How IT Teams Use Generative AI to Make Their Lives Easier

OpenAI’s ChatGPT and other generative AI (GenAI) platforms have become wildly popular because of their extraordinary ability to improve productivity — and generally make life easier.

When ChatGPT hit the market, within one week it exploded in popularity with more than 1 million users jumping onto the platform. Not long after launch, the platform boasted more than 100 million monthly active users, which by some estimates makes it the fastest growing consumer application in history.

Looking at the impact globally, applications like these have incredible potential. One McKinsey report shares the global economy could see up to $4.4 trillion in benefits from adopting and integrating generative AI across 63 use cases, which range from software engineering to legal and supply chain.

Many in IT, software engineering and development are seeing the benefits unfold in real time. “Something that used to take an engineer 30 minutes to do can now be done by AI in one minute,” said Bridget Frey, CTO at Redfin, to GeekWire. “We’ve also found ways to use these tools to help us serve customers more efficiently.”

Today, use cases vary widely in the workplace with still more in development. From software engineering to coaching, the possibilities feel endless. But where exactly is it having the greatest impact? How is it making work easier, faster, or more efficient for those in IT?

Let’s break it down:

Scan Logs, Detect Threats, and Automate Tasks to Offload Work

If you’re reviewing logs, scripts, or other textual data, generative AI tools can help serve as a second set of eyes to quickly spot anomalies.

Given the near instantaneous feedback from these platforms, GenAI stands to greatly improve the speed and efficiency of reviewing logs and detecting what has a high likelihood of threatening the organization — rather than being another false positive. This, in turn, can help security analysts respond to more pressing threats faster.

Further, security professionals may also look to these tools for automating script writing or SIEM queries, presenting risk assessments and recommendations, and generally cutting down the workload for security professionals.

But What About Hackers?

Scanning networks or recommending configuration improvements are helpful defensive applications for generative AI — but what about more offensive use cases?

There are concerns that bad actors will use GenAI tools to bolster their efforts.

For example, bad actors could glean what public information they can about a person, and then plug that data into the chat function looking for potential password variations. With this type of information, bad actors may be able to quickly crack into someone’s account and gain access to private information.

What’s more, bad actors may be able to scan networks or find intrusion points to exploit vulnerabilities, develop more convincing phishing tactics, and even write polymorphic malware. (Scary, right?)

For the ethical hackers reading this, think about reverse engineering these tactics to build a defensive strategy. Employing the same tactics, ethical hackers can also find vulnerabilities in software or across networks and then act quickly to improve their organization’s security posture.

It’s fighting fire with fire — but given the power behind GenAI, it’s important to understand the tools, how bad actors may deploy them, and then leverage those same tools to harden your defenses.

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Generate Commands and Code Faster; Debug and Test for Efficacy, Vulnerabilities

Web and software developers, programmers, and systems analysts all stand to move faster by relying on GenAI tools and so-called copilots to supplement their efforts. McKinsey research has found developers stand to benefit the most in these ways:

• Speeding up manual, repetitive work
• Drafting new or updating existing code
• Increasing bandwidth at work

The findings show developers moved up to 50% faster when writing documentation, 45% for code generation, and 30% for code refactoring. “With the right upskilling and enterprise enablers, these speed gains can be translated into an increase in productivity that outperforms past advances in engineering productivity, driven by both new tooling and processes,” the report says.

Whether it’s to remind yourself of commands, translate from one language to another, or generate lines upon lines of code, these tools can pump out work at non-human speeds.

In an interview, Augmend CEO and co-founder Diamond Bishop said: “We’re a team of five devs, and we estimate productivity impact of almost 2X. Each of us leverage both Copilot and ChatGPT in day-to-day development, debugging, and learning.”

While these tools may work well to create an initial draft or work through specific problems, they’ll still require an extra set of (human) eyes to check code that’s still in development. What’s more, the McKinsey research shows less benefit in using these tools for more complex projects or for those developers unfamiliar with frameworks or still early in their careers.

To this end, as developers become more familiar with these tools, their abilities to use them effectively will also increase. Being able to prompt GenAI platforms to produce the result you want takes time to master, but once those skills are sharp, the possibilities are basically endless.

Worried about AI taking your job? Think again.

While generative AI does stand to help speed up development, there are worries of it replacing or taking jobs away from developers.

Is this fear worth losing sleep over?

It’s important to remember that this is already a stretched labor pool, with too few in the business to meet the growing demand for these skills. Consider the U.S. Bureau of Labor Statistics projections of jobs in web development growing much faster than the national average.

AI won’t replace developers but augment those teams who support the many organizations struggling with open head count and skills gaps.

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Without a doubt, GenAI tools have been a dream come true for many who’ve felt underwater at work or just wanted to offload tedious tasks.

However, with the spike in adoption and high accessibility, they’ve also gotten ahead of IT departments causing a flurry of security concerns. One study revealed 81% of participants worry about potential breaches, data leaks, and more.

“A most concerning risk for organizations is data privacy and leaking intellectual property… Think about potential trade secrets, classified information, and customer data that is fed into the tool. This data could be stored, accessed, or misused by service providers,” said Dennis Bijker, CEO of SignPost Six, to Zapier.

In some ways, it’s become a classic case of shadow IT — or a lack of organizational oversight into what technology the workforce uses day to day.

One survey shows 30% of those in tech and 50% in business services use tools like ChatGPT without their employer’s knowledge. Many use them simply to generate ideas or write emails, but this survey also shows many rely on them to code or for research.

While applying these tools for use cases like these makes perfect sense, not all of these tools are rock solid with respect to security.

For these reasons, technology and business leaders must work together to raise awareness of the potential risks involving these tools to safeguard data and protect against threats. Anyone using tools like these should do so in compliance with your organization’s artificial intelligence policy.

GenAI can make your work life a little easier, but it pays dividends once you’ve become familiar with how it works. Skillsoft offers several new courses and an Aspire Journey focused on generative AI to help everyone from web developers to business leaders understand the technology, its benefits and limitations, and how to use it productively and ethically.

Gain access to this training today for free by signing up for a trial of Skillsoft’s Percipio. Or, learn about Skillsoft’s training solutions here: