Examples of companies with custom AI systems

Most companies are using AI for efficiency. Some are accelerating value creation. A great case study is how Colgate-Palmolive is driving innovation. Here are specific ways they are embedding GenAI across innovation processes to substantlly improve research and product development. These come from an excellent article in MIT Sloan Management Review by Tom Davenport and Randy Bean (link in comments). 💡 AI-Driven Product Concept Generation Accelerates Ideation By linking one AI system that surfaces consumer needs with another that crafts product concepts, Colgate-Palmolive can swiftly generate creative ideas like novel toothpaste flavors. This AI-augmented workflow produces a broader product funnel and allows rapid iteration, enabling more employees to participate in the innovation process under guided human oversight. 🔍 Retrieval-Augmented Generation Enhances Data Reliability The firm’s use of retrieval-augmented generation (RAG) integrates company-specific research, syndicated data, and real-time trends from sources like Google search data. This approach minimizes the risk of hallucinations and ensures that responses are deeply grounded in verified, internal content—delivering more accurate market analysis and trend detection. 🤖 Digital Consumer Twins Validate and Refine Concepts Moving beyond traditional focus groups, the company has developed “digital consumer twins”—virtual representations of real consumer behavior. These digital twins rapidly test hundreds of AI-generated product ideas. Early evaluations show a high level of agreement between virtual feedback and actual consumer responses. This innovation speeds up early-stage concept validation and reduces reliance on slower, more limited human panels. 🔐 Democratizing AI Through a Secure Internal AI Hub Colgate-Palmolive’s AI Hub provides employees with controlled access to advanced AI tools (including models from OpenAI and Google) behind corporate firewalls. Mandatory training on responsible AI use, including guardrails and prompt engineering best practices, ensures that employees harness these tools safely and effectively. Built-in surveys and KPI tracking further enable the company to measure improvements in creativity, productivity, and overall work quality. 🌐 Bridging Traditional Analytics with Next-Gen AI for Measurable Impact By integrating traditional machine learning with cutting-edge generative AI, Colgate-Palmolive is not only boosting operational efficiencies but also driving strategic growth. This seamless blend supports tasks ranging from market research and innovation to marketing content creation—demonstrating a holistic, value-driven approach to adopting AI that is a model for other organizations.

Johnson & Johnson, the world’s biggest pharmaceutical company by revenue, revealed details on its AI strategy. After a year of experimentation with over 900 AI applications, they kept on using the ones that drove the most value: A life sciences division uses a generative AI sales assistant that delivers compliant, product-specific insights tailored to each customer. It’s now being adapted for complex medtech sales like robotics and implants. AI is speeding up pharma R&D—from optimizing chemical synthesis steps to spotting promising compounds using image-based models. A predictive AI tool scans for disruptions in the supply chain from fires to material shortages so managers can act before delays hit. Clinical trials are getting a boost from AI: algorithms now match diverse patients to studies faster and even double enrollment rates in some programs. A company-wide chatbot is helping employees navigate HR policies and benefits with instant answers and direct links. Separate AI and data governance units ensure ethical development and scalability, while staff receive hands-on training, including in generative AI. Do you know about other similar use cases at pharma companies? Source: https://lnkd.in/evfrcTaq

