Head of People & Culture Says AI Transformations Can Collapse Under Silos and Technical Debt

During these 24 years, I have worked across every aspect of the Human Resources function, including roles at Wipro and Microsoft.

Building strong business connections and making an impact through my initiatives energizes me. I have led and managed talent transformations in complex, matrix business environments.

I add value by influencing business and people decisions with empathy and purpose. I pride myself on being a keen listener to voices on the ground. I focus my work on areas that drive real change — such as early talent, new-age leadership, and diversity. I am passionate about what organizations can achieve by being purposeful.

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How AI is Transforming HR and Leadership Roles

HR leaders need a clear vision to guide the function’s future…The future of HR is not about choosing between humans and AI, but about harnessing the power of both.

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Shweta MohantyOpens new window

Head of People & Culture at SAP in India

While AI already streamlines repetitive and administrative tasks previously handled by people, it also prompts a deeper question: how will HR evolve as AI moves beyond basic support functions into areas traditionally requiring human judgment and expertise?

The future of HR is not about choosing between humans and AI, but about harnessing the power of both. With AI advancing rapidly, HR leaders are at a critical crossroads. To remain relevant and impactful, they must strengthen distinctly human capabilities while learning to collaborate with AI to enhance HR’s strategic influence and value.

How AI Enhances HR Operations and Employee Engagement

AI and People teams collaborate effectively in HR operations and service delivery. AI significantly removes friction through policy queries, onboarding automation, and transactional processing. But HR leaders bring in the human element through escalation judgment and exceptional handling.

Our Lounge experience complements and emphasizes the importance of human touch by ensuring an HR representative is available to meet employees for any sensitive, confidential conversation.

Another area is employee experience & engagement. Here, AI detects patterns, and People functions respond with empathy using listening-based interventions. At SAP, we extensively use AI for sentiment analysis, pulse surveys, engagement drivers, and burnout signals. But humans act on the feedback with nuanced interventions, ensuring psychological safety.

Why AI Improves Talent Visibility and Internal Mobility

AI can surface insights that traditional approaches may not always reveal. It has helped us move towards a more inclusive, forward-looking way to identify and develop talent, while allowing leaders to focus more on judgment and context rather than data synthesis.

AI has meaningfully changed how we approach talent visibility and internal mobility through the Talent Intelligence Hub in SAP SuccessFactors.

Before, our talent processes relied significantly on manager inputs, static profiles, and periodic talent reviews. While these provided useful insights, visibility and subjectivity often limited them, and they did not always reflect the full range of skills individuals brought to the organization.

With Talent Intelligence Hub, we built a more dynamic, skills-based view of our workforce. AI infers skills from multiple sources such as resumes, performance data, and learning history, and continuously updates employee profiles. It integrates with internal opportunities and learning platforms, allowing more personalized recommendations for roles, projects, and development pathways.

This has changed how we make talent decisions. Conversations are now more data-informed, with greater visibility into skills, potential, and adjacent capabilities across the organization. It has also enabled more proactive internal mobility, reducing reliance on networks or self-nomination.

How to Address AI's Promise vs Organizational Reality

Shweta Shares

AI has humbled me. It challenged my ‘know-it-all’ attitude at multiple levels.

Rather than seeing AI as a tool for control or top-down optimization, I’ve come to view it as a copilot that enhances thoughtful, empathy-driven decision-making instead of replacing it.

The growing hype around AI’s promise of rapid, industry-wide transformation concerns me. The narrative suggests sweeping change, yet the reality inside most organizations looks very different.

A clear gap exists between AI ambition and AI literacy, compounded by organizational inertia and long-standing legacy constraints. While productivity may improve incrementally, organizations often lack the capability and maturity to translate those gains into scaled, enterprise-level impact.

Despite strong pressure to adopt AI, many organizations struggle to move forward due to silos, technical debt, fragmented systems, and poor data quality.

