🔍Our customers increasingly put AI at the centre of their #digitalisation efforts. But in our experience, 75% of these AI initiatives struggle for one reason: They fail to properly integrate AI applications into their business value chains at the right point in time. Many companies explore AI applications within single departments as an extension of their existing capabilities. If left to grow without high quality integration into the existing structures, these disparate AI activities lead to a fractured business. It consists of disorganised AI islands, each using different tools and solutions. That often brings several problems: ❎ unnecessary costs ❎ challenges on regulatory requirements ❎ inefficient collaboration ❎ delays in time-to market for new AI applications. 💼 Having recognised that issue, we attempt to widen the focus from merely meeting business needs. Instead, we aim for high quality integration from the beginning. That means also considering regulatory obligations, architectural requirements and organisational oversight to properly incorporate AI platforms into the given corporate architecture. That brings numerous advantages: ✅ Reduce IT-complexity and cost ✅ Speed up time-to-market ✅ Integrate new trends like GenAI ✅ Improve user experience within the business departments 💡The dynamic development of AI makes such a flexible enterprise architecture crucial to embed AI Platforms. We unite experience in tech developments, collaboration between IT and data science and in comprehensive reviews of AI Platforms. Thereby, we bring together #DataScience and modern #EnterpriseArchitecture to create Digital-AI-Fitness. ❓ What is your experience with sustainable AI Solutions?
DEVnet’s Post
More Relevant Posts
-
I'm excited to share DEVnet's latest insights on the importance of integrating AI into business value chains. Our team has observed that while many companies focus on AI, about 75% struggle due to poor integration. This leads to fragmented AI efforts, higher costs, regulatory challenges, and inefficiencies. At DEVnet, we prioritize high-quality integration from the start, considering all necessary aspects like regulatory requirements and organizational oversight. This approach not only reduces IT complexity and costs but also accelerates time-to-market and enhances user experience. Proud to be part of a team that combines Data Science with modern Enterprise Architecture to achieve true Digital-AI-Fitness. What are your thoughts on sustainable AI solutions? #DataScience #EnterpriseArchitecture #AIIntegration #DigitalTransformation
🔍Our customers increasingly put AI at the centre of their #digitalisation efforts. But in our experience, 75% of these AI initiatives struggle for one reason: They fail to properly integrate AI applications into their business value chains at the right point in time. Many companies explore AI applications within single departments as an extension of their existing capabilities. If left to grow without high quality integration into the existing structures, these disparate AI activities lead to a fractured business. It consists of disorganised AI islands, each using different tools and solutions. That often brings several problems: ❎ unnecessary costs ❎ challenges on regulatory requirements ❎ inefficient collaboration ❎ delays in time-to market for new AI applications. 💼 Having recognised that issue, we attempt to widen the focus from merely meeting business needs. Instead, we aim for high quality integration from the beginning. That means also considering regulatory obligations, architectural requirements and organisational oversight to properly incorporate AI platforms into the given corporate architecture. That brings numerous advantages: ✅ Reduce IT-complexity and cost ✅ Speed up time-to-market ✅ Integrate new trends like GenAI ✅ Improve user experience within the business departments 💡The dynamic development of AI makes such a flexible enterprise architecture crucial to embed AI Platforms. We unite experience in tech developments, collaboration between IT and data science and in comprehensive reviews of AI Platforms. Thereby, we bring together #DataScience and modern #EnterpriseArchitecture to create Digital-AI-Fitness. ❓ What is your experience with sustainable AI Solutions?