From MIT SMR - how 14 companies across a wide range of industries are generating value from generative AI today: McKinsey built Lilli, a platform that helps consultants quickly find and synthesize information from past projects worldwide. The system integrates with over 40 internal sources and even reads PowerPoint slides, leading to 30% time savings and 75% employee adoption within a year. Amazon deploys AI across multiple divisions. Their pharmacy division uses an internal chatbot to help customer service representatives find answers faster. The finance team employs AI for everything from fraud detection to tax work. In their e-commerce business, they personalize product recommendations based on customer preferences and are developing new GenAI tools for vendors. Morgan Stanley empowers their financial advisers with a knowledge assistant trained on over a million internal documents. The system can summarize client video meetings and draft personalized follow-up emails, allowing advisers to focus more on client needs. Sysco, the food distribution giant, uses GenAI to generate menu recommendations for online customers and create personalized scripts for sales calls based on customer data. CarMax revolutionized their car research pages with GenAI, automatically generating content and summarizing thousands of customer reviews. They've since expanded to use AI in marketing design, customer chatbots, and internal tools. Dentsu transformed their creative agency work with GenAI, using it throughout the creative process from proposals to project planning. They can now generate mock-ups and product photos in real-time during client meetings, significantly improving efficiency. John Hancock deployed chatbot assistants to handle routine customer queries, reducing wait times and freeing human agents for complex issues. Major retailers like Starbucks, Domino's, and CVS are implementing GenAI voice interactions for customer service, moving beyond traditional phone menus. Tapestry, parent company of Coach and Kate Spade, uses real-time language modifications to personalize online shopping, mimicking in-store associate interactions. This led to a 3% increase in e-commerce revenue. Software companies are integrating GenAI directly into their products. Lucidchart allows users to create flowcharts through natural language commands. Canva integrated ChatGPT to simplify creation of visual content. Adobe embedded GenAI across their suite for image editing, PDF interaction, and marketing campaign optimization. For more information on these examples and to gain insight into how companies are transforming with GenAI, read the full article here: https://lnkd.in/eWSzaKw4 images: 4 of the 20 I created with Midjourney for this post. #AI #transformation #innovation

In recent times, #AgenticAI has emerged as a transformative force within India's IT sector, marking a significant evolution from traditional AI applications. Unlike earlier systems, #AgenticAI focuses on creating autonomous, context-aware agents capable of interacting seamlessly with complex workflows, thereby enhancing efficiency and productivity across various industries. Major Indian IT companies are actively integrating #AgenticAI into their service offerings: Tata Consultancy Services (TCS): TCS has embedded AI into a majority of its transformation deals, viewing AI adoption as core to business strategies. The company emphasizes moving beyond initial chatbot phases to incorporate AI into automation and intelligence. Infosys: Infosys is leveraging small language models and multi-agent AI to automate processes and improve efficiency. Generative AI is now a part of all large programs, transformations, and cost-efficiency initiatives, transitioning from pilots to full-scale enterprise adoption. Wipro: Focusing on reskilling employees and building AI-driven consulting, Wipro categorizes its projects into AI-led, AI-infused, and AI-powered solutions, viewing AI as a net positive for the industry. HCLTech: Through partnerships with AWS, Google, and NVIDIA, HCLTech is expanding its AI offerings, particularly through initiatives like AI Force and AI Labs, to meet the growing demand for AI and GenAI solutions. LTIMindtree: LTIMindtree is making AI accessible across industries, reporting significant AI wins in manufacturing, finance, and energy sectors, and ensuring AI fluency across the company through workforce training. Tech Mahindra: Distinctively, Tech Mahindra is developing its own AI models, positioning itself uniquely in the market by building sovereign AI models from scratch, aiming to redefine enterprise AI beyond chatbots to autonomous workflows. Mid-sized IT firms are also embracing Agentic AI through strategic investments and acquisitions. For instance, LTIMindtree committed $6 million to Voicing AI, a U.S.-based startup specializing in human-like AI #voiceagents, aiming to enhance conversational, contextual, and emotional intelligence across more than 20 languages. India's tech ecosystem is poised to play a critical role in the advancement of #AgenticAI. With a robust engineering talent pool and a focus on application-driven innovation, Indian startups and established firms are at the forefront of developing AI agents that integrate seamlessly into business processes. Companies like Kore.ai are utilizing platforms such as #Redis to power their #virtual #AIagents, exemplifying India's contribution to this evolving field. In conclusion, #AgenticAI is not merely a technological upgrade but a fundamental transformation in the Indian IT landscape, promising to enhance efficiency, drive innovation, and maintain global competitiveness. Image Credit : AIM Magazine #generativeai #aiagents #futuretrends #transformation #servicenow

