Emerj Artificial Intelligence Research

"Webinar: Investing in the Future of Automotive Tech in Canada - Part 1 & 2"" https://lnkd.in/d6FQnhXQ During a recent webinar in partnership with Emerj Technology Research and automotive software company LeddarTech- Automotive Software: Low-Level Sensor Fusion & Perception, Flavio Volpe, President of the Canadian Automotive Parts Manufacturers' Association (APMA), gave a glimpse of the future that self-driving cars can offer commuters, consumers, and communities as AI-enhanced softwares become more commonplace in the industry: “Ten or twenty years from now – regardless of the volume of the vehicles that are on the road – the way that they will move, from the way that they speak to each other, and they speak to the infrastructure, the way that transportation is timed; the fact that fewer, if maybe none of us will actually be steering in situations – urban areas during rush hour, highways, on cross country trips – I think there's so many ways you can shape societal benefit. You win back time. You win back time and hopefully in that time that you get back, you’re either recharging or you’re working on something else.” - Flavio Volpe, President of the Automotive Parts Manufacturer Association & Recipient of the Order of Canada

“Infrastructure Challenges in Life Sciences Through the Lens of Data - with Robert Wenier of AstraZeneca” https://lnkd.in/d7Twr-82 On a recent episode of the ‘#AIinBusiness’ podcast, AstraZeneca Global Head of Cloud and Infrastructure Robert Wenier offered advice for life sciences leaderss navigating the necessary infrastructure investments in an era of hybrid strategies balancing cloud capabilities and local end-point storage services. In conversation with Emerj Artificial Intelligence Research Senior Editor Matthew DeMello, Robert was very keen to point out the advantages of object storage in letting life sciences enterprises be more flexible with their data strategies:

“Winning Buy-In for Life Sciences Manufacturing and Supply Chain Management - with Shreyas Becker of Sanofi” https://lnkd.in/gd7mscj6 Life sciences organizations are increasingly adopting AI to improve productivity, streamline operations, and enhance quality. To ensure sustained success, it is crucial to align AI initiatives with business goals and adapt traditional return on investment (ROI) metrics. These practices are key to gaining executive support and maximizing AI’s long-term value. The McKinsey Global Institute estimates AI could generate between $60 billion and $110 billion annually for the pharmaceutical and medical product industries. This value comes from AI’s ability to accelerate drug development, approval processes, and optimize marketing strategies. Additionally, life sciences firms are using AI to enhance supply chain management, addressing key challenges in areas such as procurement and inventory. On the ‘#AIinBusiness’ podcast, Shreyas Becker, Head of AI and Data Products in Manufacturing and Supply at Sanofi, discussed the importance of securing executive buy-in by aligning AI initiatives with stakeholder priorities. His conversation with Emerj Artificial Intelligence Research Senior Editor Matthew DeMello emphasizes shifting ROI metrics from focusing solely on outcomes to measuring process optimization, enabling organizations to drive sustained improvements. This article explores two critical insights from their conversation for business leaders across logistics, manufacturing and life sciences spaces: - Aligning AI initiatives with stakeholder objectives - Shifting ROI metrics from outcomes to process optimization #AI #LifeSciences #Pharma #AIAdoption #BusinessAlignment #Productivity #SupplyChain #McKinsey #Sanofi #ROI #Innovation #AIinBusiness #AIProducts #ProcessOptimization #PharmaceuticalIndustry #ExecutiveBuyIn

“Experimenting with GenAI Reporting Capabilities in Fortune 500 Companies - with Dan Helfrich of Deloitte” https://lnkd.in/gNfFpGW Today’s guest on the AI Consulting podcast is Dan Helfrich, Chair and CEO of Deloitte Consulting LLP, who recently sat down with Emerj Artificial Intelligence Research Founder and Head of Research, Daniel Faggella, to discuss the current state of Gen AI in Fortune 500 companies which reveals that nearly every organization is experimenting with GenAI at scale, with a third achieving expected benefits. One crucial element to this is leadership trusting Gen AI adoption, with 60% of respondents believing it will affect their talent strategies in less than two years. Adoption of AI in enterprises requires a change in mindset towards viewing it as a strategic capability, with tangible benefits being key to gaining traction. The growing pressure to adopt AI technology is driven by various factors, and organizations must navigate the AI revolution by demonstrating benefits and adopting a cautious approach to the black box problem and hallucination issue. Listen to our full podcast for further insight on this riveting topic. #GenAI #ArtificialIntelligence #Fortune500 #Leadership #Deloitte #AIAdoption #DigitalTransformation #TalentStrategy #EnterpriseAI #Innovation #TechLeadership #AIinBusiness #Consulting #AIImplementation #DataStrategy

“How to Rethink Banking in the Age of AI - with Ian Wilson, Former Head of AI at HSBC” https://lnkd.in/ea2paTN7 Banks and financial vendors turn to Emerj Artificial Intelligence Research to help them maximize ROI by allocating their funds to the most high-need areas. Our research also helps them make more intelligent decisions by identifying projects with greater accessibility and the highest chance of resulting in near-term financial ROI. While we supply a lot of valuable data and research, our insights would be worthless if they weren’t corroborated by the testimony of AI and banking leaders working on the ground. Emerj CEO Daniel Faggella recently sat down with Ian Wilson, the former Head of AI at HSBC, to discuss AI applications in banking on the AI in Business podcast. Business leaders reading this analysis of their conversation will gain a greater understanding of: - Why banks focus on specific areas of AI over others. - The obstacles in turning ideas about AI adoption into working solutions.

