Q&A: Wipro’s Global Chief Privacy and AI Governance Officer

Data is the driving force behind today’s digital economy, fueling innovation, economic growth and transformative change across industries. 

Yet, the analogy of “data as the new oil” oversimplifies its unique properties: unlike oil, data can be reused endlessly, making it both a powerful asset and a source of complex challenges. 

The prevailing model of “data extractivism” — where vast amounts of information are harvested, stored and exploited — has led to mounting ethical, environmental and privacy concerns, from data breaches and profiling to the escalating energy demands of global data centers.

Amid these challenges, synthetic data has emerged as a promising, though not unproblematic, alternative.

Ivana Bartoletti is the Global Chief Privacy and AI Governance Officer at Wipro, as well as an adviser to the council Europe on AI and gender rights. 

She’s also the co-founder of the Women Leading in AI Network and author of An Artificial Revolution: On Power, Politics and AI.

She ensures that both Wipro’s internal AI initiatives and those it delivers for its clients are developed with strong privacy, security and legal safeguards. 

Leading global technology services and consulting company Wipro supports clients in an increasingly complex and fast-evolving world — particularly in the field of artificial intelligence.

With a workforce of more than 230,000 people and partnerships across 65 countries, the company focuses on building innovative solutions that address its clients’ most complex digital transformation needs.

“At its core, the work of my team is about embedding ethical principles into the heart of technology,” she says.

In this Q&A with Technology Magazine, Ivana discusses the challenges that come with masses of data, the benefits synthetic data brings and underscores the need for robust safeguards and thoughtful governance as organisations seek to balance innovation with responsibility.

With such a mass volume of data generated daily, how should organisations respond to the associated environmental and ethical challenges?

The fundamental question organisations should ask is: do we truly need all this data? Simply generating vast volumes of information is not of inherent value. 

Organisations need to critically evaluate their data collection practices and recognise the environmental impact of data storage.

Equally important is the adoption of eco-conscious practices, such as investing in energy-efficient hardware, deploying deduplication tools to eliminate redundant files and important not only for reducing environmental harm but also for upholding ethical standards in data management.

In light of increasing concerns over data breaches, profiling and lack of transparency in data collection, how can companies rebuild public trust and ensure individuals have meaningful control over their personal data?

Transparency is key.

If someone is shown a targeted advertisement or denied a loan, they should be informed of the reasoning behind these outcomes, rather than being left in the dark by opaque algorithms. 

Organisations must go beyond simply complying with privacy regulations, they need to communicate clearly with people and be open about how their data is being used to make decisions that impact their lives.

Expecting people to manage every aspect of their personal data is increasingly unrealistic in our highly connected world. Who genuinely reads all the terms and conditions? Yet that doesn’t mean people shouldn’t feel confident in the systems and applications they rely on.  Quite the opposite. Organisations should go above and beyond helping users understand what they need to and empowering  — rather than overwhelming — them.

In an age where privacy, security, ethics and innovation intersect, companies that embed these values into their operations not only safeguard their users, they also earn trust and gain a meaningful competitive edge.

How does synthetic data work in practice and what are the potential benefits of it in enhancing privacy, reducing environmental impact and improving data availability?

Synthetic data is artificially generated using models trained on real datasets to replicate their patterns, structures and statistical properties. 

When done well, synthetic data should yield similar analytical outcomes to the original data without revealing any real individual’s information. 

Its effectiveness hinges on how accurately it reflects the original dataset while removing identifiable elements.

In the context of machine learning, synthetic data is playing an increasingly vital role. 

From a privacy standpoint, it offers significant advantages: it allows organisations to develop and test models without compromising personal data, which is particularly valuable in highly regulated or sensitive sectors.

Synthetic data can also help reduce environmental impact by lessening the need for repeated data collection, which is often energy and resource intensive. 

It also enhances data availability, enabling innovation in situations where real data is scarce, sensitive, or costly to obtain.

Challenges remain in ensuring high enough data quality, avoiding the risk of re-identification and balancing the trade-offs between privacy, accuracy and utility are critical areas that require continued attention and oversight.

What role should regulation and governance play in shaping responsible data practices, particularly with emerging technologies like synthetic data? How can organisations balance innovation with robust privacy and ethical standards?

Strong corporate governance plays a critical role in shaping responsible data practices, particularly in the context of emerging technologies such as synthetic data. 

Again, this goes far beyond simply meeting legal obligations, it’s about earning and maintaining trust with consumers, partners, and regulators.

Organisations must adopt a comprehensive risk management strategy, underpinned by clear governance structures that span all departments. Education is vital. 

Every team member should understand how to develop and use technologies effectively and responsibly, including how to engage with AI tools without becoming overly dependent on them.

Responsible innovation means designing with privacy, security and legal compliance in mind from the outset, not collecting data indiscriminately, but using it in a fair, transparent and ethical way. 

Synthetic data can be a key enabler in this process, supporting the development of advanced AI systems while reducing the risks associated with using real personal data.

Ultimately, organisations should view privacy and ethical data use not as a regulatory burden, but as a strategic advantage.

Investing in upskilling teams and embedding responsible practices into the innovation lifecycle is essential for building long-term resilience and trust.

Explore the latest edition of Technology Magazine and be part of the conversation at our global conference series, Tech & AI LIVE.

Discover all our upcoming events and secure your tickets today.

Technology Magazine is a BizClik brand