Sweden Business Artificial Intelligence Leadership’s Post

Success with AI isn't just about the technology itself, it's the preparation and maintenance you invest in as well. Attentive + communicative leadership, collaboration (across departments AND with partners), and data governance all come together to help organizations not only identify risks but learn how to use AI more thoughtfully! #AI #DigitalTransformation #Technology #Data

It’s alarming that a third of AI projects are launched more to impress stakeholders than to create real value. This wastes resources, damages trust in the technology, and demoralizes teams. The root issue lies in leadership’s limited understanding of AI, leading to misaligned initiatives and unrealistic expectations. To unlock AI’s potential, companies must anchor efforts in clear business goals, promote continuous learning, and ensure ethical implementation—transforming hype into lasting impact. #AI #Leadership #DigitalTransformation #BusinessStrategy #AIethics #Innovation #TechTrends #MachineLearning #ITStrategy #AIAdoption

I recently listened to an insightful podcast featuring #AlisonMcCauley where she talks about Digital Transformation and AI. Her reflections truly struck a chord with me, as they closely mirror my experiences working with #transformatin, #innovation, #data, and #AI at #RamsaySanté. Her key points are: 1. Cultural Shift in Digital Transformation – AI isn’t just another tool; it represents a deep cultural change. 2. Building AI Fluency – It’s vital to foster continuous learning at all levels. 3. Decentralized Innovation – Empowering all teams, not just specialists, to drive AI initiatives. 4. Data Governance and Readiness – Ensuring that data is structured, governed, and ready for AI. 5. Leadership Support – Top-down leadership is essential for decentralizing innovation. 6. Pressure to Innovate – Staying ahead with AI requires aligning it with long-term strategy. 7. Practical AI Implementation – Start with manageable, high-value projects, and scale from there. AI offers enormous opportunities but comes with significant challenges, particularly when it comes to data. I fully agree with her view that companies that fail to prioritize data readiness will simply fall behind. For some companies AI, data governance and data readiness present a classic "Chicken and Egg Dilemma." AI’s success hinges on high-quality, well-structured data. Without AI, it can be difficult to extract true value from data, but without the right data governance, AI cannot realize its full potential. In my experience, many organizations underestimate the need for a coherent data strategy from the outset. Data is foundational to all AI initiatives—organizations that rush into AI without ensuring their data is governed, accessible, and reliable are setting themselves up for failure. It's crucial to build your AI around a solid data infrastructure. We’re still just scratching the surface of what AI can do, and the companies that prioritize these areas will be the ones leading the way. Very insightful! #AI #DigitalTransformation #DataGovernance #Innovation #Leadership #GenAI #AIinHealthcare #Strategy

A fascinating read on CIO reveals a striking disconnect in AI data readiness between the C-suite and IT professionals. While nearly 90% of business leaders are confident in their data ecosystems, a staggering 84% of IT experts are bogged down by daily data issues. This highlights a crucial need for better alignment and collaboration to truly leverage AI's transformative power. Let's bridge this gap and turn AI dreams into reality! 🌟 https://lnkd.in/dQcMgikV #AI #Leadership #ITChallenges #Innovation #ArtificialIntelligence #TEKSystems

Just finished the course “𝐁𝐨𝐚𝐫𝐝 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 𝐢𝐧 𝐭𝐡𝐞 𝐀𝐠𝐞 𝐨𝐟 𝐀𝐈” by Dr. Lisa Palmer! Check it out: https://lnkd.in/g3jDYmm9 #artificialintelligenceforbusiness #boardleadership. ▶️𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐨𝐛𝐣𝐞𝐜𝐭𝐢𝐯𝐞𝐬 📖 ✅𝐀𝐥𝐢𝐠𝐧 AI initiatives with organizational goals to enhance efficiency and drive innovation. ✅𝐂𝐫𝐞𝐚𝐭𝐞 and enforce robust AI governance frameworks. ✅𝐈𝐧𝐯𝐞𝐬𝐭 in the necessary structural and cultural adaptations required for successful AI integration. ✅𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐲 and mitigate potential risks associated with AI deployments, ensuring alignment with organizational ethics and values. ✅𝐃𝐞𝐯𝐞𝐥𝐨𝐩 strategic foresight for AI investment, focusing on effective resource allocation and long-term sustainability. ✅𝐀𝐩𝐩𝐥𝐲 best practices for data management to ensure the accuracy, reliability, and applicability of AI technologies in driving business value. ▶️𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 🎯 👉𝐄𝐭𝐡𝐢𝐜𝐚𝐥 𝐀𝐈 𝐢𝐬 𝐞𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥: Prioritize responsible AI with strong governance and ethical frameworks. 👉𝐀𝐈 𝐝𝐫𝐢𝐯𝐞𝐬 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧: Adopt AI strategically to reshape organizational culture and processes. 👉𝐃𝐚𝐭𝐚 𝐟𝐮𝐞𝐥𝐬 𝐀𝐈 𝐬𝐮𝐜𝐜𝐞𝐬𝐬: Invest in robust data management for accurate and reliable AI. 💡 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐓𝐢𝐩 🤖 🌟 The exercise files contain a wealth of resources and references that can enhance your learning experience. , ___________________________________________ 𝑯𝒐𝒘 𝒄𝒂𝒏 𝒘𝒆 𝒆𝒏𝒔𝒖𝒓𝒆 𝒕𝒉𝒂𝒕 𝑨𝑰 𝒆𝒎𝒑𝒐𝒘𝒆𝒓𝒔 𝒉𝒖𝒎𝒂𝒏𝒊𝒕𝒚, 𝒓𝒂𝒕𝒉𝒆𝒓 𝒕𝒉𝒂𝒏 𝒓𝒆𝒑𝒍𝒂𝒄𝒊𝒏𝒈 𝒊𝒕? Kindly share your views in the comment below 👇 👉 Follow me Biswajeet Sahu & 📢 𝑺𝒖𝒃𝒔𝒄𝒓𝒊𝒃𝒆 𝐭𝐨 "𝐈𝐓 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 & 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬" 👉 https://lnkd.in/g3mMBuUf 𝘵𝘰 insights into and#IT #ProductExcellence & #QualityEngineering with trends, strategies, and best practice 📢 𝑺𝒖𝒃𝒔𝒄𝒓𝒊𝒃𝒆 to "𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐈𝐓 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬" 👉 https://lnkd.in/gEsYXMr4 to stay up to date on the latest #HealthcareIT Advancements. #AI, #ArtificialIntelligence, #MachineLearning, #DigitalTransformation, #Innovation, #Technology, #BusinessStrategy, #Leadership, #FutureofWork, #AIleadership, #AIGovernance, #EthicalAI, #ResponsibleAI, #DataManagement, #OrganizationalChange, #AIethics, #AIstrategy, #Management, #ExecutiveDevelopment, #BusinessIntelligence, #DataScience, #TechTrends LinkedIn Linkedin News LinkedIn News LinkedIn News India LinkedIn for Learning

