Reframing the Conversation Around Cybersecurity, AI, and the Future of Work

At Gula Tech Adventures, we introduced the concept of Data Care in 2022 to make cybersecurity more professional, inclusive, and rooted in personal responsibility. But as artificial intelligence becomes deeply embedded in how organizations operate and how data is processed, the stakes of Data Care have never been higher: without cybersecurity, there is no trustworthy AI. Embracing Data Care prepares individuals, companies, and society for the reality that secure systems are foundational to trusted digital life.

1. Cybersecurity Must Become a True Profession

The cybersecurity industry has built amazing technical expertise and sophisticated solutions — but framing cyber as something only “experts” do has limited public understanding, workforce growth, and diversity. The term Data Care shifts this narrative. It positions data protection as a shared, human responsibility — the same way health care evokes care for people, not just procedures or tools.

Rather than hiding behind jargon like “penetration tester” or “security operations,” Data Care highlights that everyone who uses or touches data has a role and responsibility in keeping it secure and private. This framing is essential for recruiting a broader, more diverse workforce and cultivating professional norms that go beyond checklists to actual stewardship.

2. There Is No Trustworthy AI Without Cybersecurity

AI systems do not operate in a vacuum — they inherit the security and trustworthiness (or lack thereof) of the data and infrastructure beneath them. As AI transforms decision-making across business, government, and society, it also expands the impact of cyber risk. If data pipelines, models, or ecosystems fail to be secure, AI amplifies those failures. Therefore, Data Care isn’t just about defending networks — it’s about defending the very integrity of intelligent systems that touch every part of modern life.

This means focusing not just on technology, but on the systems of trust that make AI reliable — from secure model training data to key management and governance frameworks.

3. AI Is Reshaping Work — and Cyber Roles Must Evolve

The rise of AI isn’t eliminating work — it’s transforming it. Cybersecurity roles are evolving to require new skills in AI safety, model assurance, and risk governance. The role of security leaders, especially CISOs, is no longer confined to traditional cyber practices: they must now navigate how AI augments detection, adversarial risk, and strategic business decisions.

Data Care provides a human-centered framework that helps professionals adapt. By emphasizing responsibility over tools alone, it prepares practitioners and leaders to integrate AI safely and ethically, and to communicate why security matters to boards, policymakers, and the public.

4. Trust Is Both Technical and Human

In an AI-driven world, trust must be engineered — not assumed. This means:

• Controlling and tracking who can access your Data

• Building systems that can be explained and audited

• Designing for accountability and human understanding

• Recognizing that the internet and AI supply chains may be unreliable and hostile, and designing systems accordingly

Data Care connects these technical requirements with social expectations, making trust a shared goal across communities, companies, and governments.

5. Communication Matters — Especially for Adoption and Awareness

One of the biggest barriers to better cyber and AI practices isn’t technology — it’s how we talk about it. Traditional cybersecurity pronounces complexity; Data Care invites clarity. It enables:

• Better public awareness of digital risk

• Broader participation in cybersecurity careers

• More meaningful conversations between tech teams and business leaders

By speaking the same language society uses — one grounded in care, responsibility, and stewardship — we can increase engagement and grow the talent pipeline the industry desperately needs.