Deloitte’s Abhilasha Kataria Shankar on designing human-centred firms in the age of Agentic AI

As organisations begin to experiment with autonomous AI agents capable of participating in operational decisions and workflows, the relationship between human expertise and intelligent systems is entering a new phase. The Deloitte India CXO Playbook: Human with Agentic AI Era examines how this shift may reshape leadership priorities, governance structures, and workforce design as enterprises move from simple automation toward agentic AI systems.

In this conversation, Abhilasha Kataria Shankar, Partner and Organisational Change Management Leader at Deloitte India, reflects on the implications of this transition, outlining how organisations can build trust in AI and ensure that human judgment remains central as intelligent systems become more embedded in everyday work.

1. Deloitte India’s CXO Playbook on the “Human with Agentic AI” era examines the growing role of autonomous AI agents in organisational decision-making and workflows. From your perspective, how might this shift reconfigure the relationship between human expertise and intelligent systems in the workplace?

The relationship between humans and intelligent systems is moving from substitution to partnership. Agentic AI is increasingly capable of handling high-volume, rules-based decisions and operational tasks, which allows people to focus on areas where human judgment remains critical.

In practice, this means AI can take care of repetitive or structured workflows while humans step in where context, empathy, ethical judgment, and complex trade-offs are required. Many organisations are already moving towards a model where AI handles most of the operational activity, while people focus on exceptions, oversight, and strategic decision-making. This shift does not reduce the importance of human expertise; rather, it elevates it. Employees become supervisors, interpreters, and decision-makers who guide AI systems, validate outcomes, manage culture and relationships, and address areas that technology cannot resolve on its own. When designed well, this balance allows organisations to achieve both scale and accountability.

2. The report introduces the AgenticAdopt Kompass™ framework, which outlines six pillars for enabling effective AI adoption. Which of these pillars do you believe will prove most decisive for organisations in India as they begin integrating agentic AI into their operating models, and why?

While all six pillars of the AgenticAdopt Kompass™ framework are interconnected and necessary for scaling agentic AI, trust and Human-in-the-Loop (HITL) governance will be the most decisive for organisations in India in the near term.

Agentic AI introduces a new paradigm where intelligent agents can participate in operational workflows and decision processes. Especially in India’s context, where enterprises often operate at significant scale with large and diverse workforces, clearly defined HITL models help establish when humans intervene, how accountability is maintained, and how intelligent systems are guided within business processes.

This makes the human dimension of AI transformation particularly important. AI alone cannot make this transformation successful. Humans will continue to play a critical role in guiding AI, monitoring its outcomes, and ensuring that it is delivering the intended business value. Therefore, organisations must go beyond deploying technology and focus on creating a culture where employees understand, trust, and feel confident working alongside AI. 

When organisations deliberately design these guardrails while combining transparent governance with a culture that is receptive to AI, and a culture equally committed to empowering the human workforce, the adoption accelerates significantly. Ultimately, the organisations that succeed with agentic AI will be those that embed trust, clarity, and human-AI collaboration into their operating models from the outset.

3. As AI systems become increasingly capable of performing complex, decision-oriented tasks, how should organisations approach role redesign and workforce planning to ensure humans and AI complement rather than compete with each other?

Role redesign should start by identifying which tasks are routine and structured and which require human judgment or interaction. AI can manage repetitive tasks efficiently, while people focus on work that needs context, creativity, and accountability. 

Workforce planning, therefore, becomes less about replacing roles and more about rebalancing how work is distributed between humans and intelligent systems. As AI is also changing the social dynamics of the workplace, employees will need to collaborate with both humans and AI, the seamlessness of which will influence workflows and efficiencies. 

Leaders, therefore, need to address the psychological aspects of this shift by clarifying how human expertise complements AI, ensuring transparency in how AI contributes to decisions, and fostering a culture where employees see AI as a collaborator that enhances their impact rather than a competitor.

4. With India’s demand for AI talent projected to exceed 1.25 million by 2027, what strategies should organisations adopt to scale reskilling and capability-building efforts while keeping their existing workforce engaged and future-ready?

Organisations will need a blended workforce strategy that combines building, buying, borrowing, and automating talent depending on their sector and business needs.

Reskilling existing employees will remain essential, particularly in industries where large operational workforces already exist. Training employees in areas such as prompting, AI oversight, data fundamentals and deeper domain expertise can help them transition into roles that involve guiding or supervising AI systems. It is equally important to pay attention to the social fabric of a workplace, which highlights how people interact with each other and with AI systems. As AI becomes embedded in everyday work, sociology and psychology will play a critical role in shaping organisations and culture, building trust, influencing collaboration, and redefining relationships in both human-to-AI and human-to-human interactions. 

Alongside reskilling, organisations may need to hire specialised talent to accelerate innovation in areas like product development and advanced models. Partnerships with universities, startups and gig talent can also help address short-term capability gaps. HR will play a pivotal role in orchestrating this transition by designing large-scale reskilling programs, redefining roles and career pathways, and fostering a culture of continuous learning. The most effective strategies balance these approaches while encouraging individuals to take ownership of their own learning journey. Companies can create the ecosystem and opportunities; however, employees must step forward to develop the skills that will define the next phase of work.

5. Large-scale technological change often brings uncertainty among employees. In your experience, what are the most effective change management practices organisations can adopt to build trust and drive successful AI adoption?

Successful AI adoption depends as much on trust between humans and AI as it does on technology. Organisations that manage change well tend to focus on transparent communication, clear governance, and consistent engagement with employees.

One important step is clearly explaining how AI will be used, where human oversight will remain essential and how decisions will be governed. When employees understand the boundaries and safeguards, uncertainty reduces significantly.

Equally important is listening to employees, upskilling and cross-skilling them, and recognising that different teams may feel differently about the technology. Some may be enthusiastic, while others may be cautious. Addressing these micro-cultures through targeted communication and training helps move adoption from policy to everyday practice. Organisations should measure not only usage but also confidence and readiness. Indicators such as how many employees are proactively learning new skills or proposing new use cases provide a clearer signal of whether AI is truly being embraced.

6. Looking ahead, what new capabilities or mindsets will HR leaders need to develop as they take on a more central role in guiding organisations through AI-led workforce transformation?

HR leaders will play a central role in ensuring AI transformation remains human-centred. This means working closely with technology teams while understanding workforce sentiment, capability gaps, and organisational culture, and also helping design clear Human-in-the-Loop (HITL) models. Even as AI becomes more capable, humans will continue to play a critical role in training AI systems and validating their outputs to supervising workflows and ensuring that outcomes remain aligned with organisational goals and values.

As AI becomes embedded in operational processes, HR leaders will also need to guide role evolution and workforce redesign efforts. Employees will increasingly move into roles such as AI supervisors, human-in-the-loop analysts or domain specialists who interpret outputs, manage exceptions and steer AI systems toward desired outcomes. This requires organisations to consciously design human–AI interaction pathways—defining how humans initiate, guide and review AI-driven work, and where human judgment must intervene.

Equally important is shaping the right mindset and culture. HR leaders must foster psychological safety, so employees feel confident experimenting with new tools, building new capabilities and adapting to evolving responsibilities. By combining structured reskilling with thoughtful design of human-AI collaboration, HR can ensure that AI adoption strengthens both organisational performance and the human experience of work.