University of Kwazulu-Natal

Digital Security In The Age Of Ai Why Executives Must Be Forbes

Bonisiwe Shabane
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digital security in the age of ai why executives must be forbes

Chad Angle, Head of ReputationDefender at Gen Digital | Expert in Growth Strategy, Online Reputation Management, & Executive Privacy. For years, executive security has focused on reputation management—mitigating negative press, countering misinformation and protecting personal brands. But a new threat is rapidly transforming the way digital security should be approached. AI: Every day you hear about companies around the globe discovering new ways to harness and maximize this powerful technology to improve services, products and even healthcare. The excitement surrounding AI is palpable, and there is no denying that it is transforming the world. But for all the amazing opportunities that AI is opening up for visionaries everywhere, it’s not just the “good guys” benefitting.

As AI becomes more sophisticated, so do scams, fraud and other schemes perpetrated by bad actors. And now, AI-driven threats go far beyond reputation and into a direct security risk for executives and high-profile individuals. From deepfake scams to AI-powered data harvesting, cybercriminals are exploiting AI to target executives at an unprecedented scale. The numbers tell a clear story: • Deepfake fraud cases have surged tenfold globally from 2022 to 2023, according to Sumsub. • In 2022, 76% of threats were highly targeted spearphishing attacks focusing on credential theft.

Dharmesh Acharya is the COO of Radixweb, a global tech consultation and bespoke software service provider. You’ve heard people say, "Your AI is only as good as your data," and that may have made you parse, clean, structure and restructure your data. But while you were running after perfect data, your AI models were slyly evolving themselves, going beyond automation and learning to reason, adapt and mimic human cognition. Your AI tools can now write production-grade code, personalize user experiences with tailored content, optimize cloud infrastructures anonymously and detect faults and vulnerabilities in cybersecurity. From rule-based passive tools to active collaboration in business strategy, security and software development, AI is evolving beyond human comprehension. As it begins to "think" on its own, it brings on a load of opportunities for fast-scaling businesses.

But on the other side of the coin, AI also brings a broad spectrum of cybersecurity risks that are rapid, unique and overwhelming. We are now at the juncture where tech leaders must rethink the governance of intelligent systems, the future of AI security and the landscape of ethical governance. Nick Raziborsky, co-founder of Sonoma Security. Cybersecurity innovator transforming identity management. Artificial intelligence (AI) is no longer a futuristic promise—it’s a core driver of business transformation, and cybersecurity is emerging as its most critical battleground. For tech entrepreneurs, the post-AI era presents a dual reality: AI empowers defenses while simultaneously providing cybercriminals with advanced tools for attack.

Understanding this dynamic is essential for developing a resilient security strategy. AI-driven threats are growing at an unprecedented pace. Cybercriminals are now leveraging generative AI to create highly persuasive phishing emails and deepfake media. Recent reports indicate a staggering 1,265% surge in AI-generated phishing attacks, making it easier for fraudsters to impersonate trusted executives and authorize unauthorized transactions. Deepfake technology further compounds these risks by enabling attackers to fabricate convincing video messages that can deceive even experienced professionals. The World Economic Forum’s Future of Jobs Report 2025 warns that nearly half of business leaders are increasingly concerned about adversarial AI techniques undermining trust in digital communications.

While threats escalate, AI also offers transformative solutions for cybersecurity. Modern AI-driven tools analyze vast streams of data in real time to detect anomalies that may signal a breach. Machine learning algorithms deployed across networks now identify and isolate threats much faster than traditional methods. As artificial intelligence (AI) accelerates transformation across industries, it simultaneously exposes enterprises to unprecedented cybersecurity risks. Business leaders can no longer afford a reactive posture, businesses need to safeguard their assets as aggressively as they are investing in AI. Recently, Jason Clinton, CISO for Anthropic, underscored the emerging risks tied to non-human identities—as machine-to-machine communication proliferates, safeguarding these "identities" becomes paramount and current regulations are lagging.

Without a clear framework, machine identities can be hijacked, impersonated, or manipulated at scale, allowing attackers to bypass traditional security systems unnoticed. According to Gartner’s 2024 report, by 2026, 80% of organizations will struggle to manage non-human identities, creating fertile ground for breaches and compliance failures. Joshua Saxe, CISO of OpenAI, spotlighted autonomous AI vulnerabilities, such as prompt injection attacks. In simple terms, prompt injection is a tactic where attackers embed malicious instructions into inputs that AI models process—tricking them into executing unauthorized actions. For instance, imagine a chatbot programmed to help customers. An attacker could embed hidden commands within an innocent-looking question, prompting the AI to reveal sensitive backend data or override operational settings.

