Generative AI Applications for Business Transformation

GenAI has indeed put CIOs on the hot seat 🥵 CEOs and their executive peers are looking at CIOs to drive the generative AI strategy for the business. In my interactions with CIOs over the last 6 months, it’s apparent that the role of the CIO has become more relevant than ever. One value stream that shows up consistently is employee service. Why is this a lucrative area for applying Generative AI? 1. Reduce the high spend on employee service desks 2. Create employee productivity surplus 3. Repetitive nature of tasks lends itself to GenAI application 4. Safe area to start using GenAI 5. Excellent opportunity to learn at scale As a result, it's not surprising to see CIOs setup audacious goals like “zero service desk” as they look at the next 2-3 years. They are also clear eyed about the requirements of a generative AI service desk. They don’t want to “sprinkle” a copilot and hope for transformative results. Instead, here is what they are thinking of 1. Search across variety of documents and manuals across dozens of enterprise systems, and summarize answers (eg troubleshooting VPN, benefits policies) 2. Perform actions on behalf of employees to resolve their issues (eg provision applications, change permissions, book time off) 3. Provide real time business data to employees securely and responsibly (eg PO / invoice data, or time off data) 4. Enable their engineers to extend the copilot for new workflows and automations (eg enable sellers to submit requests for deal discounts) 5. Empower tech writers, service owners, HRBPs to create new knowledge / content faster 6. Provide insight to services leaders to help them identify new areas of opportunity for further automation 7. Have up to date success plans that continuously transform their service desk 8. Ensure data and information security while achieving this transformation The next few years will be transformative for employee service. It is emerging as the only consensus value stream for all CIOs to target with GenAI. https://lnkd.in/gg6T2Vky

McKinsey & Company: "𝗧𝗵𝗮𝘁'𝘀 𝗛𝗼𝘄 𝗖𝗜𝗢𝘀 𝗮𝗻𝗱 𝗖𝗧𝗢𝘀 𝗖𝗮𝗻 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗳𝗼𝗿 𝗠𝗮𝘅𝗶𝗺𝘂𝗺 𝗜𝗺𝗽𝗮𝗰𝘁" This McKinsey & Co report highlights how #GenAI, when deeply integrated, can revolutionize business operations. I took a stab at CPG eCommerce use case below, and thriving with generative #AI isn’t about just deploying a model; it demands a deep integration into your enterprise stack. 𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀: 𝗠𝘂𝗹𝘁𝗶-𝗹𝗮𝘆𝗲𝗿𝗲𝗱 𝗚𝗲𝗻𝗔𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗖𝗣𝗚⬇️ 𝟭. 𝗖𝘂𝘁𝗼𝗺𝗲𝗿 𝗟𝗮𝘆𝗲𝗿: → The user logs in, browses personalized product recommendations, and either finalizes a purchase or escalates to a support agent—all seamlessly without grasping the backend processes. This layer prioritizes trust, rapid responses, and tailored suggestions like skincare routines based on user preferences. 📍Business Impact: Boosts customer satisfaction and loyalty, increasing conversion rates by up to 40% through hyper-personalized interactions that drive repeat purchases. 𝟮. 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗟𝗮𝘆𝗲𝗿 → Oversees user engagement: - Chatbot launches and steers the dialogue, suggesting complementary products - Escalation to a human agent activates if AI can't fully address complex queries, like ingredient allergies 📍Business Impact: Enhances efficiency in consumer support, reducing resolution times and operational costs while minimizing cart abandonment in #eCommerce flows. 𝟯. 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗟𝗮𝘆𝗲𝗿: → Performs smart actions using context: - Retrieves user profile data - Validates promotions and inventory - Creates customized options, such as virtual try-ons - Advances the process, like adding to the cart 📍Business Impact: Accelerates innovation in product discovery, lifting marketing productivity by 10-40% and enabling dynamic pricing that optimizes revenue in competitive #FMCG markets. 𝟰. 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗔𝗽𝗽 𝗟𝗮𝘆𝗲𝗿 → Links AI to essential enterprise platforms: - User verification and access management - Promotion rules and order processing - Support agent routing algorithms 📍Business Impact: Streamlines supply chain and sales workflows, cutting technical debt by 20-40% and improving inventory accuracy to reduce stockouts and overstock costs. 𝟱. 𝗗𝗮𝘁𝗮 𝗟𝗮𝘆𝗲𝗿 → Delivers instant contextual details: - Consumer profiles - Purchase records - Promotion guidelines - Support team directories 📍Business Impact: Powers precise AI insights, enhancing demand forecasting and personalization to minimize waste in perishable goods while boosting overall data-driven decision-making. 𝟲. 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗟𝗮𝘆𝗲𝗿 → Supports scalability, efficiency, and oversight: - Cloud or hybrid setups - AI model coordination - High-speed response handling - Privacy and compliance controls 📍Business Impact: Ensures robust, secure operations at scale, unlocking value by optimizing resource use, slashing IT ops costs.

