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Essential Skills for AI Workforce in 2025: What to Master

Want to Work in AI? Here Are the Skills to Master, Economist Says – CBS News: What Business Leaders Should Know in 2025

Estimated reading time: 5 minutes

  • Mastering both technical and soft skills is essential for breaking into the AI industry.
  • The most in-demand AI roles require strategic thinking, data fluency, and interdisciplinary knowledge.
  • Skills in Python, machine learning, and tools like TensorFlow are critical.
  • Entrepreneurs, marketers, and SMBs can capitalize on these trends to hire effectively and leverage AI.
  • This article provides actionable insights on the skills needed to succeed in AI.

Table of Contents

What Are the Top Skills for Working in AI, According to Economists?

The CBS News article cited economists who highlighted a changing skill equation for AI jobs. It’s no longer enough to be a technical wizard—you need a hybrid toolbox.

Top Skills Employers Now Seek:

  • Programming Languages (Python, R, Java): Core technical skills remain foundational. Python, especially, remains the lingua franca of AI and data science.
  • Machine Learning Frameworks: Mastery of tools like TensorFlow, PyTorch, and Scikit-learn is now a baseline expectation.
  • Data Literacy: Not just managing data—but interpreting, cleaning, and translating it into business insights.
  • Systems Thinking & Strategy: Understanding how AI fits into larger business operations is uniquely valued in cross-functional roles.
  • Soft Skills (Communication, Collaboration, Ethics): Economists urge future professionals to hone the ability to explain AI’s value, risks, and impact to non-technical audiences.

“If you want to work in AI, it’s not just about algorithms—it’s about applying them responsibly and effectively inside business settings,” states the CBS News article.

For business owners and team leaders, this shift means recruitment and training need to focus as much on context and communication as technical specifications.

How Are These Skills Relevant to Business Owners and Entrepreneurs?

While the article targets job seekers, business leaders actually benefit the most from understanding these core competencies.

Why It Matters for SMBs & Enterprises:

  • Better Hiring Decisions: Knowing what makes a great AI hire helps prevent budget wasted on one-dimensional candidates.
  • Smarter Strategy: Understanding AI skillsets makes it easier to identify opportunities for automation, optimization, and competitive advantage.
  • In-House Team Development: Upskilling internal teams in data fluency and AI application strengthens business resilience and innovation.

Case brief: One retail-focused SMB teamed with AI Naanji to automate their order processing via n8n workflows. They didn’t need to hire a data scientist, but understanding what skills to look for in a freelance AI consultant saved them weeks of downtime and thousands of dollars in operating inefficiency.

Which Tools and Technologies Should You or Your Team Learn?

The right tools are as important as skillsets. Here’s what your team should prioritize.

Top Open-Source & Commercial AI Tools:

  • Programming Language: Python tops the list, thanks to its simplicity and deep ecosystem.
  • Machine Learning Platforms:
    • TensorFlow: Backed by Google, ideal for full-scale deployment.
    • PyTorch: More intuitive syntax, favored in academics and startups.
  • Workflow & Automation Tools: For SMBs and digital agencies, low-code tools like n8n offer drag-and-drop automation with AI integrations.
  • Language Models & APIs:
    • OpenAI’s GPT for natural language understanding
    • ElevenLabs for AI-generated audio content
    • Google Vertex AI for enterprise-level deployments

Tool Considerations for SMBs:

  • Pros: Low-cost adoption, scalable, supports rapid prototyping
  • Cons: Requires basic data and Python fluency; some tools lack documentation for non-dev users

How to Implement This in Your Business

Whether you’re hiring AI talent or building internal AI capacity, follow these steps:

  1. Assess Internal Fluency

    Survey your team on data, automation, and tool usage comfort. Identify training gaps before investing in advanced tools.

  2. Start With One Process

    Choose one routine task (e.g., lead scoring, invoice processing) and find an AI-native alternative or automation using n8n.

  3. Use Freelancers or Consultants Strategically

    If full-time hiring isn’t feasible, platforms like Toptal or Upwork offer vetted AI specialists.

  4. Invest in Communication Training

    Encourage your team to learn how to explain AI tools in layman’s terms—this builds trust with stakeholders.

  5. Pilot Before Scaling

    Launch one AI project (such as automating email responses with GPT API), document performance, and iterate.

  6. Monitor for Ethics & Bias

    Build responsible use guidelines even in small-scale AI applications.

How AI Naanji Helps Businesses Leverage AI Talent and Skills

At AI Naanji, we help businesses bridge the gap between AI ambition and practical execution. Whether you’re looking to embed AI into existing workflows or build custom automations with tools like n8n, our consulting, automation, and integration services give you everything you need to scale—without needing a full in-house AI team.

From assessing current processes to implementing intelligent automation and chatbot flows, AI Naanji specializes in turning theoretical skills into ROI-driving systems tailored to SMBs and fast-growing companies.

FAQ: Want to Work in AI? Here Are the Skills to Master, Economist Says – CBS News

  • Q1: What skills should someone master to work in AI according to economists?

    Economists emphasize a blend of technical and strategic skills. Programming (especially Python), machine learning frameworks, data literacy, and strong communication are essential.

  • Q2: Do I need a PhD to work in AI?

    No. While advanced roles may benefit from academic backgrounds, many AI-based positions prioritize hands-on experience with tools and practical knowledge over formal education.

  • Q3: Can marketing and business professionals enter the AI field?

    Absolutely. AI needs professionals who can apply insights, build user stories, and analyze stakeholder impacts. Roles for “AI Product Managers” and “AI Strategists” are growing fast.

  • Q4: How long does it take to become proficient in AI?

    With focused effort, a solid foundation in AI and ML can be built in 6–12 months via project-based learning, online courses, and hands-on experimentation with tools.

  • Q5: What tools should non-developers learn?

    Automation builders like n8n, AI content tools like Jasper or ChatGPT, and analytics platforms like Power BI offer user interfaces that non-coders can navigate effectively.

Conclusion

As the CBS News article outlined, “Want to work in AI? Here are the skills to master, economist says,” the future of AI is inclusive of coders, communicators, and strategists alike. For business leaders, this is the time to identify which of these roles you need to fill—and which tools you can invest in immediately.

To make that leap simpler, AI Naanji offers strategic support to help businesses integrate automation and AI workflows with minimal friction. Explore how we can help you automate with confidence.

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