It has become a cliché to say that artificial intelligence will “take care of the boring stuff” so humans can focus on higher-value work. But clichés often hide more than they reveal. As AI scales into coding, scheduling, data analysis and even creative drafting, the real question is whether organisations are equipped to preserve and cultivate the skills that machines cannot master.
The paradox is stark. AI is advancing fastest in domains that are easily measurable — throughput, optimisation, efficiency. Yet employers are paying a rising premium for precisely those human capabilities that resist codification: empathy, ethical judgement, the ability to interpret ambiguity, and the knack for inspiring others to act.
Independent evidence backs this up. The World Economic Forum’s Future of Jobs 2023 report lists analytical and creative thinking as the two most in-demand core skills through 2027, followed closely by resilience, flexibility, and emotional intelligence.
Nearly 60% of workers will need retraining by 2027, but only half are expected to have adequate access. LinkedIn’s own surveys echo the urgency: a majority of hiring managers now rank so-called soft skills above technical knowledge when predicting long-term success.
To understand how this paradox is playing out in real companies, People Matters invited three senior leaders to share perspectives: Deepti Varma, Vice President, PXT – Amazon Stores (India, Japan and Emerging Markets); Priti Kataria, CHRO at Birlasoft; and Suprabha Subramaniam, People Director at AB InBev GCC India.
Their insights reflect a wider shift underway: not a retreat from technology, but a deliberate effort to build leadership, collaboration and empathy into the operating system of business.
AI makes human skills more — not less — valuable
For Subramaniam, the starting point is cultural. “As people increasingly leverage AI and automation for transactional and technical tasks, human qualities of empathy, collaboration, adaptability, and critical thinking have become non-negotiable. At AB InBev GCC, these skills are not just competencies – they are reflected in our core values,” she explains.
Her observation echoes a global sentiment. Across sectors, employers are realising that technology alone cannot differentiate. It is the human interface — whether in how teams resolve conflicts, how managers earn trust, or how leaders frame decisions in times of uncertainty — that sustains competitive advantage.
Subramaniam goes further: “As AI handles the more transactional or automated tasks, we place greater value on enabling and empowering our people to lead through ambiguity, influence stakeholders, and collaborate across cultures — skills now embedded into how we attract and develop great talent.”
In other words, far from being threatened by AI, these capabilities are being elevated to the centre of talent strategy.
Hiring in the age of AI: testing for judgement, not just skill
If the recruitment process once prized technical prowess, it is now as much about decision quality under pressure.
Varma explained: “At Amazon, we have evolved our approach to evaluating what may be called ‘soft skills’ though we see them as fundamental professional capabilities. Our hiring explicitly assesses capabilities like navigating ambiguity and synthesising diverse perspectives alongside technical skills.”
That assessment begins with Amazon’s well-documented Leadership Principles, which include imperatives such as Learn and Be Curious, Bias for Action, and Dive Deep. As Varma points out, these principles map directly onto behavioural traits like adaptability, relationship building and critical thinking.
Amazon operationalises this in practice. Rather than hypothetical scenarios, interviewers ask candidates to describe specific situations where they demonstrated ownership, resilience or judgement. Collaborative problem-solving exercises are used in technical hiring to reveal how candidates think aloud, accept feedback and adjust their approach.
The philosophy carries over into internal mobility. Amazon tracks “patterns of behaviour” — not just technical results — to determine readiness for new roles. "We have found that employees who demonstrate these skills often succeed in new roles even when they don't have all the technical requirements at the outset," said Varma.
This matters because it signals a new kind of meritocracy: one that values how people think and decide, not simply what they already know.
Rebuilding leadership pipelines
For Kataria, the rise of AI has forced organisations to rethink leadership development from the ground up. “The rise of AI has called for a conscious focus on embedding soft skills,” she says. “AI-enabled data drives efficiency and effective decision-making, but it cannot be truly impactful without empathy, adaptability, critical thinking, and ethical judgment going hand in hand.”
At Birlasoft, this belief has reshaped the company’s learning and development programmes. Fresh graduates are exposed early through Campus-to-Corporate initiatives that emphasise collaboration and inclusivity. Mid- and senior-level managers go through capability-building series like Manager as a Coach and the High Performing Manager Series, which equip them to influence, resolve conflict and coach others — not just manage deliverables.
