Innovation in AI Technology Will Accelerate AI Adoption
85 percent of enterprises believe investing in GenAI technology in the next 24 months is critical, a new ISG report finds
The ISG AI Platforms Buyers Guides, produced by
The ISG report notes that hiring and retaining experienced AI professionals is the biggest IT resource challenge and the biggest impediment to enterprises adopting AI on a broader scale.
“Enterprises need objective, independent assessments of AI software providers,” said
The most common tasks where GenAI is being applied include natural language processing (NLP) such as chatbots, copilots and assistants, extracting information from and summarizing documents, and assisting with software development tasks such as code generation and application migration. GenAI is expected to have a bigger impact in these areas than predictive AI.
While the rise of GenAI has been meteoric, enterprises still plan to invest one-half of their AI spend on predictive or traditional AI. Predictive AI is expected to have a bigger impact in areas such as credit risk, fraud detection, algorithmic trading and customer acquisition.
Developing and deploying AI models is a multistep process, beginning with collecting and curating the data that will be used to create the model. Once a model is developed and tuned using the training data, it needs to be tested to determine its accuracy and performance. Then the model needs to be applied in an operational application or process.
The study notes enterprises need to monitor and maintain the models, ensuring they continue to be accurate and relevant as market conditions change. In the case of third-party Large Language Models (LLMs), providers are constantly updating and improving their models, so enterprises need to be prepared to deploy newer models as well.
Software providers have slowly recognized that a lack of Machine Learning Operations (MLOps) and LLMOps tooling was inhibiting the successful use of AI. AI software providers have expanded their platforms to address many of these capabilities, and specialist providers have emerged with a focus on MLOps/LLMOps.
The ISG AI Platforms Buyers Guides are designed to provide a holistic view of a software provider’s ability to serve a combination of traditional AI, GenAI and MLOps/LLMOps workloads with either a single AI platform product or a set of AI platform products. The AI Platforms Buyers Guides include the full breadth of overall AI capabilities and considered whether the capabilities were available from a software provider in a single offering, or a suite of products or cloud services.
For its 2024 AI Platforms Buyers Guides, ISG evaluated software providers across three AI platform categories – AI Platforms, GenAI Platforms and MLOps/LLMOps – and produced a separate Buyers Guide for each. A total of 30 providers were assessed:
AI Platforms: Oracle, AWS and IBM
GenAI Platforms: Oracle,
MLOps: Oracle, AWS and
”We are seeing dramatic changes in technological innovation related to the use of enterprise software for AI, with platforms designed to support a range of requirements for GenAI and Machine Learning,” said
The ISG Buyers Guides for AI are the distillation of more than a year of market and product research efforts. The research is not sponsored nor influenced by software providers and is conducted solely to help enterprises optimize their business and IT software investments.
Visit this webpage to learn more about the Buyers Guides for AI and read executive summaries of each of the three reports. The complete reports, including provider rankings across seven product and customer experience dimensions and detailed research findings on each provider, are available by contacting
About
About ISG
ISG (
View source version on businesswire.com: https://www.businesswire.com/news/home/20240625287540/en/
Press Contacts:
+1 203 517 3119
will.thoretz@isg-one.com
+1 978-518-4520
isg@matternow.com
Source: