Emerj Artificial Intelligence Research

AI adoption often fails not because of the technology itself but because organizations start with the wrong problems. Identifying the right challenges to address is essential for building lasting solutions. In this clip from Vision to Value in Enterprise AI, Kuo Zhang, President of Alibaba.com, explains Alibaba’s methodology for designing agentic AI systems. He emphasizes that products succeed only when they target real, high-value problems that matter to businesses and customers. For enterprise leaders, this lesson is critical: sustainable AI adoption requires prioritizing problem selection before implementation, ensuring that investments align with measurable outcomes. Watch the full episode on Vision to Value in Enterprise AI: https://lnkd.in/dumE-fd3 #VisiontoValueinEnterpriseAI #AI #artificialintelligence #AIinBusiness #AIadoption #AIstrategy #digitaltransformation #enterprisetech #AIcommerce #AItools #AIinSupplyChain #AIinProcurement #futureofwork #AIgovernance #globaltrade

“Artificial Intelligence at Wells Fargo - Two Use Cases” https://lnkd.in/d6hBzEVg Wells Fargo continues to integrate AI into its operations, driving innovation in customer engagement and decision-making. With a presence in 35 countries and a customer base of 70 million, the financial institution has focused on AI to enhance personalization and improve fairness in lending. This article extends on Emerj’s research on AI initiatives at Wells Fargo from 2019, exploring two mature use cases supporting two critical business objectives at the company: - Advanced analytics to personalize customer engagement at scale - Leveraging modern machine learning for fairer loan decisions Wells Fargo's AI-driven approach to personalization leverages real-time decisioning and generative AI to deliver targeted experiences at scale. Its customer engagement strategy, supported by Pega’s Customer Decision Hub, processes billions of digital interactions to determine the most relevant next-best actions for individual customers. Meanwhile, the bank’s adoption of machine learning models aims to improve the accuracy and fairness of loan decisions, addressing challenges in traditional risk assessment. These initiatives highlight AI’s role in advancing financial services, improving customer experiences, and enhancing operational efficiency. #WellsFargo #AIinFinance #MachineLearning #CustomerEngagement #AIInnovation #BankingAI #DataScience #Personalization #LoanDecisions #ExplainableAI #DeepLearning #RiskAssessment #FinancialTechnology #AIinBusiness #Fintech

“Picking a First AI Project – A 3-Step Guide for Leaders” https://lnkd.in/g3cRY4g Artificial intelligence is poised to revolutionize industries, unlocking trillions in economic value. Yet, 80-90% of initial enterprise AI projects fail. Why? Often, wrong project selections. Explore our guide on executive AI fluency to master project selection and unlock our entire library of resources for enterprise leaders at emerj.com/p1. #AI #BusinessLeadership #ProjectSelection #EmergingTech

“Unlocking Infrastructure as the Engine of Transformation – with Deborah Golden from Deloitte” https://lnkd.in/dDXR7bqN Legacy infrastructure wasn’t built for the speed and volatility of AI — and enterprise leaders are feeling the strain. In a recent conversation on the ‘#AIinBusiness’ podcast, Daniel Faggella, Founder and Head of Research at Emerj Artificial Intelligence Research, spoke with Deborah Golden, U.S. Chief Innovation Officer at Deloitte, about why traditional infrastructure models may be falling short — and what it can take to support trustworthy, scalable AI at the enterprise level. Golden outlines how infrastructure should evolve from a static utility into a dynamic system that enables innovation. That can mean treating infrastructure as a strategic asset, building cross-functional teams to break down silos, and embedding governance directly into system design — before deployment. Read the full article to explore three strategies that can help make infrastructure AI-ready while balancing performance, risk, and cost. #AIInfrastructure #EnterpriseAI #DigitalTransformation #AIinBusiness #ScalableAI

“Treat this as an R&D project — focus on building a usable data platform first. ROI comes later, after iteration and fine-tuning.” — Joe Lang, Vice President of Service Technology and Innovation at Comfort Systems USA In this Pure Storage–sponsored episode of the ‘#AIinBusiness’ podcast, Joe Lang joins Emerj Artificial Intelligence Research Editorial Director Matthew DeMello to share how field service organizations structure data and workflows to scale AI performance without bottlenecks. Executives can use this approach to align storage, data strategy, and AI initiatives, ensuring operational efficiency and measurable ROI as projects grow: https://lnkd.in/dkeQeG89 #EnterpriseAI #DataInfrastructure #FieldServiceInnovation

