Customer Service Archives - gettectonic.com

23Apr

Alaska Inspires

Alaska Airlines Launches Guest-Facing Generative AI Tool, Alaska Inspires Alaska Airlines has become the first airline to introduce a guest-facing Generative AI (GenAI) tool with the launch of Alaska Inspires. Designed to simplify travel planning, this AI-powered assistant helps guests discover destinations more efficiently. “We heard from our guests that planning a trip to a new destination can take up to 40 hours,” says Bernadette Berger, Director of Innovation at Alaska Airlines. “Much of that time is spent comparing destinations, prices, travel times, and reading reviews. We built a Natural Language Search tool to let guests explore travel options using their own words, preferred language, or voice.” With Alaska Inspires, travelers can ask questions like, “Where can I go in Europe for under 80,000 miles?” or “Where can I go skiing within four hours?” Powered by OpenAI, the tool provides highly personalized responses and recommends up to four destinations, explaining why each was selected. This initiative is part of Alaska Airlines’ broader effort to develop a suite of GenAI tools that make discovering, shopping, and booking travel faster and more intuitive. Enhancing the Day-of-Travel Experience with AI Beyond trip planning, Alaska Airlines is leveraging GenAI to provide real-time, personalized travel insights. Berger highlights the growing role of AI in understanding guest preferences and delivering information in their preferred format. “Using voice as an interface—especially in a guest’s preferred language—is ideal for quick questions or simple tasks,” she explains. “How many minutes until I board?” or “Check me in for my flight” are prime examples of how voice-enabled GenAI can enhance the customer experience. Additionally, translating live announcements and direct messages into a traveler’s native language helps improve clarity and engagement. Bridging the Gap Between Data and Human Understanding Airlines operate in a world of complex policies, acronyms, and industry jargon. GenAI helps bridge this gap by translating raw operational data into clear, guest-friendly language. “GenAI excels at ingesting rules, policies, and operational data while generating responses that explain situations in a brand-aligned, easy-to-understand way,” Berger says. Currently, Alaska Airlines uses GenAI to assist customer service agents in quickly answering policy-related questions and responding to guest inquiries with speed and care. Balancing Innovation with Privacy and Quality While the opportunities with GenAI are vast, Berger acknowledges the challenges of implementing AI responsibly. “Building AI-powered tools is fast, but it requires time for model training, security, and rigorous user testing,” she notes. Ensuring privacy and maintaining high-quality outputs remain top priorities. Advice for the Industry: Experiment, Learn, and Scale For airlines, airports, and industry stakeholders exploring GenAI, Berger offers practical advice: focus on reducing the cost of testing. “If your AI roadmap is filled with expensive, time-consuming trials, your team will get stuck in hypotheticals,” she warns. “Build fast, low-cost experiments to validate the technology, use case, inputs, and outputs. Identify failures quickly and move on, then scale what works. This approach helps separate marketing hype from real business value and, most importantly, delivers solutions that truly enhance the customer experience.” With Alaska Inspires and a growing suite of AI-driven innovations, Alaska Airlines is leading the way in making travel planning and the day-of-travel experience more seamless and personalized. 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

April 23, 2025in AI Tools, Data, Generative AI, Salesforce Hospitality Travel and Transportation, Technology0 Comments

22Apr

Why Salesforce is the Key to Cloud Transformation

Cloud transformation is essential for businesses aiming to scale, boost efficiency, and enhance customer experiences. As a leading cloud platform, Salesforce plays a pivotal role in this transition—connecting cloud ecosystems, optimizing operations, and ensuring seamless customer interactions. But to unlock its full potential, organizations need the right Salesforce experts to drive the transformation successfully. The Role of Salesforce in Cloud Transformation As a cloud-native platform, Salesforce provides automation, AI-driven insights, and deep integration across business functions. It acts as the central hub, linking sales, marketing, customer service, and back-end operations. During cloud migration, Salesforce ensures:✅ Customer data remains accessible and secure✅ Workflows stay optimized for efficiency✅ AI-powered insights drive smarter decision-making Without experienced Salesforce professionals, businesses risk data silos, inefficient processes, and failed integrations—leading to costly delays and operational setbacks. Challenges in Hiring Salesforce Experts 1. Talent Shortages & High Demand The growing reliance on Salesforce has created a ultra-competitive hiring landscape. Roles like Salesforce Developers, Architects, and Administrators are in high demand, making it challenging for companies to attract and retain top talent. 2. The Need for More Than Just Technical Skills Many organizations focus solely on coding expertise, but cloud transformation demands professionals who understand business processes, data architecture, and integration strategies. A developer who codes without considering business goals may create solutions that don’t align with the organization’s needs. 3. Integration Complexities Salesforce rarely operates in isolation—it must integrate with ERP systems, marketing automation tools, and other cloud platforms. Poorly planned integrations can lead to inefficiencies and disrupt transformation efforts, underscoring the need for specialists who can manage system connectivity effectively. Strategies for Hiring the Right Salesforce Experts 1. Clearly Define Roles & Responsibilities Before hiring, identify the specific expertise required. For example: 2. Prioritize Certifications & Hands-On Experience Look for candidates with certifications like: Additionally, hands-on experience with cloud integrations, API development, and data migration is crucial for success. 3. Assess Problem-Solving Abilities Cloud transformation is complex, often presenting unexpected challenges. A structured hiring process should include scenario-based questions and technical assessments to evaluate candidates’ ability to handle real-world Salesforce challenges. 4. Explore Contract & Full-Time Hiring Models Given the talent shortage, companies may need a mix of contract and full-time hires: 5. Align Hiring with Cloud Strategy Salesforce experts must collaborate with cloud engineers and IT teams to ensure seamless integration. When hiring, prioritize candidates who understand system architecture and can align Salesforce capabilities with long-term business goals. Building a Strong Salesforce Team for Cloud Transformation Hiring the right Salesforce experts is critical for a smooth and effective cloud transformation. By defining roles, prioritizing experience, and assessing real-world skills, businesses can build teams that drive long-term success. Salesforce managed services is an alternative to the talent shortage. If your organization is looking to strengthen its Salesforce talent strategy, partnering with experts like Tectonic can bridge hiring gaps. Tectonic delivers top-tier Salesforce talent to power your digital transformation. With a vast network of vetted professionals and data-driven recruitment strategies, we help companies secure skilled experts—fast without increasing headcount. Let’s build your Salesforce dream team. 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