Leadership conversations are also designed differently. Kataria points to “Listening Lounges” and other formats that encourage transparency and psychological safety, creating forums for managers to align direction and surface ethical concerns.
This isn’t simply a cultural flourish. Kataria frames it as a strategic necessity: “Balancing rapid AI adoption with sustained investment in human potential is not a choice between the two, it’s about harmonising them. Technology by itself does not create differentiation; it’s how people leverage, adapt, and apply it responsibly that delivers true value.”
The company has even embedded capability development into its AI strategy. While rolling out platforms like GenAI Academy to scale AI literacy, Birlasoft has simultaneously expanded behavioural programmes that strengthen resilience and ethical decision-making. The result is what Kataria calls an “integrated approach” that ensures teams are both technically competent and humanly discerning.
Making empathy operational
Empathy has long been described as a “soft” trait, but the leaders interviewed insist it is a hard-edged business capability.
Varma frames it in terms of leadership foresight. “Apart from the soft skills shared above — life skills, well-being as a skill, and change agility — we believe the most successful leaders in an AI-powered enterprise will be defined by their ability to make judgement calls and co-lead with AI. That means exercising judgement with speed, balancing multiple truths, and making principled decisions when data alone doesn’t give a clear answer.”
For Amazon, this translates into what she calls “adaptive wisdom”: the unique blend of human judgement, emotional intelligence and strategic foresight. To cultivate it, Amazon designs environments where leaders are “immersed in real-world scenarios that stretch decision-making capabilities and challenge conventional thinking.”
At AB InBev GCC India, the strategy is to ensure empathy is systemically reinforced. “At AB InBev GCC, we’re investing in a wide range of programs from technical and enterprise to leadership programs to help catalyse this skillset evolution, amplify decision-making, drive innovation, and deliver long-term impact,” Subramaniam explains.
Empathy here is not ornamental. It is a process requirement: ensuring leaders are equipped to balance data with human context, and that teams retain psychological safety even as workflows accelerate.
The measurement challenge
If there is one consensus across business and research, it is that soft skills are hardest to measure — and therefore hardest to protect in budget debates.
Kataria warns that without deliberate effort, organisations risk under-investing. “Balancing rapid AI adoption with sustained investment in human potential is not a choice… We’ve embedded human capability development into our AI strategy from the outset,” she stresses.
The WEF has flagged the danger: while six in ten workers will require training by 2027, fewer than half are projected to access it. Deloitte analysis suggests soft skills could contribute trillions to global GDP by 2030, but few firms have robust ROI frameworks to justify the spend.
Some proxies exist — tracking internal mobility, correlating manager training with retention, or linking customer satisfaction to leadership behaviour. But these remain imperfect. Until measurement matures, soft skills investment risks being seen as discretionary, precisely when it is most critical.
The human premium
Despite the measurement problem, market behaviour indicates a clear repricing of human skills. A 2023 report by the Burning Glass Institute found wage premiums for roles requiring strong communication, critical thinking and leadership, even in technical industries. Employers are not simply paying for AI literacy; they are competing for employees who can interpret complexity, rally teams and make judgement calls.
This premium is visible in the language of all three leaders. Varma underscores the need for adaptive wisdom. Kataria insists on harmonising AI with human judgement. Subramaniam describes empathy and collaboration as non-negotiable.
None of them suggest technical skills are irrelevant. But all argue that without the distinctly human layer — the glue of trust, the clarity of communication, the discipline of ethical reasoning — organisations will end up with what Kataria describes as “high-speed systems and low-capacity teams.”
A new social contract at work
What emerges from their perspectives is a new social contract. AI will take over what is codifiable: data crunching, scheduling, repetitive coding. Humans are expected to excel at what is ambiguous: interpreting incomplete signals, balancing values, and communicating decisions with empathy.
But this shift is not automatic. It requires deliberate investment in:
Clarity: Defining which human skills matter most to the organisation’s mission.
Design: Building assessments and learning pathways that reinforce those capabilities.
Measurement: Protecting investment by tying human skills to retention, innovation and customer outcomes.
Without these steps, organisations risk being hollowed out: efficient but fragile, technologically sharp but strategically underpowered.