By 2026, 75% of newly developed enterprise applications will incorporate AI or ML based models, up from less than 5% in 2023. Compelling opening by Mark Beyer and Rita Sallam at the Gartner Data & Analytics Summit 2024. The key insights: 1️⃣ Governance as a value driver: "Prioritise execution to accelerate your strategy. Build focus on the fundamentals of D&A governance and extend them to AI.” This insight emphasises the critical role of governance in realising the full potential of data analytics and AI. Successful leaders focus more on execution and delivering value than endless strategising. 2️⃣ Removing the communication barriers: "We have reached a point at which it is time to dissolve several communications barriers all at once.” This is about the the need for better storytelling that is less focused on ROI and focused on winning hearts and minds. 3️⃣ Collective intelligence: "When we share data, big things happen. What new value will you create?" Harnessing collective intelligence can lead to significant advancements and career-defining opportunities for leaders in the field. 4️⃣ AI literacy: "Allow everyone to lead with purpose from the core to the edge". Expanding the understanding of AI across organisations is vital for effective utilisation of AI technologies. “The rapid evolution of AI has presented leaders with the opportunity to rethink and evolve their data and analytics operating models, we learned today that 75% of respondents in Gartner's CIO survey already doing so to spur innovation” - Lisa Bouari 5️⃣ Look beyond the sugar hit of AI: "Look beyond ROI more toward long-term business outcomes. When you establish your enterprise's AI ambition... that's where success comes from". Focusing on the long-term impact of AI and data analytics strategies is crucial for sustainable success. My takeaway: Prioritising execution and collaboration are critical in shaping a future where AI and data analytics drive value and innovation long term. Lisa Bouari John Hoffman Tim Madin Lukas Bower Ean Evans Thanks for having us Gartner James Mackay Sreenath B.
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According to Gartner, 80% of data and analytics innovations will use graph technologies by 2025. From marketing to healthcare, Knowledge Graphs are revolutionizing data analytics for every department. Read our latest blog to explore business use cases for knowledge graphs across a variety of industries. and see how your business can benefit from this cutting-edge technology: https://lnkd.in/g2CHR9UZ #KnowledgeGraphs #AI #data
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Companies should prepare for the future of work now by honing their data skills and strengthening their data analytics and machine learning/AI operations. 💡 Learn how increased utilization of an AI and data analytics strategy leads to innovation and better decision-making.
Data and the Future of Work: How Analytics and AI Are Transforming Organisations
teamhiedberg.medium.com
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Global AI Leader | Data | AI | CVM | Strategy | Marketing | Consulting | Analytics | Digital | AICoE | AIaaS | GenAI | Transformation | 40 under 40 Data Scientist | Top 100 AI Leader | Board Member | Speaker | LBS MBA
Excited to share my latest article "Insights to Action: How Data and AI are Powering Business Decisions" published on CXO Insight Middle East In this piece, I explore how #AI and #data analytics are revolutionizing decision-making processes across industries. Drawing from our recent AI & Smart Data Conference in Dubai, I discuss key findings on: - The critical importance of data harmonization - AI's impact on supply chain #optimization - The potential of #generativeAI in enhancing customer experiences - Challenges and opportunities in implementing AI-driven strategies I am happy to announce that the full AI & Smart Data Report is now available! This comprehensive report dives deeper into how businesses are leveraging these technologies to stay competitive in the #digital age. I invite you to explore the report and gain valuable insights that could transform your business strategy. As Head of Data and AI Practice at e& enterprise I am passionate about helping organizations unlock the full potential of AI and data. If you are interested in how these technologies can drive growth and innovation for your business, let's connect! #AI #DataAnalytics #GenAI #LLMs #DigitalTransformation #BusinessGrowth #Innovation #eAndenterprise https://lnkd.in/d9fEVjSB Check out the full report here 👉https://lnkd.in/d3NnJAZC
Insights to action: How data and AI are powering business decisions
cxoinsightme.com
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AI First Technology Leader and Startup/Platform Launch Expert Driving Business & Digital Revenue Growth through Cutting-Edge Solutions
Gartner's latest report, "Over 100 Data, Analytics, and AI Predictions Through 2030," highlights the profound impact of data, analytics, and AI on industries worldwide. The predictions underscore the accelerated pace of AI adoption, the crucial role of data management, and the ongoing transformation of business landscapes. For leaders in data and analytics, these insights are essential for shaping strategic initiatives and driving future innovation. Five Key Takeaways: AI and Data are Driving Business Transformation: By 2027, data and AI will be critical to business strategies across sectors, with over 60% of CDAOs needing to deliver data literacy and AI culture changes to stay relevant. Generative AI is Reshaping Industries: By 2028, 70% of AI-generated SaaS applications will become composites for enhanced digital engineering, emphasizing the rapid evolution of AI technology in business applications. Governance and Ethical AI: By 2027, 60% of organizations will fail to realize the value of their AI use cases due to weak governance frameworks, highlighting the need for cohesive ethical AI governance. AI’s Role in Decision Intelligence: By 2025, 60% of analytics and business intelligence platforms will integrate decision intelligence capabilities, revolutionizing how businesses make data-driven decisions. The Rise of GenAI in Business Operations: By 2028, GenAI will be embedded in 80% of workplace applications, driving substantial improvements in productivity and operational efficiency. These predictions provide a roadmap for leaders to harness AI and data to drive competitive advantage and operational excellence. Note : Link to full report available at comments section