🔔 Unleashing the Power of Generative AI in Private Equity 📣 💡 The latest report from Bain & Company on "Gen AI for Private Equity firms 2024" highlights some important aspects around application of Generative AI for PE firms at fund level and portfolio companies level. 🌈 It is now widely accepted fact that Generative AI stands as a critical reasoning engine, capable of transforming how we interact with customers, create content, and extract insights from vast data stores. ⭐ In the world of private equity, firms are mobilizing to harness the potential of generative AI in three key areas: ⚡ Portfolio Assessment: Leading firms are proactively evaluating the impact of generative AI on their portfolio companies. Will these technologies disrupt value chains or economic models? Can generative AI be leveraged to drive innovation and competitive advantage? Through rapid test-and-learn initiatives, firms are turning insights into action. ⚡ Enhanced Due Diligence: Generative AI is becoming a routine part of the due diligence process. Firms are developing AI-powered scorecards to assess threats and opportunities, while leveraging these tools to accelerate and sharpen underwriting. The ability to rapidly prototype disruption theses during diligence is a game-changer. ⚡ Supercharging Investment Decisions: At the firm level, generative AI offers a powerful opportunity to expand the information and institutional knowledge brought to bear on investment decisions. These tools can streamline back-office functions while dramatically enhancing the insights available to investment professionals across the entire value creation cycle. 🔦 The true value of generative AI lies in its strategic deployment as a tool to achieve pragmatic business objectives. Firms are prioritizing initiatives that directly impact customer experience, revenue generation, cost reduction, and operational efficiency. Change management and clear execution plans are critical to ensuring successful adoption and realizing tangible benefits. 📚 As the generative AI revolution continues to unfold, early movers in the private equity space are positioning themselves to stay ahead of the curve. By harnessing the power of these technologies, firms can drive superior returns, sharpen competitive edges, and unlock new opportunities for value creation. 🥁 If you're a private equity firm or portfolio company looking to harness the transformative potential of generative AI, this is the time to work towards AI/Gen AI adoption across your portfolio. 🔦 Link to Bain Report : https://lnkd.in/gVvWFFHN 🎩 I share AI/Gen AI content frequently. To continue getting such interesting content/updates : https://lnkd.in/gXHP-9cW

Microsoft's embrace of generative AI is reshaping the technological landscape, offering a plethora of applications that are enhancing the way businesses operate and innovate. Here are some specific applications of generative AI at Microsoft: 1. **Azure OpenAI Service**: With the integration of OpenAI's GPT-4, developers can now create custom AI-powered experiences within their applications.    2. **Azure AI Studio**: This tool allows developers to ground powerful conversational AI models on their own data, enabling natural language-based app interfaces for better data discovery. 3. **Accessibility**: Generative AI is being used to improve accessibility, with tools like Microsoft Copilot and Seeing AI, which assist in a variety of tasks from coding to vision assistance. 4. **Healthcare**: AI-powered chatbots and mental health support systems are being developed to provide assistance and improve patient care. 5. **Content Creation**: Language models are automating content generation, enhancing quality, and enabling personalization in marketing and branding. 6. **Industry-Specific Solutions**: Microsoft Research is focusing on customizing large language models (LLMs), exploring multi-modal generative AI, and developing foundation models for various industries. These applications demonstrate Microsoft's commitment to harnessing the power of generative AI to drive innovation, efficiency, and accessibility across different sectors. As we continue to witness the evolution of AI, it's clear that Microsoft is at the forefront, pushing the boundaries of what's possible with technology. 🚀

The tech field is cluttered with consultants and vendors positioning #genai as the thing that will solve the challenges of marketing. It will not. But it presents an opportunity to transform nearly everything about marketing. Tools with GenAI capabilities can be embedded in use cases that span creative, digital experience, operations, personalization and data and analytics. GenAI can also support marketing priorities, including revenue growth, agility/speed to market, cost optimization, talent development and risk reduction. The path to success is equally a technology and people solution, as GenAI is poised to transform the way we work and society. The question then becomes identifying which use cases you can effectively deploy GenAI for today to support the needs of your business and employees and to drive future transformation. This use-case dimension grid plots top-priority use cases against business value and feasibility axes, inviting strategic conversations with #CEOs, #CMOs and #CIOs and driving investment decisions. Thrilled to share the "Use-Case Prism: Generative AI for Marketing." Gartner clients can read the full research here: https://lnkd.in/gBTCvvfT Special thanks to co-authors Andrew Frank Matthew Wakeman and Dan Gottlieb along with our reviewers, Mattias Velinder, Grant McGalliard and our creative team.  #gartner #gartnermktg #cmo #ai #usecases

