Accelerate Enterprise AI Adoption With a Center of Excellence

Artificial intelligence and machine learning are all the rage right now. No matter what industry you’re in, deploying AI applications is becoming a business imperative and many organizations are finding that establishing an AI Center of Excellence (COE) can help them cope with the new technologies and skills needed to help them meet their objectives.

There’s no doubt future business operations will be increasingly dependent on AI/machine learning technologies. As enterprises grapple with deploying AI strategies, AI COEs are emerging to help them figure it out.

If you want to make enterprise AI adoption a success, you “should set up a COE focused initially on informing, persuading, enforcing or innovating products and services, but expect its goals to evolve as AI usage matures,” according to Gartner.

Starting the process

What exactly is a COE? Essentially, it is a framework for helping organizations research and learn about new technologies, skills and disciplines that are not yet tried and true by forming strategies and methodologies around AI. Its members can include CIOs, chief data officers and chief technology officers, as well as data scientists and systems architects.

But setting up a COE first requires understanding what you want to accomplish. Although it is a place for conducting research and experiments, it should also deliver business results, applications and a program for how to use AI software in your organization.

There are three components to consider when formulating a COE: AI business innovation, AI policies and governance and skills, notes SearchCIO.

Like any new system, you want to understand the pain points that lines of business have and how a COE can make a difference.

A COE should address enterprise AI adoption by analyzing business objectives, market demand and customer need, according to Forbes.

Different flavors

There are different styles a COE can take, Forbes points out. One is building a shared database so that all members working on an AI project have access to data. Often, organizations have a siloed approach when it comes to where data is housed and different repositories, depending on the department. But there should be a culture of treating all data as an asset. You must be able to collect, distribute and validate data in formulating AI applications, stresses Medium.

Another style is to build a team of experts with niche AI skills. The team is generally tasked with developing and integrating AI applications and sharing ideas with other employees to enhance their knowledge of AI.

Yet, this could prove to be your biggest challenge. It’s no secret recruiting and retaining AI talent is a time-consuming process. You need to get HR involved in finding individuals with AI skills and convince executive sponsors why this is necessary or your business risks falling behind on deploying AI.

A third approach is for the COE to mandate the way AI will be implemented in the enterprise. The team approves vendors, experts and the types of technology that will be put into effect to deliver specific applications and achieve business objectives, Forbes says.

Results driven

A COE doesn’t necessarily have to have a physical location. There are some schools of thought that COEs are just as effective with people contributing and collaborating from wherever they are located to address business challenges. The key is ensuring someone is tracking progress.

Leadership will want to see measured progress and it should be transparent and comprehensive, advises Medium.

A key step toward establishing a successful COE is to build prototypes with a long-term view and enhance ecosystems and partnerships to promote purposeful artificial intelligence use cases, the site also recommends.

If your organization is serious about being proactive with AI, establishing a COE is a great place to start. Take a look at what you have internally in terms of staff and existing products and services. Utilize cloud stacks if you don’t have infrastructure internally and start building good data strategies.

All business operations should be utilizing AI and machine learning to stay competitive. A COE provides structure, oversight and accountability and prioritizes how AI initiatives will be carried out.

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