Key Benefits of Genai Adoption

What do a bank, a hospital, and a logistics firm have in common? They’re all quietly experimenting with GenAI in ways that actually matter. Not to win headlines. Not to build shiny copilots. But to drive results. That’s what stuck with me while exploring Deloitte’s GenAI Use Case Navigator. https://lnkd.in/eskkGqH4 It’s not just a catalog of AI ideas, it’s a reality check. Because here’s what it reveals: ➤ GenAI’s biggest impact isn’t in customer experience fluff. It’s in fixing the unseen bottlenecks that drag businesses down. ➤ The most transformative use cases? Not the ones that sound fancy—but the ones that reduce manual effort, save time, cut cost. ➤ Think: claims intake, RFP responses, contract summarization, fraud detection, supply chain prediction. Real examples? ➡️ A global insurer used GenAI to automate underwriting analysis, reducing quote generation time from 5 days to 30 minutes. ➡️ A healthcare system used it to summarize complex patient histories before physician review, cutting admin time by over 40%. ➡️ A logistics company deployed GenAI to optimize route planning and fuel usage, saving millions in operational costs. ➡️ A government agency implemented GenAI to automate the review of grant applications, ensuring consistency and reducing cycle times. ➡️ A legal team used it to draft NDAs and review contract clauses—freeing up attorneys for higher-value work. ➡️ A finance team built a GenAI-powered dashboard that answers natural language queries about spend, variances, and forecast anomalies—no analyst needed. They’re not talking about “prompt engineering.” This is so 2023. They’re engineering out inefficiencies. They’re not building AI for the sake of it. They’re using AI to solve what’s broken, fragmented, or too slow to scale. Because. ChatGPT is NOT your strategy. AI is NOT your strategy. Your strategy IS to run your business better. Smarter. Leaner. Faster. AI's power depends on where and how you use it. Because in the end, it’s not about being an “AI-first company.” It’s about being a results-first company. So here's the question: What’s the real ROI of GenAI? The pilot… or the process it quietly replaces forever?

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

🧠 Workers using AI performed just as well as full teams while working 16% faster and reporting more excitement, energy, and enthusiasm. This isn’t speculation...it’s what 776 professionals at Procter & Gamble just proved in a study. The latest research reveals something we’re only beginning to grasp: AI isn’t just a tool. It’s a teammate. Here’s what People Analytics leaders need to know: 1️⃣ AI boosts individual performance to team-level outcomes 🔹 Individuals using GenAI improved performance by +0.37 standard deviations, matching the effectiveness of human teams. 🔹 They also worked 16.4% faster, producing longer, more detailed solutions. 📌 Takeaway: One AI-enabled employee can now match the output of a traditional 2-person team. 2️⃣ AI breaks down expertise silos 🔹 Commercial specialists started suggesting technical solutions. 🔹 R&D pros brought forward customer-facing ideas. 🔹 AI leveled the playing field across specialties. 📌 Takeaway: GenAI is becoming the great equalizer in cross-functional collaboration. 3️⃣ AI improves emotional experience at work 🔹 Participants reported more energy, excitement, and enthusiasm. 🔹 They also saw lower frustration and anxiety when AI was in the loop. 📌 Takeaway: AI isn’t just changing how we work—it’s changing how we feel at work. 4️⃣ AI helps surface breakthrough ideas 🔹 AI-enabled teams were 3x more likely to generate top 10% solutions. 🔹 Even less experienced employees delivered ideas on par with veterans. 📌 Takeaway: AI is democratizing creativity and unlocking hidden potential across the org. 💡 Bottom line for People Analytics teams: AI isn’t just enhancing productivity. It’s reshaping how teams form, how they collaborate, and how individuals experience their work. Check the comments for the full research paper and Ethan Mollick’s excellent breakdown. How is your organization measuring the real impact of AI on collaboration, expertise, and experience? #GenAI #AIAdoption #PeopleAnalytics #FutureOfWork #WorkforceTransformation

My favorite part of the quarter is here: Deloitte just released our State of GenAI in the Enterprise Q3 Survey. Analyzing input from over 2,700 directors to C-suite level respondents around the world and across industries on how their organizations are approaching the transformative power of #GenAI, we’re seeing an interesting mix of trends.     For example: two thirds of respondents say their organization is increasing investment in GenAI because they have seen strong value to date. While there are still improvements to be made in terms of data sharing and education, I was proud to see so many putting in the work to invest in integrating this technology into their workforce.      As more gain exposure to AI, people are discovering efficiency is just the tip of the iceberg when it comes to GenAI benefits. In this survey, respondents note things like innovation, reduced costs, improved products and services, and bettered customer relationships.      Those who are reaping the fullest benefits of GenAI are focusing on deep, heart-of-the-business integration, which we think is key to harnessing this transformative technology. They are also focused on data modernization, getting the data ready to be used by AI, as well as trust and implementing risk management frameworks to drive governance.      This was a pleasure to read through and chalked full of insights, thank you Beena Ammanath, Costi Perricos, Brenna Sniderman, David Jarvis, for working so hard to put this together. You can read the full survey for yourself here: https://deloi.tt/3TjSyBx

