How to get hired and promoted in AI-first world where certificates matter less than output

For the modern professional, the greatest risk isn’t losing their job to an algorithm; it’s losing it to a human who knows how to use one. Amid fears of an artificial intelligence (AI) “takeover,” the emerging labour market looks less like a wasteland and more like a high-stakes upgrade.

Data from PwC’s ‘The Fearless Future: 2025 Global AI Jobs Barometer’ reveals that wages are actually growing in AI-exposed occupations, provided workers can adapt. The shift is clear: employers are moving away from paying for ‘effort’ and toward paying for the high-level judgment required to steer AI tools.

In this new economy, what was once considered a supplementary skill has now become fundamental: the ability to integrate AI into workflows now defines the baseline for career survival and income growth.

Output over effort

Layoffs linked to AI adoption are often concentrated in roles where acclimatisation has been slower or tasks have become easier to automate. Increasingly, “human effort” by itself is no longer a strong differentiator. What matters is the quality of the output and how efficiently it is delivered, regardless of whether it is generated by AI or a human.

Haris Mirza, Founder & CEO of marketing agency UPCLUB, offers a candid view: “We heavily rely on AI and don’t try to hide it from our clients. The work pressure is high, but AI helps us meet multiple deadlines efficiently. We are transparent about it with our clients. They care about the outcome, not the tools.” He says access to AI tools alone doesn’t guarantee strong results. “Even though AI is available to everyone, not everyone can generate the same quality of output.”

According to Mirza, this is where skill and judgement come in. He says he is constantly on the lookout for people who can extract strong outputs from AI tools, but that technical proficiency alone is not enough.

“It is equally important that the candidate understands the industry well enough to judge what the AI produces,” he adds.

Think of the professional’s role shifting from the ‘doer’ of tasks to the ‘editor-in-chief’ of their own workflow. Employers no longer pay for the hours you spend drafting; they pay for your judgement, the ability to look at AI output and know exactly what is missing, what is factually wrong, and what is off-brand.

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Human judgement matters

This underscores the importance of vision and decision-making. Having the ability to judge quality, refine ideas, and apply context has become more valuable than simply executing tasks with AI. If a person has clarity of vision and the skills to evaluate AI-generated work, they can build almost anything, even if the final output is largely machine-assisted. Delhi-based Rajeev Mehta is a working example of this shift.

In pre-AI times, he used to run a traditional marketing agency and worked with many large companies. “I had all the skills needed in graphic design and advertising, and that helped me understand the industry,” he says.

As generative AI tools matured, his workflow changed dramatically. “My revenue more than doubled, and I could do more work in a much shorter amount of time,” he says.

That realisation prompted a major decision: Mehta shut down his agency and began relying almost entirely on AI-driven work. Nearly 60% of his earnings now comes from teaching AI creative direction. “I never realised AI had this much potential,” he notes.

Big advantage for small brands

One reason for the rapid adoption of AI is that this technology has democratised capabilities that were once accessible only to large brands. High-end visual effects, polished videos, and complex creative executions, which once required large budgets and specialised teams, are now within reach of smaller companies. AI has lowered both cost and complexity. As a result, many startups and mid-sized brands are embracing AI-first workflows to compete with larger players. This has also led to the emergence of new job titles and responsibilities.

“New roles, like AI delivery lead, AI program manager, AI business analyst, AI risk and compliance, prompt engineer, AI/ML engineer, and LLM operations engineer, are becoming more common,” says Devashish Chakravarty, founder of Salarynext.com.

While many of these roles are still evolving, they point to a clear shift in how organisations structure work around AI.

As a prompt engineer at Nvidia, Drishti Mittal of Pune works remotely in one such AI-first role. Her job, however, is drastically different from the popular perceptions of prompt engineering. The 25-year-old does not use public tools such as ChatGPT, Grok, or Claude. Instead, she works on an internal Nvidia AI system accessible only to employees of the American tech giant. Her role highlights how the rise of AI is also creating entirely new job titles within organisations.

Rajeev Mehta,37
Delhi
PROFESSION AI creative director
ANNUAL TURNOVER
Rs.2.4 crore
HOW HE WORKS
Mehta transitioned from running a traditional digital media agency to building an AI-first education business. While his earlier work involved managing large teams, AI allowed him to collapse these siloed skills into a single workflow. Today, his company earns the majority of its revenue through AI in advertising training programmes.

“To make AI better, we need humans to judge the output,” Mittal says. Her role involves improving the quality of AI-generated responses by applying human judgement, context, and verification. Her responsibilities include correcting responses, correcting errors, running fact checks, and comparing multiple outputs to improve accuracy.

Interestingly, Mittal comes from a nontechnical background. A commerce graduate from Gujarat University, her experience shows that AI-first roles are not limited to engineers; they are open for professionals from diverse educational backgrounds.

While AI is turning into a universal tool, its use cases vary. Through illustrations of Mittal’s and Mehta’s trajectories, we see two distinct career paths. In Mehta’s case, AI is used for scale; in Mittal’s, it is a tool for accuracy and risk management.

AI-first roles still limited

Despite these examples, AI-first roles remain relatively limited across industries.