Individual adoption of AI tools does not automatically translate into meaningful organizational transformation. Enterprise change requires structural alignment, capability building, and cultural evolution, not just access to new technology.

How AI Tools Enhance HR Decision-making and Efficiency

My approach to using AI is tool-agnostic but outcome-focused. My goals have been to reduce administrative workload, improve decision quality, and enable better communication. In the last few months, these are the tools I have used the most:

1. ChatGPT/Copilot: Hands down the best tool for drafting HR communications (policies, emails, performance feedback), creating structured interview questions, summarizing meeting notes, drafting learning content, and documentation.
2. Perplexity AI: I use Perplexity for research, academic work, fact-checking, references, and benchmarking information. I find Perplexity more reliable for these purposes.
3. Joule: Joule is SAP's own conversational AI copilot, and I use it extensively for information within SAP. I frequently use it for contextual analysis and data insights.
4. Tableau, Power BI: I use these for analytics and predictive models.
5. Claude: I have just started using Claude for presentations.

Why AI-assisted drafting in ChatGPT is impactful

Shweta Shares

I appreciate it (AI) because it functions as a real-time thinking partner rather than just a productivity tool.

Over the past year, I've been loving AI-assisted drafting and summarization in ChatGPT. It's integrated into Copilot, making it handy to use at work to produce structured first communication drafts quickly, which I then refine for tone and context.

I also use it for meeting intelligence, capturing meeting notes and transcripts, creating meeting summaries for different stakeholders, and extracting action areas and key decisions.

I appreciate it because it functions as a real-time thinking partner rather than just a productivity tool. It helps convert unstructured thoughts into clear outputs quickly, which is extremely valuable in leadership roles where communication, documentation, and clarity on decisions are critical.

How to Overhaul HR Workflows with AI Integration

At SAP, we are in the middle of a massive transformation called "All In on AI," which involves re-evaluating all people processes with an AI lens. We have made tangible progress in a few areas:

1. Recruiting: Last year, we acquired 'SmartRecruiters,' an AI-powered recruiting platform. We are implementing it internally at SAP. It uses AI, particularly through its "Winston" AI agent and "SmartAssistant" feature, to accelerate hiring, reduce bias, and automate repetitive tasks. We are already seeing improved recruiting productivity by screening applicants, providing intelligent candidate recommendations, matching skills to jobs, and offering a personalized, engaging candidate experience.
2. At SAP SuccessFactors Growth Portfolio, we are implementing Talent Intelligence Hub, a dynamic, AI-driven profile that maps employee skills, strengths, and career aspirations. AI features automatically infer skills from resumes and performance data, recommend development goals, match employees with internal gigs, and provide personalized career insights to drive talent mobility. AI-Assisted Skill Mapping automatically populates skills from resumes/CVs, reducing manual maintenance. Skill Gaps Identification highlights top skills to improve and top strengths to guide development, and dynamic recommendations suggest learning opportunities, mentoring, and roles based on AI analysis.

I have personally seen the tangible impact of these initiatives, as AI acts as a force multiplier, allowing leadership teams to focus more on strategic people decisions rather than administrative overhead.

How to Build AI Literacy and Become AI-ready

Building AI literacy is a key focus for us. We believe access to tools alone does not translate into impact, capability and confidence do. At SAP, we approach this through a structured, multi-layered learning ecosystem.

Programs like the AI Developer Foundation help more than 1,200 employees build hands-on AI skills, while the AI Leader Foundation helps managers and experts build an AI-first mindset, covering areas such as generative AI, agents, and use-case productization.

Alongside this, initiatives like Learning Fest and the SAP Experience Garage ensure learning applies in real contexts, as employees work on customer use cases, build proofs-of-concept, and contribute to product innovation.

We also invest in continuous learning through internal tracks across engineering roles, as well as academic partnerships with institutions like IIITB, IIMB, and ISB to deepen advanced AI capabilities. Importantly, we do not limit our focus to technical roles. We expand AI literacy across non-technical teams and leadership to ensure enterprise-wide readiness.

