Maria Mingallon’s Post

The honeymoon phase of generative AI is over—CIOs must now focus on scaling the technology to create real business value. • 🎯 Eliminating nonperforming pilots and scaling up successful ones is crucial for achieving impact. • 🛠️ Integration of components, not just the components themselves, is key to scaling gen AI effectively. • 💸 Managing costs, especially ongoing operational expenses, is essential to avoid budget overruns. • 🌐 Streamlining tools and infrastructures helps in scaling efficiently without adding unnecessary complexity. • 👥 Building cross-functional teams that embed gen AI into business operations ensures value beyond just technology. • 📊 Prioritizing clean, well-organized data is vital for the success of gen AI applications. • ♻️ Reusing code and assets can accelerate development and ensure scalable solutions. #GenerativeAI #CIO #DigitalTransformation • 🎯 Focusing on impactful use cases helps in avoiding resource spread across too many initiatives. • 🔗 Effective orchestration of different technologies and systems is necessary to manage the complexity of gen AI solutions. • 💡 Continuous cost optimization ensures that gen AI initiatives remain financially sustainable. • 📐 Adopting widely used standards and tools increases flexibility and future-proofing. • 🧩 Reusability in AI development can significantly reduce time and resources needed for future projects. https://lnkd.in/gDj2aHK4

🆕 Blog drop alert! Day 1: Is your company ready for AI | The Human Side of AI Adoption? We enjoyed our time last week at the GDS Digital Innovation Summit! The summit's theme was “Digital Frontiers: Where Trust, Humanity, and Innovation Converge,” and attendees expressed the desire for a balanced, thoughtful approach to AI adoption in many conversations. Bryan Dunn, VP of Product, shares the 5 key questions tech leaders are asking about Generative AI (Gen AI). While Gen AI offers exciting possibilities for efficiency and innovation, challenges exist. The biggest challenges aren't technical but human-centered issues around trust, education, and responsible implementation. https://lnkd.in/g_-8PZfR #AI #technologyinnovation #softwaredevelopment

If you're curious about how Sand Technologies is helping companies and governments capture the value of data and AI, please read this and let me know your thoughts.

Embracing AI doesn't mean losing our human touch it can help us unleash more of it. Our latest white paper explores how we can harness AI while leveraging human creativity. Join us in shaping a collaborative future. https://dub.sh/2z3ZGpZ

🚀 From AI Honeymoon to Lasting Success: Insights for Scaling AI Effectively 🚀 At Soko, we're passionate about the transformative power of AI. We recently delved into McKinsey's article discussing the transition from AI pilot programs to scalable solutions and discovered invaluable insights for CIOs and tech leaders. Here’s what stands out: 🔸 Focus on Core Applications: Zero in on fewer, impactful applications rather than spreading efforts too thinly. 🔸Strategic Scaling: Scale solutions that have proven value and impact. 🔸Enhance Data Management: Prioritize robust data management to fuel AI effectiveness. 🔸Talent Investment: Invest in hiring and training for AI-specific roles and skills. 🔸Governance and Ethics: Establish strong governance frameworks to manage risks associated with AI. 🔸Stakeholder Engagement: Keep communication open with stakeholders to align AI goals with business objectives. 🔸Innovation and Adaptation: Stay adaptive and open to evolving AI technologies and market changes. We understand the challenges and opportunities of integrating AI into business at scale. Reach out to us to learn more! Article: https://lnkd.in/dSEY6CdC #AI #DigitalTransformation #TechLeadership #Innovation #CIO

