In today's rapidly evolving technological landscape, artificial intelligence (AI) governance has emerged as a critical ingredient for successful AI deployments. It helps build trust in the results of AI models, it helps ensure compliance with regulations and it is necessary to meet internal governance requirements. Effective AI governance must encompass various dimensions, including data privacy, model drift, hallucinations, toxicity and perhaps most importantly, bias. Unfortunately, we expect...
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Topics:
AI,
Generative AI,
AI and Machine Learning,
Machine Learning Operations,
Analytics and Data
As I’ve written recently, artificial intelligence governance is a concern for many enterprises. In our recent ISG Market Lens study on generative AI, 39% of participants cited data privacy and security among the biggest inhibitors to adopting AI. Nearly a third (32%) identified performance and quality (e.g., erroneous results), and an equal amount (32%) mentioned legal risk.
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Topics:
AI,
Generative AI,
AI and Machine Learning,
Machine Learning Operations,
Analytics and Data
Having just completed our AI Platforms Buyers Guide assessment of 25 different software providers, I was surprised to see how few provided robust AI governance capabilities. As I’ve written previously, data governance has changed dramatically over the last decade, with nearly twice as many enterprises (71% v. 38%) implementing data governance policies during that time. With all this attention on data governance, I had expected AI platform software providers would recognize the needs of...
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Topics:
AI,
Analytics & Data,
AI and Machine Learning,
Machine Learning Operations
I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The AI Platforms: Ventana Research Buyers Guide is the distillation of a year of market and product research by Ventana Research.
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Topics:
AI,
Generative AI,
Machine Learning Operations
The emergence of generative artificial intelligence (GenAI) has significant implications at all levels of the technology stack, not least analytics and data products, which serve to support the development, training and deployment of GenAI models, and also stand to benefit from the advances in automation enabled by GenAI. The intersection of analytics and data and GenAI was a significant focus of the recent Google Cloud Next ’24 event. My colleague David Menninger has already outlined the key...
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Topics:
Analytics,
AI,
natural language processing,
data platforms,
Generative AI,
AI and Machine Learning
The artificial intelligence (AI) market is exploding with activity, which is part of the reason we recently announced that we have dedicated an entire practice at Ventana Research to the topic. Large language models (LLMs) and generative AI (GenAI) have taken the AI world by storm. In fact, we assert that through 2026, one-half of all AI investments will be based on generative rather than predictive AI. My colleague Rob Kugel has written about how AI can improve productivity and benefit the...
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Topics:
AI,
natural language processing,
Analytics & Data,
Generative AI,
AI and Machine Learning
Analytics software is used by business analysts and decision-makers to facilitate the generation of insights from data. It encompasses business intelligence and decision intelligence software, including reports and dashboards as well as embedded analytics and the development of intelligent applications infused with the results of analytic processes. Analytics software enables enterprises to improve business outcomes by operating more efficiently, accelerating product development and enhancing...
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Topics:
Analytics,
AI,
Analytics & Data,
Generative AI
I recently attended the Salesforce Trailblazer DX event to learn more about Salesforce’s artificial intelligence products and strategy. Fueled by generative AI, awareness and investment in AI seems to be exploding. ISG research shows that enterprises plan to nearly triple the portion of budgets allocated to AI over the next two years. This doesn’t come as a big surprise when you look at the outcomes enterprises are achieving: Of those that have invested in AI, more than 8 in 10 (84%) have had...
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Topics:
AI,
natural language processing,
Generative AI,
Computer Vision,
Model Building and Large Language Models,
Deep Learning,
Machine Learning Operations
Data and analytics have become increasingly important to all aspects of business. The modern data and analytics stack includes many components, which creates challenges for enterprises and software providers alike. As my colleague Matt Aslett points out, a better term might be modern data and analytics smorgasbord. There are arguments for and against using an assortment of tools versus a consolidated platform. For example, purchasing, integrating and deploying a variety of tools can be complex....
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Topics:
Analytics,
AI,
data operations,
Analytics & Data,
Generative AI,
Data Intelligence
Artificial intelligence seems poised to change everything, although naturally a great deal of attention tends to be paid to the cool things it makes possible. AI can also make the humdrum less tedious and even transform the dullest of back-office operations into something more meaningful. For example, AI can take accounts receivable automation to the next level.
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Topics:
Office of Finance,
AI,
digital finance,
AI and Machine Learning,
Order-to-Cash