Privacy frameworks to strengthen global governance, responsible AI in 2025: Inspira

Globally, cybersecurity ranks among the top priorities for organizations to ensure resilience and secure digital transformation.

According to a KPMG report, 68% of organizations prioritize cybersecurity for investment, making it a core area of focus alongside AI/automation (65%) and edge computing (61%).

While India leads the initiatives to enhance data security and governance​, enterprises continue to leverage and experiment with emerging technologies.

Munish Gupta,
President and Global Head – Cybersecurity, 
Inspira Enterprise

Munish Gupta is the President and Global Head of cybersecurity at Inspira Enterprise. He has spent more than two decades navigating the shifting landscape of cybersecurity, a path that has taken him through roles of increasing responsibility and global reach.

In a conversation with CIO&Leader, Munish shares his perspectives on emerging threats, the role of AI in defense strategies, and the broader societal responsibilities that now accompany cybersecurity leadership.

CIO&Leader: As we see AI coming out of theoretical discussions and into widespread application, how are AI-driven tools transforming threat detection and proactive cyber defenses, especially given that AI can sometimes become part of the problem?

Munish Gupta: The journey of AI in cybersecurity has moved well beyond the conceptual stage. Until a couple of years ago, AI and machine learning were part of high-level boardroom conversations, often confined to future-proofing strategies. Now, AI is integrated into actual product offerings, shaping real-time threat detection, anomaly identification, and proactive response frameworks. Before this, we relied heavily on predefined rules and a certain degree of automation, which could highlight suspicious activities but often lacked the contextual awareness needed to distinguish a genuine threat from a harmless anomaly.

With AI, and more specifically large language models and deep learning techniques, the security apparatus can understand context at a far deeper level. Another area where AI excels is in evaluating the human factor. Humans have always been a key vulnerability, no matter how robust the technical controls. AI can simulate phishing scenarios tailored to different user profiles and identify individuals more prone to clicking suspicious links. Rather than applying a one-size-fits-all training session, organizations can now deliver targeted awareness programs, focusing efforts where they’re truly needed. This helps build a human firewall that is as adaptive and informed as the technology behind it.

CIO&Leader: For CIOs looking at these AI tools, what should they consider beyond the simple act of purchasing a product to ensure long-term and meaningful value?

Munish Gupta: Selecting an AI-driven solution must start with a clearly defined purpose. CIOs and CISOs should ask themselves what problem they aim to solve, is it faster threat detection, more refined user behavior analytics, or improved data classification that respects privacy constraints? Once the objective is set, it becomes easier to evaluate which tools align best with these goals. The technology market is filled with vendors offering AI-infused products—vendors like Palo Alto and Zscaler, or platforms leveraging next-gen capabilities like Darktrace. Yet without a well-defined use case, organizations risk ending up with flashy tools that don’t solve core business problems.

Another critical consideration is data governance. AI models often need large datasets to learn effectively, but this raises questions about privacy, confidentiality, and compliance. CIOs must establish clear policies on what data can feed their AI models and what safeguards—such as masking, anonymization, or pseudonymization—are in place. This is even more crucial for regulated sectors like finance or healthcare, where mishandling sensitive data can lead to compliance violations and reputational damage. Rather than rushing into AI adoption, CIOs should take a step back and ensure their frameworks, controls, and privacy policies are robust. They must also consider ongoing oversight, including internal audits and external assessments, to verify that data is being handled ethically and in line with regulatory expectations.

CIO&Leader: As we grapple with evolving data protection laws, how does the rise of India’s DPDP Act and similar regulations worldwide affect an organization’s approach to data protection and AI adoption?

Munish Gupta: Emerging privacy regulations, like India’s Digital Personal Data Protection (DPDP) Act, elevate privacy and data protection from a compliance box-checking exercise to a fundamental pillar of organizational strategy. Such laws enforce stricter controls on how data is collected, stored, processed, and shared. It’s no longer enough to say that you protect personal data; you must demonstrate that you do so in a transparent, purpose-driven manner. This means organizations need to justify why they’re using data, for how long, and under what conditions. They must also be ready to disclose these details to regulators and, in some cases, to the individuals whose data they hold.