April 22, 2025in Data, Marketing Automation, Salesforce0 Comments

20Apr

Architecture for Enterprise-Grade Agentic AI Systems

LangGraph: The Architecture for Enterprise-Grade Agentic AI Systems Modern enterprises need AI that doesn’t just answer questions—but thinks, plans, and acts autonomously. LangGraph provides the framework to build these next-generation agentic systems capable of: ✅ Multi-step reasoning across complex workflows✅ Dynamic decision-making with real-time tool selection✅ Stateful execution that maintains context across operations✅ Seamless integration with enterprise knowledge bases and APIs 1. LangGraph’s Graph-Based Architecture At its core, LangGraph models AI workflows as Directed Acyclic Graphs (DAGs): This structure enables:✔ Conditional branching (different paths based on data)✔ Parallel processing where possible✔ Guaranteed completion (no infinite loops) Example Use Case:A customer service agent that: 2. Multi-Hop Knowledge Retrieval Enterprise queries often require connecting information across multiple sources. LangGraph treats this as a graph traversal problem: python Copy # Neo4j integration for structured knowledge from langchain.graphs import Neo4jGraph graph = Neo4jGraph(url=”bolt://localhost:7687″, username=”neo4j”, password=”password”) query = “”” MATCH (doc:Document)-[:REFERENCES]->(policy:Policy) WHERE policy.name = ‘GDPR’ RETURN doc.title, doc.url “”” results = graph.query(query) # → Feeds into LangGraph nodes Hybrid Approach: 3. Building Autonomous Agents LangGraph + LangChain agents create systems that: python Copy from langchain.agents import initialize_agent, Tool from langchain.chat_models import ChatOpenAI # Define tools search_tool = Tool( name=”ProductSearch”, func=search_product_db, description=”Searches internal product catalog” ) # Initialize agent agent = initialize_agent( tools=[search_tool], llm=ChatOpenAI(model=”gpt-4″), agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION ) # Execute response = agent.run(“Find compatible accessories for Model X-42”) 4. Full Implementation Example Enterprise Document Processing System: python Copy from langgraph.graph import StateGraph from langchain.embeddings import OpenAIEmbeddings from langchain.vectorstores import Pinecone # 1. Define shared state class DocProcessingState(BaseModel): query: str retrieved_docs: list = [] analysis: str = “” actions: list = [] # 2. Create nodes def retrieve(state): vectorstore = Pinecone.from_existing_index(“docs”, OpenAIEmbeddings()) state.retrieved_docs = vectorstore.similarity_search(state.query) return state def analyze(state): # LLM analysis of documents state.analysis = llm(f”Summarize key points from: {state.retrieved_docs}”) return state # 3. Build workflow workflow = StateGraph(DocProcessingState) workflow.add_node(“retrieve”, retrieve) workflow.add_node(“analyze”, analyze) workflow.add_edge(“retrieve”, “analyze”) workflow.add_edge(“analyze”, END) # 4. Execute agent = workflow.compile() result = agent.invoke({“query”: “2025 compliance changes”}) Why This Matters for Enterprises The Future:LangGraph enables AI systems that don’t just assist workers—but autonomously execute complete business processes while adhering to organizational rules and structures. “This isn’t chatbot AI—it’s digital workforce AI.” Next Steps: 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

April 20, 2025in Agentic AI, Data, Enterprise0 Comments

18Apr

How AI Can Help Canadian Manufacturers Stay Competitive in a Changing Economy

Canada’s manufacturing sector faces mounting pressures—from a weak Canadian dollar to persistent supply chain disruptions. According to Salesforce’s Trends in Manufacturing Report, 63% of Canadian manufacturers say supply chain issues that began years ago still linger today, while unexpected equipment downtime costs large producers 8% of annual revenue. To navigate these challenges and future-proof operations, Canadian manufacturers must embrace AI-driven modernization—leveraging data intelligence, predictive analytics, and autonomous AI agents to boost efficiency, cut costs, and unlock new revenue streams. The Data Accessibility Challenge While 84% of Canadian manufacturers recognize the need to modernize, many struggle to extract real value from their digital investments. Key findings reveal: The problem? Siloed data prevents manufacturers from delivering real-time insights to frontline workers and AI tools—hindering predictive maintenance, inventory optimization, and customer service improvements. How AI Agents Drive Manufacturing Efficiency To maximize AI’s impact, manufacturers need a unified data platform (like Salesforce’s Manufacturing Data Cloud) that integrates: Autonomous AI agents (powered by natural language processing) can then automate decision-making, such as:✅ Detecting sales contract deviations and auto-correcting pricing or fulfillment issues.✅ Predicting equipment failures and scheduling proactive maintenance.✅ Optimizing stock levels by auto-reordering when inventory dips. 3 Key Areas Where AI Delivers Immediate ROI The Path Forward: Building an AI-Ready Foundation With economic uncertainty looming, Canadian manufacturers must act now to:🔹 Break down data silos (integrate IoT, ERP, and CRM systems).🔹 Deploy AI agents for autonomous decision-making in sales, maintenance, and logistics.🔹 Train teams to work alongside AI—not against it. The bottom line? AI isn’t just a competitive advantage—it’s becoming a necessity for survival in modern manufacturing. By harnessing connected data and intelligent automation, Canadian manufacturers can cut costs, boost productivity, and secure their future in an unpredictable global market. Ready to modernize? Start by auditing your data infrastructure—because AI is only as powerful as the insights it can access. Tectonic can help. 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