A 2024 MIT study found that 70% of large language models are susceptible to prompt injection, posing significant risks for AI-driven operations from customer service to automated decision-making. Furthermore, despite the gold rush to deploy AI, it is still well understood that poor AI Governance Frameworks remain the stubborn obstacle for enterprises. A 2024 Deloitte survey found that 62% of enterprises cite governance as the top barrier to scaling AI initiatives. Regardless of the threat, its evident that our surface area of exposure increases as AI adoption scales and trust, will become the new currency of AI adoption. With AI technologies advancing faster than regulatory bodies can legislate, businesses must proactively champion transparency and ethical practices. That’s why the next two years will be pivotal for establishing the best practices in cyber security.

Businesses that succeed will be those that act today to secure their AI infrastructures while fostering trust among customers and regulators, and ensure the following are in place: By Craig Davies, Chief Information Security Officer, Gathid. Artificial intelligence (AI) is no longer a distant prospect. It is reshaping industries, automating workflows and redefining the way organizations manage data and security. However, as AI’s influence expands, leaders face a crucial challenge: how to embrace AI-driven digital transformation while maintaining a strong identity and access governance. Without proper controls, AI’s ability to surface insights could lead to unintended data exposure, regulatory violations and operational disruptions.

To successfully prepare for the next wave of AI-powered transformation, business and technology leaders must take a proactive approach. This means addressing identity and access governance at the core of their AI strategy, ensuring that AI has access to the right data without inadvertently exposing sensitive information. AI’s potential lies in its ability to analyze vast amounts of data, drawing insights and making connections that might otherwise go unnoticed. However, organizations often struggle to reconcile two opposing goals: 1. Empowering AI With Access To Comprehensive Datasets: The more data AI has, the more powerful its insights become.

Vivek Venkatesan leads data engineering at a Fortune 500 firm, focused on AI, cloud platforms and large-scale analytics. In every industry today—including finance, healthcare, energy and retail—the digital landscape is expanding faster than any team can monitor. Systems stretch across multiple clouds, regulations evolve constantly and AI is everywhere. Yet most organizations still rely on point-in-time audits and after-the-fact incident response. One of the most promising ideas emerging from advanced engineering is the digital twin, a live, continuously updated model of an enterprise system. Born in manufacturing, digital twins now sit at the intersection of AI, automation and cybersecurity.

They offer something leaders have been missing: real-time visibility, continuous compliance and predictive resilience. A digital twin is a virtual replica of a system. It's an environment that mirrors physical or digital infrastructure through constant data synchronization. In manufacturing, twins model turbines or assembly lines. In IT, they can model cloud networks, CI/CD pipelines or security architectures. Marcus Fowler is SVP of Strategic Engagements and Threats at Darktrace and CEO of Darktrace Federal.

A rise in cybercrime as a service, combined with accelerating automation and offensive AI, has increased the scale, speed and sophistication of cybersecurity attacks—from novice threat actors seeking ransom payments to nation-state actors aiming... This is happening against the backdrop of an increasingly complex geopolitical environment where cyber is almost certainly a standing tactical and strategic operational area. According to the World Economic Forum's 2024 Global Cybersecurity Outlook, 70% of surveyed leaders reported that geopolitics have at least moderately influenced their organization's cybersecurity strategies. Organizations have long operated in a reality where the potential for cyberattacks is a constant threat. For many security leaders, however, this pressure is reaching new levels. We recently surveyed nearly 1,800 security leaders across 14 countries and found that a majority (74%) report their organizations are seeing significant impacts from AI-augmented cyber threats.

More concerningly, nearly two-thirds (60%) believe their organizations are inadequately prepared to defend against those attacks. To date, security teams have been forced into a reactive state—playing a nonstop game of whack-a-mole to stay ahead of security alerts. Constantly operating in this way can not only lead to poor decision-making but can also cause burnout among teams. To effectively defend a business in this challenging environment, organizations must shift cybersecurity practices from reactive to proactive. However, this transition is often easier said than done. Jani Hirvonen is Global Head of Channel Partnerships at Google.

Artificial intelligence is evolving fast. Every week brings new tools, new terms and new hype. It’s easy to feel behind. But the truth is, we’re still in the early stages. The best leaders won’t wait to understand every model or master every technology. They’ll lead with curiosity, focus on business outcomes and build a culture that can adapt.

AI is changing not just what we do but how we work and how we lead. Here’s how I believe great leaders can position themselves—and their teams—for success. The first step isn’t choosing a model or tool. It’s identifying a real problem that matters to your business. That could mean improving customer experience, boosting efficiency or supporting growth. Whatever it is, start there.

Then explore how AI can help. You don’t need to be a technical expert to lead on AI. But you do need to be curious and intentional. Try using AI in your own work. Build hands-on experience, ask questions and share what you learn. Modeling that mindset helps others feel confident doing the same.

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