There is boundless enthusiasm -- or perhaps relentless pressure -- to move to artificial intelligence (AI), edge systems, and more sustainable architectures. The problem is that many existing systems just won't cut it. Hence, a fresh wave of IT modernization is now underway, with renewed pushes to move from older on-premises systems to hybrid or multi-cloud services.

Also: AI adds new fuel to autonomous enterprises, but don't write off humans

Adoption of hybrid and multicloud clouds is expected to double over the next one to three years, according to a new survey of 1,500 IT executives commissioned by Nutanix. CIOs and IT leaders are pressing new platforms and architectures into service as rapidly as possible to support AI, edge systems, security, and sustainability. Close to four in ten respondents, 37%, say running AI applications on their current IT infrastructure will be a "significant" challenge.

"IT modernization," of course, is all relative and applicable to any era, because all legacy systems were once new systems. The meaning of modernization in 2024 context is to adopt hybrid cloud strategies to manage and run applications and data -- and to reduce some complexity and costs in the process (fingers crossed).

Tellingly, it's a top priority, the survey also shows. IT executives report that they're increasing investments in their first-ranked priority for the year, which is -- no surprise -- AI. Right behind AI on the priority list is IT modernization, which means more cloud.

Of course, these two priorities go hand in hand. AI is propelling this new wave of IT infrastructure modernization, with the goal of also achieving greater data mobility across core cloud and edge environments. Nearly all (99%) respondents say they plan to upgrade their AI applications or infrastructure, with more than half saying they need to improve the transfer of data between cloud, data center, and edge environments to support their AI initiatives.

Many industry leaders concur that AI is spurring a range of new investments across the board. "Because AI relies on data, a solid data strategy is needed for AI implementation," says Puneet Kohli, president of the application modernization business unit at Rocket Software. "In turn, automation can also play a helpful role in data governance and data management. Companies from all industries worldwide continue to increase investments in business process management, workflow, and robotic process automation, and accelerate operational transformations."

Also: AI is supercharging collaboration between developers and business users 

No modernization effort will succeed without the full engagement of the people working on the migration and new solutions, Kohli continues. "Modernization is about collaboration. While investing in the newest, shiniest tools can be exciting, no new solution will ever be the silver bullet for an organization. Instead, leaders must work to drive value in a way that positions their business for the long term -- which doesn't always mean adopting every trending technology on the market. Instead, successful modernization must be approached as a continuing endeavor that uses the best of what a business has and takes it to the next level."

Along with AI, the Nutanix survey finds edge computing is also taking center stage as a technology investment area in 2024. At least 90% of executives seek to strengthen their edge strategies, and 72% will be pouring more money into related technologies, be they additional server capacity, network gear, readers, or sensors. 

"Infrastructure deployment and management in edge locations is a critical ingredient of any AI/ML strategy," the study's authors point out. "Acceleration of AI solution adoption has the potential to catalyze an increased sense of urgency regarding edge infrastructure deployment -- especially as one ingredient of a hybrid multicloud infrastructure -- to support faster processing and access to data which supports real-time processing."

Also: AI is changing cybersecurity and businesses must wake up to the threat

The challenge to moving to the cloud is that "lift-and-shift" approaches can be clunky. More than one third of IT executives, 35%, say workload and application migration is a significant challenge given their current IT infrastructure. There's an increased demand for application containerization, which can serve as workarounds to supporting both legacy and more modern environments. Thus, containerization - the creation of portable self-sufficient applications that can be moved across any platform at any time -- also continues at full speed. Everyone is doing it -- 97% indicate that some portions of their application assets are containerized.

As they say: Mile by mile, it's a trial. Inch by inch, it's a cinch. That could help ease the pain of organizations undergoing modernization efforts as well. 

Artificial Intelligence

I asked Gemini and GPT-4 to explain deep learning AI, and Gemini won hands down

How to use ChatGPT's file analysis capability (and what it can do for you)

I tried Copilot Notebook: Microsoft's new AI tool offers two handy prompt features

What to know about Mistral AI: The company behind the latest GPT-4 rival

• I asked Gemini and GPT-4 to explain deep learning AI, and Gemini won hands down
• How to use ChatGPT's file analysis capability (and what it can do for you)
• I tried Copilot Notebook: Microsoft's new AI tool offers two handy prompt features
• What to know about Mistral AI: The company behind the latest GPT-4 rival