April 18, 2025in Agentforce Platform, AI Tools, Data, Salesforce, Salesforce Manufacturing Automotive Energy0 Comments

17Apr

AI and Automation

The advent of AI agents is widely discussed as a transformative force in application development, with much of the focus on the automation that generative AI brings to the process. This shift is expected to significantly reduce the time and effort required for tasks such as coding, testing, deployment, and monitoring. However, what is even more intriguing is the change not just in how applications are built, but in what is being built. This perspective was highlighted during last week’s Salesforce developer conference, TDX25. Developers are no longer required to build entire applications from scratch. Instead, they can focus on creating modular building blocks and guidelines, allowing AI agents to dynamically assemble these components at runtime. In a pre-briefing for the event, Alice Steinglass, EVP and GM of Salesforce Platform, outlined this new approach. She explained that with AI agents, development is broken down into smaller, more manageable chunks. The agent dynamically composes these pieces at runtime, making individual instructions smaller and easier to test. This approach also introduces greater flexibility, as agents can interpret instructions based on policy documents rather than relying on rigid if-then statements. Steinglass elaborated: “With agents, I’m actually doing it differently. I’m breaking it down into smaller chunks and saying, ‘Hey, here’s what I want to do in this scenario, here’s what I want to do in this scenario.’ And then the agent, at runtime, is able to dynamically compose these individual pieces together, which means the individual instructions are much smaller. That makes it easier to test. It also means I can bring in more flexibility and understanding so my agent can interpret some of those instructions. I could have a policy document that explains them instead of hard coding them with if-then statements.” During a follow-up conversation, Steinglass further explored the practical implications of this shift. She acknowledged that adapting to this new paradigm would be a significant change for developers, comparable to the transition from web to mobile applications. However, she emphasized that the transition would be gradual, with stepping stones along the way. She noted: “It’s a sea change in the way we build applications. I don’t think it’s going to happen all at once. People will move over piece by piece, but the result’s going to be a fundamentally different way of building applications.” Different Building Blocks One reason the transition will be gradual is that most AI agents and applications built by enterprises will still incorporate traditional, deterministic functions. What will change is how these existing building blocks are combined with generative AI components. Instead of hard-coding business logic into predetermined steps, AI agents can adapt on-the-fly to new policies, rules, and goals. Steinglass provided an example from customer service: “What AI allows us to do is to break down those processes into components. Some of them will still be deterministic. For example, in a service agent scenario, AI can handle tasks like understanding customer intent and executing flexible actions based on policy documents. However, tasks like issuing a return or connecting to an ERP system will remain deterministic to ensure consistency and compliance.” She also highlighted how deterministic processes are often used for high-compliance tasks, which are automated due to their strict rules and scalability. In contrast, tasks requiring more human thought or frequent changes were previously left unautomated. Now, AI can bridge these gaps by gluing together deterministic and non-deterministic components. In sales, Salesforce’s Sales Development Representative (SDR) agent exemplifies this hybrid approach. The definition of who the SDR contacts is deterministic, based on factors like value or reachability. However, composing the outreach and handling interactions rely on generative AI’s flexibility. Deterministic processes re-enter the picture when moving a prospect from lead to opportunity. Steinglass explained that many enterprise processes follow this pattern, where deterministic inputs trigger workflows that benefit from AI’s adaptability. Connections to Existing Systems The introduction of the Agentforce API last week marked a significant step in enabling connections to existing systems, often through middleware like MuleSoft. This allows agents to act autonomously in response to events or asynchronous triggers, rather than waiting for human input. Many of these interactions will involve deterministic calls to external systems. However, non-deterministic interactions with autonomous agents in other systems require richer protocols to pass sufficient context. Steinglass noted that while some partners are beginning to introduce actions in the AgentExchange marketplace, standardized protocols like Anthropic’s Model Context Protocol (MCP) are still evolving. She commented: “I think there are pieces that will go through APIs and events, similar to how handoffs between systems work today. But there’s also a need for richer agent-to-agent communication. MuleSoft has already built out AI support for the Model Context Protocol, and we’re working with partners to evolve these protocols further.” She emphasized that even as richer communication protocols emerge, they will coexist with traditional deterministic calls. For example, some interactions will require synchronous, context-rich communication, while others will resemble API calls, where an agent simply requests a task to be completed without sharing extensive context. Agent Maturity Map To help organizations adapt to these new ways of building applications, Salesforce uses an agent maturity map. The first stage involves building a simple knowledge agent capable of answering questions relevant to the organization’s context. The next stage is enabling the agent to take actions, transitioning from an AI Q&A bot to a true agentic capability. Over time, organizations can develop standalone agents capable of taking multiple actions across the organization and eventually orchestrate a digital workforce of multiple agents. Steinglass explained: “Step one is ensuring the agent can answer questions about my data with my information. Step two is enabling it to take an action, starting with one action and moving to multiple actions. Step three involves taking actions outside the organization and leveraging different capabilities, eventually leading to a coordinated, multi-agent digital workforce.” Salesforce’s low-code tooling and comprehensive DevSecOps toolkit provide a significant advantage in this journey. Steinglass highlighted that Salesforce’s low-code approach allows business owners to build processes and workflows,

April 17, 2025in AgentExchange, Agentic AI, Data, Enterprise, Generative AI, Mulesoft, Salesforce, Technology0 Comments

