Something strange is happening in corporate boardrooms across the globe. The same executives who spent years treating privacy as a nuisance—a cost center staffed by people who existed mainly to say no—are now writing enormous checks to expand those very programs.
Cisco just dropped its 2026 Data and Privacy Benchmark Study, and the numbers are wild. The percentage of organizations spending $5 million or more on privacy nearly tripled in a single year. Tripled. From 14% to 38%.
That’s not a trend. That’s a panic.
The AI Reckoning Has Arrived
Let’s be honest about what’s driving this. It’s not some sudden corporate awakening to the sacred importance of personal data rights. It’s fear. Fear of deploying AI systems that blow up spectacularly. Fear of regulatory hammers dropping. Fear of customers walking away when they discover what’s happening to their information.
Ninety percent of organizations told Cisco their privacy programs expanded because of AI. Not slightly adjusted. Not tweaked around the edges. Expanded. Nearly half said the expansion was significant.
This is what happens when you realize the shiny new technology everyone’s racing to deploy runs on data—and you’ve spent the last decade treating data like digital garbage stuffed into whatever drawer was handy.
Turns out you can’t train AI models on a mess. You can’t govern what you don’t understand. And you can’t explain to regulators or customers what your system is doing when you don’t know what data it consumed or where that data came from.
The Governance Theater Problem
Here’s where the study gets uncomfortable. Three-quarters of organizations have established AI governance committees. Sounds responsible, right? Shows they’re taking this seriously.
Except only 12% describe those committees as mature and proactive.
Twelve percent.
The other 88% have essentially created governance theater. They’ve checked the box. They can point to the committee when auditors ask questions. But the actual work of governing AI—establishing clear policies, enforcing standards, creating real accountability—remains undone.
And look at who’s sitting on these committees. IT leads at 57%. Legal and compliance at 35%. Product teams? A pathetic 8%. The people building AI systems barely have a seat at the table governing them.
This is how organizations end up with policies that look great in PowerPoint and accomplish nothing in practice. The governance function operates in a parallel universe from the development function, and everyone pretends this is fine.
The Data Quality Disaster No One Wants to Discuss
Buried in the study is a finding that should terrify every executive betting big on AI: 65% of organizations struggle to access relevant, high-quality data efficiently.
Think about that. Two-thirds of companies can’t reliably get good data to their AI systems. They’re building supposedly intelligent applications on foundations of digital quicksand.
This isn’t a technology problem. It’s a consequence of decades of neglect. Organizations hoarded data without cataloging it. They collected everything because storage was cheap, then never bothered to classify or tag what they’d accumulated. They merged companies and inherited incompatible systems that nobody ever reconciled.
Now AI demands clean, structured, well-documented data—and everyone’s discovering they have a junk drawer the size of a warehouse.
Only half of organizations with data tagging systems describe their approach as comprehensive. The rest rely on partial tagging, ad hoc processes, or customer-identified classification. For AI applications, this is a recipe for disaster. Models trained on poorly classified data produce unreliable outputs. Systems incorporate information they shouldn’t. And when things go wrong, nobody can trace what happened.
The Transparency Twist
Here’s the finding that should reshape how every organization thinks about privacy: When companies ranked what builds customer trust most effectively, clear communication about data practices won by a landslide.
Forty-six percent selected transparency. Only 18% chose regulatory compliance. A mere 14% picked breach prevention.
Read that again. Customers care more about understanding what you’re doing with their data than whether you’re following privacy laws or keeping hackers out.
This inverts the traditional privacy hierarchy. Organizations have historically focused on compliance first, security second, and communication somewhere around fifteenth. The market is saying that’s backwards. People want to know what’s happening. They want explanations, not assurances.
The organizations figuring this out are building dashboards, embedding transparency commitments in contracts, and telling customers how AI systems use their information. They’re treating communication as a feature, not an afterthought.
The Uncomfortable Truth
The Cisco study confirms something many privacy professionals have known for years but struggled to articulate how privacy isn’t a constraint on innovation. It’s the infrastructure that makes responsible innovation possible.
Ninety-nine percent of organizations report tangible benefits from privacy investments. Ninety-six percent connect enhanced data controls to greater agility and innovation. The companies treating privacy seriously are moving faster, not slower.
This makes intuitive sense once you stop thinking of privacy as bureaucratic friction. Good data governance means you understand what data you have. It means you can find what you need quickly. It means you can deploy AI systems with confidence because you know what they’re consuming. It means you can answer customer and regulator questions without launching a forensic investigation.
The organizations still treating privacy as a tax are falling behind. They’re discovering that you can’t bolt governance onto AI systems after the fact. You can’t fix data quality problems with a crash program. You can’t build customer trust through press releases.
Privacy isn’t dead. It’s just finally being taken seriously.
The question is whether your organization figured that out before the bill came due—or whether you’re now scrambling to catch up with everyone else who spent the last decade actually doing the work.