IT Infrastructure And Operations: Meeting The Mandate For Today’s Enterprise
Posted May 1, 2025 by Sayers
IT infrastructure and operations leaders face a daily hustle to drive innovation, security, and scalability for business growth. Such a mandate requires staying ahead of technology trends and disruptions.
From AI to hybrid cloud, key I&O themes continue to grab headlines and challenge I&O leaders to deliver for their organizations.
AI: GenAI Early Adopters Aim To Move Beyond Strategy To Production
Will generative AI drive the next wave of digital transformation in enterprise IT? According to the 2025 Nutanix Enterprise Cloud Index Report survey of IT, DevOps, and platform engineering decision-makers, 85% already have a GenAI strategy in place.
However, half of those leaders aren’t yet prepared to move from strategy to production:
- 52% acknowledge the need for more IT training related to GenAI
- 48% believe their organization needs to hire new IT talent to support GenAI
- All but 5% believe they could do more to secure their GenAI models.
Early adopters looking to build their AI capabilities in-house include those in the legal, manufacturing, finance, and healthcare sectors. The top challenge they face in scaling GenAI workloads is integration with existing IT infrastructure.
As companies consider investing in IT infrastructure to support GenAI, they’re looking at the benefits they can achieve in efficiency, productivity, and automation. Law firms, for example, can use GenAI to generate contracts more quickly and cost-effectively.
Kevin Finch, Senior Business Resiliency Architect at Sayers, says:
“A law firm needed to write a multi-jurisdictional contract. They wanted to have GenAI go through all the applicable statutes and then write a statutes-compliant contract. Lawyers bill at several hundred dollars an hour for that kind of work, so if they can get AI to generate it in 15 seconds, they’ll want to do that.”
Chinese AI startup DeepSeek drew headlines this year with the release of its open-source R1 large language model. The AI model demonstrated higher efficiency at a lower cost to create compared to rival technologies. But those headlines evolved to cautions about security and privacy concerns, plus questions about the actual cost and equipment used.
The potential for data leakage outweighs potential productivity if not securely leveraged. Doug Close, SVP of Solutions at Sayers, says:
“DeepSeek has some definite efficiencies, and it’s open source so anybody can validate the code. Don’t use the actual app they provide because of the security concerns. But nothing stops you from taking the open source code and running it in air-gapped isolation to be sure it’s secure in your own environment.”
Cyber Resiliency: Going Beyond Disaster Recovery
Organizations continue to grapple with ransomware and other cybersecurity events. According to Cybersecurity Ventures and the World Economic Forum:
Global cybercrime is expected to cost $10.5 trillion annually by 2025. To put it in perspective, if annual cybercrime were a country, it would have the third-largest gross domestic product (GDP) worldwide, behind only the U.S. and China.
Proofpoint’s 2024 Voice of the CISO Report found 70% of CISOs feel at risk of experiencing a material cyber attack over the next 12 months. Nearly a third rate the risk as very likely.
What’s the difference between cyber recovery and disaster recovery? At a high level, consider these two scenarios:
Disaster Recovery. A natural disaster, power outage, or hardware failure leaves your data center unavailable. You restore your data onto fresh hardware using a recent backup copy of your data.
Cyber Recovery. A cybercriminal has breached your data, installed ransomware, or perpetrated another malicious digital attack. You minimize the spread through your environment and then restore an uncorrupted copy of your data to get back up and running.
Finch, who offers more on DR vs. cyber recovery in his blog, says:
“One of the big differences between traditional DR and cyber recovery is in a cyber recovery situation, you don’t know if you can trust your data backups. That’s one of the first things ransomware attacks go after. You need an immutable copy of your backups, preferably air gapped, to prevent someone from getting into and corrupting it before you can pull it back into your environment.”
With rising cybersecurity threats, data protection companies are emphasizing their ability to address both disaster recovery and cyber resiliency with solutions spanning infrastructure and security.
Partnerships in this space include Microsoft’s recent equity investment in Veeam Software to develop AI-powered solutions that enhance data protection and recovery. The partnership integrates Microsoft’s AI services into Veeam’s data resilience platform.
Platform Engineering: Moving To Self-Service Infrastructure
Infrastructure platform engineering (IPE) holds the promise of orchestration and automation capabilities that can deliver software applications into your IT infrastructure more quickly and reliably.
IPE emphasizes automation, observability, portability, and self-service portals, regardless of whether you’re in the cloud or on premise.
Last year HPE acquired Morpheus Data, a software platform that empowers DevOps teams with self-service access to provision workloads. By fully integrating Morpheus with HPE GreenLake cloud and HPE’s private cloud portfolio, the solution simplifies multicloud and hybrid IT management with self-service provisioning and unified control.
Hybrid Cloud: Infrastructure And Operations Remain Relevant Here
Wherever your company is in its cloud migration, workloads dispersed throughout a hybrid cloud model bring an array of I&O topics to consider. Among them:
- Platform engineering involving automation and containers
- Networking options such as network segmentation and network as a service
- Data protection tools outside of native cloud backups
- Business resiliency and ransomware readiness.
Current AI proofs of concept are mostly cloud-based, allowing organizations to determine their ROI before they purchase equipment and build out actual infrastructure.
Mark McCully, Director of Modern Data Center Engineering at Sayers, says:
“For now, most companies are starting their Generative AI initiatives in the public cloud using tools like Azure AI Foundry or Microsoft Copilot to prove out use cases and determine ROI. When companies are ready to move GenAI workloads from public cloud into more of a hybrid-cloud or on-prem model, HPE and Dell are making it as easy as possible to do so with consumable, purpose-built reference architectures, so you can start small and “pay as you grow” with your GenAI environment.
Questions? Contact us at Sayers today to discover extensive technology solutions, services, and expertise to cover all areas of your business.