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Is your data AI-ready? The next 24 months will define your competitive edge. Discover how data readiness, skill investment, and strong governance can unlock AI’s full potential for your organization. #ArtificialIntelligence #DataStrategy #AILeadership #DigitalTransformation #AIReady
Strategic Commercial Leader | Driving Scalable Growth with Digital Innovation, AI & Sustainability
Is Your Data AI-Ready? The Next 24 Months Will Define Your Competitive Edge Yesterday, I attended “Leadership in AI: From Vision to Results,” an event hosted by 2021.AI and Dansk IT on AI’s transformative power in business. Here are my top takeaways for C-level executives and Board Members: The next 24 months should be about data—getting it AI-ready will be mission-critical if you want to compete. Top 10 Key Takeaways for Leadership 1. Data Is Foundational: Effective AI begins with quality data. AI-ready data is essential to enable accurate outputs and insights. 2. Invest in Skills: The right technical AI skills are scarce, so your AI-ready workforce should focus on data science and programming skills. Investing in these skills and upskilling in AI literacy will be foundational to keeping your organization ahead. 3. Leverage AI Tools: Empower employees with AI tools like ChatGPT to enhance productivity. Developing in-house applications improves data access and security while controlling sensitive data. 4. Set Realistic Expectations: AI initiatives can easily overpromise, so manage expectations carefully. Align initiatives with achievable goals based on data readiness to avoid disappointments. 5. Evaluate ROI: AI’s ROI is still emerging. Tracking productivity gains in AI initiatives shows promising results, but taking the long view to understand the long-term impact on the bottom line will be essential. 6. Optimize Operations with Data-Driven AI: Use AI to streamline processes like transactions; even a 5% improvement can yield substantial savings. 7. Action Over Hype: With data readiness, move from talk to action. Start pilot projects with clear objectives and measurable outcomes. Implementing practical applications provides a competitive edge. Having a framework and process for overseeing your AI use cases is vital. 8. Customize AI Solutions for Data Needs: Select and tailor AI models to fit each use case, balancing large and small models that best meet your needs. 9. Reinvent Business Models with AI: AI insights will disrupt business models. Adapt your business proactively to uncover new opportunities and stay competitive. 10. Strengthen Governance with Data and AI Solutions at the Core: Establish frameworks to ensure data and AI solution integrity, transparency, and accountability, managing risks like AI solution failure and misinformation. Don't forget to monitor third-party AI applications as part of risk management, especially those originating from outside the EU. Conclusion In the next 24 months, data readiness will determine which organizations lead with AI. Prioritizing data, skills, and governance will position your organization to unlock AI’s potential and gain a competitive advantage. Is your data AI-ready? Feel free to reach out to discuss applying these insights to your AI strategy. #ArtificialIntelligence #DataStrategy #AILeadership #DigitalTransformation #AIReady
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Unlock the power of AI-enhanced Business Intelligence and Data Analytics to drive your business growth! 🌟 John Burke discusses how UBIX.AI combines Artificial Intelligence (AI) with Business Intelligence (BI) and Data Analytics creates a powerful synergy, providing deeper, more actionable insights. Key Highlights: 🔍 AI-Powered Insights: Automates data analysis for deeper insights. 💪 Overcoming Challenges: Addresses fragmented data sources and slow decision-making. ⏩ Accelerated Decision-Making: Unifies data sources and generates real-time insights. At UBIX.AI, we offer advanced cloud AI solutions that seamlessly integrate with your existing BI and Data Analytics tools. Our platform processes and analyzes data from various sources, delivering clear, actionable insights. This empowers business leaders to make informed decisions faster and allows data science teams to focus on strategic initiatives. Learn more about how UBIX.AI can help your business turn data overload into data-driven decision making, driving growth and competitive advantage. 🧠 www.ubixlabs.com #ai #bi #analytics #nocode