“The bigger shift is in how careers are evolving. Professionals are increasingly moving toward roles where judgement, problem-solving, creativity, and collaboration matter alongside technical skills,” says Nirajita Banerjee, Career Expert, LinkedIn India. “In most roles, AI is embedded into everyday workflows rather than treated as a standalone function.”

This gap is especially visible in large organisations. At scale, many established brands prefer to differentiate themselves through human creativity and craftsmanship rather than through overt AI use.

Mehta explains that for some brands, openly disclosing their work as “AIgenerated” can be damaging. “For them, AIgenerated content is catastrophic for brand identity. They want to stay differentiated and do not want to look like everyone else jumping onto the same trend,” he points out.

Another reason companies hesitate to fully adopt AI-first workflows is data privacy concerns. “To make the best use of AI, we often need to provide very detailed prompts, which can include sensitive company information,” says Vamsi Karavadi, Partner, Deloitte India. “In many organisations, that is simply not allowed.” Mirza agrees that this is where the limitation lies. He believes midsized and smaller companies are far more willing to experiment with AI-first roles, while large enterprises remain cautious.

“Roles where AI is the primary tool are still in a nascent stage,” Karavadi adds to this sentiment. “You will not find many jobs today where you can rely solely on AI”.

Even in Mittal’s case, Nvidia discourages employees from relying on external AI tools for core work. She says other AIs can be used to understand complex concepts, but not to correct or refine responses. “Nvidia wants outputs that feel human, accurate and context-aware.”

Echoing this view, Niren Srivastava, Group Chief Human Resources Officer at Motilal Oswal Financial Services, says, “Even though AI in financial services is moving from experimentation to becoming a core strategic asset across research, advisory, risk, operations and customer experience, not every job is AI-heavy.”

“Many roles exist in a hybrid zone where AI accelerates work but does not replace domain expertise, judgment or relationshipbuilding,” he adds. Having AI skills today is like having computer skills in the ’90s. They are becoming essential across roles, but they are not sufficient on their own to secure a job.

75% of today’s demand for AI skills comes from three occupation groups
Employees in US jobs where AI-related skill was listed in at least 5% of postings1

Drishti Mittal,25
Pune
PROFESSION Prompt engineer
ANNUAL INCOME
Rs.7.8 lakh
HOW SHE WORKS
Mittal works on Nvidia’s internal AI systems. Her job involves evaluating and improving AI-generated responses rather than generating content herself. She compares multiple AI responses to the same prompt, checks for accuracy, relevance and usefulness, and refines outputs to make them more human, professional and context-appropriate. Her income compared to her peers is almost double.

The earning potential

That said, demonstrating strong AI skills has become increasingly important for career growth. “Having AI skills does command a premium compared to someone with similar abilities but no exposure to AI,” says Karavadi. Srivastava adds that companies will increasingly expect employees to be AI-ready, comfortable experimenting with tools, working alongside AI agents, and continuously upgrading their skills.

Banerjee adds that AI capability is fast becoming a baseline skill across sectors. “Many leaders already factor AI proficiency into hiring and performance decisions, indicating that AI skills are translating into real career opportunities rather than remaining a buzzword,” she says.

According to Chakravarty, compensation is usually anchored to the underlying job family, such as operations, marketing or product. “The biggest pay jumps happen where AI delivers direct business impact,” he says. Entry-level salaries in such roles range from Rs.5 lakh to Rs.15 lakh per annum, while mid-level professionals with proven impact can earn up to Rs. 40 lakh annually.

AI AND JOBS AT A GLANCE

1.Workers with AI skills command a 56% wage premium
2.45% of employers expect to hire workers with skills in AI. This trend is expected to significantly increase.
3.77% of employers plan to prioritise upskilling their existing workforce, signalling that AI adoption is driving reskilling rather than mass layoffs.
4.Skills demanded by employers are changing 66% faster in occupations most exposed to AI
5.39% of workers’ existing skills will be transformed or become outdated by 2030
6.41% of employers say they may downsize roles where AI can replicate tasks.
Source: PwC’s ‘The Fearless Future: 2025 Global AI Jobs Barometer’, WEF’s ‘Future of Jobs Report 2025’

Courses alone not enough

This also means that simply accumulating AI certificates is unlikely to help. Randomly listing courses from platforms like Udemy or Coursera is not an effective way to showcase AI capability. Chakravarty advises candidates to structure their resumes around use cases, tools, workflows and measurable impact. For example, instead of naming a course, candidates should explain how they built an AI-assisted workflow, what problem it solved and what business outcome it delivered.

He also notes that shortlisted candidates typically demonstrate three things clearly. They show business impact in terms of revenue, cost, time or efficiency. They provide proof of work through portfolios or pilots. They also explain guardrails, including data privacy, failure handling, and risk management. Candidates who are rejected, in contrast, tend to focus only on tools, exaggerate results, or fail to explain how their work reduces risk or errors.

Ultimately, companies care far more about outcomes than certificates. While AI-first roles may expand over the next three-to-five years, they are currently most common in the technology sector and often involve working with internal large language models and machine learning systems. Even so, there is little doubt that strong AI skills in any sector, combined with domain expertise and judgment, will significantly boost earning potential in the years ahead.