17Apr

Revolutionizing Government Services with AI-Powered Support

Government customer service isn’t just about solving problems—it’s about building trust, efficiency, and accessibility for all citizens. That’s why innovations like Salesforce’s AI-powered Agentforce are transforming public sector operations. As reported in CX Today, 85% of Salesforce’s own customer inquiries are now resolved by Agentforce—proving that AI can dramatically reduce wait times, improve accuracy, and free up human agents for high-value tasks. What This Means for Government Agencies 1. Faster, More Accurate Citizen Services ✔ AI assistants can instantly handle common inquiries—benefits applications, tax questions, permit requests—reducing delays.✔ 24/7 self-service ensures citizens get answers anytime, without long hold times. 2. Empowered Public Sector Teams ✔ By automating routine tasks, employees focus on complex cases, policy work, and personalized support.✔ AI-driven insights help identify trends, improving service design and resource allocation. 3. Greater Efficiency & Cost Savings ✔ Reduced operational costs by minimizing manual processing.✔ Scalable solutions that adapt to demand spikes (e.g., tax season, emergencies). 4. Trust Through Transparency & Compliance ✔ Built-in audit trails, data security, and governance ensure AI aligns with public sector regulations.✔ Citizens gain clear, consistent, and accountable interactions. Agentforce: A Tailored Solution for Government Salesforce’s Agentforce is designed to meet the unique needs of the public sector, offering: 🔹 Automated Case Management – Smart routing, status tracking, and self-service portals.🔹 Real-Time Analytics – Predictive insights to anticipate citizen needs.🔹 Emergency Response Tools – Rapid communication during crises.🔹 Seamless Salesforce Integration – Leveraging Service Cloud, Marketing Cloud, and Einstein AI for end-to-end citizen engagement. The Future of Public Service is Here By integrating AI like Agentforce, governments can:✅ Deliver faster, more equitable services.✅ Optimize limited resources.✅ Restore public trust through transparency. The goal? A smarter, more responsive government that works better for everyone. Ready to transform your agency’s service delivery? Let’s discuss how AI can empower your team. #PublicSector #GovTech #AI #DigitalTransformation #CitizenExperience 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 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

April 17, 2025in Agentforce Platform, Data, Public Sector Solutions, Salesforce, Salesforce Public Sector Solutions0 Comments

17Apr

Salesforce Unveils Agentforce for Consumer Goods

Salesforce Unveils Agentforce for Consumer Goods: Accelerating AI Adoption in Retail San Francisco, [April 2025] – Just eight days after launching Agentforce for Field Service, Salesforce has introduced Agentforce for Consumer Goods—a tailored solution designed to help brands quickly deploy AI agents across four key sectors: customer service, key account management, retail sales, and field operations. Unlike previous editions that offered pre-built AI agents for specific roles, this release provides a library of industry-specific skills and actions, empowering consumer goods companies to rapidly customize and deploy their own AI assistants. Why Agentforce for Consumer Goods? While businesses could already build agents on the standard Agentforce platform, this industry-focused edition accelerates deployment with:✔ Pre-configured skills for customer service, sales, and field teams✔ Faster implementation with ready-made automation components✔ Lower-risk experimentation for brands new to agentic AI “Salesforce is curating a smooth onboarding experience for companies entering the agentic AI era,” says Martin Schneider, VP & Principal Analyst at Constellation Research. “This gives quick wins—building confidence before diving into advanced multi-agent workflows.” Key Use Cases for Consumer Goods Brands 🛎️ AI-Powered Customer Service Agents Example: A rep at a home appliance company can ask an AI agent to check a customer’s product health—if maintenance is due, the agent drafts a service quote in seconds. 📈 Smarter Sales Assistants Example: If an account’s order volume drops unexpectedly, an AI agent can recommend new products to pitch, helping sales teams react faster. 🚚 Optimized Field Operations Example: When a customer requests a replacement, an AI agent instantly books delivery, assigns the nearest driver, and updates schedules—no manual input needed. The Bigger Picture: Salesforce’s Agentforce Momentum This launch follows: With 5,000+ customers already on Agentforce, industry-specific editions like this lower the barrier to entry—letting more brands test AI agents in low-stakes scenarios before scaling. What’s Next? Expect more vertical-focused Agentforce releases in 2025, building on earlier launches like Agentforce for Retail. For now, consumer goods brands have a new toolkit to turn repetitive tasks into automated workflows—freeing teams to focus on growth. Ready to explore AI agents for 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 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

April 17, 2025in Agentforce Platform, Agentic AI, Data, Generative AI, Salesforce0 Comments

16Apr

Secure AI Innovation for CIOs

Secure AI Innovation for CIOs: Balancing Speed & Stability CIOs No Longer Choose Between Innovation and Security The role of the CIO has transformed. Once focused on maintaining infrastructure, today’s IT leaders are drivers of innovation—especially with AI reshaping business. But with great opportunity comes great responsibility: ✅ How do we innovate quickly without compromising security?✅ How do we protect customer data in an AI-driven world?✅ How do we optimize operations at scale? Salesforce Platform provides the secure, unified foundation CIOs need to lead AI adoption while maintaining governance. 3 Key Challenges for Modern CIOs 1. Innovate Fast—But With Guardrails AI’s potential is limitless, but implementation must be strategic: Salesforce Solution: 2. Protect Data to Build Trust AI runs on data—but unsecured data is a liability. CIOs must: Salesforce Solution: 3. Optimize Operations at Scale With 900+ SaaS apps per enterprise, visibility is critical. AI can: Salesforce Solution: Announcing: Enhanced Data Protection with Own Salesforce Platform now integrates Own Company—a leader in data management trusted by 7,000+ customers. New capabilities include: Product Key Benefit Backup & Recover Automated, scalable data restoration Salesforce Discover Feed clean data to BI tools—no prep needed Archive Store inactive data without bloating production Data Mask & Seed Anonymize sensitive data for safe testing The CIO’s AI Playbook With Salesforce Platform, you don’t choose between innovation and stability—you get both. 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

April 16, 2025in Data, Enterprise, Mulesoft, Salesforce, Salesforce Shield0 Comments

Can Tech Companies Use Generative AI for Good?

