Artificial intelligence (AI) has firmly taken center stage in today’s enterprise landscape. From the rapid integration of AI into company products, the rising demand for AI skills in job postings, and the increasing presence of AI in industry conferences, it’s clear that businesses are paying attention.
However, awareness alone isn’t enough. For AI to be implemented responsibly and securely, organizations must invest in robust training and skill development. This is becoming even more urgent with another technological disruptor on the horizon—quantum computing. Quantum advancements are expected to supercharge AI capabilities, but they will also amplify security risks.
As AI evolves, so do cyber threats. Deepfake scams and AI-powered phishing attacks are becoming more sophisticated. According to ISACA’s 2025 AI Pulse Poll, “two in three respondents expect deepfake cyberthreats to become more prevalent and sophisticated within the next year,” while 59% believe AI phishing is harder to detect. Generative AI adds another layer of complexity—McKinsey reports that only “27% of respondents whose organizations use gen AI say that employees review all content created by gen AI before it is used,” highlighting critical gaps in oversight.
Quantum computing raises its own red flags. ISACA’s Quantum Pulse Poll shows 56% of professionals are concerned about “harvest now, decrypt later” attacks. Meanwhile, 73% of U.S. respondents in a KPMG survey believe it’s “a matter of time” before cybercriminals exploit quantum computing to break modern encryption.
Despite these looming challenges, prioritization is alarmingly low. In ISACA’s AI Pulse Poll, just 42% of respondents said AI risks were a business priority, and in the quantum space, only 5% saw it becoming a top priority soon. This lack of urgency is risky, especially since no one knows exactly when “Q Day”—the moment quantum computers can break current encryption—will arrive.
Addressing AI and quantum risks begins with building a highly skilled workforce. Without the right expertise, AI deployments risk being ineffective or eroding trust through security and privacy failures. In the quantum domain, the stakes are even higher—quantum machines could render today’s public key cryptography obsolete, requiring a rapid transition to post-quantum cryptographic (PQC) standards.
While the shift sounds simple, the reality is complex. Digital infrastructures deeply depend on current encryption, meaning organizations must start identifying dependencies, coordinating with vendors, and planning migrations now. The U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) has already released PQC standards, and cybersecurity leaders need to ensure teams are trained to adopt them.
Fortunately, the resources to address these challenges are growing. AI-specific training programs, certifications, and skill pathways are available for individuals and teams, with specialized credentials for integrating AI into cybersecurity, privacy, and IT auditing. Similarly, quantum security education is becoming more accessible, enabling teams to prepare for emerging threats.
Building training programs that explore how AI and quantum intersect—and how to manage their combined risks—will be crucial. These capabilities could allow organizations to not only defend against evolving threats but also harness AI and quantum computing for advanced attack detection, real-time vulnerability assessments, and innovative solutions.
The cyber threat landscape is not static—it’s accelerating. As AI and quantum computing redefine both opportunities and risks, organizations must treat workforce upskilling as a strategic investment. Those that act now will be best positioned to innovate securely, protect stakeholder trust, and stay ahead in a rapidly evolving digital era.