The enterprise guide to securing and scaling AI

3 challenges of AI implementation — and how a connectivity cloud can help

For many enterprises, the return on AI investments is still forthcoming. AI technology spans a wide range of use cases and is often complex and resource-intensive to build, scale, and secure — which can have a tangible impact on enterprise-level earnings.

In The enterprise guide to securing and scaling AI, we dive deeper into each of these challenges (and provide practical strategies for moving past them), including…

Why enterprises struggle to meaningfully build AI infrastructure at scale
How hyperscalers fall short of enterprise expectations
What security issues affect AI usage and reliability

What areas of your organization’s cybersecurity do you have responsibility for? Please select all that apply. *

Executive level strategy and planning

Security Leadership (e.g. defining organization’s security posture)

Security Management (e.g. running day-to-day of security team)

Technical (e.g. providing technical support expertise in areas such as engineering, architecture, response, intelligence)

None

What strategic initiatives are a priority for your organization? (Check all that apply)*

Network modernization

Modernizing application development

Reducing tech complexity through consolidation

Holistic, intelligent threat defense

Data protection and compliance

Data visibility and localization

Integrating AI into IT, security, and engineering operations

Other

What does your current technology vendor landscape look like? (Check all that apply) *

Cisco

Zscaler

Palo Alto Networks

Akamai

Homegrown technology solutions

Other/do not know

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