Generative AI (GenAI) has moved past its experimental phase. It is now deeply embedded in core business workflows, from sophisticated financial modeling and predictive analytics to dynamic content creation and strategic decision-making.
This means the very definition of a “job-ready” professional has dramatically changed. Global surveys reveal the same trend: employers no longer prioritize degrees or job titles. They want proof of applied AI skills. Recruiters are looking for professionals who can design machine learning pipelines, apply responsible AI principles and generate insights using enterprise-grade tools. The market is clear: skills now speak louder than credentials.
According to Naukri’s “AI: Friend, Foe or Frenemy” report, published in July 2025, 72% of recruiters prioritize real-world AI and analytics skills over traditional degrees or job titles. This report highlights AI-linked roles growing 38% year-on-year in Q1 FY26.
The rapid expansion of AI opportunities is accompanied by a widening skills gap. Entry-level positions increasingly expect capabilities like prompt engineering and responsible AI – skills that were niche just a few years ago. Employers report frustration with resumes filled with theoretical certifications but little evidence of practical project work.
Globally, job markets will face some of the same issues: enormous demand and equally high expectations for job readiness.
The real risk? Doing nothing
Staying still means falling behind. Entry-level roles increasingly demand capabilities like Prompt Engineering and Responsible AI, skills barely mainstream just a few years ago. Traditional resumes with generic course certificates struggle to break through.
Most candidates have watched videos or taken theoretical courses, but they struggle to explain their project work. We need people who can apply what they’ve learned. Analytics Hiring Manager, BFSI Sector
This critical gap between learning and doing means opportunities are lost. Employers aren’t hiring for familiarity; they’re investing in proven capability.
What defines success in today’s AI-driven job market?
To thrive in GenAI career readiness, you’ll need:
- Core competencies: Strong foundations in analytics, data engineering, and AI/ML.
- Technical proficiency: Working with structured data, large language models (LLMs), and automated pipelines using tools like Python, R, TensorFlow, SAS Viya, or cloud platforms such as AWS and Azure.
- Prompt engineering: Crafting effective inputs for GenAI models.
- Responsible AI: Applying ethical practices in model development for AI ethics training.
- Decision intelligence: Extracting actionable insights using tools like SAS, Tableau, or Power BI.
- Real-world application: Hands-on experience solving business challenges across various domains.
Many self-paced courses or generic certifications often lack the structured roadmap, enterprise tools or expert mentorship needed to bridge this critical skills gap.
Why your current learning may not be enough
If you’ve taken free massive open online courses (MOOCs) or basic certifications, that’s a start. But they often fall short because:
- No expert guidance: You get stuck and stay stuck.
- Lack of real-world tools: No exposure to enterprise platforms used in jobs.
- No applied projects: You can’t prove practical skills.
- No job-role alignment: Your resume lacks specific relevance.
The result? You may know about AI, but you’re not yet someone a company would hire for AI roles.
Are you truly job-ready for AI careers?
Ask yourself, can you confidently say “yes” to all of these?
- I’ve worked on prompt engineering for real use cases.
- I can build and explain machine learning pipelines.
- I’m proficient in Python, SAS Programming, or R for data analysis.
- I’ve worked with ETL workflows or data pipelines.
- I can apply responsible AI principles in model development.
- I’ve used decision intelligence tools to generate practical insights.
If you’re answering “no” to any, that’s your learning gap. Closing it now could redefine your career trajectory, opening doors to lucrative AI jobs.
The roles that are booming in AI
Roles leveraging AI and advanced analytics are seeing significant growth. Recent industry reports indicate that AI-skilled professionals often command 20-50% higher salaries than their non-AI counterparts, with premiums for freshers being particularly notable. These high-demand roles include:
- AI and ML engineers
- GenAI workflow developers
- Data engineers and architects
- Business analysts with decision intelligence skills
- AI-driven automation consultants
Importantly, the AI revolution isn’t exclusive to tech. Consultancies and industry bodies highlight a significant expansion of AI hiring beyond the traditional IT sector, with strong growth observed in banking, financial services and business process outsourcing (BPO) domains as well.
The smarter way to prepare for AI careers
What truly works is structured transformation. Look for programs that combine:
- Structured learning paths: Aligned to specific job roles.
- Real-world tools: Hands-on experience with Python, R, SAS Viya, TensorFlow, or AWS.
- Guided labs and projects: Building a robust portfolio.
- Expert mentorship: Support to build confidence.
- Industry-recognized certifications: Credentials recruiters trust, boosting job traction.
Elevate your career with SAS Academy for Data and AI Excellence
One such comprehensive option is the SAS Academy for Data and AI Excellence. This academy offers rigorous, role-aligned tracks in business analytics, data engineering and AI/ML. It provides access to the full suite of SAS tools alongside open-source technologies, and its globally recognized certifications are specifically designed to validate your practical, job-ready skills for the GenAI economy.
SAS Academy programs address common challenges, such as time constraints (weekend sessions + recorded content), cost concerns (flexible payment plans), existing skill gaps (beginner-to-advanced roadmaps) and practicality (industry-aligned projects).
Don’t wait for change. Be the change.
GenAI is already transforming jobs in India. Recruiters now seek career-ready skills, not just credentials. You don’t need to be an expert overnight, but you do need to start. Assess your skills, choose a structured learning path like the SAS Academy, and begin building what employers actually value.
The AI career wave is here. Ride it, or risk being left behind.
Ready to get started? Explore these structured learning paths.
