How CIOs can take advantage of the AI revolution

The demand for AI extends beyond the classroom; leveraging it for enterprise-level solutions will be the next phase.
Victor Ekwere Jnr
Victor Ekwere Jnr
Victor Ekwere Jnr is the director for Innovation, Operations and Solutions at Oral Roberts University.

Artificial Intelligence (AI) has taken the world by storm. Global Market Insights predicts the AI education market will reach $20 billion by 2027. We are also seeing educators and students adopt AI faster than previous disruptive and transformative technologies. The demand for AI extends beyond the classroom; leveraging it for enterprise-level solutions will be the next phase.

CIOs and their network support engineers constantly have to find creative ways to improve their network configurations to support the ever-growing number of devices on campus. However, human knowledge and expertise have a limit and cannot adapt to the real-time network needs of a campus. This is where AI shines. AI can empower CIOs and their network teams to build future-ready campus networks that can automatically detect, diagnose and resolve network problems, thereby improving Wi-Fi coverage and performance across the network infrastructure. By tapping into the power of AI-driven solutions, campuses can stay ahead of the curve, providing reliable connectivity and facilitating a seamless learning experience for all stakeholders.

Challenges for CIOs to implement AI on a campus network

Similar to the adoption of disruptive technologies, the adoption of AI for managing campus networks will require a methodological approach in order to garner the approval and support of all stakeholders. Here are some common challenges to implementing AI on-campus networks:

  1. Legacy Equipment: Most AI technology will require modern equipment and higher ed is known for legacy technology due to limited resources. In order to leverage the automation and optimization that AI brings to a network, campus leaders will need to invest resources in upgrading network hardware and software.
  2. Budgetary Restrictions: AI implementation at an enterprise level is not cheap. CIOs and other C-suite leaders will need to prioritize investments in new network hardware that will be AI-compatible. More importantly, CIOs will need to demonstrate the return on investment of AI implementation by showing how it can cut operational costs, enhance productivity and improve user experience.
  3. Limited Expertise for Implementation: With AI being a new industry, network engineers implementing AI solutions will experience a learning curve and must be willing to adapt. Most importantly, CIOs must foster an innovative and experimental culture that will enable the network engineers to try out new AI solutions on the network.
  4. Privacy: CIOs and their network teams will need to master the art of communicating the benefit of AI being implemented across networks while reassuring the campus that adequate steps have been taken to ensure data privacy. CIOs and network engineers must tackle these issues by ensuring that any 3rd party AI solutions deployed on the campus network comply with relevant higher ed laws and regulations, such as the Family Educational Rights and Privacy Act (FERPA) and the General Data Protection Regulation.

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Oral Roberts University leveraging AI for the campus network

ORU has experienced 15 years of consecutive enrollment growth, fueled by the visionary leadership of the President, Dr. William Wilson. With this growth has also come an increased need to rethink how the campus network is managed on a day-to-day basis, from troubleshooting to dynamic scaling during peak times. Oral Roberts University is currently deploying AI solutions on its campus network by leveraging Extreme Networks CloudIQ CoPilot.

Extreme CoPilot makes troubleshooting easier by offering auditable recommendations and reducing the number of irrelevant alarms that waste the time and efforts of network engineers. Extreme’s CoPilot also provides explainable insights, allowing network engineers to examine, evaluate and trust the evidence underlying each advice. One of the interesting features of CoPilot is its ability to continue learning and provide bidirectional communication, ensuring that network teams are receiving the best and most accurate advice about their network.

As academia continues to grapple with the speedy advancement of AI, CIOs must be willing to step up and educate their campuses on practical use cases of this groundbreaking technology. Ready or not, AI is here to stay. Also, choosing the right vendors will be vital in rolling out any AI solutions for campus networks.

By leveraging the expertise of vendors in the AI space, universities will be able to close the talent gap prohibiting many institutions from making any progress with AI technologies. Finally, just like with all new transformative technologies, AI is still evolving and far from its full potential. Higher ed tech teams must remain flexible and ride the wave of every evolution by maintaining an investigative and explorative mindset during this technological revolution.


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