Can AI help us survive the inevitable federal government retirement tsunami?

For many years, experts have predicted a tsunami of federal employees retiring as more and more baby boomers reach pension eligibility. Though the tidal wave ha...

For many years, experts have predicted a tsunami of federal employees retiring as more and more baby boomers reach pension eligibility. Though the tidal wave has been slow to materialize, it still seems inevitable. In fact, the delay may only be making the eventual impact worse as the total number of retirement-aged employees who have not retired but could do so at any time grows ever larger.

The problem

A mass exodus of experienced federal employees through retirement could lead to what some have labeled a “brain drain” — a lack of skilled, qualified federal employees to carry on the critical work of running the nation’s government and infrastructure.

This is especially concerning for technical roles such as IT administrators. There’s a well-known shortage of technical talent, also known as the IT skills gap. In fact, recent projections suggest there will be a global shortage of 85 million tech workers by 2030, with the U.S. alone short 6 million.

In most cases, federal agencies won’t see their entire IT departments obliterated. After all, the average age of U.S. technology professionals is 40 (46 for IT managers), but with a quarter of U.S. IT professionals and one out of every five IT managers at least 55 years old, federal agencies are certain to be affected.

This problem is compounded by two other key trends:

  • Multi-cloud: The benefits of cloud computing are well-known, and federal IT departments were commendably quick to take advantage, but many agencies assumed that moving to the cloud meant they were buying an outcome, when they were actually simply buying infrastructure. That means that the hardware was no longer theirs to manage, but the ultimate responsibility for their data remained with them, and now with the proliferation of multi-cloud infrastructure, that data is spread across an immensely complex data estate with dozens of workloads in multiple public cloud environments, all with disparate management tools.
  • Ransomware: A 21st century digital plague that is spreading faster than ever, ransomware is the federal IT professional’s worst nightmare. By some estimates, there were more than 623 million ransomware attacks overall last year.

The federal government isn’t sitting idly by waiting for this “brain drain” to happen. For example, the White House recently hosted the National Cyber Workforce and Education Summit focused on reducing the IT skills gap and building up the cyber workforce. Nevertheless, even with the considerable efforts being made, the impact of the above trends will be fewer federal IT employees doing more work, leaving less time for them to focus on strategic initiatives that drive innovation.

A solution

Autonomous IT technologies driven by artificial intelligence can play an important role in navigating the inevitable federal employee retirement boom.

It’s important here to clarify and define some commonly confused ideas: autonomy versus automation and AI versus machine learning.

Autonomy means something is self-sufficient, requiring no human intervention. Autonomous systems can learn and adjust to dynamic environments. On the other hand, automation refers to something that is narrowly focused on a specific task based on well-defined criteria.

Any required changes to what an automated system is doing requires humans to change the criteria. On the other hand, autonomous systems function through AI. AI is the ability for a computer system to essentially “think” for itself. The system uses math and logic to mimic human reasoning to learn from new information and make its own decisions, but with human oversight. ML, on the other hand, is how systems continue to develop their intelligence through mathematical modeling.

To illustrate how autonomous systems powered by AI can help shrinking federal IT staff, consider autonomous data management.

Automation has already played a key role in managing data for quite some time. Backup software has long been able to easily automatically back up data from specific stores after a pre-defined time period or as the result of some other trigger. It then got a bit more sophisticated with things like automated discovery and automated protection of new workloads.

Now, basic AI-driven autonomy powers anomaly detection that helps protect data against the effects of the ever-evolving threat landscape, where ransomware comes back into this discussion. AI is also currently helping to predict hardware failures in backup storage devices and enable relevant hardware to be replaced before failure to avoid backup performance impact and recovery failures.

The next step is AI-driven technology that can fully autonomously self-provision, self-optimize and self-heal data management services for the vast amounts of data in today’s multi-cloud environments. In practice, this will look like autonomous provisioning of data protection policies when new services and users are deployed and autonomous monitoring and rollout of new policies that match the observed usage of a company’s data, all without human intervention needed, though human oversight is not sacrificed.

Autonomous IT systems powered by AI, such as the autonomous data management I’ve described here, are all about freeing technology professionals from the mundane aspects of IT, which for government IT staff are sure to continue increasing as more and more of their colleagues opt for retirement. These autonomous IT systems can help federal IT departments not only survive the retirement tsunami, but ride it to greater innovation by allowing staff to focus on more strategic, transformational initiatives.

Kevin Youngquist is vice president for U.S. public sector at Veritas Technologies.

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