and efficiency, addressing the challenges of today’s demanding software ecosystems. Why AI-Checking Agents? Traditional QA methods fall short in delivering exhaustive coverage for the diverse behaviors and interactions of modern software. AI-Checking Agents close this gap by introducing: Synthetic Users: Revolutionizing User Experience (UX) Testing One of the most groundbreaking features of AI-Checking Agents is the ability to create synthetic users. These AI-driven personas simulate real-world user interactions, offering a novel approach to UX analysis. Key Features of Synthetic Users: UX Insights Delivered by Synthetic Users: Benefits of AI-Checking Agents in QA Integrating AI-Checking Agents with Existing QA Practices AI-Checking Agents are not a replacement for traditional methods but a powerful complement to existing practices: Transforming the Development Process AI-Checking Agents not only streamline QA but also enhance the overall development process: The Future of Quality Assurance AI-Checking Agents represent a paradigm shift in software testing, blending the best of AI-driven insights with traditional QA practices. By integrating these agents into their workflows, development teams can achieve: In a world of ever-evolving software demands, AI-Checking Agents are the key to achieving unparalleled speed, depth, and precision in quality assurance. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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December 2, 2024in Generative AI
gen z and retail travel
25Nov

Gen Z and Retail Travel Insights

Is Travel Retail Ready for Gen Z? New Research Highlights Gaps in Alignment The latest research from Swiss-based travel retail agency m1nd-set sheds light on the shopping and travel behaviors of Gen Z—a group poised to become the largest segment of traveling shoppers within the next few years. The findings reveal a pressing need for the travel retail industry to better align its offerings with the unique expectations and values of this influential generation. Gen Z: A Generation with Distinct Values and Habits Peter Mohn, CEO and Owner of m1nd-set, emphasized the importance of prioritizing Gen Z consumers, noting their markedly different behaviors compared to other generations. “Like the focus placed on Millennials and Chinese consumers in recent years, it’s critical to give equal or greater attention to Gen Z. This generation exhibits distinct traits, particularly in their consumer habits, lifestyle preferences, and media consumption,” Mohn said. Key insights from m1nd-set’s research include: How Gen Z is Reshaping Travel and Retail The research highlights how Gen Z is redefining the travel industry by prioritizing experiences that are authentic, eco-conscious, and culturally meaningful over traditional luxury goods and activities. “Gen Zs are reshaping tourism,” Mohn explained, “by focusing on flexible, short-haul travel and unique experiences. They spend a significant portion of their budgets on international travel, favoring local and sustainable options over dining or shopping at home. Cultural experiences resonate far more than nightlife or traditional tourism.” Key data points from m1nd-set’s study include: Challenges in Engaging Gen Z in Travel Retail Despite their growing presence, the research highlights key challenges in converting Gen Z travelers into loyal shoppers in duty-free and travel retail spaces: Opportunities for Travel Retail: Winning Over Gen Z Mohn emphasized the vital role of shop floor sales staff in boosting Gen Z conversion rates, noting that interactions with staff positively influence purchase decisions for over 70% of Gen Z shoppers who engage with them. To capture the attention of this discerning generation, m1nd-set recommends that travel retail businesses: A Generation of Growing Influence By 2030, Gen Z and their successors, Gen Alpha, are expected to spend three times as much as all other generations combined. Currently, Gen Z already wields a staggering $200 billion in spending power, solidifying their position as a key demographic for travel retail. However, to fully tap into this potential, the industry must evolve quickly to meet the demands of this purpose-driven, tech-savvy, and sustainability-focused generation. As Mohn concluded, “Travel retail must become more than just a place to shop—it should be an engaging, socially conscious destination that resonates deeply with Gen Z values.” 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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November 25, 2024in Data, Salesforce Hospitality Travel and Transportation
human centered ai
23Nov

Human-Centered AI

Be the change you want to see in the artificial intelligence world. Or scramble to catch up. Hope Is Not Lost for Human-Centered AIHow designers can lead the charge in creating AI that truly benefits humanity. The rapid proliferation of Artificial Intelligence (AI) brings with it a range of ethical and societal concerns. From inherent biases in datasets to fears of widespread job displacement, these challenges often feel like inevitable trade-offs as AI becomes deeply embedded in our lives. However, hope remains. Human-centered AI—designed to be fair, transparent, and genuinely beneficial—is not only possible but achievable when crafted with intentionality. For UX professionals, this is an opportunity to drive the creation of AI systems that empower rather than overshadow human capabilities. A Quick Note on AI Literacy To make meaningful contributions to AI product development, designers need a foundational understanding of how AI works. While a PhD in machine learning isn’t necessary, being an informed practitioner is essential. Think of learning about AI like learning to invest. At first, it seems daunting—what even is an ETF? But with time, the jargon and processes become familiar. Similarly, while you don’t need to be a machine-learning expert to work with AI, understanding its basics is critical. AI refers broadly to a computer’s ability to mimic human thought, while machine learning (ML)—a subset of AI—enables systems to learn from data. Unlike traditional programming, where explicit instructions are coded line by line, ML models identify patterns within training datasets. These models then function as “black boxes,” generating outputs based on user inputs—though the inner workings are often opaque. Understanding these fundamentals empowers designers to bridge the gap between AI’s technical potential and its real-world application. Design-Led AI Ideally, designers are involved from the very beginning of AI product development—during the discovery phase. Here, we evaluate whether AI is the right solution for a given problem, ensuring user needs drive decisions rather than the allure of flashy tech. Key questions to ground AI solutions in user needs include: Basic AI literacy allows designers to make informed judgments and collaborate effectively with engineers. Engaging early ensures that AI solutions are designed to adapt to users—not the other way around. But what happens when design isn’t brought in until after AI decisions have been made? Design-Guarded AI Even when AI is a foregone conclusion, designers can still shape outcomes by focusing on the two areas where users interact directly with AI: inputs and outputs. Input Design Whether inputs involve transaction data, images, or text prompts, the method of collection must be intuitive and user-friendly. Established design principles, such as affordances, help ensure clarity and simplicity. For example: Frequent user testing ensures input methods align with real workflows and pain points. The result? Streamlined, user-centric experiences that reduce friction and save time. Output Design Designing outputs requires a focus on transparency and mitigating automation bias—the tendency to over-rely on AI. Users must understand that AI is fallible. For instance: AI should act as a collaborator, not an authority. Outputs must empower users to make informed choices while supporting their next steps within a seamless workflow. Ethics Must Take Center Stage No discussion of human-centered AI is complete without addressing ethics. Designers must champion transparency, inclusivity, and fairness throughout the product lifecycle. Questions around bias, privacy, and unintended consequences must be raised early and revisited often. While ethical considerations may sometimes conflict with short-term business goals, prioritizing them is essential for building AI that serves humanity in the long term. These conversations won’t always be easy—but they are necessary. As designers, we have the tools and responsibility to ensure AI remains a force for good. By advocating for human-centered design principles, we can help shape an AI-powered future that enhances human potential rather than undermining it. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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November 23, 2024in Artificial Intelligence, Data, Generative AI
AI Productivity Paradox
20Nov

