Part 9 in the AI and Your Tech Career Series
Welcome to Part 9 of "AI and Your Tech Career," Dice's 10-part article series walking through the basics of how to successfully integrate artificial intelligence and machine learning into your tech career journey, resulting in great AI careers. We'll cover everything from the most popular jobs and skills, to non-technical roles in AI, industry applications and more. You can take full advantage of the future of tech jobs, and AI can help!
The tech landscape is constantly evolving, and artificial intelligence (AI) and machine learning (ML) are at the forefront of this AI career transformation. These powerful tools are rapidly changing how we work, and for tech professionals, this presents a unique opportunity. By embracing AI and ML skills, you can position yourself for exciting new roles and ensure your career remains future proof.
This post explores several tech jobs that will be heavily influenced by AI and ML in the coming years. Each section details the core aspects of the position, the necessary skillset, and how AI will fundamentally reshape the way these jobs are done. But first, why does it make sense to even consider adding these skills into your repertoire?
Why Add AI and Machine Learning to Your Portfolio of Tech Skills?
There are several compelling reasons to integrate AI and ML into your skillset. Here are a few key benefits of AI and ML skills.
- Increased Demand: Jobs requiring AI and ML expertise are growing exponentially, with increased demand for AI jobs with every passing quarter. By acquiring these skills, you'll open doors to a wider range of high-demand, high-paying opportunities.
- Enhanced Efficiency: AI and ML can automate repetitive tasks, freeing you to focus on higher-level problem-solving and strategic thinking. This allows you to deliver greater value and achieve more in your role, in addition to better decision-making with AI.
- Improved Decision-Making: As we just implied, AI can analyze vast amounts of data to identify patterns and trends that humans might miss. This empowers you to make data-driven decisions that are more accurate and effective.
“Other” Tech Jobs That Will Be Transformed by AI and Machine Learning
The usual suspects, including data science, machine learning engineering and others who are directly involved in building and enhancing LLMs, are of course a big part of the AI revolution. But what about all of the other tech jobs that have not traditional been tied to AI? Well, those will all see an impact on various tech roles, as well. Let's delve into some of those specific tech roles that are likely to see changes based on the rise of AI and Gen AI:
AI User Experience (UX) Designer:
- Core Responsibilities: Design user interfaces (UIs) and user experiences (UX) for AI-powered systems. This involves understanding user needs, designing intuitive interactions, and ensuring a seamless experience between humans and AI technology.
- Required Skills: Expertise in UX design principles, understanding of human-computer interaction (HCI) best practices, familiarity with AI and machine learning capabilities.
- AI Impact: AI will automate user research tasks and generate user persona insights. Machine learning algorithms can be used to A/B test different UI elements and personalize user experiences based on individual needs and preferences.
- Related User Experience (UX) Career Resources:
- UX Designer Career Path
- The type of UX Designer Degree you would need.
- The amount you can make with a UX Designer salary.
- The UX Designer skills you would need.
Robotic Process Automation (RPA) Specialist:
- Core Responsibilities: Identify, develop, and deploy RPA solutions to automate repetitive tasks within an organization. This involves analyzing workflows, configuring RPA tools, and ensuring seamless integration with existing systems.
- Required Skills: Understanding of business processes and automation principles, familiarity with RPA tools and platforms, strong analytical and problem-solving skills.
- AI Impact: AI will enhance RPA capabilities by enabling intelligent process discovery and task automation. Machine learning can be used to identify patterns in data and automate complex decision-making processes within workflows.
Software Engineer:
- Core Responsibilities: Design, develop, test, and maintain software applications. This involves writing clean, efficient code and ensuring software functionality meets user requirements.
- Required Skills: Strong programming skills (e.g., Java, Python), proficiency in software development methodologies, understanding of system design principles.
- AI Impact: AI will automate code generation and testing, freeing software engineers to focus on building innovative features and functionalities. AI tools can also be used to identify potential bugs and security vulnerabilities within code.
- Related Software Engineer Career Resources:
Cybersecurity Analyst:
- Core Responsibilities: Detect, analyze, and respond to cyber threats. This involves monitoring systems and networks for vulnerabilities, investigating security incidents, and implementing security measures.
- Required Skills: In-depth knowledge of cybersecurity principles and best practices, experience with security tools and technologies, strong analytical and problem-solving skills.
- AI Impact: AI can be used to analyze network traffic and user behavior in real-time to identify and prevent cyberattacks. Machine learning algorithms can also be used to detect anomalies and suspicious activities within systems.
- Related Cybersecurity Analyst Career Resources:
Business Intelligence Developer:
- Core Responsibilities: Develop and maintain business intelligence (BI) systems that provide data-driven insights to support decision-making.
- Required Skills: Understanding of data warehousing and data visualization concepts, proficiency in BI tools and technologies, strong communication and collaboration skills.
- AI Impact: AI will automate data extraction and transformation tasks within BI systems. Machine learning algorithms can also be used to create advanced dashboards and visualizations that deliver more nuanced insights to business stakeholders.
How Dice Can Help
You know by now that the rise of AI and ML presents a unique opportunity for tech professionals. By embracing these powerful tools and acquiring the necessary skills, you can position yourself for exciting new roles and ensure your career remains relevant in the ever-evolving tech landscape.
As you can see from the roles outlined above, one important thing to remember is that AI and ML are not only creating new types of jobs and increasing the popularity of core AI positions such as Data Scientist and Machine Learning Engineer. Because the impact will be much broader, spreading across most tech roles, keys to success will include focusing in on building the right skills, pursuing the right certifications, and charting a concrete career path. To position yourself in the best way possible, it’s less about the job or title you have, and more about the pursuit of constant improvement and the value of the different skills you’re bringing to the table.
Whether you’re just starting out in your career or you’re well underway, you know that your tech career will be defined by a series of decisions. While you make each choice the right one through attitude, perseverance, and a commitment to learning, it pays to approach each of these decisions with as much knowledge as you can. To gain that knowledge, consider joining the Dice community. As the only career marketplace designed exclusively for tech professionals, we know what you’re going through and what’s at stake for every decision in your career journey, and we want to provide you with the tools and information you need to build the right career for you.
For more information on Dice and how to get started:
- Check out our AI Careers and Resource Center, our hub for AI-focused content for tech professionals
- Learn more about Dice here
- How to create your Dice profile
- Search for AI and other tech jobs
We hope you enjoyed Part 9 of our AI and Your Tech Career Series! To read the full series and take command of your career in AI, view them on the links below.
Part 1: Unveiling AI Career Opportunities: Key Roles and Emerging Hybrid Jobs in Artificial Intelligence
Part 3: AI Jobs Demand Analysis: Current Trends and Future Outlook in Artificial Intelligence Careers
Part 4: Transitioning into AI: Adding Artificial Intelligence and Machine Learning Skills to Your Repertoire
Part 5: Charting AI Tech Career Pathways: Navigating From Entry to Senior Level
Part 6: How AI is Revolutionizing Industries: Real-World Applications and Talent Implications
Part 7: Top AI Certifications to Get You Ahead in Your Tech Career
Part 8: AI Tech Hubs: Top U.S. Cities for AI and Machine Learning Jobs
Part 10: How to Think About AI: A Tech Professional’s Guide to Growth, Not Fear