16Apr

AI and the Future of IT Careers

AI and the Future of IT Careers: Jobs That Remain Secure As AI technology advances, concerns about job security in the IT sector continue to grow. AI excels at handling repetitive, high-speed tasks and has made significant strides in software development and error prediction. However, while AI offers exciting possibilities, the demand for human expertise remains strong—particularly in roles that require interpersonal skills, strategic thinking, and decision-making. So, which IT jobs are most secure from AI displacement? To answer this question, industry experts shared their insights: Their forecasts highlight the IT roles most resistant to AI replacement. In all cases, professionals should enhance their AI knowledge to stay competitive in an evolving landscape. Top AI-Resistant IT Roles 1. Business Analyst Role Overview:Business analysts act as a bridge between IT and business teams, identifying technology opportunities and facilitating collaboration to optimize solutions. Why AI Won’t Replace It:While AI can process vast amounts of data quickly, it lacks emotional intelligence, relationship-building skills, and the ability to interpret nuanced human communication. Business analysts leverage these soft skills to understand software needs and drive successful implementations. How to Stay Competitive:Develop strong data analysis, business intelligence (BI), communication, and presentation skills to enhance your value in this role. 2. Cybersecurity Engineer Role Overview:Cybersecurity engineers protect organizations from evolving security threats, including AI-driven cyberattacks. Why AI Won’t Replace It:As AI tools become more sophisticated, cybercriminals will exploit them to develop advanced attack strategies. Human expertise is essential to adapt defenses, investigate threats, and implement security measures AI alone cannot handle. How to Stay Competitive:Continuously update your cybersecurity knowledge, obtain relevant certifications, and develop a strong understanding of business security needs. 3. End-User Support Professional Role Overview:These professionals assist employees with technical issues and provide hands-on training to ensure smooth software adoption. Why AI Won’t Replace It:Technology adoption is becoming increasingly complex, requiring personalized support that AI cannot yet replicate. Human interaction remains crucial for troubleshooting and user training. How to Stay Competitive:Pursue IT certifications, strengthen customer service skills, and gain experience in enterprise software environments. 4. Data Analyst Role Overview:Data analysts interpret business and product data, generate insights, and predict trends to guide strategic decisions. Why AI Won’t Replace It:AI can analyze data, but human oversight is needed to ensure accuracy, recognize context, and derive meaningful insights. Companies will continue to rely on professionals who can interpret and act on data effectively. How to Stay Competitive:Specialize in leading BI platforms, gain hands-on experience with data visualization tools, and develop strong analytical thinking skills. 5. Data Governance Professional Role Overview:These professionals set policies for data usage, access, and security within an organization. Why AI Won’t Replace It:As AI handles increasing amounts of data, the need for governance professionals grows to ensure ethical and compliant data management. How to Stay Competitive:Obtain a degree in computer science or business administration and seek training in data privacy, security, and governance frameworks. 6. Data Privacy Professional Role Overview:Data privacy professionals ensure compliance with data protection regulations and safeguard personal information. Why AI Won’t Replace It:With AI collecting vast amounts of personal data, organizations require human experts to manage legal compliance and maintain trust. How to Stay Competitive:Develop expertise in privacy laws, cybersecurity, and regulatory compliance through certifications and training programs. 7. IAM Engineer (Identity and Access Management) Role Overview:IAM engineers develop and implement systems that regulate user access to sensitive data. Why AI Won’t Replace It:The growing complexity of digital identities and security protocols requires human oversight to manage, audit, and secure access rights. How to Stay Competitive:Pursue a computer science degree, gain experience in authentication frameworks, and build expertise in programming and operating systems. 8. IT Director Role Overview:IT directors oversee technology strategies, manage teams, and align IT initiatives with business goals. Why AI Won’t Replace It:Leadership, motivation, and strategic decision-making are human-driven capabilities that AI cannot replicate. How to Stay Competitive:Develop strong leadership, business acumen, and team management skills to effectively align IT with organizational success. 9. IT Product Manager Role Overview:Product managers oversee tech adoption, service management, and organizational change strategies. Why AI Won’t Replace It:Effective product management requires a human touch, particularly in change management and stakeholder communication. How to Stay Competitive:Pursue project management training and certifications while gaining experience in software development and enterprise technology. Staying AI-Proof: Learning AI Expert Insights on Future IT Careers Final Thoughts As AI continues to reshape the IT landscape, the key to job security lies in adaptability. Professionals who develop AI-related skills and focus on roles that require human judgment, creativity, and leadership will remain indispensable in the evolving workforce. 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 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

April 16, 2025in AI Tools, Data, Enterprise, Generative AI, Laws, Technology0 Comments

14Apr

Tectonic Shook Things Up at AgentForce World Tour in Denver

The Tectonic team attended Salesforce’s Denver AgentForce World Tour this week. It was a great experience to develop our AgentBlazer team and a true seismic time was had by all! AI Agents were the topic of conversation and kept things lively! One almost expected to meet an Agentic Robot around every corner. We were all excited to network with Salesforce, customers, and partners alike. Key Takeaways Autonomous AI agents can understand and interpret customers’ questions using natural language, with minimal human intervention. Here’s what you need to know. The AI Assistant Revolution: Empowering Every Employee Imagine if every person in your company—from the CEO to frontline employees—had a dedicated assistant at their fingertips. An assistant who:✔ Knows your customers inside out✔ Delivers instant, data-driven insights✔ Helps prioritize next best actions Thanks to AI agents, this future is already here—and it’s transforming how businesses operate. How AI Agents Are Supercharging Teams 1. Instant Insights, No Manual Work 🔹 Generative AI agents analyze your trusted customer data in seconds—eliminating hours of manual research.🔹 Sales, service, and marketing teams get real-time recommendations, allowing them to focus on high-impact work. 2. Scaling Teams Without Adding Headcount 🔹 AI agents handle routine tasks—customer inquiries, data entry, meeting prep—freeing employees for strategic work.🔹 Quickly ramp up productivity during peak demand without overburdening staff. 3. Proactive Problem-Solving 🔹 AI doesn’t just react—it predicts.🔹 Identifies risks, suggests optimizations, and prevents small issues from becoming big ones. 4. Personalized Support for Every Role 🔹 Sales: AI suggests the best leads, crafts follow-ups, and forecasts deals.🔹 Service: Resolves common cases instantly, escalating only when needed.🔹 Leadership: Delivers real-time business insights for faster decisions. The Future of Work Is AI-Augmented AI agents aren’t replacing humans—they’re empowering them. By automating the mundane and enhancing decision-making, they help teams:✅ Work smarter, not harder✅ Deliver better customer experiences✅ Stay ahead of the competition The question isn’t if your company should adopt AI agents—it’s how soon you can start leveraging them. Tectonic, a trusted Salesforce partner, is here to help. Ready to explore AI-powered productivity? Let’s talk about the right AI strategy for your business. AI Agents: Your Intelligent Digital Workforce What Is an AI Agent? An AI agent is an autonomous artificial intelligence system that understands, processes, and responds to customer inquiries—without human intervention. Built using platforms like Agentforce, these agents leverage machine learning (ML) and natural language processing (NLP) to handle tasks ranging from simple FAQs to complex problem-solving. Unlike traditional AI, which requires manual programming for each task, AI agents continuously learn and improve from interactions, becoming smarter over time. How Do AI Agents Work? AI agents operate through a seamless four-step process: 💡 Result? Faster resolutions, happier customers, and more efficient teams. 6 Game-Changing Benefits of AI Agents Feature Impact 1. 24/7 Availability Instant support across time zones. 2. Hyper-Efficiency Handle thousands of queries simultaneously—no wait times. 3. Smarter Escalations Auto-route complex cases to the best-suited human agent. 4. Personalized Experiences Tailor responses using real-time customer data. 5. Scalability Grow support capacity without hiring more staff. 6. Data-Backed Insights Uncover trends to optimize operations & CX. “72% of companies already deploy AI—with generative AI adoption accelerating.” – McKinsey AI Agents in Action: Industry Use Cases 🏦 Finance ✔ Personalized wealth advice based on spending habits✔ Auto-summarize client cases for faster resolutions 🏭 Manufacturing ✔ Predict equipment failures before they happen✔ Optimize supply chain decisions with real-time data 🛒 Retail & Consumer Goods ✔ Smart inventory tracking (e.g., flagging stock discrepancies)✔ AI-generated promo content for targeted campaigns 🚗 Automotive ✔ Proactive vehicle maintenance alerts via telematics✔ Dynamic dealership promotions to boost sales 🏥 Healthcare ✔ Automated patient scheduling with the right specialist✔ Clinical trial matching using AI-driven eligibility checks Join the AI Revolution with Agentforce AI agents aren’t just tools—they’re productivity multipliers that help teams:✅ Work faster with automated workflows✅ Serve customers better with personalized AI assistance✅ Stay ahead with predictive insights 📈 Ready to transform your business? Connect with Tectonic today, or check out our Agentforce Quickstart offering. Connect with the Tectonic Agentforce team and launch your Agentic Revolution. AI Agents: The Ultimate Productivity Multiplier for Every Team AI agents aren’t just transforming customer service—they’re revolutionizing how every department operates. From 24/7 customer support to hyper-personalized marketing campaigns, AI agents help teams work smarter, move faster, and deliver exceptional experiences. Here’s how AI agents supercharge key business functions: 🤝 AI Agents for Service Teams Never miss a customer inquiry—even at 2 AM.✔ Instant, 24/7 support across email, chat, and social media✔ Smart escalation—AI routes complex cases to human agents with full context✔ Brand-consistent responses powered by your CRM data 🔹 With Agentforce for Service, deploy AI agents in minutes using prebuilt templates—or customize them for your unique needs. 💰 AI Agents for Sales Teams Turn every lead into a conversation—automatically.✔ Autonomous lead engagement—AI answers product questions & books meetings✔ Always-on SDRs—Agentforce Sales Development Reps qualify leads 24/7✔ Controlled escalation—Set rules for when & how AI hands off to your team 🔹 No more missed opportunities—AI keeps your pipeline full while your reps focus on closing. 🛍️ AI Agents for Commerce Teams Personal shopping assistants—powered by AI.✔ Smart product recommendations based on browsing & purchase history✔ Guided shopping experiences—AI helps customers find what they need faster✔ Omnichannel support—Engage shoppers on your site, WhatsApp, and more 🔹 Boost conversions with AI that acts like your best sales associate—for every customer. 📢 AI Agents for Marketing Teams Campaigns that write, optimize, and improve themselves.✔ AI-generated campaign briefs—audience targeting, messaging & KPIs✔ Automated content creation—draft ads, emails & social posts in your brand voice✔ Performance optimization—AI analyzes results & suggests improvements 🔹 With Agentforce Campaigns, launch better campaigns in hours—not weeks. Why AI Agents? The Bottom Line ✅ Scale operations without scaling headcount✅ Deliver instant, personalized experiences 24/7✅ Free your team to focus on high-value work “Companies using AI agents see 40% faster response times and 30% higher customer satisfaction.” Ready to deploy your AI workforce? See how Agentforce can transform your business #FutureOfWork

April 14, 2025in Agentforce Platform, Artificial Intelligence, Data, Generative AI, Salesforce0 Comments

11Apr

Optimizing AI Agent Performance Through Strategic Data Management

The Foundation of Effective AI Implementation The success of your Agentforce deployment directly correlates with your organization’s data maturity. While comprehensive, well-structured data yields optimal AI performance, businesses at any stage of their data journey can benefit from implementing AI agents. The key lies in adopting a strategic, phased approach that delivers measurable impact while building toward long-term data excellence. Building a Robust Data Infrastructure Data Quality Optimization The principle of “garbage in, garbage out” remains particularly relevant for AI systems. To ensure high-quality outputs: Data Unification Strategy Creating a centralized knowledge ecosystem enables AI agents to deliver consistent, informed responses. Essential integration points include: Platforms like Unified Knowledge facilitate seamless consolidation of disparate data sources into Salesforce, enhancing AI grounding effectiveness. Knowledge Base Development for AI Excellence Effective AI Grounding Techniques Retrieval-augmented generation (RAG) transforms your knowledge base into a powerful AI enabler by: Knowledge Base Optimization To maximize AI agent performance: Continuous Knowledge Improvement Cycle Proactive Knowledge Maintenance Implement these practices to sustain AI relevance: Feedback-Driven Enhancement Leverage multiple feedback channels to identify knowledge gaps: Strategic Implementation Framework Focused Use Case Development Begin with high-impact scenarios by: Phased Deployment Methodology Channel Optimization Strategy Alignment with Business Objectives Tailor channel strategy to organizational priorities: Customer Journey Mapping Human-AI Collaboration Model Workforce Transformation Seamless Transition Protocols Performance Measurement Framework Key Success Metrics By implementing this comprehensive framework, organizations can systematically enhance their AI capabilities while delivering immediate business value and building toward increasingly sophisticated implementations. The approach balances quick wins with long-term transformation, ensuring sustainable success in AI-powered customer service. 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