AI Productivity Paradox

The AI Productivity Paradox: Why Aren’t More Workers Using AI Tooks Like ChatGPT?The Real Barrier Isn’t Technical Skills — It’s Time to Think Despite the transformative potential of tools like ChatGPT, most knowledge workers aren’t utilizing them effectively. Those who do tend to use them for basic tasks like summarization. Less than 5% of ChatGPT’s user base subscribes to the paid Plus version, indicating that a small fraction of potential professional users are tapping into AI for more complex, high-value tasks. Having spent over a decade building AI products at companies such as Google Brain and Shopify Ads, the evolution of AI has been clearly evident. With the advent of ChatGPT, AI has transitioned from being an enhancement for tools like photo organizers to becoming a significant productivity booster for all knowledge workers. Most executives are aware that today’s buzz around AI is more than just hype. They’re eager to make their companies AI-forward, recognizing that it’s now more powerful and user-friendly than ever. Yet, despite this potential and enthusiasm, widespread adoption remains slow. The real issue lies in how organizations approach work itself. Systemic problems are hindering the integration of these tools into the daily workflow. Ultimately, the question executives need to ask isn’t, “How can we use AI to work faster? Or can this feature be built with AI?” but rather, “How can we use AI to create more value? What are the questions we should be asking but aren’t?” Real-world ImpactRecently, large language models (LLMs)—the technology behind tools like ChatGPT—were used to tackle a complex data structuring and analysis task. This task would typically require a cross-functional team of data analysts and content designers, taking a month or more to complete. Here’s what was accomplished in just one day using Google AI Studio: However, the process wasn’t just about pressing a button and letting AI do all the work. It required focused effort, detailed instructions, and multiple iterations. Hours were spent crafting precise prompts, providing feedback, and redirecting the AI when it went off course. In this case, the task was compressed from a month-long process to a single day. While it was mentally exhausting, the result wasn’t just a faster process—it was a fundamentally better and different outcome. The LLMs uncovered nuanced patterns and edge cases within the data that traditional analysis would have missed. The Counterintuitive TruthHere lies the key to understanding the AI productivity paradox: The success in using AI was possible because leadership allowed for a full day dedicated to rethinking data processes with AI as a thought partner. This provided the space for deep, strategic thinking, exploring connections and possibilities that would typically take weeks. However, this quality-focused work is often sacrificed under the pressure to meet deadlines. Ironically, most people don’t have time to figure out how they could save time. This lack of dedicated time for exploration is a luxury many product managers (PMs) can’t afford. Under constant pressure to deliver immediate results, many PMs don’t have even an hour for strategic thinking. For many, the only way to carve out time for this work is by pretending to be sick. This continuous pressure also hinders AI adoption. Developing thorough testing plans or proactively addressing AI-related issues is viewed as a luxury, not a necessity. This creates a counterproductive dynamic: Why use AI to spot issues in documentation if fixing them would delay launch? Why conduct further user research when the direction has already been set from above? Charting a New Course — Investing in PeopleProviding employees time to “figure out AI” isn’t enough; most need training to fully understand how to leverage ChatGPT beyond simple tasks like summarization. Yet the training required is often far less than what people expect. While the market is flooded with AI training programs, many aren’t suitable for most employees. These programs are often time-consuming, overly technical, and not tailored to specific job functions. The best results come from working closely with individuals for brief periods—10 to 15 minutes—to audit their current workflows and identify areas where LLMs could be used to streamline processes. Understanding the technical details behind token prediction isn’t necessary to create effective prompts. It’s also a myth that AI adoption is only for those with technical backgrounds under 40. In fact, attention to detail and a passion for quality work are far better indicators of success. By setting aside biases, companies may discover hidden AI enthusiasts within their ranks. For example, a lawyer in his sixties, after just five minutes of explanation, grasped the potential of LLMs. By tailoring examples to his domain, the technology helped him draft a law review article he had been putting off for months. It’s likely that many companies already have AI enthusiasts—individuals who’ve taken the initiative to explore LLMs in their work. These “LLM whisperers” could come from any department: engineering, marketing, data science, product management, or customer service. By identifying these internal innovators, organizations can leverage their expertise. Once these experts are found, they can conduct “AI audits” of current workflows, identify areas for improvement, and provide starter prompts for specific use cases. These internal experts often better understand the company’s systems and goals, making them more capable of spotting relevant opportunities. Ensuring Time for ExplorationBeyond providing training, it’s crucial that employees have the time to explore and experiment with AI tools. Companies can’t simply tell their employees to innovate with AI while demanding that another month’s worth of features be delivered by Friday at 5 p.m. Ensuring teams have a few hours a month for exploration is essential for fostering true AI adoption. Once the initial hurdle of adoption is overcome, employees will be able to identify the most promising areas for AI investment. From there, organizations will be better positioned to assess the need for more specialized training. ConclusionThe AI productivity paradox is not about the complexity of the technology but rather how organizations approach work and innovation. Harnessing AI’s potential is simpler than “AI influencers” often suggest, requiring only

