Partner with the IBM AI enterprise accelerator to replicate AI capabilities

Data strategy

Start with understanding your business strategy. Then, create a data strategy that aligns AI and data resources accordingly. This is your compass for all future data-driven AI initiatives.

AI enterprise data architecture

The bedrock of an AI enterprise is formed by two entities: A multicloud architecture plus associated workflows for seamless integration and movement of data across AI and analytic workloads.

Automated metadata generation

Generate metadata automatically for your AI enterprise data lake by using deep learning and natural language understanding.

The AI enterprise accelerator offers five foundational IBM showcases for you to replicate. These showcases serve as examples of where and how AI-transformed business processes generate value.

Data privacy

Deploy AI resources and automation that address data privacy regulations such as GDPR. A framework for governance, security, communication and automation can provide strong support for current and future data privacy regulation compliance.

AI applications

AI sales enablement
Get a 360-degree view of clients with AI-powered seller recommendations. The view can be used throughout your enterprise as the “single truth” for client insights, and is coupled with product insights that are delivered through an AI-powered chatbot.

Contractual insights
Use annotators and machine learning for proactive client contractual relationship management and expansion management.

Risk insights
AI lets you identify how natural disasters and other disasters will impact your data centers and supply centers in real time.

Start your journey today

Work with the IBM Global Chief Data Office to implement these solutions. Jumpstart your journey to becoming an AI enterprise.

What is a cognitive enterprise?

IBM leaders on extracting value from data

Beth Smith, GM Watson Data and AI, and Inderpal Bhandari, IBM Global Chief Data Officer, talk about how companies can identify and scale projects where there is value to be gained from data.

Infrastructure for the end-user

Ed Walsh, GM of Storage, IBM, and Steven Eliuk, VP of Deep Learning, IBM GCDO, cover simplifying architecture to make data-driven insights easier to achieve.

Harnessing data starts with breaking down silos

Asim Tewary, Head of Data Science and Advanced Analytics, Verizon, and Seth Dobrin, VP and Chief Data Officer, IBM Analytics, stress the importance of businesses working together internally to truly transform into an AI enterprise.

Leading industry analyst weighs in

Brandon Purcell, Principal Analyst at Forrester Research, joins Caitlin Halferty, IBM Client Engagement Executive, to discuss the future of AI, data privacy, and more.

IBM cognitive enterprise data architecture

A detailed view of the CEDP architecture

Discover how your Chief Data Officer can help harness the power of data

It’s a slam dunk: the NBA and IBM

IBM Global Chief Data Officer Inderpal Bhandari created a program that analyzed data from NBA games and found patterns to help teams optimize their lineups and rotations during playoff games. Orlando Magic coach Brian Hill used insights gleaned from data patterns to slow down "Mr. Crossover," also known as Tim Hardaway Sr.

Contact our Global Chief Data Office

Embark today on your journey to become an AI enterprise.