The AI Center of Excellence: It’s Not What You Think It Is
In the AI era, AI CoE guides enterprises through tech evolution, ensuring adaptation and thriving in this dynamic field.
Dr. Debbie Qaqish explores the crucial role of AI Centers of Excellence (AI CoE), comparing them to traditional models. She highlights their unique importance in fostering innovation and adaptation during the AI era.
I’ve had a front-row seat to some of our most significant technological evolutions. The journey has been remarkable, from transitioning from a landline with a rotary dial to a cell phone, which I now call my ‘life device.’ I recall the early days of the internet, when I, as a road warrior, would rearrange hotel furniture to find a phone port for VPN access to my server. I remember when my eldest daughter first used MySpace to chat with a high school friend and how I was puzzled by the concept of an ‘app’ in the early iPhone days.
Professionally, my first encounter with a marketing automation platform was in 2004. The Eloqua demo stunned me, so I bought and integrated it with Salesforce in the same quarter (I was customer #12 for Eloqua). And I vividly recall moving technology from on-prem to the cloud. There have been so many significant changes in technology.
But nothing was as earth-shaking as the release of ChatGPT on November 30, 2022. Once I started exploring the various possibilities of AI, I was astounded. The closest analogy I can think of is watching Captain Kirk in the early Star Trek episodes, using his communicator, reminiscent of an early flip phone, to talk to his ship in orbit and coordinate beaming back onboard.
In other words, the evolution of AI is unparalleled and will be unpredictable for quite some time. We are in an unknown territory. In this transformative era, two structures are crucial for success: an AI Council and an AI Center of Excellence (CoE). This article focuses on the latter, contrasting it with traditional models and underscoring its unique significance and value.
AI Council vs. AI Center of Excellence
To discuss an AI CoE, I need to mention an AI Council. Both structures are necessary and serve different yet complementary purposes. The AI Council manages risk and ensures compliance with AI policies, guidelines, and ethical standards.
In contrast, an AI Center of Excellence is a structure for instilling new work processes comprised of ongoing experimentation and continuous change; so far, it is not a responsibility we typically equate with a CoE.) These new work processes enable the company to build AI competencies and capabilities. The AI CoE is a proactive force driving AI support, development, and training in best practices and core processes. These two structures will need to work closely together for the foreseeable future.
The Unprecedented Nature of AI
There are significant differences in how AI is currently evolving versus other technological predecessors:
- Rather than thriving in a step-chain and continuous improvement model, AI necessitates an environment and set of work processes based on ongoing and big changes.
- Because no one can predict how AI will continue to evolve, it is a ground-up, not a top-down, initiative.
- Unlike other CoEs set up to implement and use a particular technology, an AI CoE requires more leadership, resourcing, and budget.
The Obsolete Models and Continuous Change
Marketers live and work in a tech-driven world. The typical marketing team deploys over 30 different technologies, and they’ve been tech-fluent for years. Given this experience, marketers have developed a format to pilot, test, customize, implement, and train on new software. AI throws all of this process out the window. But why?
All prior technologies came with a stable platform that evolved by adding new features and functions. Further, these other technologies subscribed to a defined set of use cases. With a clear path of use and predictable evolution, the CoE for this technology was about implementation, best practices, optimization, and training.
However, AI shatters this predictability. It demands a very different kind of CoE, one centered on continuous, managed experimentation that drives learning, application, and change in a constant cycle. The journey with AI is perpetual, necessitating readiness for abrupt, and evolving to change. This dynamic requires a paradigm shift in approaching technology adoption and integration.
See More: Achieving Digital Agility Through Change Management
Leadership and the Bottom-up Approach
AI defies the conventional top-down technology implementation model. With prior technologies, leadership had a distinct problem that needed solving. They had a process for evaluating and selecting technology and had timelines, goals, and results defined. It was a top-down effort involving the hands-on people in the most tactical ways. Throw all that away with AI because we don’t know what we don’t know.
The predictions and prognostications can’t come from the top – they must come from the hands-on folks working in an environment of managed and continuous experimentation. The hands-on users are responding to the latest changes, developing new use cases, and gathering the learnings and insights they share up the chain. This grassroots knowledge generation is pivotal to AI’s successful integration and application across organizational levels.
Finally, this is a new way to conduct business for many organizations. How can leaders prepare for this new dynamic? By instituting an AI Center of Excellence.
Leadership and Dedication
I’ve watched many companies create and use all variations of a center of excellence. These cases shared the perception of the Center of Excellence as a nice-to-have rather than an essential must-have. CoE members participated in their free time, and primary workloads took precedence over any work for the CoE. Meetings were sporadic, and CoE members seldom shared best practices.
The AI CoE requires a more stringent approach with leadership and dedication. The executive sponsor or AI CoE leader needs clout and power to make things happen and happen quickly. Leadership is closely connected with the CoE, so as new learnings, insights, and information are gleaned, they can be used to create or change strategy, branding, go-to-market motions, and more. Think about how this information dynamic upsets standard corporate protocols. This will be a powerful dynamic.
More dedication relates to this CoE being an intentional, empowered, resourced, financed, structured, and incented structure. Working in an AI environment takes more time away from the primary job and more time to think and reflect. It requires new skills and agile processes. It requires new levels of collaboration and communication – especially for those employees threatened by AI. Finally, it requires new incentives – ways to motivate excellence in this new environment.
See More: Ineffective Leadership Is the Top Reason Leaders
Are You Ready?
The AI CoE is not just another organizational structure; it’s a vital mechanism for navigating the AI revolution. Unlike traditional CoEs, it demands continuous learning, a grassroots approach, strategic leadership, and deep organizational commitment.
As we venture further into the AI era, the AI CoE stands as a beacon, guiding organizations through uncharted technological landscapes and ensuring they adapt and thrive in this new, dynamic world of AI.
Are you looking to elevate your organization with an AI Center of Excellence (CoE)? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
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