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November 20, 2024in AI Tools, Data, Einstein 1 Platform, Generative AI, Google, Technology
Scarf and Salesforce
13Nov

Scarf and Salesforce

Scarf Integrates Open Source Software Tracking Platform with Salesforce At KubeCon + CloudNativeCon 2024, Scarf announced the integration of its open-source software usage tracking platform with Salesforce CRM. This integration arrives as debates around the definition and economics of open source remain a hot topic in the tech community. Scarf also introduced updates to its platform, including enhanced event data correction and flagging capabilities for improved accuracy in company matching and attribution. New data filtering options were also added for more refined data exports. The Scarf platform enables IT vendors to identify organizations consuming open-source software at significant scale, presenting opportunities to offer additional support or promote commercial add-ons for open-source tools. To date, the Scarf gateway has tracked over seven billion events, connecting usage data to specific organizations via attributes such as internet addresses. Strengthening the Open Source Ecosystem Scarf CEO Avi Press emphasized the platform’s role in maintaining the economic viability of the open-source ecosystem, often in partnership with organizations like The Linux Foundation. Without these insights, fewer IT vendors would sponsor open-source projects, Press noted, which would hinder the ecosystem’s growth and sustainability. However, the open-source community frequently experiences friction. Licensing changes by IT vendors often lead to project forks, with contributors reverting to previous licensing terms, sometimes backed by cloud providers. Press believes targeted commercial value opportunities—supported by tools like Scarf—can reduce this friction by fostering more productive engagements between vendors and organizations. Challenges and Evolving Definitions in Open Source While open source remains foundational to the tech world, it continues to face ideological and practical challenges. For decades, debates over licensing models have sparked disagreements, including the current contention around defining open-source AI models. Many models fail to disclose critical training details, leading to further disputes. Ultimately, each organization must navigate these issues by adopting its own definition of open source and deciding how best to support the ecosystem. Tools like Scarf’s platform aim to bridge gaps, enabling IT vendors and organizations to collaborate more effectively, ensuring the continued growth of open source. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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November 13, 2024in Data, Salesforce, Technology
Enterprises are Adopting AI-powered Automation Platforms
12Nov

Enterprises are Adopting AI-powered Automation Platforms

The rapid pace of AI technological advancement is placing immense pressure on teams, often leading to disagreements due to the unrealistic expectations businesses have for the speed and agility of new technology implementation. A staggering 88% of IT professionals report that they are unable to keep up with the flood of AI-related requests within their organizations. Executives from UiPath, Salesforce, ServiceNow, and ManageEngine offer insights into how enterprises can navigate these challenges. Leading enterprises are adopting AI-powered automation platforms that understand, automate, and manage end-to-end processes. These platforms integrate seamlessly with existing enterprise technologies, using AI to reduce friction, eliminate inefficiencies, and enable teams to achieve business goals faster, with greater accuracy and efficiency. This year’s innovation drivers include tools such as Intelligent Document Processing, Communications Mining, Process and Task Mining, and Automated Testing. “Automation is the best path to deliver on AI’s potential, seamlessly integrating intelligence into daily operations, automating backend processes, upskilling employees, and revolutionizing industries,” says Mark Gibbs, EMEA President, UiPath. Jessica Constantinidis, Innovation Officer EMEA at ServiceNow, explains, “Intelligent Automation blends Robotic Process Automation (RPA), Artificial Intelligence (AI), and Machine Learning (ML) with well-defined processes to automate decision-making outcomes.” “Hyperautomation provides a business-driven, disciplined approach that enterprises can use to make informed decisions quickly by analyzing process and data feedback within the organization,” adds Constantinidis. Thierry Nicault, AVP and General Manager at Salesforce Middle East, emphasizes that while companies are eager to embrace AI, the pace of change often leads to confusion and stifles innovation. He notes, “By deploying AI and Hyperintelligent Automation tools, organizations can enhance productivity, visibility, and operational transformation.” Automation is driving growth and innovation across industries. AI-powered tools are simplifying processes, improving business revenues, and contributing to economic diversification. Ramprakash Ramamoorthy, Director of AI Research at ManageEngine, highlights how Hyperintelligent Automation, powered by AI, uses tools like Natural Language Processing (NLP) and Intelligent Document Processing to detect anomalies, forecast business trends, and empower decision-making. The IT Pushback Despite enthusiasm for AI, IT professionals are raising concerns. A Salesforce survey revealed that 88% of IT professionals feel overwhelmed by the influx of AI-related requests, with many citing resource constraints, data security concerns, and data quality issues. Business stakeholders often have unrealistic expectations about how quickly new technologies can be implemented, creating friction. According to Constantinidis of ServiceNow, many organizations lack transparency across their business units, making it difficult to fully understand their processes. As a result, automating processes becomes challenging. She adds, “Before full hyperautomation is possible, issues like data validation, classification, and privacy must be prioritized.” Automation platforms need accurate data, and governance is crucial in managing what data is used for AI models. “You need AI skills to teach and feed the data, and you also need a data specialist to clean up your data lake,” Constantinidis explains. Gibbs from UiPath stresses that automation must be designed in collaboration with the business users who understand the processes and systems. Once deployed, a feedback loop ensures continuous improvement and refinement of automated workflows. Ramamoorthy from ManageEngine notes that adopting Hyperintelligent Automation alongside existing workflows poses challenges. Enterprises must evaluate their technology stack, considering the costs, skills required, and the potential benefits. Strategic Integration of AI and Automation To successfully implement Hyperintelligent Automation tools, enterprises need a blend of IT and business skills. Mark Gibbs of UiPath points out, “These skills ensure organizations can effectively implement, manage, and optimize hyperintelligent technologies, aligning them with organizational goals.” Salesforce’s Nicault adds, “Enterprises must empower both IT and business teams to embrace AI, fostering innovation while ensuring the technology delivers real value.” Business skills are equally crucial, including strategic planning, process analysis, and change management. Ramamoorthy emphasizes that these competencies help identify automation opportunities and align them with business goals. According to Bassel Khachfeh, Digital Solutions Manager at Omnix, automation must be implemented with a focus on regulatory and compliance needs specific to the industry. This approach ensures the technology supports future growth and innovation. Transforming Customer Experiences and Business Operations As automation evolves, it’s transforming not only back-end processes but also customer experiences and decision-making at every level. Constantinidis from ServiceNow explains that hyperintelligence enables enterprises to predict outcomes and avert crises by trusting AI’s data accuracy. Gibbs from UiPath adds that automation allows enterprises to unlock untapped opportunities, speeding up the transformation of manual processes and enhancing business efficiency. AI is already making an impact in areas like supply chain management, regulatory compliance, and customer-facing processes. Ramamoorthy of ManageEngine notes that AI-powered NLP is revolutionizing enterprise chatbots and document processing, enabling businesses to automate complex workflows like invoice handling and sentiment analysis. Khachfeh from Omnix highlights how Cognitive Automation platforms elevate RPA by integrating AI-driven capabilities, such as NLP and Optical Character Recognition (OCR), to further streamline operations. Looking Ahead Hyperintelligent Automation, driven by AI, is set to revolutionize industries by enhancing efficiency, driving innovation, and enabling smarter decision-making. Enterprises that strategically adopt these tools—by integrating IT and business expertise, prioritizing data governance, and continuously refining their automated workflows—will be best positioned to navigate the complexities of AI and achieve sustainable growth. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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November 12, 2024in Agentforce Platform, Artificial Intelligence, Data, Enterprise, Salesforce, Technology

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