Jason Morris’ Post

"Enterprises are increasingly viewing AI not as a standalone tool, but as a comprehensive intelligence framework that can generate actionable insights, automate complex processes, and create competitive advantages."

How do you think AI is changing the way we protect and recover data? AI isn’t just a buzzword — it’s quietly revolutionizing backups. By analyzing patterns, it can predict potential failures before they happen, ensuring your backups are always reliable. AI can also automate recovery processes, making downtime shorter and less stressful. But like any tool, it works best when paired with a solid strategy. Backups aren’t just about technology — they’re about preparation and planning. What’s your take on the role of AI in making backups smarter and faster?

Feel like you’re constantly battling between AI and people? Confused about which one is the best one to invest in for your business’s future? 😰 Automation is being implemented everywhere. But that’s not to say that human intelligence (HI) has lost its value - particularly when it comes to document processing obstacles such as; 🕴️Staff shortages ❌Errors, duplications or inaccurate data  📉Scalability barriers All of these 👆 are being overcome by combining AI and HI to improve document processing in businesses. Because AI will always have its limitations - And so will HI. Collective intelligence strikes a balance ⚖️ Have you tried it out for yourself?

How AI is Revolutionizing Modern Business Strategies This detailed exploration provides a comprehensive view of how AI is revolutionizing modern business strategies Continue reading on Medium »

The sanity checks you need to run before making AI work for your business

Artificial intelligence (AI) is extensively integrated across diverse industries and business processes, revolutionizing corporate operations. AI is employed throughout organizations, from marketing to human resources, to automate procedures, improve data analysis, and facilitate quicker, more informed decision-making. It is a tool to be deployed and how it is deployed determines the outcomes

Just completed the course "Artificial Intelligence and Business Strategy" This course provides insights into the integration of AI and its diverse applications in Business Strategy Formulation.Also the course sheds light on the significance of data in AI algorithm development and how to harness the power of AI to meet and exceed customer expectations. The modules covered in the course also extended to aspects of supplychain network as optimizing our supply chain network, enhancing efficiency, responsiveness, and resilience through AI-driven solutions, including innovative concepts such as digital twin technology. Understanding how digital twins can replicate physical supply chain processes in a virtual environment opens new avenues for enhancing visibility, forecasting accuracy, and decision-making within the supply chain operations. #artificialintelligenceforbusiness, #businessstrategy#supplychain#PMI #constantlearning #strategicbusiness

Thoughts on AI Tools AI tools are revolutionizing the way we approach tasks by automating repetitive processes, enhancing creativity, and providing insights that would otherwise be hard to uncover. They empower individuals and businesses to save time, improve efficiency, and focus on higher-level work. However, there are also challenges to consider, such as: 1. Productivity vs. Dependency: While these tools can boost productivity, over-reliance might reduce the development of certain skills. 2. Ethics and Privacy: AI systems often require large datasets, raising concerns about how data is collected and used. 3. Job Displacement: Some industries face the challenge of balancing automation with the human workforce. Ultimately, AI tools should be seen as collaborators rather than replacements, enabling us to push the boundaries of what’s possible. Responsible adoption will play a key role in maximizing their benefits while addressing potential risks.

🚀 Is AI and Machine Learning the Future of Software Testing or just the next new buzzwords? In 2024, AI and Machine Learning are spoken as key players in transforming how we approach software testing. But how much of an impact are they really making? 🔍 Efficiency Gains: in some cases AI-driven automation is already reduce testing time by 50%, allowing teams to focus on more complex tasks. ⚙️ Predictive Power: With machine learning's ability to analyse data and forecast potential issues, businesses are reducing downtime and preventing costly errors. 🤖 Smarter Test Coverage: With AI's ability to find hidden test cases that might be missed by human testers, overall coverage, reliability and as a consequence software quality is improving at a faster pace than ever before. Looking forward, the value and benefit may seem obvious so can companies really afford to skip integrating AI and ML in their testing processes?