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        Ventana Research Analyst Perspectives

        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

        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

        The first wave of discussions around artificial intelligence (AI) in the contact center was focused on providing software buyers with a general understanding of what the technology could do. Now the conversations are becoming more specific, focused and direct. Buyers are more aware of the spectrum of available use cases and appear to be exploring how to map new tools to the particular business problems they face. Contact center buyers are approaching new technology deployments (or enhancements...

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        Topics: Customer Experience, Contact Center, AI, natural language processing, agent management, Intelligent Self-Service, Generative AI, Computer Vision

        We’ve been saying for years that natural language processing (NLP) and natural language analytics would greatly expand access to analytics. However, prior to the explosion of generative AI (GenAI), software providers had struggled to bring robust natural language capabilities to market. It required considerable manual effort. Many analytics providers had introduced natural language capabilities, but they didn’t really resonate with enterprise requirements. They required significant effort to...

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        Topics: business intelligence, Artificial intelligence, natural language processing, Analytics & Data, AI and Machine Learning, GenAI

        Ventana Research recently announced its 2024 Market Agenda for Artificial Intelligence, continuing the guidance we have offered for two decades to help enterprises derive optimal value from technology and improve business outcomes.

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        Topics: Artificial intelligence, natural language processing, Generative AI, Computer Vision, Model Building and Large Language Models, Deep Learning

        Ventana Research recently announced its 2024 Market Agenda for Analytics and Data, continuing the guidance we have offered for two decades to help enterprises derive optimal value and improve business outcomes.

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        Topics: embedded analytics, Business Intelligence, Data Governance, Data Management, natural language processing, data operations, Process Mining, Streaming Analytics, Analytics & Data, Streaming Data & Events, operational data platforms, Analytic Data Platforms, AI and Machine Learning

        I previously discussed the trust and accuracy limitations of large language models, suggesting that data and analytics vendors provide guidance about potentially inaccurate results and the risks of creating a misplaced level of trust. In the months that have followed, we are seeing some clarity from these vendors about the approaches organizations can take to increase trust and accuracy when developing applications that incorporate generative AI, including fine-tuning and prompt engineering. It...

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        Topics: Analytics, Business Intelligence, Data, Digital Technology, natural language processing, Analytics & Data, operational data platforms, Analytic Data Platforms, AI and Machine Learning

        It is a mark of the rapid, current pace of development in artificial intelligence (AI) that machine learning (ML) models, until recently considered state of the art, are now routinely being referred to by developers and vendors as “traditional.” Generative AI, and large language models (LLMs) in particular, have taken the AI world by storm in the past year, automating and accelerating the development of content, including text, digital images, audio and video, as well as computer programs and...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Data, Digital Technology, natural language processing, AI & Machine Learning, Analytics & Data, Analytic Data Platforms

        As we celebrate the first half of what seems to be the year of generative artificial intelligence, with an apparently unlimited discussion of use cases and bogeymen, my attention is turning to the very mundane question of costs. Specifically, how costs incurred – through investment and operation – will be distributed along the value chain and how this will affect the demand for AI ‒ by whom and for what purpose. It’s a question that needs asking even though, at this stage in the market’s...

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        Topics: Office of Finance, Continuous Planning, Business Planning, Enterprise Resource Planning, natural language processing, digital finance, AI & Machine Learning, Consolidate/Close/Report, Continuous Supply Chain & ERP
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        Our Analyst Perspective Policy

        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

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