AI Ready Data is an Adaptive Challenge

Leadership is all about handling adaptive challenges.

It includes being prepared with an innovative mindset, finding appropriate ways to solutioning previously unsolved problems using appropriate tools. Planning to address unknown, hidden and difficult to initially comprehend situations is a significant part of such challenges.

Having your ducks of facts, contexts, previously solved problems, among other things in a row significantly reduces your business and technical complexity in addressing adaptive challenges.

The tech industry has embraced AI as a service and solution enabler, among others, putting it on the map of critical capabilities.

AI impacts the operating model of both business and technology capability delivery. However, stakeholders are responding to this change impact, mostly, differently.

Some large Tech Services companies have carved out a separate line of business, whereas a few others have taken a matrixed approach. A financial giant, in its technology competencies have taken a mixed bag approach with changes in its technology ops where implementation services are separated and centralized horizontally with LOBs having business focused SMEs in specialized vertical AI Teams per LOB.

Data, Measurable Vertical Models, Matrixed AI Ops Models among others are trending with COO, CIO and CTO becoming partners in such competitive initiatives.

Translating solutions and visions into great analytical and User Experience for adaptive challenges, you must invest in Enterprise Data Backbone to become AI Ready beyond garnering optimal AI and ML Operations and related capabilities.

Suboptimal data preparations result in costlier, longer and higher complexity technical journey and therefore missed outcome expectations. It will reduce productivity, draw wildly at creative and innovative organizational juices at crunch time reducing your speed of delivery.

AI Ready Enterprise Data empowers orgs to connect and remediate the locked up or data with challenged access across disparate, federated and distributed models and architecture marred with many known and unknown anomalies. A data ready enterprise will always have the potential for business and technical users to relatively easily and with speed analyze enterprise data, build apps, produce outcomes to meet their business and technical objectives and goals.

Realizing this aspirational outcome is a matter of approach, arguably with making your Enterprise Data AI Ready as one of the top significant steps.

Where are you on the roadmap of being AI Ready with your Enterprise Data?

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