John "JT" Scott’s Post

Large technological shifts inside organizations are nothing new. The advent of the PC in the 1980s and the rise of the spreadsheet and word processor was one such moment. The internet and World Wide Web was another, but AI could be bigger than these previous waves of change. “The internet era lowered the cost of information transmission, and CIOs rode that thing and brought digital technologies inside of their organizations and so forth. But AI is a markedly different type of technology. It’s lowering the cost of expertise,” Karim Lakhani, faculty chair at Harvard’s Digital Data Design Institute, told TechCrunch. #ai #tech #business

#Playbook for #Crafting #AIStrategy, by Massachusetts Institute of Technology Crafting an effective #AI strategy requires organizations to move from #experimentalphases to enterprise-wide deployment. This playbook emphasizes the importance of aligning #AIinitiatives with #business goals, ensuring robust data #foundations, and fostering collaboration between technical and business teams. Key pillars include selecting appropriate AI use cases, integrating AI into existing workflows, managing associated risks like bias and data privacy, and preparing for evolving regulatory landscapes. The strategy must also focus on measuring ROI and fostering a culture of innovation to ensure sustainable and impactful AI adoption. 10 Key Takeaways 1. Enterprise-Wide AI Adoption: Successful strategies transition AI from isolated pilots to comprehensive integration across business functions. 2. Data Quality and Liquidity: High-quality, accessible data is crucial for enabling scalable and effective AI deployment. 3. AI Use Case Selection: Prioritize use cases that address specific business needs and offer measurable impact. 4. Human-AI Collaboration: AI augments human capabilities but requires clear oversight and governance frameworks. 5. Risk Management: Address issues like bias, data security, and hallucinations to build trust and ensure compliance. 6. Strategic Partnerships: Collaborate with AI vendors and leverage pre-built models for cost-effective and faster deployment. 7. Cost and ROI Analysis : Accurately assess AI’s financial impact by balancing initial investments with long-term gains. 8. Regulatory Preparedness: Align AI deployments with global regulatory standards to avoid legal and ethical pitfalls. 9. Cultural and Organizational Change: Foster a culture that embraces AI through training, collaboration, and open communication. 10. Sustainability and Scalability: Design AI systems that can grow with the business while maintaining operational efficiency. #AIStrategy #EnterpriseAI #DataDrivenDecisions #EthicalAI #InnovationLeadership #RiskManagement #DigitalTransformation #AIAdoption #BusinessImpact #FutureOfWork

🚀 Weekend Takeaways: Scaling AI Across Enterprises 🚀 Before the weekend approached, I delved into some insightful reads and attended a session on - Enabling enterprises with a vision of ‘AI Everywhere’.Here are the key takeaways for enterprises of all scales: 🧑💻Tech and Data Overhaul🧑💻: Embrace a comprehensive approach by integrating AI into every aspect (Thats right- every) of your technology stack and processes. While you are at it, it’s important to understand how AI models can learn from the right data and start by preemptively preparing your organisation.Repetitive or incorrect information access to AI models should be avoided as this can only mislead the ‘learning’ and making the model less dependable. 🎯Work Smarter not Faster 🎯: Incorporate AI development into product management, software development, and operational processes to enhance efficiency. Its important to make sure that your organisations data compliances are not compromised. This can be ensured by implementing security guardrails like ‘just enough’ access while integrating AI models and stakeholders. 🏌️Skill up🏌️: It's crucial to upskill engineering teams to proficiently integrate, test, and scale AI systems, leveraging AI tools to boost productivity. While a lot of people are already getting a taste of it with pilot programs in enterprises, tracking the extent of use by the decision makers can help channel the next level of super intelligence for them in the right direction. 💰Budget Wisely💰: Redefine your tech spending to support AI investments and infrastructure, capturing efficiencies in software development and service management. You don’t want it to just be another “talk on technology” anymore, no matter which industry you belong to. Hype cycles of technologies will continue to be crowded with AI related developments for quite sometime,and will be directed at the next level of enhancements. 🙅Responsible AI & More🙅: Review and update risk management and governance processes to ensure successful AI deployment and upgrades which adhere with ethical standards. #AIinEnterprises #ArtificialIntelligence #AIinPractice

