Tag: Red Hat

The tech industry is changing as quickly as artificial intelligence (AI) is evolving. Every day we’re seeing new tools emerge to help streamline repetitive tasks, augment creative endeavours and improve decision-making.

Many people are anxious about what the proliferation of AI tools means for the future of their job and career. And that’s completely understandable—these tools are often mindblowing in what they can do based on a handful of simple prompts.

Generative AI (gen AI) is practically brand new but can already:

• Generate code
• Write marketing copy
• Produce graphic design
• Create art in a vast array of styles
• Generate full videos, including scripts and music
• Formulate strategic business plans
• Develop social media posts
• …and more

So it’s not surprising that many of us are nervous about our future employment prospects.

But all is not lost.

While it’s essential for most people in the tech industry to learn how to effectively use these new AI-infused tools, there are some human capabilities that machines can’t match—deeply human skills such as intuitive design, creative problem-solving and empathetic understanding. These and other soft skills determine your ability to innovate, to communicate effectively and to navigate complex problems in ways that AI simply can’t replicate.

In this article we dig into some of the soft skills that tech professionals should focus on developing to adapt and thrive in this new age of AI.

6 vital soft skills for an era of AI

While there are an enormous number of AI tools being introduced across our industry, many of which are focused on specific roles and tasks, the soft skills tend to be more universal and things we should all focus on developing and improving, regardless of our role.

1. Problem-solving

For all that gen AI can do, it cannot match human problem-solving capabilities. It can generate code, but humans are still needed to design efficient and scalable systems, troubleshoot unexpected issues and watch for the bugs and potential security issues that these AI tools can introduce.

While gen AI can help monitor for and discover security anomalies, humans are still needed to evaluate and rate the criticality of these risks. AI-driven automation can perform a huge array of repetitive tasks, but it still needs to be carefully designed and actively monitored.

On the marketing and communications side of things, AI sentiment analysis tools can help quickly detect potential issues, but human judgement is needed in order to respond effectively and defend or build a brand’s reputation.

How to get started

Developing your foundational problem-solving skills is something that happens naturally over time, but there are loads of articles and courses out there that can help you approach it more deliberately and methodically.

2. Critical thinking

AI is still far from perfect, as large language models (LLMs) are fundamentally limited by their training and the data used in the training process. If you’re using any of these new tools, you should hone your ability to critically evaluate AI outputs, understand their limitations and learn how to identify model biases and potentially toxic or problematic output.

While AI is excellent at detecting patterns, it takes a human to interpret those patterns properly and to spot anomalies that the AI may miss or misinterpret. Avoiding bias and similarly complicated ethical issues also requires human intelligence, as does making sure that AI-enhanced tools and processes continue to meet legal and compliance requirements.

How to get started

While critical thinking can improve naturally with experience, like problem solving it is a skillset that can be deliberately developed over time. It has been said that learning critical thinking skills is the most important part of an undergrad degree, but you don’t have to go to university to build these skills.

LinkedIn Learning has a wide variety of courses focused on improving your critical thinking, as does Khan Academy and Udemy. Of course there’s no shortage of books on the topic as well.

3. Collaboration

Humans’ ability to collaborate, cooperate and work together is one of our greatest strengths. As the saying goes, “none of us is as good as all of us.” Current AI is still fundamentally limited in this way—it simply cannot match humans’ ability to build relationships and work together.

When developing AI applications, engineers will have to work closely with an ever increasing number of AI specialists, data scientists, product and project managers and other stakeholders. And of course collaboration skills are utterly vital in open source projects, and are the very foundation of how they work.

In other disciplines, such as public relations (PR) and communications, we can use AI to analyze sentiment and media trends, but it takes humans to develop and maintain strong relationships with journalists, partners and other stakeholders. 

How to get started

Collaboration skills are essential for effective teamwork and building trust. There are books you can read and courses you can take (on all of the previously mentioned learning platforms), but you can get started over on YouTube.

4. Communication

Communication skills are also vital across disciplines in the tech industry. Engineers have to be able to clearly articulate technical ideas and strategic approaches to design and architecture problems, which AI is unable to do.

Security experts have to be able to interpret AI’s findings and communicate those insights so leadership and non-technical teams are able to understand how serious the potential risks are (or aren’t).

And communication is the heart of marketing and PR—AI tools can provide analyses and insights, but humans are needed to craft narratives and tell a brand story that resonates with the people we’re trying to reach.

How to get started

Communication skills enable tech professionals to collaborate effectively, bridge technical and non-technical gaps, and drive innovation by translating complex ideas into clear, actionable strategies. There is a range of different types of communication skills, but focusing on workplace communication is the best place to start.

5. Pragmatism

AI is an exciting new technology that is quickly being built into what feels like every device and app out there. But in reality, AI is still relatively limited and more effective at some things than others. AI applications should be designed and built to solve real user problems and be strategically aligned to existing business needs.

This ability to be pragmatic, to be able to clearly evaluate the practicality and usefulness of a particular technology or solution, is a fundamentally human strength. Being able to balance “can” and “should” to emphasize a focus on real solutions to actual problems, is something AI tools are currently incapable of doing.

Like critical thinking, pragmatism is something we all naturally develop with experience, but like any skill, it is something you can train yourself to become better at with deliberate study and practice.

How to get started

Being pragmatic doesn’t mean being a skeptic or trying to tamp down others’ enthusiasm with stop energy. It’s more about being able to look at potential solutions or approaches with a realistic and measured eye.

As a tech professional, you can become more pragmatic by focusing on real results and choosing practical and effective solutions that work in real-world scenarios. Embrace iterative development, testing and continuous feedback, as this can help keep things practical and grounded.

6. Adaptability

Early humans survived and thrived because of their fundamental ability to adapt to changing conditions, which continues to be vital today. As we’ve seen over the past few years, the tech industry is undergoing tectonic shifts, a large part of which is being caused by how quickly AI tools and capabilities are evolving.

How to get started

Improving your adaptability in the workplace largely boils down to cultivating a flexible mindset (simply being open to new things) and engaging in continuous learning. Be open to new ideas and responsibilities, commit to personal development, be proactive in suggesting solutions or improvements when you see issues, and stay current with the (admittedly, often overwhelming) changes in our industry.

Wrapping up

It’s appropriate that this article ended talking about continuous learning, because that’s what it’s really all about. AI tools are being deployed across nearly every role and discipline in the tech industry, making many of us concerned about the future of our jobs. But human “soft” skills are increasingly vital in this age of AI—AI can help us all do more, faster, but it cannot replace our ability to solve problems, think critically, communicate effectively, work together, be pragmatic and adapt quickly to these rapidly changing conditions.

It’s natural to be anxious about the future, but for many of us AI presents an incredible opportunity to use these new tools to handle the more repetitive and (frankly) boring parts of our work so we can focus on developing our own deeply human skills and doing the really interesting stuff that AI can’t.