How To Create an Enterprise 'AI Center of Excellence'
The strategy of establishing a "center of excellence" (CoE) to entrench artificial intelligence (AI) in an enterprise to meet business objectives is gaining momentum in the new year.
While an AI CoE has no official definition, it has to do with organizations centralizing AI resources and initiatives to infuse AI tech throughout workflows and process, providing the resources needed for executing predetermined business objectives with the help of AI. While not specific to AI, Wikipedia provides this definition of a generic CoE: "a team, a shared facility or an entity that provides leadership, best practices, research, support and/or training for a focus area."
When the focus area is AI, there are numerous sources of guidance, which has already picked up in the new year. Here's a roundup of recent advice, opinions and commentary on the idea:
How to Set Up an AI Center of Excellence
Just yesterday (Jan. 16), Harvard Business Review published this article by Thomas H. Davenport, professor, research fellow and senior adviser at Deloitte Analytics, and Shivaji Dasgupta, a managing director and head of Data Architecture and Smart Analytics for Deutsche Bank's Private and Commercial Bank.
"We believe that companies need to establish dedicated organizational units to entrench AI," the authors say. "This is an important business tool that cannot be left to bottom-up whimsy. Companies are devoting considerable financial resources to AI, and necessary skills and experience are too rare to assume that they will be scattered around the organization with little coordination or collaboration. Just as e-commerce led to Chief Digital Officers and groups to support online presence and commerce, we believe that AI will engender new competence centers (CC) or centers of excellence (COE), and new roles within them."
The duo provide tips on: what an AI team should do; acquiring and building talent and organizational structures and processes. Under the first category, they go into detail on the following suggested actions:
- Create a vision for AI in the company
- Identify business-driven use-cases
- Determine the appropriate level of ambition
- Create a target data architecture
- Manage external innovation
- Develop and maintain a network of AI champions
- Spread success stories
The piece also touches on ethics: "Companies may want to establish ethics-related positions or review boards as a part of their AI efforts. Microsoft, for example, has created an 'AI Ethicist' role to guide businesses on such issues as algorithmic bias and the impact on consumers of AI applications."
Derive Maximum Value from Artificial Intelligence with a Center of Excellence
Just today (Jan. 17), Naveen Joshi published this advice in Forbes, with the central theme being: "The key to making the most of artificial intelligence is to build the right center of excellence (CoE) that supports organizations by driving artificial intelligence initiatives from formulation to execution."
Tips included in the article by the founder and CEO of engineering and technology solutions firm Allerin include:
- Executive sponsorship is necessary from business leaders like CDOs, CIOs and CTOs
- For CoE success, organizations should hire a team having niche technical skills
- As the technology matures, experts should modify the CoE's goals too. Hence, the artificial intelligence CoE should be flexible
- Experts should analyze the critical series of problems that artificial intelligence can solve for them, then assign the roles and responsibilities to the appropriate talent
- See to it, that for experts to train an artificial intelligence model, there is enough data available
"Companies must follow the right procedure to adopt the technology successfully," Joshi said. "No doubt, artificial intelligence has smoothly made its way into larger organizations, but what about the medium-sized companies or startups? Medium-sized organizations and startups lack the right infrastructure, expertise, funds, and other resources. The simple and most straightforward way for such organizations to adopt artificial intelligence is via a center of excellence (CoE). A CoE will allow organizations to drive innovation and growth in business by equipping experts, selecting the right artificial intelligence initiatives, and guiding AI implementation in organizations lacking necessary resources."
How to Set-up an Artificial Intelligence Center of Excellence in Your Organization?
Written by Yogesh Malik in April 2018, this post for The Startup on the Medium site examines why organizations need CoE, strategies to create them, building teams, making data actionable and more.
Included in the strategies section is:
- Securing executive sponsorship
- Finding the right team
- Capture benchmarks that can demonstrate value
- Find the right problem
- Leverage data to solve problems
- Build repeatable AI solutions
"So, tired old management advice on starting a COE won't cut it, your approach must be unique and strategic for AI initiatives," Malik concludes. "Building an 'AI first' culture or 'AI first' policies could be very challenging, but without any delay you need to start looking at your organization's existing products and services through the lens of artificial intelligence. You need to start building good data strategies and create unique data sets so that you are ready with a failure-proof artificial intelligence center of excellence."
A Center of Excellence – The Vehicle for AI in the Enterprise
This May 2018 article on the site of Ayasdi Inc. says that "the future of all business operations fundamentally relies on utilizing AI and machine learning technologies."
A CoE, of course, is a good way to secure that future, and author Gurjeet Singh explores: what AI is; what makes an AI platform; why you need a CoE; the mission of a CoE; and more.
Singh describes a CoE as a vehicle or framework of execution that will differ among organizations but includes the following consistent themes:
- Value Management: Ensure the organization invests in valuable projects and derives optimal benefit from its AI investments
- Demand Management: Allocating resources (people, funding) across all projects in flight and monitoring spend. This will be critical as choosing the right projects is key as is funding them for success.
- Execution Support: The CoE supports various lines of business during its lifetime. This requires a provision of dedicated technical and subject matter experts, working together with operational resources from the line of business.
- Data management: Manage data through stages in its lifetime, from growth to maturity to a managed decline.
- Enablement: Provide systematic and iterative education by role, with support at every step in the form of classes and consultations.
- Application delivery: Delivery of business specific applications (and associated documentation) that integrate the workflow end to end, from incoming data, to output into downstream applications or dashboards.
Choosing the Right Center of Excellence Style for Integrating Artificial Intelligence
This is another Forbes article, penned last October by contributor Joshi, who this time, as the title suggests, focuses on different themes for establishing a CoE. These themes are centered around: creating a shared database; assembling the right team with the right skills; mandating the final practices for AI implementation in an organization; and innovating the AI-powered products based on the needs of the organization, customers, and the market.
Done right, Joshi says, the "right" CoE can provide the following benefits:
- AI adoption strategy
- Knowledge and guidance
- Regular AI coaching
- Business need analysis
- AI business use cases
- Optimum AI outcomes
- Reuse of data
"A center of excellence is a concept propelled by organizations that have skillful teams of experts responsible for offering leadership, best practices, techniques, training, advice and more to achieve success," Joshi says in this post. "By analyzing business objectives, market demand, and customer needs, a center of excellence can focus on uncovering the right AI business use cases to drive organizational growth. Most importantly, a center of excellence is open to modifications and upgrades in technology, resources, competencies, and AI offerings."
With new guidance already accelerating in the new year (two new articles in the past two days), 2019 will likely see more enterprises adopt the CoE approach to leveraging the exciting new developments in the AI space.
David Ramel is an editor and writer for Converge360.