Remove Automation Remove ESG Remove Machine Learning
article thumbnail

How the right data and AI foundation can empower a successful ESG strategy

IBM Journey to AI blog

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

ESG 259
article thumbnail

IBM named a leader in ESG reporting and data management software by independent research firm

IBM Journey to AI blog

Independent research firm Verdantix recently identified IBM as a leader in their report, “ Green Quadrant: ESG Reporting and Data Management Software ” (July 17, 2023), which evaluated and provided a detailed assessment of solution providers and their product offerings.

ESG 178
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Alibaba Cloud targets global AI growth with new models and tools

AI News

PolarDBs in-database machine learning capability eliminates the need to move data for inference workflows, which significantly cuts processing latency while improving efficiency and data security. See also: Amazon Nova Act: A step towards smarter, web-native AI agents Want to learn more about AI and big data from industry leaders?

ESG 184
article thumbnail

The five key benefits of AIOps and automation

IBM Journey to AI blog

natural language processing and machine learning models) to automate and streamline operational workflows. In this blog post, we will examine traditional IT operation problems through the lens of data-driven automation and the benefits of AIOps. It is the application of artificial intelligence (AI) capabilities (e.g.,

article thumbnail

Sustainability trends: 5 issues to watch in 2024

IBM Journey to AI blog

As more companies set broad environmental, social and governance (ESG) goals, finding a way to track and accurately document progress is increasingly important. 2 For example, some are turning to software solutions that can more easily capture, manage and report ESG data. The smart factories that make up Industry 4.0

ESG 283
article thumbnail

How deep industry expertise enables breakthrough technology for today’s complex business needs

IBM Journey to AI blog

AI-driven insights and automation are no longer an option but must-haves in industries like aviation, to achieve predictive maintenance of complex aircraft systems for improved safety and cost reduction and for energy companies to optimize production while reducing their carbon footprint.

ESG 222
article thumbnail

How to accelerate your data monetization strategy with data products and AI

IBM Journey to AI blog

Take the example of a client who integrated a set of disparate company ESG data into a new dataset. Their data services were a full dataset download plus an API wrap around the data, which could be queried for ESG data based on a company ticker symbol. Popular service consumption types include download, API and streaming.

ESG 315