April 11, 2025in Agentforce Platform, Data, Salesforce, Unified Knowledge0 Comments

11Apr

CaixaBank and Salesforce Partner to Revolutionize Banking with AI-Powered Personalization

Barcelona – CaixaBank, Spain’s leading digital bank, has deepened its collaboration with Salesforce to redefine customer experience through AI-driven personalization and data intelligence. The partnership will integrate Salesforce’s Agentforce AI assistants and Data Cloud solutions into CaixaBank’s operations, enhancing efficiency, decision-making, and customer engagement. Transforming Banking with AI Assistants and Real-Time Data Under the agreement, CaixaBank will deploy Salesforce’s Agentforce—a suite of AI-powered virtual assistants designed to: Additionally, Salesforce Data Cloud will enable real-time data unification, ensuring secure, instant access to customer insights for hyper-personalized interactions. Use Case: AI-Powered Remote Contracting Assistant A flagship implementation is CaixaBank’s Remote Contracting Support Assistant, which leverages generative AI to: The assistant will soon evolve into an Agentforce AI agent, autonomously suggesting products, scheduling follow-ups, and promoting tailored offers. Why This Matters CaixaBank’s AI Leadership With 100+ dedicated AI specialists, CaixaBank is a pioneer in generative AI for finance, already deploying cognitive assistants and now scaling transformative use cases. Looking Ahead: The partnership will expand Salesforce’s role as CaixaBank’s centralized platform for sales and service, with further AI integrations underway. Key Takeaways:🔹 Agentforce AI automates service and empowers advisors.🔹 Data Cloud unlocks real-time, secure customer insights.🔹 Remote Contracting Assistant cuts wait times to <2 minutes.🔹 CaixaBank cements its status as Spain’s top digital bank. 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

April 11, 2025in Data, Generative AI, Salesforce, Salesforce Data Cloud0 Comments

11Apr

Supercharge Salesforce Agentforce with OpenText AI-Powered Insights

The future of intelligent customer engagement is here. OpenText and Salesforce are revolutionizing AI-driven workflows with deep content integration, empowering sales and service teams to work smarter, faster, and with greater accuracy. AI in Sales & Service: The Need for Trusted Data AI is transforming business operations:✅ 83% of AI-powered sales teams report revenue growth✅ 93% of service teams achieve time and cost savings But success depends on trusted data. With 98% of sales leaders emphasizing the need for accurate, secure, and compliant information, OpenText Content Cloud provides the foundation for reliable AI—seamlessly integrated with Salesforce. OpenText + Salesforce: AI Innovation Leaders Since 2016, OpenText has enhanced Salesforce with powerful content management solutions. Now, we’re taking it further with GenAI-powered automation:✔ OpenText™ Content Aviator delivers AI-driven insights from unstructured data (contracts, emails, documents)✔ Selected as a launch partner for the Agentforce Partner Network✔ First-to-market solution on Salesforce’s new AgentExchange—making AI agent deployment faster than ever Key Use Cases 🔹 Sales Teams – Summarize customer buying trends, auto-generate upsell recommendations🔹 Customer Service – Instantly resolve claims by extracting key details from documents🔹 Claims Processing – Automate approvals with AI-powered document analysis How It Works: AI Insights → Agentforce Actions OpenText Content Aviator for Agentforce unlocks hidden insights from unstructured content stored in OpenText Content Management, then feeds them directly into Salesforce Agentforce to trigger smart, automated actions. Key Benefits 🚀 Accelerate Sales Cycles – Auto-summarize contracts, identify upsell opportunities🎯 Enhance Customer Service – Resolve cases faster with AI-generated insights✍ Reduce Manual Work – Auto-update Salesforce records, eliminating errors📧 Personalize at Scale – Draft tailored email responses using AI insights Now Available ✔ Integrated with OpenText Content Management CE 25.1✔ Coming soon to OpenText Core Content SaaS (CE 25.3) OpenText Content Aviator and Salesforce Agentforce integration provides AI-driven insights for Sales and Customer Service teams, enhancing productivity and accelerating processes. This integration enables users to discover, summarize, and translate business workspace content directly within Agentforce, eliminating the need to switch applications. Essentially, it leverages AI to extract valuable insights from unstructured data like documents, contracts, and emails, and then uses those insights to drive data-driven actions within Agentforce What’s Next? The Future of AI-to-AI Integration This is just the beginning. OpenText is expanding AI-driven automation across the entire content lifecycle, with upcoming innovations including:🔹 More AI agents for sales, service, and operations🔹 Industry-specific solutions (banking, insurance, healthcare)🔹 Bi-directional AI – Blending insights from multiple AI systems for smarter decision-making OpenText™ Content Aviator puts AI into the hands of business users to leverage conversational search, discover content, or even summarize a document or workspace, offering new ways to interact with content and extract knowledge. Content Aviator enables organizations to combine the power of generative AI and large language models (LLMs) with OpenText content services platforms, including OpenText™ Core Content Management, OpenText™ Documentum™ Content Management (CM) and OpenText™ Content Management (Extended ECM), to make document management, knowledge discovery, and business process automation more efficient, effective and intelligent. Get Started Today ✅ Explore OpenText Content Aviator for Agentforce on Salesforce AgentExchange✅ Discover all OpenText-Salesforce integrations on the Salesforce AppExchange Unlock the power of AI-driven content intelligence—and transform the way your teams work. Contact Tectonic today to leverage AI-driven content intelligence. 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 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

