This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
The emergence of artificialintelligence (AI) brings datagovernance into sharp focus because grounding large language models (LLMs) with secure, trusted data is the only way to ensure accurate responses. So, what exactly is AI datagovernance?
This is my monthly check-in to share with you the people and ideas I encounter as a data evangelist with DATAVERSITY. This month, we’re talking about the interplay between DataGovernance and artificialintelligence (AI). Read last month’s column here.)
As I’ve been working to challenge the status quo on DataGovernance – I get a lot of questions about how it will “really” work. In 2019, I wrote the book “Disrupting DataGovernance” because I firmly believe […] The post Dear Laura: How Will AI Impact DataGovernance? appeared first on DATAVERSITY.
The post DataGovernance at the Edge of the Cloud appeared first on DATAVERSITY. With that, I’ve long believed that for most large cloud platform providers offering managed services, such as document editing and storage, email services and calendar […].
But the widespread harnessing of these tools will also soon create an epic flood of content based on unstructured data – representing an unprecedented […] The post Navigating the Risks of LLM AI Tools for DataGovernance appeared first on DATAVERSITY.
Data has become a driving force behind change and innovation in 2025, fundamentally altering how businesses operate. Across sectors, organizations are using advancements in artificialintelligence (AI), machine learning (ML), and data-sharing technologies to improve decision-making, foster collaboration, and uncover new opportunities.
ArtificialIntelligence (AI) has earned a reputation as a silver bullet solution to a myriad of modern business challenges across industries. From improving diagnostic care to revolutionizing the customer experience, many industries and organizations have experienced the true transformational power of AI.
The current wave of AI is creating new ways of working, and research suggests that business leaders feel optimistic about the potential for measurable productivity and customer service improvements, as well as transformations in the way that […] The post DataGovernance in the Age of Generative AI appeared first on DATAVERSITY.
In this article, you’ll discover: upcoming trends in business intelligence what benefits will BI provide for businesses in 2020 and on? top 5 key platforms that control the future of business intelligence impacts BI may have on your business in the future. Below we break down the latest trends in business intelligence.
The business case for datagovernance has been made several times in these pages. There can be no disagreement that every company and every government office must have a datagovernance strategy in place. Establishing good datagovernance is not just about avoiding regulatory fines.
The global market for artificialintelligence (AI) in insurance is predicted to reach nearly $80 billion by 2032, according to Precedence Research. This growth is being driven by the increased adoption of AI within insurance companies, enhancing their operational efficiency, risk management, and customer engagement.
In the digital age, organizations increasingly rely on data for strategic decision-making, making the management of this data more critical than ever. This evolution underscores the importance of master […] The post How to Ensure Data Quality and Consistency in Master Data Management appeared first on DATAVERSITY.
The project management profession, like many others, faces an emergent threat from artificialintelligence (AI)-based technologies. Gartner has predicted that by 2030, upwards to 80% of project management work will be automated by artificialintelligence (AI). Although 80% is arguably a bit extreme, I expect […]
In late 2023, significant attention was given to building artificialintelligence (AI) algorithms to predict post-surgery complications, surgical risk models, and recovery pathways for patients with surgical needs.
A large language model (LLM) is a type of artificialintelligence (AI) solution that can recognize and generate new content or text from existing content. It is estimated that by 2025, 50% of digital work will be automated through these LLM models.
With the rapid development of artificialintelligence (AI) and large language models (LLMs), companies are rushing to incorporate automated technology into their networks and applications. However, as the age of automation persists, organizations must reassess the data on which their automated platforms are being trained.
Artificialintelligence (AI) is no longer the future – it’s already in our homes, cars, and pockets. Click to learn more about author Anne Hardy. As technology expands its role in our lives, an important question has emerged: What level of trust can – and should – we place in these AI systems? Trust is […].
Reusing data is a fundamental part of artificialintelligence and machine learning. Yet, when we collect data for one purpose, and use it for other purposes, we could be crossing both legal and ethical boundaries. How can we address the ethics of reusing data?
The world of artificialintelligence (AI) is evolving rapidly, bringing both immense potential and ethical challenges to the forefront. In this context, it is essential to remember that intelligence, when misused, can be graver than not having it at all.
Part 1 of this article considered the key takeaways in datagovernance, discussed at Enterprise Data World 2024. […] The post Enterprise Data World 2024 Takeaways: Key Trends in Applying AI to Data Management appeared first on DATAVERSITY.
This month, we’re enjoying some time in the fall sun and the local library diving into Laura Madsen’s “AI & The Data Revolution.” The central theme of this book is the management and impact of artificialintelligence (AI) disruption in the workplace.