🚀 Exciting news! 🚀 As the Director of Innovation, I'm always on the lookout for the latest insights and trends in the world of artificial intelligence (AI). Today, I came across an incredible article that I just had to share with all of you. It's titled "How to Think About AI: 4 Things Artificial Intelligence Experts Want You To Know" by Jordan Thayer, PhD. Trust me, this is a must-read for anyone interested in AI! So, what are the key takeaways from this article? Let me break it down for you: 1️⃣ AI is a spectrum: From thermostats to systems that mimic human thinking, AI comes in various forms. By understanding this spectrum, we can identify simple yet profitable opportunities for AI implementation. It's all about recognizing the potential and finding the right fit for your organization. 2️⃣ AI is not a monolith: It encompasses a wide range of subdisciplines and techniques that have been developed over the past 70 years. Don't just focus on the latest advances; explore the reliable and tested techniques from the past. There's a wealth of knowledge waiting to be discovered! 3️⃣ Automation in AI: Automation can range from full automation to partial automation and decision support systems. Understanding the different levels of automation allows us to identify opportunities to increase work efficiency and reduce costs. It's about finding the right balance between human and machine collaboration. 4️⃣ Building AI software: Building AI software follows similar principles to building any other type of software. It's all about using cross-functional teams, adopting an agile mentality, and breaking down the work into manageable pieces. This ensures continuous value delivery and success in your AI projects. Now, I know what you're thinking. Is this article biased or sponsored by a software vendor? Well, I'm happy to inform you that it's not! This article provides an unbiased overview of AI concepts and principles without promoting any specific software, company, or service. So, if you're ready to dive into the world of AI and gain valuable insights from experts, I highly recommend checking out this article. It's a game-changer! #AI #ArtificialIntelligence #Innovation #Technology #FutureReady

🚀 Scaling Generative AI: Post 2 of 3 🚀 LLMs are not only expensive to develop but also to operate, with hidden costs lurking in areas such as energy consumption and infrastructure maintenance. Since models are just 15% of the overall cost of GenAI applications, McKinsey & Company recommends identifying where the hidden costs lurk and applying the right tools to control them. Trustwise provides a single API that addresses these challenges by dramatically cutting AI costs and reducing environmental impact. Through operationalizing effective cost management and strategic infrastructure planning, Trustwise ensures that organizations’ GenAI initiatives are not only cost-effective but also sustainable. https://lnkd.in/dSEY6CdC #AI #generativeAI #GenAI #TrustworthyAI #SustainableAI #McKinsey #ScalingAISeries

Just returning back to CPH from a week with my Ipsos peers from around the world leading innovation teams and we spend a lot of time on our new AI solution InnoExplorer - such exciting times in market research! Read our press release below and reach if you want to learn more. 👉🏻 InnoExplorer is the industry's first generative and analytical AI-supported product development solution. With InnoExplorer, we can identify and optimize unmet needs, ideas, concepts, products, packs, and even gain valuable insights for product transference. Our innovative approach uses generative AI in a responsible and safe way, and we strongly believe in the power of HI+AI for better and faster product development. We understand the importance of avoiding cultural bias and hallucinations by generative AI, which is why we prioritize responsible and safe use of this technology. https://lnkd.in/ewQjXw27

Learn how adaptive applications are unlocking innovation in a new AI age with this insightful article by #Couchbase's Tyler Mitchell on The New Stack

Why a full stack approach is needed for AI adoption at scale? The buzz around generative AI (GenAI) is undeniable. But for true enterprise-wide transformation, a one-size-fits-all approach won't cut it. Here's why a full-stack approach is the key to unlocking GenAI's true potential: 1. Reality Check: It's Not Magic. Gartner predicts 80% of enterprises will utilize GenAI by 2026, but a recent study shows 73% struggle with model explainability (XAI). Without understanding "why" behind the "what," trust and responsible AI practices crumble. 2. Beyond Hype: Cutting-Edge Advancements. The future lies in hybrid reasoning systems that combine symbolic AI and deep learning, mimicking human-like decision making. Brain-inspired architectures are also on the rise, offering a more efficient and interpretable path to AI. 3. Collaboration is Key. Forget siloed AI. Collaborative AI tools allow seamless human-machine interaction, fostering trust and improving outcomes. Active learning empowers models to "ask for help" on uncertain tasks, continuously improving accuracy. 4. Zero Hallucination, Maximum Impact. Tired of fantastical AI outputs? Zero-shot hallucination techniques ensure factual outputs, crucial for high-stakes enterprise applications. 5. Integrating the Present with the Future. A full-stack approach seamlessly integrates GenAI with existing workflows. This empowers a smooth digital core transformation, maximizing ROI without major disruptions. The Future is Now: By embracing a full-stack approach, enterprises can harness the power of GenAI responsibly, ethically, and with maximum impact. #generativeAI #AI #fullstack #enterpriseAI #digitaltransformation #futureofwork Let's discuss! What are your thoughts on the future of GenAI adoption?