AI data privacy and governance reshape enterprise strategy: Cisco study

Cisco has released the findings of its 2026 Data and Privacy Benchmark Study, highlighting a fundamental shift in how organisations approach AI data privacy and governance. The study shows that as AI adoption accelerates, enterprises are expanding privacy programmes and governance frameworks to protect data while continuing to innovate at scale.

The growing demand for high-quality data to support AI systems is exposing gaps in oversight, increasing the importance of trust, security, and competitiveness. According to the study, scalable and responsible AI strategies now depend on a mature and integrated approach to privacy and data governance.

Survey scope and rising investment trends

Cisco surveyed 5,200 IT, technology, and security professionals with data privacy responsibilities across 12 global markets. The results indicate that AI has become the primary driver of change, with 90% of organisations reporting expanded privacy programmes and 93% planning further investment to keep pace with AI system complexity and evolving regulatory expectations.

Spending levels have also increased. Globally, 38% of organisations surveyed reported investing at least USD 5 million in their privacy programmes over the past year, a significant rise from 14% in 2024.

Privacy and trust move beyond compliance

The study finds that 95% of organisations believe strong privacy frameworks enable greater AI agility and innovation. An equal proportion recognise privacy as essential to building customer trust in AI-powered services.

In India, the shift is particularly pronounced. All organisations surveyed in the country reported at least one tangible benefit from privacy initiatives, including improved agility, innovation, and stronger customer loyalty. Clear communication around data collection and usage emerged as a key trust factor, with 46% identifying it as the most effective way to build customer confidence.

Despite this progress, governance maturity remains uneven. While nearly two-thirds of organisations in India have established a dedicated AI governance body, only 12% describe these structures as mature. In addition, 70% of organisations report difficulty accessing relevant, high-quality data efficiently as AI systems increasingly rely on complex and distributed datasets.

Jen Yokoyama, Senior Vice President, Legal Innovation and Strategy at Cisco, said AI is driving a fundamental shift in how organisations manage data, requiring holistic governance of both personal and non-personal information. She noted that understanding and structuring data is essential to ensure automated decisions are explainable, supporting not only compliance but also scalable AI innovation.

Data localisation and cross-border challenges intensify

The expansion of AI is also amplifying challenges related to global data flows. While 79% of respondents in India express general confidence in data privacy laws, there is growing pressure to simplify and modernise data requirements.

According to the study, 91% of organisations in India face increased demands related to data localisation and global data complexity. The same proportion report that localisation requirements add cost, complexity, and risk to cross-border service delivery, while 87% say these requirements limit their ability to provide seamless, round-the-clock services across markets.

These pressures are shaping partner preferences. Globally, 87% of organisations believe technology providers operating at global scale are better positioned to manage cross-border data flows effectively.

Harvey Jang, Vice President and Chief Privacy Officer at Cisco, said organisations are increasingly advocating for harmonised international standards to unlock AI’s potential. He added that consistent global approaches are viewed as an economic necessity to ensure secure data flows while maintaining high protection standards required for trust.

From reactive compliance to responsible AI strategies

The study concludes that organisations seeking to thrive in an AI-driven economy must move beyond reactive compliance models. Recommended actions include investing in robust data infrastructure, prioritising transparency, embedding privacy and security across AI initiatives, and making informed decisions around data localisation.

Establishing strong AI governance structures and equipping teams with appropriate training and safeguards are identified as critical steps for building long-term trust, enabling responsible innovation, and sustaining competitiveness as AI adoption continues to expand.

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