🌟 𝗨𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝗔𝗜'𝘀 𝗙𝘂𝘁𝘂𝗿𝗲: 𝗧𝗿𝗲𝗻𝗱𝘀 𝗙𝗼𝗿 𝟮𝟬𝟮𝟱⁣ ⁣ In the ever-evolving realm of 𝗮𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲, the year 2024 served as a pivotal turning point. Reflecting on the transformative strides, the MIT Sloan Management Review enlightens us with five trends shaping the future of AI and data science.⁣ ⁣ 🔹 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜: Empowering systems to function independently, sparking both curiosity and skepticism.⁣ 🔹 Generative AI: Revolutionizing 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗰𝗿𝗲𝗮𝘁𝗶𝗼𝗻 with groundbreaking technological shifts.⁣ 🔹 Unstructured Data: Embracing insights from texts, images, and videos for a competitive edge.⁣ 🔹 AI Ethics and Governance: Prioritizing ethical frameworks as systems become self-governing.⁣ 🔹 AI and Data Leadership: Cultivating data-driven cultures for aligned 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗴𝗼𝗮𝗹𝘀.⁣ ⁣ Leaders, are you ready to embrace these waves of change? 🌊 Dive deeper into these trends and envision the AI revolution: https://lnkd.in/eWhC8B6Z ⁣ What trend excites you the most and how do you foresee its impact? 🤔⁣ ⁣ #DigitalRobots #WorkSmarter #AIRevolution #FutureTech

AI is reshaping the CIO role, pushing leaders to balance fast innovation with ethical oversight. As adoption grows, CIOs must ensure AI decisions are transparent, unbiased, and compliant. Success in 2025 depends on responsible AI strategies, collaboration, and staying ahead of regulations. When focusing on governance and accountability, CIOs can guide their organizations to a future where AI drives innovation with trust. #CIO #AI #leadership

Is Data Leadership evolving to be synonymous with AI leadership? Not so fast... We asked five veterans to weigh in... 🎯 Business Understanding: Patrick van den Berg ✔️ highlights the importance of identifying valuable use cases by staying close to the organization and understanding where AI can truly make a difference. 📊 Dual Focus: Dennis van Bregt emphasizes that while data can exist without AI, AI can't exist without data. Data leaders must understand both domains - maintaining strong data foundations while developing AI knowledge. 🌟 Momentum matters: Jocelyn Darbroudi emphasizes that AI has created unprecedented momentum after years of advocating for data's importance, but with this opportunity comes responsibility. Ivan Branco views this not as a revolution but as an evolution. 🛡️ Quality First: Aisan Baird emphasizes data leaders' responsibility in ensuring data integrity and reducing bias. Without reliable data foundations, AI applications will fail. What do you think about data leadership in the AI age? ⬇️ PS: Interested in joining conversations like these with fellow data leaders? Drop a comment to learn more about our community! ⬇️ #DataLeadership #AI #DataStrategy #AITransformation #DataQuality #AI #DataManagement #TheDataCommunity

So, this is where I'm working now and these are the 2 top chaps who founded SimSage. Little bit of background in https://lnkd.in/efv9wRPa As someone correctly pointed out to me recently, "search means different things to different people" so I'm genuinely having fun talking to lots of firms about the various applications of SimSage to solve a range of search related issues! #search #innovation #ai #dsars #enterprisesearch

A common stumbling block for companies that can result in failed AI implementations is not rooted in the technology itself but rather organizational structure and corporate culture that impede progress. To successfully deploy AI, executives must foster a culture that enables seamless collaboration. Hence, a framework is required to help executives prepare their organization for implementing AI at scale. This framework should include embracing a data-driven decision-making culture, clearly defining roles and responsibilities of the stakeholders, building AI awareness across the organization and ensuring a solid integration and change management process. #Artificialintelligence #Data #Implementation #Bigdata #Dataculture #Innovation #Technoloty #Strategic