Is your healthcare business ready for AI?
With the extraordinary rise of artificial intelligence (AI) over the past few years, a recent report revealed an alarming trend: many companies do not believe their IT infrastructure has the scalability, flexibility or manageability required to support the very AI technologies they are working to deploy.1
AI has the potential to transform healthcare, but it depends on a network that can handle the load with agility and speed. Explore these four actionable steps that will help ensure your network is AI-ready to deliver personalized, secure, 24/7 access for patients, providers, employees and more.
Enable seamless healthcare processes with scalable, high‑speed networking.
Expand your bandwidth.
AI applications can provide medical practitioners with a real-time, holistic view of a patient’s health status, but they require high-speed data transmissions and more bandwidth than legacy infrastructure can provide. Without a reliable, modern network, healthcare companies could face delays when processing, analyzing and acting on the data that is at the core of AI applications.
Improve operational efficiency.
92% of healthcare leaders see the promise of Generative AI for improving efficiency.2
Reduce the risk of a devastating cyberattack or regulatory error.
Avoid breaches, frauds, and fines.
Healthcare companies handle vast amounts of confidential information that is extremely valuable to threat actors. This is why healthcare AI models are ripe targets for model manipulations and data poisoning, which can leave your organization more vulnerable to attack. At the same time, you must ensure your network complies with a complex and dynamic regulatory framework.
Maintain data integrity and business uptime.
In 2024, the average cost for a breach in the healthcare industry was $9.8 million, making it the most expensive industry for responding to and recovering from a data breach for 13 consecutive years.3
Bypass data bottlenecks.
Traditional network infrastructure can’t keep up with the AI-driven influx of data. This creates bottlenecks as data move inefficiently across a dispersed network to a data center and back. Failure to modernize can cause delays across healthcare environments, which can be particularly detrimental during emergencies or in diagnostic situations where real-time decisions are made.
Minimize latency and maximize speed with edge fabric.
Omdia’s AI Network Traffic Forecast, 2023-33 Report predicts that by 2027, AI will be involved in the majority of application content carried by telecom networks.4
Drive fast ROI with expert guidance.
Keep your systems running smoothly.
Uptime is money, downtime is expensive, and both impact revenue and your reputation. Inefficiently implemented AI systems can become unreliable and frustrating for providers, patients and your employees as they experience delays and inaccuracies. Unmonitored security vulnerabilities can also expose sensitive healthcare data to cyberattacks and bring down the system.
Partner with an award-winning, trusted adviser.
AI implementation will likely fail without expertly designed network infrastructure that supports the powerful AI tools that are quickly spreading throughout the healthcare industry. The right partner can help you implement future-ready network solutions without the need to upskill or increase headcount, so you can put your AI tools to work to help increase revenue, lower costs, create seamless, meaningful user experiences and minimize risks.