Generative AI (GenAI) is transforming DevOps by addressing inefficiencies, reducing manual effort, and driving innovation. Here's a practical breakdown of where and how GenAI shines in the DevOps lifecycle—and how you can start implementing it.  Key Applications of GenAI in DevOps  𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀   - Automatically generate well-defined 𝘂𝘀𝗲𝗿 𝘀𝘁𝗼𝗿𝗶𝗲𝘀 and documentation from business requests.   - Translate technical specifications into simple, 𝗵𝘂𝗺𝗮𝗻-𝗿𝗲𝗮𝗱𝗮𝗯𝗹𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 to improve clarity across teams.  𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁   - Automate 𝗯𝗼𝗶𝗹𝗲𝗿𝗽𝗹𝗮𝘁𝗲 𝗰𝗼𝗱𝗲 generation and unit test creation to save time.   - Assist in debugging by analyzing 𝗰𝗼𝗱𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 and suggesting potential fixes.  𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁   - Generate test cases from 𝘂𝘀𝗲𝗿 𝘀𝘁𝗼𝗿𝗶𝗲𝘀 𝗮𝗻𝗱 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 to ensure robust testing coverage.   - Automate deployment pipelines and 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗽𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝗶𝗻𝗴, reducing errors and deployment times.  𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀   - Analyze 𝗹𝗼𝗴 𝗱𝗮𝘁𝗮 in real-time to identify potential issues before they escalate.   - Provide actionable insights and 𝗵𝗲𝗮𝗹𝘁𝗵 𝘀𝘂𝗺𝗺𝗮𝗿𝗶𝗲𝘀 of systems to keep teams informed.  How To Implement GenAI: A Step-by-Step Approach  𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗣𝗮𝗶𝗻 𝗣𝗼𝗶𝗻𝘁𝘀   Start by pinpointing 𝘁𝗶𝗺𝗲-𝗰𝗼𝗻𝘀𝘂𝗺𝗶𝗻𝗴, 𝗿𝗲𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲, 𝗼𝗿 𝗲𝗿𝗿𝗼𝗿-𝗽𝗿𝗼𝗻𝗲 𝘁𝗮𝘀𝗸𝘀 in your DevOps workflow. Focus on areas where GenAI can deliver measurable value.  𝗖𝗵𝗼𝗼𝘀𝗲 𝗧𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗧𝗼𝗼𝗹𝘀   Explore GenAI solutions tailored for DevOps use cases. Look for tools that integrate seamlessly with your existing CI/CD pipelines, testing frameworks, and monitoring tools.  𝗗𝗮𝘁𝗮 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻   Ensure your data is 𝗰𝗹𝗲𝗮𝗻, 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱, 𝗮𝗻𝗱 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝘁 to the GenAI models you're implementing. Poor data quality can hinder GenAI's performance.  𝗣𝗶𝗹𝗼𝘁 𝗦𝗺𝗮𝗹𝗹 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀   Start with a 𝘀𝗶𝗻𝗴𝗹𝗲 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲 in a controlled environment. Measure the outcomes and gather feedback before scaling up across your organization.  𝗠𝗼𝗻𝗶𝘁𝗼𝗿 & 𝗥𝗲𝗳𝗶𝗻𝗲   Continuously evaluate your GenAI implementation for accuracy, efficiency, and impact. Be ready to retrain models and refine your approach as needed.  𝗧𝗵𝗲 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀  ✅ Faster development and deployment cycles.   ✅ Improved collaboration through simplified communication.   ✅ Enhanced system reliability with proactive monitoring.   ✅ Reduced manual effort, enabling teams to focus on innovation.  By adopting GenAI in DevOps strategically, you can unlock its potential to create a faster, more efficient, and innovative development environment.  𝗪𝗵𝗮𝘁’𝘀 𝘆𝗼𝘂𝗿 𝘁𝗮𝗸𝗲?   How do you see GenAI reshaping the future of DevOps in your organization?

Kait Strovink, one of our Creative Directors at Pega, has been using this slide to explain the power of GenAI to transform how the marketing team at Pega is working. Historically, teams that work together in collaborative and especially "co-creative" formats often see the highest levels of aligned goals and partnerships and can deliver the best results. But that level of co-creation often requires larger investments of time - which means it has historically been reserved for only the top priority projects. GenAI changes that. Using GenAI agents our marketing team can do co-creation WHENEVER THEY NEED, simply by involving an AI agent in the conversation. I think the same is true for enterprise transformation. Historically, doing things like Process Re-engineering required massive co-creation investments, and often external guidance and expertise. But now with AI tools (such as Pega GenAI Blueprint), leaders can take a co-creation approach to rethinking their workflows, but with a significantly reduced time investment. That kind of surge in innovation and creativity - and the business transformation that results - is where I think the impact of AI will be most felt at the enterprise.

While there's been a lot of speculation regarding what companies see as the benefits of deploying #GenAI, there hasn't been a great deal of research diving into the topic. In this latest post covering the results of my in-depth study of how over 1,000 US-based businesses across 10 different industries are using the technology, I've got the top things that companies reported as upsides to using GenAI in their organizations. Not surprisingly, Increased Efficiency and Productivity is number one, highlighting many of the practical benefits that things like Document Creation and Summarization can enable. Second is Improved Quality of Output which speaks to the impressive level of capabilities the technology can bring. New Revenue Streams or Business Models came in at number three, offering a sense of what companies are hoping to be able to gain from the technology more than what they're likely experiencing in these early days of the technology. One interesting difference between business sizes is that Medium Businesses are more focused on new revenues than Large Enterprises. See https://lnkd.in/gdQzZCAb, https://t.co/mHYX232sXe and https://lnkd.in/gNzYW74r for the previous posts in this series. More #GenAI info to come... If you want access to a summary of the full study, you can find it here: https://lnkd.in/g_z3TZgm