As organisations race to build AI capabilities, compensation strategies are evolving alongside them. Across India, professionals with expertise in generative AI, MLOps and agentic systems are commanding significantly higher salaries than peers in non-AI roles, prompting questions about whether a new form of pay inequality is emerging inside companies.
For Priya Venkatraman, Group Chief Human Resources Officer, Bahwan CyberTek (BCT), the issue is less about unequal pay for equal work and more about how organisations respond to a rapidly changing skills market.
She believes employers must balance market realities with internal fairness while ensuring AI opportunities are not limited to a small group of specialists.
AI skills are attracting a scarcity premium
According to Venkatraman, data increasingly reflects what organisations are witnessing across the market.
“In India, AI-skilled professionals may earn a premium of about 30-40% over comparable non-AI-related roles at the senior level and about 20% at the entry level, particularly in areas like generative AI, MLOps and agentic systems.”
However, she cautions against viewing the trend solely through the lens of pay inequality.
“But I would call it a scarcity premium rather than a pay gap. It’s not necessarily about two people doing the same job being paid differently. It’s about certain skills being in very high demand and short supply.”
She notes that organisations face a dual challenge.
Key considerations for employers include:
- Responding to market demand for scarce AI skills
- Avoiding internal compensation distortions
- Building AI capabilities through internal development
- Reducing overreliance on external hiring
“The challenge for organisations is to respond to that market reality without creating distortions internally. At the same time, we need to get much better at developing these skills from within rather than relying only on hiring from the market.”
Fairness depends on clarity, not uniformity
As AI talent commands higher rewards, employee perceptions of fairness become increasingly important.
Venkatraman says organisations need to distinguish between market competitiveness and internal equity.
“For genuinely scarce and business-critical skills, companies may have to pay a market premium. But that cannot become an excuse for arbitrary compensation decisions.”
She advocates clearer skills-based compensation models that explain what employees are being rewarded for.
“The answer is to build clearer, skills-based compensation structures so employees understand what skills, experience and impact are being rewarded.”
In her view, employees generally accept differences in pay when the rationale is transparent.
“People generally accept differences in pay when the logic behind those differences is clear and consistent. What affects morale is when those differences appear unexplained or unfair.”
She also stresses that compensation alone does not determine how employees assess their value within an organisation.
“Learning, meaningful work, career progression and the opportunity to work with emerging technologies can be equally important in how employees perceive their value and future within the organisation.”
Traditional technology skills remain critical
While AI skills are attracting greater attention, Venkatraman does not see traditional technology roles becoming less relevant.
“I don’t think the importance of traditional tech roles is going away. They are changing their form.”
She points to the continued importance of platforms, integration, operations, security, quality and infrastructure.
“AI requires strong foundations to work effectively, not a replacement for it.”
In many cases, she says, employees in traditional technology functions are well positioned to transition into AI-related work because of their understanding of systems, data and production environments.
“At BCT, we see those with a solid grounding in technology tend to move quickly into AI-driven, agentic work.”
Her assessment is straightforward. “We should therefore see traditional technology as a foundation for AI, rather than two separate camps.”
Compensation strategies are becoming more skills-focused
The competition for AI, data and emerging technology talent is reshaping how organisations reward employees.
According to Venkatraman, three shifts are becoming increasingly visible.
First, compensation is becoming more skills-based.
“The same job title can have different market value depending on the skills it involves, so companies need to benchmark skills more frequently.”
Second, rewards are becoming more targeted.
“In India, overall salary increments are averaging around 9%. More of the rewards are going toward scarce skills and top performers.”
Third, organisations are broadening the employee value proposition.
For highly sought-after talent, compensation now extends beyond fixed pay.
“For sought-after talent, companies are also leveraging variable pay, faster career progression, learning opportunities and meaningful work.”
She notes that Indian IT services firms often face intense competition from global capability centres and AI-native organisations.
“An Indian IT services company cannot always compete with global capability centers or AI-native companies on salary alone. So we have to provide a stronger overall value prop - meaningful work, domain exposure, learning and career growth.”
The risk of a two-speed workforce
Pay differences alone do not necessarily damage workplace culture, according to Venkatraman.
“Pay differences are not inherently a problem. The bigger issue is whether people understand and believe the reasoning behind them.”
She says transparency and perceived fairness are critical to employee engagement and retention.
“When compensation is transparent and perceived as fair, employees are more likely to accept differences based on skills, impact or market demand.”
Problems emerge when compensation decisions appear inconsistent.
“The trouble starts when the differences seem arbitrary. This can lead to resentment, disengagement and attrition.”
She also highlights the risk of pay compression.
“There’s also the risk of pay compression, where a new hire is paid more than an existing employee of longer tenure & experience for no apparent reason.”
Over time, such situations can create divisions inside organisations.
“This can lead to a two-speed workforce where some employees feel like they are part of the future and others feel like they are overlooked.”
For leaders, communication remains essential.
“This is why communication from managers and fairness are as important as the numbers themselves.”
Why access may matter more than pay
Looking ahead, Venkatraman expects AI salary premiums to moderate as skills become more widely available.
“I expect the premiums to come down, but not disappear.”
She compares AI’s trajectory with previous technology waves.
“We've seen the same pattern with cloud, mobile and data science. As skills become more common, the premium for basic skills reduces.”
However, she believes the premium will continue shifting towards emerging capabilities.
“Today it's generative AI and agentic systems. Tomorrow it will be something else.”
The longer-term differentiator, she argues, will be the ability to connect AI expertise with business outcomes.
“Knowing how to use AI will become common. Knowing how to use it to solve a real business problem will remain valuable.”
More importantly, she believes organisations should focus on preventing an access divide.
“The pay gap is a symptom; the bigger risk is an access gap.”
She argues that every employee should have opportunities to develop relevant AI skills and participate in the transformation of work.
“Everyone should have a pathway to build relevant AI skills, experiment with the technology and understand how their role is changing.”
This requires investment in learning, mobility and workforce development.
“That means structured upskilling, internal mobility and giving employees opportunities to move into emerging areas of work.”
Ultimately, Venkatraman sees workforce confidence as a critical factor in successful AI adoption.
“People are less likely to fear change when they have skills, opportunity and agency in that change. Compensation matters, but so do learning, career growth and the confidence that there is a place for them in the AI-enabled organisation.”