Most organizations around the world are spending more on cybersecurity than at any point in their history. Very few are spending it on the threats that are actually coming for them. That is the central tension running through PwC's 2027 Global Digital Trust Insights report, which drew responses from nearly 4,000 business and technology leaders spanning more than 70 countries.
Artificial intelligence sits at the core of the report's findings, and not in the way most organizations would prefer. Leaders surveyed identified attacks targeting their own AI systems as the single cyber threat they feel least prepared to handle. Over half of respondents, 53 percent, said they are not adequately defended against autonomous botnet attacks, where AI drives the probe and compromise of networks faster than human teams can respond. Adversarial attacks and data poisoning followed at 52 percent each, pointing to a defensive gap that has widened as attackers have adopted the same tools organizations are still trying to implement on the defense side.
Prompt injection sits squarely at the heart of this problem. Unlike conventional exploits that target code vulnerabilities, prompt injection manipulates the AI model itself, tricking it into leaking data, executing unauthorized commands, or acting entirely outside its designed purpose. OpenAI acknowledged in late 2025 that prompt injection, much like social engineering before it, is a problem that cannot be fully engineered away. The Open Worldwide Application Security Project has ranked it number one on its threat list for LLM applications for three consecutive updates, a position it has held since the list first debuted. The persistence of that ranking reflects not a shortage of incidents, but the structural difficulty of closing an attack surface that is, in effect, the model's own reasoning process.
Despite all of this, AI is simultaneously the security tool leaders trust most. The survey found it ranked first for threat detection and alerting across the respondent pool. The contradiction is in what comes next. Only 22 percent of leaders said they would let AI agents operate in cyber defense without requiring human sign-off on their actions. Fifty-five percent attributed this reluctance to reliability and maturity concerns, while 44 percent pointed to a skills shortage in AI oversight and governance.
That hesitation is not irrational, but it carries a cost. AI-driven attacks operate at a pace that leaves human response cycles behind. Requiring manual approval for every automated defensive action is, in practice, fighting a faster adversary at a slower speed. At some point, fully autonomous defense may not be optional. What makes that shift harder is that organizations have not settled on who would be accountable for it. The survey found that 29 percent of leaders placed AI security accountability with the CIO or CTO, 26 percent with a dedicated AI leadership role, and only 17 percent with the CISO. Eleven percent said responsibility was shared across multiple functions, which in most organizations means it belongs to no one in particular.
Budget signals at least suggest that leaders recognize the scale of the problem. Eighty-four percent of security and finance leaders said they expect cyber budgets to increase, with 58 percent naming AI as their top spending priority for the coming year.
The second major warning in PwC's report concerns quantum computing, and the picture there is, if anything, more concerning. Quantum computers capable of breaking the encryption that currently secures financial records, government communications, and enterprise data are not yet commercially operational. But the attack strategy does not require them to be. State-sponsored threat groups and other sophisticated actors are already collecting encrypted data now, banking on the ability to decrypt it once quantum capability matures. Most cryptography researchers put that window between 2030 and 2035, and the timeline for migrating large-scale cryptographic infrastructure is measured in years, not months. The National Institute of Standards and Technology finalized its first three post-quantum cryptography standards in August 2024, covering quantum-resistant key exchange and digital signatures, and told organizations explicitly that there is no reason to delay. PwC's survey found that only 21 percent of respondents are currently implementing those standards.
What makes this more urgent than a theoretical risk is that the harvesting is already underway. The FBI confirmed in August 2025 that a Chinese state-sponsored group tracked as Salt Typhoon had compromised more than 200 organizations spanning more than 80 countries, with nine major US telecommunications carriers among the confirmed victims. In at least one documented case, the group maintained undetected access to a telecom network for three years, collecting communications data throughout. That data, encrypted under today's standards, sits in storage waiting for the decryption capability that quantum hardware will eventually provide. Governments are beginning to respond with deadlines rather than guidelines. In June 2026, President Trump signed executive orders requiring federal agencies to migrate high-value systems to NIST-approved post-quantum cryptography standards by 2030 and 2031 respectively, with government contractors expected to follow. The private sector has no equivalent mandate, and PwC's survey makes clear that most organizations are not filling that gap on their own.
"Technology is moving incredibly fast, but the fundamentals of cybersecurity haven't changed," said Morgan Adamski, PwC's cyber, data and technology risk leader. "You can invest heavily in AI and the latest security tools, but if you don't have secure data, operational continuity, clear accountability and strong cyber hygiene underneath them, you're building on a weak foundation. The goal isn't to slow innovation down. It's to make sure your organization is resilient enough to keep up with it."
What the survey documents, across both AI and quantum, is the distance between knowing what needs to be done and actually doing it. The tools exist. The standards are published. The gap is operational, and the cost of that gap is rising by the month.
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