April 11, 2025in AgentExchange, Agentforce Platform, Data, Public Sector Solutions, Salesforce, Salesforce Development Services, Salesforce Education Solutions, Salesforce Financial Services Solutions, Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services0 Comments

08Apr

Generative AI in Marketing

Generative AI in Marketing: Balancing Innovation and Risk Generative AI (gen AI) has become a disruptive force in the marketplace, particularly in marketing, where its ability to create content—from product descriptions to personalized ads—has reshaped strategies. According to Salesforce’s State of Marketing report, which surveyed 5,000 marketers worldwide, implementing AI is now their top priority. Some companies, like Vanguard and Unilever, have already seen measurable benefits, with Vanguard increasing LinkedIn ad conversions by 15% and Unilever cutting customer service response times by 90%. Yet, despite 96% of marketers planning to adopt gen AI within 18 months, only 32% have fully integrated it into their operations. This gap highlights the challenges of implementation—balancing efficiency with risks like inauthenticity or errors. For instance, Coca-Cola’s AI-generated holiday ad initially drew praise but later faced backlash for its perceived lack of emotional depth. The Strategic Dilemma: How, Not If, to Use Gen AI Many Chief Data and Analytics Officers (CDAOs) have yet to formalize gen AI strategies, leading to fragmented experimentation across teams. Based on discussions with over 20 industry leaders, successful adoption hinges on three key decisions: To answer these, companies must assess: Gen AI vs. Analytical AI: Choosing the Right Tool Analytical AI excels at predictions—forecasting customer behavior, pricing sensitivity, or ad performance. For example, Kia once used IBM Watson to identify brand-aligned influencers, a strategy still relevant today. Generative AI, on the other hand, creates new content—ads, product descriptions, or customer service responses. While analytical AI predicts what a customer might buy, gen AI crafts the persuasive message around it. The most effective strategies combine both: using analytical AI to identify the “next best offer” and gen AI to personalize the pitch. Custom vs. General Inputs: Striking the Balance Gen AI models can be trained on: For broad applications like customer service chatbots, general models (e.g., ChatGPT) work well. But for brand-specific needs—like ad copy or legal disclaimers—custom-trained models (e.g., BloombergGPT for finance or Jasper for marketing) reduce errors and intellectual property risks. Human Oversight: How Much Is Enough? The level of human review depends on risk tolerance: Air Canada learned this the hard way when its AI chatbot mistakenly promised a bereavement discount—a pledge a court later enforced. While human review slows output, it mitigates costly errors. A Framework for Implementation To navigate these trade-offs, marketers can use a quadrant-based approach: Input Type No Human Review Human Review Required General Data Fast, low cost, high risk Higher accuracy, slower output (e.g., review summaries) (e.g., social media posts) Custom Data Lower privacy risk, higher cost Highest accuracy, highest cost (e.g., in-store product locator) (e.g., SEC filings) The Path Forward Gen AI is not a one-size-fits-all solution. Marketers must weigh speed, cost, accuracy, and risk for each use case. While technology will evolve, today’s landscape demands careful strategy—blending gen AI’s creativity with analytical AI’s precision and human judgment’s reliability. The question is no longer whether to adopt gen AI, but how to harness its potential without falling prey to its pitfalls. Companies that strike this balance will lead the next wave of marketing innovation. 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 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

April 8, 2025in Data, Generative AI, Salesforce, Technology0 Comments

04Apr

Digital Transformation for Tourism

The digital revolution is in full swing, with individuals and businesses increasingly interacting through social networks and digital devices. In this new era, consumers have grown more discerning, leveraging mobile technology to make informed decisions about products, services, and trusted providers. As mobile apps become integral to daily life, organizations are compelled to reinvent their customer value propositions and operating models through digital transformation to remain competitive in today’s market. Digital transformation has become a critical priority across industries, with the tourism sector standing out as a prime example of significant disruption driven by digital technologies. According to McKinsey & Company, the tourism industry has been undergoing a digital revolution for over a decade, transforming how travelers plan, book, and experience their trips. This shift has led to changing consumer behaviors, with travelers now demanding more personalized and seamless experiences. The push toward digital adoption in tourism is accelerating. A Skift survey found that 83% of respondents view digital transformation as a top priority. Tourism businesses are increasingly investing in technology to enhance customer experiences, optimize operations, and drive revenue growth. To boost enterprise agility, companies must make strategic decisions across five key dimensions of their operating models: One of the most notable impacts of digital transformation is the revolution in the booking process. Travelport Digital estimates that over 700 million people will book trips online by 2023, marking a 15% increase from previous years. Key statistics highlight this global shift in traveler preferences: Mobile apps have become essential tools for travelers, enabling them to research, plan, and book trips seamlessly. In the hospitality and tourism sector, key digital transformation trends include: Emerging technologies like cognitive computing, omnichannel models, and advanced personalization are further reshaping the future of the industry. Artificial intelligence (AI) and machine learning are increasingly used to tailor travel experiences based on consumer preferences and behaviors, as noted by GlobalData. AI also improves operational efficiency, with chatbots handling customer inquiries effectively. Augmented reality (AR) and virtual reality (VR) are enhancing customer experiences by allowing travelers to explore destinations virtually before booking. Meanwhile, social media continues to play a pivotal role in promoting tourism businesses and reaching new audiences. In conclusion, digital transformation is no longer optional for tourism businesses—it is a necessity to remain competitive. The adoption of digital technologies has fundamentally reshaped the travel experience, and businesses must embrace this evolution to meet changing consumer expectations and maintain relevance in an increasingly digital world. 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 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

April 4, 2025in Artificial Intelligence, Data, Enterprise, Google, Salesforce, Technology0 Comments

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