Grateful to see that ACM, Association for Computing Machinery's recently published research article, “Embedding Optimization for Training Large-scale Deep Learning Recommendation Systems with EMBark,” (https://lnkd.in/dYh7J_pf) references our Emerj Artificial Intelligence Research article on “Use Cases of Recommendation Systems in Business – Current Applications and Methods” (https://lnkd.in/dfbv4FQj). Our research explains how recommendation systems are transforming eCommerce by personalizing user experiences and boosting ROI for companies like Amazon, Netflix, and Best Buy. Extra thanks to authors Shijie Liu, Nan Zheng, Hui Kang, Xavier Simmons, Junjie Zhang, Matthias Langer, Wenjing Zhu, Minseok Lee, and Zehuan Wang. #AI #ArtificialIntelligence #eCommerce #ConsumerGoods #Marketing #Advertising #Entertainment

"Three Ways to Discover AI Trends in Any Sector" https://lnkd.in/dg7QNjm Here at Emerj Artificial Intelligence Research, most of our work in AI Capability Map services is about finding trends in quantitative data – which requires hundreds of hours of expert research and established frameworks for interpreting and categorizing data for insight. While this robust research approach is often the right step for companies on their way to building a complete AI strategy – it's easiest to begin with simple secondary research online. This simple, 4-page PDF reveals some of our favorite ways of quickly hunting down AI opportunities and trends, including how to: - Follow the venture money - Let executives tell YOU the future - Stay attuned to industry priorities #AI #venturecapital #qualitativedata

“Rethinking How Life Sciences Organizations Approach AI - Mathias Cousin of Deloitte” https://lnkd.in/d_MacVm Fragmented AI adoption and technology hype are slowing real R&D transformation in life sciences. In this episode of the #AIinBusiness podcast, Mathias Cousin, Managing Director at Deloitte, joins Emerj Artificial Intelligence Research Editorial Director Matthew DeMello to discuss how enterprise leaders move from pilot projects and excitement to sustained value creation with AI. Cousin details the need for rigor around scientific context, assembling the right “AI native” talent, and developing a series of targeted use cases that reflect organizational priorities. The conversation explores how quality data, change management, and embedding AI tools into business processes are now required for measurable cost savings and efficiency. Executives tasked with scaling data and AI in regulated industries will hear straight guidance for building actionable, adaptive innovation programs. #AIinBusiness #EnterpriseAI #AIAdoption #RnDtransformation #innovationmanagement

We’d like to thank all of the great guests who joined us on the Emerj Artificial Intelligence Research ‘AI in Business’ podcast over the past month. Subscribe today on Apple Podcasts (https://lnkd.in/dwzyJT6v) and Spotify (https://lnkd.in/dU4qPpZa) to hear: - JoAnn Stonier, Data and AI Fellow at Mastercard, discuss how AI-driven analytics reduce false positives in fraud detection, why “agent-ish” AI marks an important transition toward more autonomous systems, and how responsible governance ensures privacy and security remain at the forefront. https://lnkd.in/di_8wJbu - Abhii Parakh, VP and Head of Customer Experience at Prudential Financial, share his perspective on scaling AI in customer experience, an area facing both significant opportunity and unique regulatory challenges. https://lnkd.in/dSx8sNiG - Yunke Xiang, Global Head of Data Science for Manufacturing, Supply Chain, and Quality at Sanofi, examine how generative AI and reasoning models are evolving from simple automation to high-impact copilots across pharmaceutical operations. https://lnkd.in/dF8PtTZa - Kuo Zhang, President of Alibaba.com, share how new technologies — including Alibaba’s agentic AI system Accio — are streamlining procurement and unlocking opportunities once reserved for enterprises. https://lnkd.in/dqUQG9bY - Aaron Demory, Senior Partner at Fearlus, Chief of Information Technology and Security at the FDIC, explore how organizations can safeguard institutional memory, align data strategy with cultural goals, and rethink success in the age of AI. https://lnkd.in/dMA28yiZ - Stuart Russell, Professor of Computer Science, University of California, Berkeley, discuss the urgent challenges posed by AGI development, the incentives driving companies into a dangerous race dynamic, and what forms of international governance may be necessary to prevent catastrophic risks. https://lnkd.in/dN-iq4kN

"Transforming Manufacturing with AI-Powered 3D Digital Twins and Remote Monitoring with Rad Desiraju of Microsoft and Mike Geyer of NVIDIA" https://lnkd.in/dt52TNjf Acceleration in #DigitalTwins isn’t just about data or compute — it’s about creating structured processes that connect digital models to real-world operations. On a recent episode of the Emerj Artificial Intelligence Research #AIinBusiness podcast, Rad Desiraju, Director of Worldwide Industry Advisory at Microsoft, outlines the three-step approach: building digital models, enabling remote collaboration, and synchronizing with physical assets for scalable, AI-driven operations. #Simulation #IndustrialAI #AIinBusiness