Amit V. Singh’s Post

Hey Everybody! Check out my latest industry analysis aimed at helping you figure out what to do next about deploying generative AI apps in your business. Are you already depolying generative AI in your business? Do the #PEP and #ETP product categories make sense to you? 🧩 Transform Your Business with AI: Get a glimpse into the groundbreaking Prompt Engineering Platform (PEP) and Executive Thinking Partner (ETP) today's post. I believe these are the enterprise AI product categories that will redefine how businesses work. 🚢 Navigate through the distractions and hype to implement a phased rollout of AI that adds real value to your operations. From the prototype AI Gateway for Salesforce to the advanced ETP capabilities, the article unfolds a practical roadmap to AI success. 💼 Implement PEP First: Start with optimizing productivity and costs to build trust and infrastructure. 🎓 Tackle ETP Later: Gradually explore ETP pilots for augmented intelligence and decision-making. 🛡 Counter ShadowGPT: Deploy governed PEP solutions to prevent unauthorized consumer chatbot usage. Companies Mentioned: Salesforce Amazon Web Services (AWS) Google Cloud Microsoft Azure GPTfy Elements.cloud Metazoa #EnterpriseAI #ArtificialIntelligence #Innovation #Automation #TechnologyLeadership #BusinessTransformation #ITStrategy #AIIntegration https://lnkd.in/g9CP8nB8

I know over the last couple weeks it’s been AI this and AI that. It’s really a hit topic! There’s so much that ChatGPT and now Salesforce’s EinsteinGPT, can do! It’s honestly amazing! Also, what’s more amazing is how SM Innovations is leveraging as much information as it can to stay at the forefront of its competitors. Our team itself aims to be generative prompt experts which are the building blocks of how AI becomes more intuitive with its responses. I’ve given a little preview but check out this article to learn more about what I’m talking about: “How it works: With Einstein Studio, companies can leverage their proprietary, real-time customer data from Data Cloud to train AI models that solve specific business needs. And with Einstein Studio’s BYOM solution, companies can train their preferred AI model with Data Cloud, which connects all customer data from any source, and automatically harmonizes that data into a single customer profile that adapts to each customer’s activity in real time for use across any department” #salesforce #chatgpt #ai #salesforcepartner

#GenerativeAI empowers businesses with the ability to create, innovate & personalize content at scale.Introducing the AWS Generative AI Competency, which helps businesses unlock endless possibilities for productivity, automation & hyper-personalized customer experiences while re-inventing existing business functions & processes. According to Canalys, #AWS is the first to launch a Generative AI competency for partners. By validating the partner’s business and technical expertise in this way, AWS customers are able to invest with greater confidence in generative AI solutions from these partners. This new competency is a critical entry point into the generative AI partner opportunity, which Canalys estimates will grow to US $158 billion by 2028. Proud to have been a part of #hcltech 's partnership with AWS in accelerating incubation, adoption and acceleration of AWS' compelling GenAI services and offerings. HCLTech being a part of this launch is just the start of what will be a compelling journey #genai Vijay Guntur Kalyan Kumar (KK) Prabhakar Appana Srinivasan Seshadri Ajay Bahl Ashish Kumar Gupta Swapan Johri Siba Satapathy Gaurang Rao ☁ Kiran Sarva Mani Chandrasekaran Joao Itaqui Amit Gupta Sara Alligood Brian Bohan Mahendra Ayyalasomayajula Chandra Parvathaneni Rachel Skaff Antonio Alonso Lopez Robert Swinkin Chris Casey Vittorio Sanvito Shankar Moorthy Melissa Dougherty Arvind Murthy Tammy Whyman

Generative AI Predictive AI can prove to be a game changer for any business today. Predictive AI can study all the historical data to create predictions, and Gen AI can then use those predictions to create relevant data and talking points in a humane way. With my experience in Salesforce CPQ, I have tried to list down some possible use cases for Predictive GenAI in the world of selling. https://lnkd.in/gs2hvC_M Salesforce Salesforce Revenue Cloud Infosys #generatieveai #predictiveai #blog #cpq #salesforce #einsteinai #selling #infosys

Vertical AI refers to the application of Artificial Intelligence (AI) solutions designed for specific industries or sectors. Traditionally, many Software as a Service (SaaS) offerings have been horizontal, meaning they can be used by a variety of businesses regardless of industry. Vertical AI, in contrast, tailors AI solutions to address the unique needs and challenges of particular industries. Here are some potential benefits of Vertical AI: Deeper Industry Expertise: Vertical AI solutions can leverage domain-specific data and knowledge to deliver more effective and efficient results compared to generic AI solutions. Improved Accuracy: By focusing on a specific industry, Vertical AI can be fine-tuned to provide more accurate predictions and recommendations. Faster Time to Value: Since Vertical AI solutions are pre-configured for specific industry needs, businesses can benefit from quicker implementation and a faster return on investment (ROI). Overall, Vertical AI represents a potential future wave of AI adoption where businesses can harness the power of AI customized to their industry's specific requirements.

Generative AI is set to revolutionize the industry, but it's important to make the right decisions along the way. With so many options out there, it can be overwhelming giving up control in the form of data silos and talent limitations. As teams develop their AI strategy, it's crucial to limit the risks in innovation through proper business and IT alignment. That way, everyone can have a seat at the table, including our unfortunate friend in the comic. #GenerativeAI #DataStrategy #AIStrategy

This is *exactly* why I founded MotorUnit. *Implementing* technology is easy. *Using* technology is hard. Using technology to *accomplish* something is even harder. Think of it this way: let's say you want to start bike commuting, but you've never ridden a bike before. So you go to a bike shop and you buy a bike. In software parlance, you have "gone live." Congratulations, you are now at the beginning of your transformation. You still have to (1) learn how to ride the bike and then (2) develop your fitness enough so you can ride from your home to your office. Acquire --> Use --> Leverage That is the cycle. So many organizations stop after acquire. Don't.