🚀 𝐄𝐦𝐛𝐫𝐚𝐜𝐢𝐧𝐠 𝐆𝐞𝐧 𝐀𝐈: 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 🤖 The Indian technology services sector has been at the forefront of innovation, providing critical support to global enterprises for years. From managing business processes to developing cutting-edge applications and driving digital transformation, Indian IT/BPO companies have established themselves as trusted partners for both public and private sector initiatives worldwide. However, in the face of current economic challenges, these companies are turning to Gen AI to stay competitive and relevant. 𝐆𝐞𝐧 𝐀𝐈'𝐬 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐧 𝐓𝐞𝐜𝐡 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 Gen AI, or Generative Artificial Intelligence, is rapidly becoming a strategic imperative for technology services companies. According to a recent survey, over two-thirds of tech CXOs believe that Gen AI will have a significant impact on their businesses, with 86% either having already implemented Gen AI or planning to do so within a year. This technology promises to bring about one of the most significant shifts in enterprise technology in decades, with far-reaching implications for business and society. 𝐄𝐧𝐡𝐚𝐧𝐜𝐢𝐧𝐠 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 One of the key areas where Gen AI is making a difference is in customer experience. By leveraging Gen AI, tech services firms can provide: 📌 Improved self-service experiences through advanced classification and summarization capabilities, multi-language support, and text-to-voice solutions. 📌 Contextualized and hyper-personalized customer interactions by leveraging comprehensive insights into customer behaviors and preferences. 📌Augmentation of human teams with collaborative intelligence, creating an optimal blend of human and machine capabilities. 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Gen AI is redefining application development by reducing development time and costs significantly. Machine learning applications that once took months to develop can now be deployed in a matter of weeks. Gen AI assists in code development, code optimization, modernizing legacy code, generating documentation, and test cases. This accelerates developer velocity, reduces software quality issues, and allows teams to focus on more complex and strategic tasks. 𝐑𝐞𝐯𝐞𝐧𝐮𝐞 𝐔𝐩𝐥𝐢𝐟𝐭: Gen AI presents significant revenue opportunities for tech services companies across high-impact areas: 📌Marketing strategy and content generation 📌Data engineering, data intelligence, and workload modernization 𝐍𝐚𝐯𝐢𝐠𝐚𝐭𝐢𝐧𝐠 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 While Gen AI holds immense promise, it also presents challenges, including concerns about bias, data security, and privacy. Companies need to strike a balance between leveraging AI's capabilities and ensuring human oversight to prevent unethical outcomes. Regulations and trust-building are also critical aspects that tech companies must navigate effectively.

How can Global Business Services deliver real value with Generative AI? With #GenerativeAI, Global Business Services (GBS) has a unique opportunity to outgrow the standard transactional focus and deliver real value to the organization. Generative AI can allow global business services organizations to complete their shift from a collection of transaction-driven workbenches to functions that can add real value. These are the 4 big opportunities Generative AI creates for Global Business Services: Initiate an Internal Transformation, Create a Platform, Drive GenAI Across the Organization, and Reduce Risk While Embedding Innovation. Previous-generation automation has allowed many GBS workers to increase the value they bring to their teams. GBS leaders can use the four GenAI opportunities covered here to deliver that same transformative effect throughout the organization. Learn more about 4 big opportunities Generative AI creates for Global Business Services here: https://on.bcg.com/45HYjvQ   via - Boston Consulting Group (BCG) #artificialintelligence #ai #opportunities #leadership #cloudcomputing #iot #dei #workforce #technology #business #growth #futuretech #service #automation 