"Accelerating Lending and Underwriting – 3 AI Use Cases" https://lnkd.in/dSt_3F6E The era of humans serving as sole agents for lending and underwriting is no more. Machine learning and AI are now more ubiquitous within financial institutions and insurance companies, thanks in no small part to the automation of lending and underwriting processes. The reason for the transition being, at its core, lending and underwriting is a big data problem. While big data is the most valuable asset for lenders, machine learning can do the work of sifting through, organizing, analyzing, and modeling vast amounts of actionable data. And do so much faster and much more accurately than humans. In this article, we will examine three use cases that accelerate lending and underwriting: - Document fraud detection - Automated claims processing - Automated credit and risk evaluation

"Driving Cybersecurity Workflows with AI-Enhanced Software Development - with Frédéric Rivain of Dashlane" https://lnkd.in/d_MacVm Today’s guest on the ‘#AIinBusiness’ podcast is Frédéric Rivain, CTO of Dashlane. Dashlane is a password manager and digital wallet app, available through subscription, designed for macOS, Windows, iOS, and Android platforms. In a special episode sponsored by Pieces, Frédéric joins Emerj Artificial Intelligence Research Senior Editor Matthew DeMello to discuss how AI is transforming the cybersecurity landscape. With AI tools becoming more advanced, Frédéric explores both the risks and opportunities these technologies present to enterprises. As AI continues to evolve, it is reshaping cybersecurity by automating sophisticated attacks, which raises new challenges for organizations. At the same time, AI is also enhancing defense strategies, helping companies stay ahead in a constantly shifting digital environment. #AI #cybersecurity #cyberdefense #machinelearning #AITools #cybersecuritystrategy #digitaltransformation #securityrisks #cybersecuritytrends #cybersecuritythreats #datasecurity #cyberattacks #securityinnovation #techinnovation #cyberresilience #AIinsecurity

Grateful to see that Forbes’s recent article, “10 Business Functions That Are Ready To Use Artificial Intelligence” (https://lnkd.in/dzS87wQ7) references our Emerj Artificial Intelligence Research article on “AI in Building Automation – Current Applications” (https://lnkd.in/d9qVMBj8). The Emerj report explores AI in building automation, focusing on facility management and energy analytics. Our research demonstrates how AI optimizes energy and improves comfort, plus key trends shaping the future of automation. Extra thanks to author Bernard Marr. #AI #ArtificialIntelligence #Automation #Logistics #Security #BusinessIntelligence

“Artificial Intelligence at Zurich Insurance - Two Use Cases” https://lnkd.in/gqnpJ26g Zurich Insurance Group, founded in 1872 and based in Zurich, Switzerland, is a leading multi-line insurer that serves over 55 million customers across more than 210 countries and territories. The company provides a broad range of property, casualty, and life insurance products and services. In 2023, Zurich reported a significant increase in business operating profits, achieving USD 7.4 billion, marking a 21% rise from the previous year. The company has made substantial investments in AI to improve its services and operational efficiencies. According to its website, Zurich has implemented over 160 AI use cases throughout various divisions. In 2022, it introduced the AI Assurance Framework (AIAF) to ensure responsible AI deployment across its operations. This article examines two specific AI applications that are integral to Zurich’s strategic objectives: - Managing account receivables - Automating claims with high accuracy #ZurichInsuranceGroup #AI #InsuranceTech #BusinessGrowth #OperationalEfficiency #ArtificialIntelligence #FinancialServices #InsuranceClaims #TechnologyInnovation #GlobalInsurance #LifeInsurance #PropertyInsurance #CasualtyInsurance #AIIntegration #InsuranceIndustry

“The 3 Phases of Enterprise AI Deployment” https://lnkd.in/gcQ56vv Making AI work has a lot to do with “getting things right” even before a project starts, including: - Picking the right project - Ensuring that talent and data resources are sufficient - Aligning a project with strategic value This Emerj Artificial Intelligence Research executive guide identifies and breaks down the three key steps in enterprise AI deployment: Proof of Concept (PoC), Incubation, and Deployment. Discover this guide and explore our entire library of exclusive whitepapers, infographics, and frameworks at emerj.com/p1. #artificialintelligence #enterprise #deployment #ROI