Stop looking at flashy startups and tech companies if you want to cut through the AI hype. Instead, look at traditional "boring" businesses industries and how they are adopting AI. Here are some examples [with articles and white papers]! Colgate - https://lnkd.in/gwAvFyCg "The consumer products company is using generative AI for the full innovation cycle, from synthesizing consumer insights and highlighting unmet consumer needs to suggesting new product concepts." Cigna - https://lnkd.in/g985mrjd "By leveraging AI and machine learning, we are able to deliver faster claims processing turnaround times with higher levels of accuracy... Without removing the human element of the process, it facilitates better decisions by improving the quality of the claims data and providing a more holistic view of customer health." DuPont - https://lnkd.in/g3usXrki "The integration of generative AI into DuPont’s invention process marks a paradigm shift in how chemical products are conceptualized and developed. This technology enables DuPont to rapidly analyse vast amounts of data, including materials science knowledge, reaction kinetics, and customer requirements, to generate novel formulations and predict product properties with unprecedented speed and accuracy." Do you have any similar examples? I would love to see them!

This case study from C.H. Robinson is the perfect example of building advanced AI systems in the right way. Getting an AI system to complete over three million shipping tasks is no small feat! Why is it a good example of building AI solutions right? They didn't build the system all at once but instead chose to start small. They began with common, repetitive tasks. Built trust. Then expanded the system step by step. Each improvement layered on the last. From task prediction, to decision support, to full automation. This is what real AI adoption looks like inside a business. Not a one-off pilot. Not a chatbot at the edge. A system that grows with the maturity of the people and their understanding of how to best evolve the system. Built in the right way, an agent can incrementally understand more data, with more advanced logic that completes more pieces of a process. It moves from assisting a person to orchestrating outcomes. Because real AI capability compounds, it creates systems that learns and evolve as the ability of the organisation to adopt innovation evolves in parallel. https://lnkd.in/dFujbBiU

Silicon Valley gets all the AI Agent headlines. But have you seen what’s being built in Europe? Here are the agents I’m closely watching …most specifically to help with GTM: 1. Attio Their agent autonomously ingests calls/emails, auto-extracts insights, populates CRM fields and triggers workflows based on pre-set conditions. Example use-case: After a sales call, auto-updating deal-relevant information (value, prospect). 2. Apify Their agents, or “actors,” autonomously navigate websites, bypass anti-bot measures, and extract data. Example use-case: Extract conference attendee lists to re-engage them later. 3. Lovable Their agent builds full web apps from natural language. It writes code, sets up databases, deploys & iterates based on feedback. Example use-case: Building free mini-tools to capture email addresses. 4. ElevenLabs Their voice agent handles inbound calls 24/7, qualifies leads, books meetings & detects emotions across 32+ languages. 5. lemlist Their agent score leads against your ICP, navigates websites for personalization & generate multichannel sequences in ~3 minutes. Example use-case: Letting AI prepare a multi-channel outreach sequence from scratch for human review. 6. Linkup Their search API gives other AI agents accurate, real-time web access. Not an agent per se, but an API that powers them. Example use-case: A prospecting agent would query LinkUp to check whether a prospect has just raised funding before writing personalised outreach. 7. Dust Custom agents that connect to Slack, Notion, Google Drive & your CRM to autonomously perform analyses across all sources. Example use-case: Asking the agent to help you prep for a sales call, then the agent pulls CRM notes, recent Slack threads, and other helpful docs into a brief. 8. n8n Open-source workflow builder with AI building capabilities. Example use-case: Creating custom, agentic GTM workflows. Other EU-based agents to watch: - Make - Tidio - Modjo - arcads AI - ZenRows - Pipedrive - Jiminny - Typeform - Synthesia - Amplemarket - NiCE Cognigy - Salesforge.ai 🔥 - Jason AI (Reply) - La Growth Machine - Enginy.ai (formerly Genesy) P.S: Any agent I should be looking at?