With #AI hype hitting a crescendo, how can businesses of all sizes benefit from AI right now? By considering your organization’s pain points and mapping where AI can automate processes, inject creativity, add analysis and planning, or save cost in areas such as #CustomerService, #HR, #ProductDevelopment, #sales, #marketing, and more. The two main types of AI use Natural Language Processing (#NLP) instead of code to take instructions. However, there are differences: - #ConversationalAI is the basis for chatbots and virtual assistants. On a small scale, customers can interact with a chatbot on the 100 most-asked questions about your company. The main challenge? Conversational AI struggles with context and nuance, and requires Human-in-the-Loop (#HITL) training called Reinforcement Learning from Human Feedback, (#RLHF) and safety testing known as #RedTeaming. A definite plus - you can automate end-user sentiment analysis via a thumbs up/down to gain feedback and datasets to fine-tune the AI model behind your chatbot. - #GenerativeAI is now a familiar tool! With it, we create new content ranging from text to tables, images, audio, video, and multi-modal compositions. GenAI uses deep learning techniques and can be leveraged for product discovery, strategy, coding, computation, and workflow automation. It can also perform many types of analysis (data, competitive, sentiment, etc.) The main challenge? GenAI models are built and can be trained on datasets containing bias or inaccurate info. Because of this, genAI models confidently serve up inaccuracies - called #hallucinations - and also spread bias. In the wrong hands, genAI is used by bad actors to spread misinformation and deepfakes. Conversational AI learns from human interactions, while generative AI learns styles, tones, and patterns in order to generate content. Use this simple graphic to consider where AI can streamline your business processes and alleviate pain points today, then plan for future, more complex use cases. Where do you think AI’s greatest future impact will be on your business? Reply in comments- #ai #generativeai #conversationalai #genai #promptengineer #marketing #contentmarketing #aiprompts #chatbot #virtualassistant #nlp #linguistics #rlhf #hitl #aiethics #aiusecases #aiusecase Image credit: Data Science Central

Adopting #GenerativeAI? Take a Strategic Approach to Build Trust and Value. With all the hype around #GenAI, companies are eager to implement but hesitant to go all-in. A measured approach focused on augmenting constrained resources is key. This post provides a strategy for GenAI adoption: start by deploying GenAI to assist bandwidth-limited teams in areas like #CustomerService, #Sales, #HR, #IT, and #Legal. Target use cases where lack of staff causes bottlenecks. By incrementally proving GenAI’s value in supplementing constrained workflows, organizations can build trust and pave the way for extending GenAI more broadly across operations. The key is starting with targeted stepping-stone use cases to showcase tangible productivity gains where they're needed most today. This sets the stage for transformative GenAI adoption across the business. Read on for more on strategically rolling out GenAI in a way that builds confidence and value. What stepping stone use cases could GenAI assist within your organization today? #GenAI #generativeAI #digitaltransformation #futureofwork #emergingtech #leadership #usecases #businessvalue

Technology is a useful servant but a dangerous master. This insight by Nobel laureate, Christian Lous Lange, struck a chord with me when it was shared at the recent Gartner CSO & Sales Leaders Conference by VP Analyst, Doug Bushée. As we navigate the complexities of using GenAI in sales and marketing, how do keep AI properly controlled and governed? Here are a few of the takeaways: 🔍 77% of sales leaders are currently implementing or planning to implement GenAI within the next year, so this is a challenge everyone is dealing with now or will deal with very soon. 🧩 I've seen and used a simple 2-dimensional framework for evaluating AI use cases (value vs ease of implementing), but I like the 3-dimensional use case eval framework from Gartner, since it allows for visualizing business value against both decision complexity and risk. For instance, a high-value use case with low decision complexity and low risk (e.g. AI-driven content for sales pitches or marketing copy) might be managed with general governance. Conversely, use cases involving lower business value with high complexity and risk demand stringent controls and their usage should be blocked. . 🚀 The phased roadmap strategically integrates GenAI into the business over time. In the near-term (Defend), the focus is on enhancing specific tasks like business assistants and marketing copy generation to maintain competitive parity. It progresses to medium-term (Extend) applications in customer support and sales for differentiation. Long-term (Upend) goals aim to transform industry standards with custom AI solutions, creating new products and markets. 📈 60% of Sales leaders plan to hire new GenAI staff. As we delve deeper into AI-driven transformation, it's critical to look at the balance of leveraging AI's capabilities and retaining strategic oversight and proper governance. How are you ensuring that AI remains a tool for enhancement of your sales strategy and boosting sales efficiency, but with the proper guardrails in place? As we implement these advanced tools, having a solid data foundation and collaborating with experts who have deep knowledge of both the data and relevant use cases can be invaluable in navigating this complex landscape, ensuring that our AI solutions are both powerful and prudent 👀 Swipe through the selected slides to see how these concepts played out in the talk. How do you see these strategies impacting your approach to sales or marketing leadership and usage of AI? #GenerativeAI #SalesLeadership #AIinSales #Innovation #StrategicPlanning #TechnologyManagement