-
-
🌐As businesses increasingly adopt AI into their operations, it's essential to integrate AI as a fundamental element within your enterprise framework. Here are some vital steps to manage AI in your organization👇 🔷 Map AI to your Capability Framework: Ensure AI is included in your capability map or process framework, tailored to your specific organizational structure. 🔶 Integrate AI into your Application & Technology Architecture: Identify where AI is running, which services are utilizing it, and which applications depend on it. 🔷 Establish monitoring & KPIs: Set clear targets and KPIs for your AI initiatives, and track them through a dashboard or similar tool. ...and more! AI is more than just a tool—it's a transformative capability that requires thoughtful integration and management across your enterprise. Hear more insights from David, as well as real-world AI implementation examples from industry giant Nestle👉 https://okt.to/qMWxE9 #GenAI #AIManagement #DigitalTransformation #EnterpriseArchitecture
-
Helping organizations dramatically to increase the success rate of enterprise transformation, strategic investment allocation and risk management - Enterprise Architecture and BPM
🌐As businesses increasingly adopt AI into their operations, it's essential to integrate AI as a fundamental element within your enterprise framework. Here are some vital steps to manage AI in your organization👇 🔷 Map AI to your Capability Framework: Ensure AI is included in your capability map or process framework, tailored to your specific organizational structure. 🔶 Integrate AI into your Application & Technology Architecture: Identify where AI is running, which services are utilizing it, and which applications depend on it. 🔷 Establish monitoring & KPIs: Set clear targets and KPIs for your AI initiatives, and track them through a dashboard or similar tool. ...and more! AI is more than just a tool—it's a transformative capability that requires thoughtful integration and management across your enterprise. Hear more insights from David, as well as real-world AI implementation examples from industry giant Nestle👉 https://okt.to/uUTzvX #GenAI #AIManagement #DigitalTransformation #EnterpriseArchitecture
-
Customer Success Manager @ Bizzdesign | B2B SaaS Enthusiast | Driving Value & Strategic Relationships
🌐As businesses increasingly adopt AI into their operations, it's essential to integrate AI as a fundamental element within your enterprise framework. Here are some vital steps to manage AI in your organization👇 🔷 Map AI to your Capability Framework: Ensure AI is included in your capability map or process framework, tailored to your specific organizational structure. 🔶 Integrate AI into your Application & Technology Architecture: Identify where AI is running, which services are utilizing it, and which applications depend on it. 🔷 Establish monitoring & KPIs: Set clear targets and KPIs for your AI initiatives, and track them through a dashboard or similar tool. ...and more! AI is more than just a tool—it's a transformative capability that requires thoughtful integration and management across your enterprise. Hear more insights from David, as well as real-world AI implementation examples from industry giant Nestle👉 https://okt.to/0sRK34 #GenAI #AIManagement #DigitalTransformation #EnterpriseArchitecture
-
From Concept to Reality: The Path to Successful AI Implementation in Enterprises In the AI revolution, we empower businesses to transform AI visions into tangible value. Successful AI implementation requires cutting-edge technology, deep business acumen, and a systematic approach. Our core strategies: Customized AI Architecture: Designing flexible, scalable AI systems tailored to enterprise needs. Data Value Extraction: Utilizing advanced algorithms to derive actionable insights from enterprise data. Seamless Integration Framework: Ensuring AI systems work in harmony with existing IT infrastructure. Continuous Learning Mechanism: Establishing feedback loops for ongoing AI system optimization. Real-world results: Deployed predictive maintenance system for a manufacturer, reducing downtime by 40%. Implemented personalized recommendations for a retail giant, boosting conversion rates by 29%. We're not just technology providers, but strategic partners in enterprise AI transformation, turning AI concepts into real business growth drivers. #AI #ArtificialIntelligence #Management #Technology
-
-
Data Strategist | Co-owner at Joyful Craftsmen | Advisor for corporate data leaders | Keynote speaker | Microsoft Data & AI Solutions partner
Enhancing Business Agility Through Effective #DataManagement and #AI Embrace external AI capabilities combined with self-generated #data to quickly enhance business operations. AI has the potential to boost productivity, efficiency, and agility significantly. To keep pace with rapid AI advancements, adopting a composable architecture is key. This approach enables seamless integration of new technologies while maintaining legacy systems, avoiding continuous regression tests, and easing legacy systems migration. Successful implementation also requires process rethinking, data-centric governance, and cross-functional collaboration. Access to trustworthy data and standardized #DataGovernance is vital for faster insights and #automation. Transform into a #DataDriven organization by becoming faster, leaner, and better together. How do you plan to accelerate your AI and data integration? Share your thoughts! #DataManagement #AI #Innovation #BusinessTransformation #Efficiency
-
-
Program Manager @ xLM | Transforming Life Sciences with AI & ML | Pioneer in GxP Continuous Validation |