#GenAI is no longer just an experiment; it's poised to revolutionize businesses. As companies embrace this technology, they must navigate challenges like scaling, integration, and governance. By focusing on high-value use cases, fostering a culture of innovation, and developing a clear adoption playbook, organizations can unlock the full power of GenAI and gain a competitive edge. To harness the full potential of GenAI, consider these strategies: 👉 Identify High-Value Use Cases: Focus on areas where GenAI can deliver significant impact, such as customer service automation, content generation, or data analysis. 👉 Foster a Culture of Innovation: Encourage experimentation, provide training, and create a collaborative environment that embraces AI. 👉 Develop a Clear Adoption Playbook: Establish a roadmap for GenAI implementation, including data strategy, ethical guidelines, and risk management. 👉 Partner with Experts: Collaborate with AI experts to accelerate adoption and overcome technical challenges. By embracing these strategies, businesses can unlock the power of GenAI and gain a competitive edge. ⚡ Let’s discuss if you need any help around integrating GenAI into your business and I can provide you with all the necessary resources and roadmaps. #GenAI #AI #ArtificialIntelligence #MachineLearning #DigitalTransformation #Innovation #Technology #Business #FutureofWork

Generative AI (GenAI) holds immense potential for businesses, but scaling it effectively requires strategic leadership from the CIO. To successfully scale GenAI, CIOs must navigate a complex landscape of off-the-shelf solutions, custom models, and hybrid approaches. This requires a deep understanding of the business's unique needs and challenges, as well as a clear vision for how GenAI can drive value and innovation.   One key factor in scaling GenAI is building a cross-functional team that can bridge the gap between technical expertise and business strategy. This team should include data scientists, engineers, and domain experts who can work together to identify high-impact use cases and develop tailored solutions.   Another critical consideration is ensuring that GenAI initiatives are aligned with broader business goals and priorities to ensure that GenAI investments are delivering measurable results.   Ultimately, scaling GenAI requires a strategic, business-focused approach that balances innovation with practicality. CIOs who can lead this charge and drive meaningful impact will position their organizations for success in the AI-driven future.   🔗 https://lnkd.in/dFgEsDwa #GenAI #CIO #Innovation #Technology #BusinessTransformation Antonio Vieira Santos Oliver Kleinhenz Ruediger Reitzig, Dr. Hervé Bastian Sachin Chawak Sachin Ghate Santosh Gupta Chintan Parikh Vamsi Avva

As leaders think about their #GenAI strategy, it is critical that they understand exactly what these technologies can do and where they can add lasting value for their business. In her latest column for Forbes, my colleague, @LisaCaldwell highlights the importance of establishing a strong foundation today to be able to scale the #technology.

Appointing a Chief #AI Officer is ... (mistakenly) the first step for many organisations, as this powerful new technology looms on the horizon... Why might this move be wrong if an organisation truly pursues effectiveness, innovation, and seeks an edge over its competitors? The best way of deploying AI might be a platform architecture that hosts common services (not just software) and makes them available for teams to build on. Read Lee Bryant's breaking insights on our Shift*Academy newsletter: https://lnkd.in/dV4NzFRJ #innovation #leadership #digital

Why market leaders are scaling GenAI today? Its clear: 𝟗𝟎% 𝐨𝐟 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 have moved beyond AI experimentation to strategic investment. This isn't just following trends—it's about speed and differentiation. 𝐖𝐡𝐚𝐭 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐢𝐚𝐭𝐞𝐬 𝐬𝐮𝐜𝐜𝐞𝐬𝐬𝐟𝐮𝐥 𝐆𝐞𝐧𝐀𝐈 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧𝐬? - Clear alignment with business objectives and data foundation. - Enterprise-grade security and governance - Scalable solutions that deliver measurable ROI At Inferenz, we're helping industry leaders transform this technology investment into tangible business outcomes. Our enterprise GenAI solutions are designed for: 1. Accelerated time-to-value 2. Seamless integration with existing workflows 3. Robust compliance and risk management Forward-thinking organizations are already capturing market share through strategic AI deployment. Where does your AI strategy stand? Connect to learn how we're helping enterprises turn GenAI investment into competitive advantage. 🔗 https://inferenz.ai/ #GenAI #ArtificialIntelligence #BusinessStrategy #Innovation #DigitalTransformation #GenerativeAI #DidYouKnow Gayatri Akhani | Yash Thakkar | Srinivas Mothey | Amisha Rodrigues | James Gardner | Jalindar Karande |

Organizations seeing the largest returns from Generative AI are more likely than others to follow a range of best practices in risk, strategy ,talent, operating model, tech & data, adoption and scaling up - Mckinsey