An AI Center of Excellence for your Business
Just within the last decade, advancements in AI technology have been greatly reshaping and optimizing organizations. Harvard views that AI will become a permanent fixture in the business aspect. If sustained, it will be able to develop and support potential new business models and capabilities.
The use of AI can vary around organizations including, but not limited to:
1. Customer Service
- Chatbots- do away with having to pass calls from one person to another just to answer one question.- For FAQs, immediate answers can be provided.
- Helpdesk Apps- An app clients can go to for immediate and direct help and assistance.
- Facial Recognition- Immediate detection of guests from regular team members.
- Cyber Security- Secure websites, and other forms of online data being easily accessible to hackers.
- Schedule blocking
- Inventory- Tracking resources, predicting shelf-life/span.
- Information Database
4. Sales and Marketing
- Digital Marketing- Machine learning tools can garner data to help predict the right demographic, and what platform to use.
- Ad Management- Optimize a single ad, and manage ad budgets for multiple platforms.
- Predictive Analytics- Assess, summarize, and challenge the valuation assets.
6. Human Resources
- Application Screening- Automated screening process for applicants for faster and more efficient placement, communication, and scheduling of interviews.
- Company Culture- Machine learning tools can gather data regarding behavior and trends around team members inside the organization.
Making all these possibilities of improvement happen is exactly what an AI Center of Excellence is for.
An AI Center of Excellence is, simply put, the designated support groups that configure and establish the right AI tools need to push business growth and progress. They are the builders of models, systems, and technical infrastructures in collaborating with vendors, clients, and/ or business leaders.
How does an organization establish an AI Center of Excellence?
1. Create your vision- Executives must discuss the objective of the AI COE. What should technology achieve? How will it elevate business?
2. Identify business-driven use- cases- Developers need to create a list of prioritized use-cases or applications within the organization. There must be a balance between strategic value, and what’s achievable. Prototypes for these use- cases can be developed, but a regularly monitored “pipeline” must lead to production deployment.
3. Have an appropriate amount of ambition- It is best for the Center of Excellence to focus on tasks that are more possible than ambitious. COE should create a road map of multiple uses – cases across the timeline consisting of small projects that create big impacts for the organization(Think big, act small).
4. Identify Data Architecture- Identifying the vision and he use-case can help determine the appropriate Data platform needed. Examples of platforms: Hadoop– the standard for data management, Alteryx—user-ready platform, AWS).
5. Network for External Innovation- Create relationships with universities, vendors/ suppliers, and other experts on AI for innovation. Having an external network can help assure that the tools and technology being used are the best for their objective.
6. Internal Network of AI Champions- COE will work best if it cultivates a network of influential supporters and champions for the technology within the organization.
7. Share Success Stories- Sharing significant achievements can build excitement, motivation, and entice more function in the AI Center.
With the proper game plan in mind, how do managers and leaders pool for talent for their COE? Finding those with a background in Computer Science would be a great place to begin. They can develop and implement the algorithms, while MBA- level analysts and those fluent in AI can carry on the business applications. Recruiting consultants with previous experience in AI will be very beneficial as well. Another option managers can consider is building in-house talent from scratch, and train established team members.
Pushing forward, a good organizational structure needs to be established to develop a professional process and avoid bureaucracy. In most cases, a centralized structure with deployed units all over the organization where AI is expected to be common is recommended for greater job satisfaction and retention of roles. Short terms deliverables and frequent meetings are a must for the central unit to be familiar with each issue, project, and to allow collaboration and transparency with executives. Leaders should always check- in with the COE to avoid ethical issues.
The reality is, technological advancements change the world rapidly every day. Businesses big or small have to keep up. An AI Center of Excellence gives an organization potential to optimize operations, improve the structure, production, and output. Large, non-IT companies such as JP Morgan, Pfizer, and P&G have started to establish their own COE. Take advantage of these modernizations and explore how much more progress and efficiency your business can create.