Unveiling the Future: The Emergence of AI Agent Architecture Frameworks In the ever-evolving realm of artificial intelligence, a new paradigm is taking shape, poised to revolutionize our interactions with technology. Cobus Greyling's recent article delves into an #AI agent architecture framework that shows great promise in reshaping multiple industries. This framework is designed to offer a systematic method for constructing intelligent agents capable of independent operation while effectively collaborating with humans. It goes beyond merely creating smarter machines; it aims to enhance the synergy between human capabilities and #AI. Key Highlights 💡 👉 Modular Design: The architecture prioritizes modularity, allowing seamless integration of various AI components. This emphasis on adaptability is crucial as it empowers developers to tailor solutions according to specific requirements. 👉Interoperability: Notably, this framework spotlighted interoperability as a key feature. By facilitating smooth communication among different #AI systems, we can leverage diverse technologies' strengths for more resilient solutions. 👉Real-World Applications: The article explores practical use cases spanning industries like healthcare, finance, and logistics. From predictive analytics in healthcare to automated trading systems in finance, the potential implications are extensive and transformative. 👉Ethical Considerations: With the progression towards greater autonomy in systems, ethical considerations take center stage. The framework advocates for embedding ethical guidelines into AI design processes to promote responsible innovation. As technology and business professionals, staying abreast of these advancements is vital. Embracing this emerging architecture could pave the way for revolutionary progress in leveraging #AI for societal welfare. Source:- medium.com
-
-
Unveiling the Complexity Behind #generativeai Ecosystems Generative AI may present a seamless interface to users, but behind the scenes, the architecture is far from simple. Let's demystify what powers these innovative systems: 🔵 User Interface: Engage with AI via intuitive platforms, from chatbots to web and mobile applications, where the magic of interaction happens. 🟢 Coordination Layer: The unsung hero that aligns various services to process user inquiries with precision and speed. 🔴 Data Management: At the heart of responsiveness lies a sophisticated system of databases and caches, essential for swift data retrieval. 🔷 Connectivity & Expansion: APIs bridge the gap to proprietary and open-source AI models, enabling the seamless integration of AI into diverse applications. 🛠️ Development Tools: Crafting the AI experience requires a robust toolkit for prompt creation, model embedding, validation, and plugins that bolster app functionality. 🌐 Technical Backbone: The foundation of any AI system rests on robust hardware and cloud solutions, providing the computational might for model operation. Beneath the user-friendly exterior, a complex network of technologies and infrastructure works tirelessly. Each element plays a pivotal role in delivering the effortless experiences we've come to expect. This nuanced orchestration ensures that generative AI continues to revolutionize how we interact with technology. Credits: Rocky Bhatia
-
-
Building AI agents in-house may seem appealing, but experts warn that most organizations lack the expertise to do it successfully. ⚠️ High failure rate: Forrester predicts that 75% of organizations attempting to build AI agents on their own will fail due to the complexity and required expertise. 🤖 DIY vs. partner approach: Companies like Goldcast and Slate Technologies see success using open-source models, but partnering with external AI firms is often more efficient and reliable. 🧑💻 Specialized skills required: AI agent creation involves advanced architectures, multiple models, and MLOps strategies that most teams are not equipped to handle independently. 🔄 Continuous improvement needed: AI agents need regular human oversight, updates, and optimization to function effectively over time. 💡 Expert insights: Many organizations find success by leveraging pre-built AI solutions, which can reduce complexity and provide ongoing support. #AI #Automation #BusinessStrategy 💼 Companies must weigh the costs of DIY AI development against pre-built, vendor-supported solutions. 🏗️ Developing in-house requires specialized skills in machine learning, data management, and AI architecture. 💬 AI agents should always be deployed with human oversight to ensure continuous improvement and relevancy. https://lnkd.in/gktATNTm
-
Embracing AI in Solutions Architecture: A Key to Future Success ☑️ The integration of AI into solutions architecture offers unparalleled opportunities for efficiency, customization, and scalability. ☑️ It enables us to design systems that not only meet the current needs of businesses but also anticipate future challenges, ensuring long-term success. ☑️ The ability to analyze vast amounts of data in real-time, predict trends, and automate decision-making processes fundamentally changes how we approach design and implementation. ☑️ This shift also demands a new set of skills from solutions architects. Proficiency in AI technologies, understanding data science principles, and the ability to collaborate closely with AI teams are becoming indispensable. It's not just about knowing the algorithms but how to apply them within the architectural frameworks effectively. ☑️ It's clear that AI will continue to be a major driver of change across all sectors. For those of us in solutions architecture and technology entrepreneurship, it's an exciting time full of potential. Staying ahead means embracing these changes, investing in learning new skills, and always looking for innovative ways to incorporate AI into our work. 👉 Let's open up the discussion: How are you integrating AI into your projects? What challenges have you faced, and what successes can you share? Join me in exploring how we can harness the power of AI to build smarter solutions for tomorrow. —------------ PS - Stay tuned for more game-changing insights on AI, Business, and Productivity. PPS - Follow me, Tony Greco, as we navigate this together! ----------------------- #artificialntelligence #technology #innovation #ai
-