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In an unsurprising turn of events, the impact of generative AI is now encouraging 61% of organisations to revisit their data and analytics strategies, according to Gartner research. At Databricks, we recognised this connection early on (being the only leader in the two Gartner quadrants - data management and AI/ML platform). See, while it’s great to see that so many businesses are placing a renewed focus on how to best leverage their data for AI, this research is a clear reminder to get your data and analytics strategy right first. If your data isn’t in shape, then your AI model won’t deliver as much value. One way that organisations can develop their data strategy is through cultivating data intelligence, which is essentially using tools and methods to help an organisation and its employees better understand data. Ensuring an entire workforce has the ability to leverage and analyse data will have a huge impact on how the entire organisation operates. https://lnkd.in/eDXSEhqz #Data #Analytics #DataIntelligence #GenerativeAI #Gartner
Gartner Survey Finds 61% of Organizations Are Evolving Their D&A Operating Model Because of AI Technologies
gartner.com
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When leaders aim to become a data-driven organization, empowering business people to utilize data, predictive models, generative AI capabilities, and data visualizations becomes crucial for enhancing decision-making. The objective includes achieving smarter decisions for positive business outcomes, responding swiftly to opportunities, minimizing risks by making safer decisions, and fostering change management practices to increase the utilization of analytics tools among employees. Additionally, leaders are in search of scalable solutions integrating the latest machine learning models, AI capabilities, and new data assets while ensuring data compliance, protection, and security. Connect with QMM Technologies Private Limited for Data Analytics solutions. Read more about improving analytics for data-driven organizations: #DataAnalytics #DecisionMaking #AI #DataDrivenOrganization
7 steps to improve analytics for data-driven organizations
infoworld.com
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🚀 Unlocking Success: The Crucial Role of Data-Driven Decision Making in IT Strategy 🚀 [1] As the Director of Innovation, I am constantly exploring new ways for businesses to stay ahead of the competition. In today's fast-paced business landscape, intuition and experience are no longer enough. We need to leverage the power of data to make informed decisions and optimize our IT strategy. 📊💡 According to a recent research briefing released by the MIT Center for Information Systems Research (CISR), there are three principles that leaders should consider when making artificial intelligence (AI) investments. These principles are supported by data monetization research and can guide us in harnessing the full potential of AI. Let's dive into them! 📚 1️⃣ Principle 1: Embrace Data-Driven Decision Making Organizations today heavily rely on big data to drive decision-making and strategize for the future. [3] With an ever-expanding array of data sources, both internal and external, it's crucial to adapt and leverage this data effectively. By embracing data-driven decision making, we can uncover valuable insights and gain a competitive edge. 💪🔍 2️⃣ Principle 2: Develop a Clear Strategy Having a clear strategy is essential when it comes to turning data and analytics into profit. It's not enough to collect and analyze data; we need to have a well-defined plan in place. This includes defining our goals, identifying the right tools and technologies, and aligning our data strategy with our overall business objectives. With a clear strategy, we can effectively leverage AI to drive innovation and growth. 📈✨ 3️⃣ Principle 3: Invest in Organizational Design and Talent Management Data and analytics are emerging as core pillars of a successful modern business. However, it's not just about the technology; it's also about the people. Investing in organizational design and talent management is crucial to ensure that we have the right skills and expertise in place to make the most of our data. By fostering a data-driven culture and empowering our teams, we can unlock the full potential of AI and drive business profits. 💼🌟 In conclusion, data-driven decision making and AI investments go hand in hand. By embracing these three principles, we can leverage the power of data to make informed decisions, optimize our IT strategy, and drive business success. Let's unlock the full potential of AI and shape the future of our organizations! 💥 #DataDriven #AIInvestments #BusinessSuccess #Innovation #MITCISR #UnlockingPotential References: [1] Unlocking Success: The Crucial Role of Data-Driven Decision Making in IT Strategy: https://lnkd.in/dnh2jgQX [2] Leveraging big data for strategic business decisions: https://lnkd.in/dRjs6jNw [3] Forget money on trees: Data and analytics drive business profits: https://lnkd.in/dh_m8_Gj
Three principles leaders need to consider when making AI investments | MIT Sloan
mitsloan.mit.edu
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The article outlines four strategies for Chief Data Officers (CDOs) to lead artificial intelligence initiatives effectively: 1. Adopt an agile mindset to quickly adapt to changes in business and technology. 2. Ensure a structure that supports execution, not just strategy formulation. 3. Focus on holistic, scalable data frameworks that support enterprise-wide AI. 4. Prioritize change management to foster a data-driven culture across the organization. These practices help CDOs maximize AI's business impact while advancing data-driven decision-making. For more details, visit https://lnkd.in/ejxJWyrP
4 ways for data officers to take the helm on AI initiatives | MIT Sloan
mitsloan.mit.edu
Katherine Boiciuc we need to get you a closer seat next year based on the image. Thanks for the comments—much appreciated.