3 must-haves for a data strategy to power AI

[ServicesExperts]

Unlocking the value of artificial intelligence and machine learning starts with aligning the strategic and human aspects of the initiative.

By Sean Foley, senior director and cloud transformation strategist for HPE’s Hybrid Cloud practice.

Businesses are strongly drawn to the competitive advantages that artificial intelligence and machine learning initiatives can create, and rightly so. These are powerful allies in the quest to deliver exceptional customer experiences and achieve ambitious business goals.

At the same time, companies often focus too narrowly on the technologies and tend to underestimate the strategic aspects – especially the data foundation – as well as the human elements that are crucial for success.

What are these key elements of the AI/ML journey? I describe three of them in a recent CIO.com article: Artificial intelligence needs people intelligence. They are:

1. A data strategy aligned to business goals. It’s worth taking some time to closely define what you want to get out of the project, as well as the associated timeframes, costs, and impact on other organizational priorities. Understanding these dimensions will help you see where your overall data strategy needs to change.

2. A modern data operating model. As data grows, the processes around maintaining it and consuming it can fail to keep pace if they’re not regularly reassessed against business goals. Take a close look at governance and service levels. How clean is your data? Which assets deliver a real competitive advantage, and which are just heavy lifting?

3. A strategy for skills, roles and functions. Evaluate the skills you’ll need for a data-first strategy to enable AI/ML, and consider how much of the project you want to tackle internally. Define a shared responsibility model for skills, roles and functions that are needed immediately, during the transition and after deployment. Decide where you want to upskill your team, augment with new hires, or leverage third-party experts.

I delve into each of these factors in more detail in the CIO.com article, illustrating the key capabilities for AI/ML deployments and how they map to the eight domains in HPE’s comprehensive edge-to-cloud operating model.

HPE can help you lay out your map for the AI/ML journey with a 360-degree view of the terrain. Learn more about HPE Pointnext Services and how we help you navigate what’s next.

Read more about technology services consulting from HPE – expert advice and implementation to take your digital transformation to the next level. 

Sean Foley is a senior director and cloud transformation strategist for HPE’s Hybrid Cloud practice.  He is a seasoned technology and business strategist with more than 20 years of experience in solving growth and transformation challenges for enterprises globally. Currently he focuses on providing digital transformation leadership and guidance in the adoption of cloud operating models and technologies for Fortune 100 companies.

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