For us, being “AI-ready” means employees comfortably experimenting with AI, applying it in their day-to-day work, and collaborating across teams to drive meaningful outcomes. The biggest challenge is bridging the gap between strong interest in AI and consistent, practical adoption.

However, by anchoring learning in real-world applications and integrating it into daily workflows, we see a steady shift from awareness to meaningful impact.

How AI-native Trends Reshape Strategy and Execution

From a people perspective, it also shapes the capabilities we prioritize. There is a growing need for talent that can work across business, data, and technology — and that is comfortable working alongside AI.

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Shweta MohantyOpens new window

Head of People & Culture at SAP in India

The rise of agentic workflows and AI-native competitors is changing expectations, especially around speed, responsiveness, and how seamlessly work gets done. For us, we are not rethinking the business model entirely, but evolving how we deliver value through what we already do.

At SAP, we focus on embedding AI more deeply into our products and workflows to make outcomes more intelligent and contextual. This also influences our organization design. Work is becoming less linear and more fluid, which means teams need to collaborate more closely across functions and adapt quickly.

Overall, I see this less as a disruption to our strategy and more as a shift in how we execute it, moving faster, staying aligned, and continuously evolving how we create value.

What Leaders Should Know About Navigating AI Transformation

This moment of transformation is both exciting and challenging, and my advice to leaders — especially those in HR or people-focused roles — is to approach AI with curiosity, intentionality, and a strong commitment to human-centered leadership.

1. Experiment early and often. Leaders should actively explore AI tools themselves to understand how they can augment everyday workflows. The goal isn’t to adopt technology for its own sake, but to identify areas where AI can reduce administrative burden, accelerate insight generation, and free up time for higher-value leadership work.
2. Focus on augmentation rather than replacement. AI works best when it enhances human capabilities. In functions where judgment, empathy, and context are critical —  like HR, leadership, and people management — AI should serve as a thinking partner and productivity multiplier, not a substitute for human decision-making.
3. Invest in AI literacy across the organization. Leaders should help teams build confidence in using AI responsibly. This means encouraging employees and managers to learn how to use AI tools effectively, understand their limitations, and develop good practices around prompting, verification, and ethical use.
4. Maintain strong cultural guardrails. As organizations integrate AI more deeply into their operations, it becomes even more important to reinforce values such as transparency, fairness, accountability, and inclusion. Leaders must ensure thoughtful implementation and clear oversight of AI-driven processes, especially in areas like hiring, performance evaluation, and workforce analytics.
5. Stay anchored in the human dimension of leadership. Technology can accelerate processes and provide powerful insights, but the core of leadership will always be about building trust, developing people, and creating environments where individuals can thrive. The leaders who will navigate this transformation most successfully are those who combine technological curiosity with deep empathy and a clear sense of purpose.

Shweta Shares

In functions where judgment, empathy, and context are critical — like HR, leadership, and people management — AI should serve as a thinking partner and productivity multiplier, not a substitute for human decision-making.

Why AI Will Enhance Human-centric Business Approaches

AI will make the world more human-centric than ever before. While AI can automate tasks and surface insights at unprecedented speed, its true value lies in how effectively we use it to enhance human capability rather than replace it.

This shift will require us to move away from traditional models of linear careers, linear education, and fixed learning paths toward a future where individuals constantly learn, adapt, and explore new perspectives throughout their lives.

Although AI will dramatically increase scale and efficiency, meaningful progress will still depend on human connection, empathy, and trust. Technology can support better decisions and productivity, but it cannot replace the relational foundations that drive strong teams and resilient organizations.

As companies increasingly adopt AI-powered tools, leaders will need to be intentional about ensuring that transparency, fairness, and inclusion remain central to how organizations shape and sustain their culture.

In this sense, the real challenge of AI will not be technological. It will be how thoughtfully we integrate it into systems that continue to prioritize people.

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