Nicola Campisi’s Post

New MIT CISR research identified four stages of enterprise AI maturity, and found that financial performance improves with each stage. Most enterprises in the research were in the first two stages of AI maturity and had financial performance below industry average, while enterprises in stages three and four had financial performance well above industry average. MIT CISR researchers Peter Weill, Stephanie Woerner, and Ina Sebastian detail these findings in CISR's December 2024 research briefing, titled “Building Enterprise AI Maturity,” and explain how enterprises need to cumulatively build capabilities and learnings from AI as they move toward a future-ready state of AI use. The briefing also describes what enterprises focus on in each of the four stages, and pinpoints capabilities an enterprise needs as it progresses through the stages. #AI #EnterpriseAIMaturity #AIMaturityModel #AIFutureReady #DigitalTransformation

Want to help others navigate the complexities of enterprise AI deployment? The first round of speaker submissions for Observe closes Friday... Showcase the work your organization has been doing around LLM evaluations and AI observability. We want your use cases, deployment and scaling challenges, research questions, and future-thinking speculations. There are three tracks this year for the event happening on July 11 in SF that you can build a session around: ➕ AI Builder's Guild: Propose a hands-on session to provide pragmatic experience on evaluating and measuring the performance and reliability of AI systems using the latest open-source tools available. ➕ AI Research Frontiers: Present on cutting-edge research, emerging techniques, and theoretical advancements in AI observability and LLM evaluation. ➕ AI Innovators: Present on a use case, challenges in deploying products, or scaling of AI across organizations. Propose a session (and register): https://lnkd.in/gpEitQb5

Here is a valuable insight shared by my fellow CAIO, Karan Muthusamy, with our community regarding research conducted at MIT on the adoption of AI. The findings indicate that enterprise companies that are early adopters of AI are experiencing financial gains. Although this is just a small sample, the results would likely be consistent even at a larger scale. AI will not replace jobs; rather, it will be those who leverage AI who will thrive. "In light of the excitement and hype surrounding AI, we undertook research to help leaders navigate the chaos and understand how enterprises can create value with AI. This briefing describes the MIT CISR Enterprise AI Maturity Model, which outlines four stages of enterprise AI maturity identified through a 2022 MIT CISR survey of 721 companies. Our research found that financial performance improves at each stage, and we have pinpointed the capabilities that enterprises need as they progress through these stages. Chris Daigle Kimberly Hodgkinson, MBA, FHFMA, FACHE You can read or listen to more about it here: https://lnkd.in/e2vRhmJG #thoughtleadership #CAIO #AI

We've published several articles now outlining broad strategies for AI adoption in organizations. Now we're starting a series on more specific business applications of generative AI. Here's the first on Intelligent Document Processing. When we talk about starting fast with #genAI, these are the kind of solutions that can deliver near-term value and efficiencies for organizations right now. #IDP #AI

Recent research reveals that the surge in generative AI adoption is spurring global businesses to embrace a wider array of AI tools. However, despite high confidence in AI's transformative potential, there's a gap in understanding and effective implementation. The findings emphasize the need for businesses to enhance AI literacy and strategic investment to fully harness its capabilities. As a leading AI software company, our innovative solutions empower businesses to navigate these complexities and unleash their full potential. Visit our website to learn more https://www.naxgrp.com/. #AIInnovation #EnterpriseAI #NAXAI #BusinessTransformation

According to new #research from Pegasystems, the rapid rise of creative ‘right-brain’ #generativeAI has paved the way for increased adoption of more analytical ‘left-brain’ AI decisioning solutions by #globalbusinesses. #electrolnicsnews #technologynews

A recent analysis reveals that the enterprise verdict on AI models is increasingly favoring open-source solutions. Organizations are recognizing the strategic advantages that open-source AI offers, including enhanced transparency, flexibility, and community-driven innovation. Key points to consider include: - The growing demand for adaptable AI models that can be tailored to specific business needs. - How collaboration within the open-source community fosters rapid advancements in AI technology. - The potential for open-source AI to drive down costs while increasing accessibility for enterprises. As businesses continue to explore AI solutions, open-source models are positioned to play a pivotal role in shaping the future of enterprise AI. For a comprehensive overview of this trend, read the article: https://lnkd.in/d-GuM2YU

🌟 Exciting Developments in AI Governance! 🌟 I'm excited to share our latest publication on the critical new roles emerging as a result of the European Commission's AI Act, released on August 1. As AI continues to transform industries, it’s essential for organizations to understand and implement the right roles to stay compliant and ahead of the curve. In this publication, we explore the key positions that will be vital for navigating the AI-driven future. Curious to learn more? Read the full article here: https://lnkd.in/dRk9gu6i

🚀 Ready to explore the transformative power of AI for Enterprise in 2024? As providers of a Generative AI platform facilitating personalized, high-quality content creation at scale for Enterprise, we advocate for early AI adoption to catalyze business growth. From our observations, clients who have integrated AI into their operations have not only experienced increased efficiency and productivity but also seen improvements in innovation and competitiveness in an ever more digitized landscape. 🔗 Don't miss out on these key insights to shape the future of your business, read the article now: https://lnkd.in/d2Devskv #EnterpriseAI #AIinBusiness #FutureTrends #Innovation #BusinessSuccess

Just read this sentence: "Deploying AI models at scale and making them useful for the normal operational field is proving to be difficult at times, but it is a necessary step to ensure value generation." (You can find the context here: https://lnkd.in/eZC-tDZK) There is a bit of consulting-speak that makes this difficult to parse - what is "the normal operational field"? what is hidden/ignored in the phrase "ensure value generation" - but the thing that caught me up was "proving to be difficult at times." "At times"? Like "deploying AI models at scale" has been going on for a while (and not just like, less than a year?)? Like it's not difficult "at all times so far"?