More and more companies want to use artificialintelligence (AI) in their organization to improve operations and performance. The post Good AI in 2021 Starts with Great Data Quality appeared first on DATAVERSITY. Click here to learn more about Heine Krog Iversen. Achieving good AI is a whole other story.
Public sector agencies increasingly see artificialintelligence as a way to reshape their operations and services, but first, they must have confidence in their data. Accurate information is crucial to delivering essential services, while poor data quality can have far-reaching and sometimes catastrophic consequences.
In today’s rapidly changing and advancing world of artificialintelligence (AI), generative AI, and large language models (LLMs), data has become the lifeblood of innovation. Data fuels algorithms, powers decision-making processes, and shapes the future impact of technology.
Artificialintelligence (AI) and machine learning (ML) are continuing to transform the insurance industry. But if the proper guardrails and governance are not put into place early, insurers could face legal, regulatory, reputational, operational, and strategic consequences down the road. […].
Terms like artificialintelligence (AI) and augmented intelligence are often used interchangeably. However, they represent fundamentally different approaches to utilizing technology, especially when it comes to datagovernance.
The resulting economic uncertainty and growth of industry-wide trends, including ESG, cloud migration, and the rise of artificialintelligence and machine learning programs – such as OpenAI’s newly launched GPT-3 model and […] The post How Data Integrity Can Maximize Business Value appeared first on DATAVERSITY.
Artificialintelligence (AI) could boost company productivity by 1.5%, increasing S&P 500 profits by 30% over the next 10 years. The rapid success of generative AI technologies such as ChatGPT is an excellent example of how companies can shape their fortunes by harnessing the power of the data they hold.
I was asking them about the ways in which generative AI might impact their business and they shared that clients might not want to pay $50,000 for a slide deck anymore if they disclosed that generative AI […] The post Ask a Data Ethicist: Does Using Generative AI Devalue Professional Work?
Today, most companies are in the process of implementing various business intelligence strategies, turning to SaaS BI tools to assist them in their efforts. With a new year on the horizon, in this article, we’ll explore 10 essential SaaS trends that will stand out in 2020. 1) ArtificialIntelligence. Vertical SaaS.
Data is the viral sensation crashing the datagovernance capacity. Use of data is disrupting industries, economies, even some government elections. Unlocking the secrets data holds is the number one challenge in every single company regardless of the size or industry. And yet, execution, […].
Forty years later, almost every business and technology publication seems to have reimagined the army of robots and artificialintelligence as trading their quest for world domination for the exciting world of business processing. In the 1980s, there was a flurry of movies about robots coming to imprison or terrorize humanity.
ArtificialIntelligence (AI), Machine Learning (ML) and Large Language Models (LLM) have turned the world on its head. From finance to manufacturing to pharmaceuticals to retail, every industry is jumping on the AI/ML bandwagon. And for good reason. AI/ML applications can absorb […]
While data privacy concerns aren’t at the forefront of all consumers’ minds, it’s safe to say that many people are worried about how brands, governments, and organizations use, access, and safeguard their data.
While data has extreme potential to change how we run things in the business world, there are also cons or risks if this data is mishandled. By the time we reached the 2020s, the emphasis or the focus moved to collecting and managing high-quality data for specific requirements or purposes.
In the last few months, we have seen the wave of ArtificialIntelligence break on the shores of wide-scale business adoption and mainstream media coverage of Large Language Models, most famously ChatGPT.
Generative AI in Finance FAQs addressed in this article: What is generative AI in financial services? – Considerations include identifying and mitigating AI-related risks, developing new governance frameworks for AI oversight, and ensuring the responsible and ethical use of AI technologies.
Artificialintelligence (AI) is rapidly reshaping our world, influencing everything from the way we work to the way we live. At the heart of this transformation lies data, the fuel that powers AI systems. How we manage this data can determine whether […]
The focus of my last column, titled Crossing the Data Divide: Data Catalogs and the Generative AI Wave, was on the impact of large language models (LLM) and generative artificialintelligence (AI) and how we disseminate knowledge throughout the enterprise and the future role of the data catalogs.
However, while solutions like ChatGPT continue growing in popularity among everyday users, the most significant potential of artificialintelligence lies in […] And considering the wide range of use cases for AI tools, that’s not much of a surprise.
I also participated in an executive dinner and roundtable to focus on artificialintelligence (AI). During the CDM Media’s September 2023 Houston CDO and CIO/CISO Summit, I joined a group of business and IT leaders across various industries to share perspectives and best practices.
Explainable AI refers to ways of ensuring that the results and outputs of artificialintelligence (AI) can be understood by humans. It contrasts with the concept of the “black box” AI, which produces answers with no explanation or understanding of how it arrived at them.
We organize all of the trending information in your field so you don't have to. Join 57,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content