IT STRATEGY

Anna Kim

If you stick with IT as a career for long enough, chances are good you’ll reach your first “boss level”: middle management.

Middle managers often break down company objectives into day-to-day tasks for individuals and teams, then track how those objectives are executed. For IT pros, stepping into middle management may mean spending the bulk of your days making sure objectives are met as opposed to assisting users and troubleshooting problems.

While entering into a middle management role can feel like a rite of passage for IT pros looking to advance their career, it’s often not an easy move. Joseph Unruh, senior director of engineering at digital analytics services company Mixpanel, told IT Brew the shift can be a “tough transition,” as most professionals entering these roles come from a more technical background.

“Almost all managers in the engineering space were former engineers themselves, and becoming a manager is a totally different job that most people just aren’t equipped for,” Unruh said. “I’ve seen many managers come into the position and continue treating it like it was an engineering position and fail.”

Surviving the Hunger Games.—BM

      

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IT STRATEGY

Morning Brew Design

You can’t win them all—advice that applies to lottery tickets, national sweepstakes, and, lately, AI initiatives.

Let’s say you’ve finally charged ahead with a long-awaited and highly anticipated AI project at your organization. The hope is that the initiative goes as expected, paving the way for other AI projects down the line. But how do you recover if those efforts fail, burning lots of time and resources in the process?

Red flags. According to Rimini Street Global CIO Joe Locandro, you can consider an AI project failing if it isn’t delivering an expected outcome. There are usually signs that an AI project is floundering. For example, you might spot employees spending too much time fixing results “due to poor data quality,” he said.

“What you find is that a lot of the engineers keep spending time and getting delayed because the data wasn’t right,” Locandro said. “The second thing that you find is the results are hallucinating, and what I mean by that is they’re not generating very good and accurate results—and those two things are what causes the time and cost to blow out.”

Time to launch the turnaround.—BM

      

IT STRATEGY

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Money keeps pouring into AI, but the investments are running up against the reality of difficult integrations with legacy systems.

That’s one of the main takeaways from new research by IT services firm GFT Technologies. The study, entitled The Future of AI, Unfiltered, was released on September 29 and delves into the complexity of putting AI into practice.

GFT USA’s CEO Rishi Chohan told IT Brew that legacy applications can range in age from two to 50 years old, paired in many cases with complex mainframe architectures.

“They have a lot of silos, they have a lot of disintegrated stuff going on,” Chohan said. “That poses many limitations in terms of scaling AI, in terms of implementing AI.”

Establish your legacy.—EH

      

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patch notes

Francis Scialabba

Today’s top IT reads.

Stat: 28%. That’s the percentage of an IT budget that goes to upgrades, migrations, and licensing changes, according to a survey of IT decision-makers in the US and the UK. (The Register)

Quote: “Vendors want you to use AI agents everywhere, and they want you to build momentum for their products, or to just buy more tokens.”—Daryl Plummer, Gartner distinguished VP analyst and chief of research, on AI vendors pushing their products despite only a small percentage of enterprises seeing AI-powered productivity gains (CIO Dive)

Read: Nvidia CEO Jensen Huang wants Europe to accelerate AI development (and buy some hardware). (Business Insider)

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