For CIOs and CISOs, these regulations influence every stage of AI deployment. Before feeding data into an AI model, one must consider whether it contains personal information and if so, how to handle it responsibly. Organizations that fail to meet these standards could face significant financial penalties and the ensuing loss of trust from customers and stakeholders. The DPDP Act and its global counterparts essentially raise the bar, compelling businesses to integrate ethical and privacy-by-design principles into their technology stacks. Companies that navigate this environment thoughtfully can differentiate themselves by offering secure, privacy-focused solutions.

CIO&Leader: With the rapid automation of routine tasks, how do you approach building the right skill sets within your teams? Do you rely on reskilling existing staff, hiring new talent, or both?

Munish Gupta: There’s no single approach that works for every organization, but at Inspira, we find a combination of reskilling and recruiting to be most effective. Our existing workforce possesses invaluable domain knowledge and an understanding of our organizational culture. By upskilling them—teaching them about new AI models, scripting languages like Python, or advanced data analytics methodologies—we essentially enhance the strategic value they already bring to the table. At the same time, hiring fresh talent is vital for injecting new perspectives and competencies. This might mean bringing in professionals who have already specialized in AI or data science, reducing the ramp-up time for certain projects.

It’s worth noting that not all roles are equally vulnerable to automation. Entry-level tasks in Security Operations Centers, such as basic log analysis, might increasingly be handled by automated tools. However, higher-level security analysis, strategy formulation, and decision-making still demand human intelligence, judgment, and creativity. For professionals, the message is clear: continuous learning is non-negotiable. For organizations, the goal is to create a sustainable talent pipeline, one where the synergy of domain expertise and emerging tech skills creates a resilient and forward-thinking security posture.

CIO&Leader: What does Inspira’s roadmap look like when it comes to emerging technologies like AI?

Munish Gupta: We have deep roots in cybersecurity services, which currently make up roughly 90% of our overall business. Moving forward, we are determined to integrate AI deeply into our existing offerings, including Security Operations Centers and Managed Security Operations. The objective is to strengthen these core services with advanced analytics, adaptive threat detection, and more proactive defense mechanisms. Beyond refining what we already do well, we’re also setting our sights on new frontiers. We are incubating AI-driven initiatives designed to broaden our service portfolio, enhance user experience, and address complex industry-specific challenges that remain unsolved by traditional tools. Partnering with global technology leaders and innovative AI-focused companies is a key part of this strategy. 

For instance, we’ve established global partnerships with Nvidia and are collaborating closely with iHuman, a Romania-based AI firm, to explore new applications and validate emerging use cases. Our timeline involves making tangible strides by 2025, ensuring that any AI integration is not only effective in bolstering cybersecurity but also adheres to strict standards of ethical data use and compliance. However, we recognize that technology does not stand still. With quantum computing advancing rapidly, we stay ready to adjust our plans so that we continue to deliver cutting-edge and future-proof solutions.

CIO&Leader: Looking ahead, which technology trends do you see dominating the landscape by 2025?

Munish Gupta: By 2025, the technology environment will likely be reshaped by several critical shifts. One of the most significant developments will be the emergence of quantum computing from conceptual discussions into more tangible deployments. Quantum capabilities could disrupt current cryptographic methods, prompting a fundamental reassessment of cybersecurity strategies. Concurrently, AI applications are expected to move from broad-spectrum implementations to more targeted, domain-specific solutions. This precision will allow organizations to leverage AI in specialized workflows and processes, making digital ecosystems more efficient and resilient. On the regulatory side, privacy and data protection frameworks will continue to gain momentum. India’s DPDP Act, for instance, will likely evolve alongside other international regulations, reinforcing the necessity for strict data governance and responsible AI practices. Collectively, these trends mean that businesses must remain agile, proactive, and prepared to navigate a landscape where technological advancements come hand in hand with heightened accountability.

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