We are in the middle of an exciting wave of tech innovation, largely driven by AI. But even as these tech advances have driven powerful gains in efficiency and innovation, they have also introduced new risks.
Advancing AI and new modes of tech innovation are forcing a fundamental rethink of how organizations understand, govern and invest in cyber risk. All too often, as companies integrate more AI and third-party tools into their processes, they are not adequately prepared to manage the cyber risk that comes along with it.
As companies rely on an ever-growing network of third-party vendors for various software services, they create new entry points and vulnerabilities, many of which are outside the scope of a company’s internal controls. This requires added vigilance and security oversight, especially with third-party partners such as AI vendors.
Tech innovation is going to continue, but smarter approaches to cyber risk need to evolve alongside it. The firms that treat cybersecurity as a strategic enabler of innovation, not just a compliance cost, will own the next decade.
How Risk Profiles Continue To Grow
Even as a growing number of organizations recognize their cyber risks, far fewer are actually prepared to handle these challenges. According to a report from Panorays, even though 77% of CISOs consider cyber risks from third party vendors to be their biggest threats, only 21% have an actual plan in place for if a vendor is breached. Similarly, when it comes to AI vendors, while 60% of CISOs view them as “uniquely risky,” only 22% report that they have a dedicated onboarding plan to evaluate their cyber-risk profile.
These trends highlight a distinct strategic shift over the past few years. Leading into 2024, AI was considered a potential enabler of cybersecurity, and in 2025, the majority of companies charged ahead with implementing AI in a variety of use cases. As the report concludes, however, AI’s adoption has come faster than security-focused governance and onboarding practices could catch up.
While many AI applications are able to aid in reducing cyber risk, AI has also become a distinct risk category of its own as it has spread everywhere. Of course, AI is not the only area creating new cyber-risk categories. Cloud adoption, remote work and other SaaS tools create a growing web of potential attack venues.
All too often, traditional legacy security measures simply are not equipped to handle these types of threats, especially with bad actors using AI and other tech to develop more sophisticated attack methods.
AI Presents A New Approach To Cybersecurity
While the rapid pace of AI innovation has often outpaced security updates to legacy systems, AI is also a key part of changing how we approach cyber risk. Cybersecurity systems that utilize AI algorithms are able to conduct complex behavioral analyses so they can quickly detect anomalous behaviors and other risks and patterns linked to cyberattacks.
The ability to analyze and learn from massive data sets goes a long way in expanding the capabilities of human cybersecurity engineers, with real-time analysis and automation of more routine tasks like security scans enabling human engineers to implement higher-level responses.
This approach is critical to becoming proactive and adapting alongside tech innovations, rather than constantly trying to play a game of catch-up. AI-powered cybersecurity can have a powerful impact in areas such as:
- Advanced biometrics: Fingerprint, facial features and DNA biometric authentication can enable more secure and less easily compromised account access.
- Predictive cybersecurity: AI analyzes patterns to predict potential cyberattack techniques so organizations can strengthen their preventative measures accordingly.
- Self-healing systems: The race to develop self-directed AI systems also delivers the potential for cybersecurity systems that can detect and patch their own vulnerabilities automatically, based on AI learning.
Cybersecurity Culture Shifts Are Also Necessary
All the cybersecurity advances in the world are not going to have a meaningful impact if they are not accompanied by a corresponding change in how businesses treat cybersecurity.
This requires a shift in cybersecurity culture.
For example, a report published in The HIPAA Journal noted that 70% of data breaches in healthcare are caused by employees, in large part because 65% of the industry’s employees take security shortcuts that put patient data at risk. From phishing scams and malware downloads to sharing patient data with ChatGPT or misconfiguring data or networks, the sheer range of ways that cyber risk has presented itself in just one industry is alarming.
While many companies still have a long way to go in adapting their cybersecurity approaches for modern tech innovations, there are signs of improvement. The growing adoption of Zero Trust architecture, which emphasizes continuous monitoring and validation of users, giving the minimum level of permission required and operating on the assumption that the network has already been breached, is a worthwhile approach that helps maintain control over individual networks.
Of course, with many enterprises using hundreds of tools as part of their tech stack — and the majority of enterprises opting for third-party AI apps over internal tools — businesses need to expand their outlook beyond their own internal systems. As noted in the Panorays report cited earlier, enterprises must consider how they can implement ongoing oversight of third-party integrations to prevent breaches through partners.
From Perimeter Defense To Intelligent Risk Orchestration
Leading organizations are quietly moving from static security controls to what is essentially intelligent risk orchestration across the tech and innovation stack.
Several shifts stand out:
- From assets to business outcomes: Legacy programs start with “what servers or devices do we have?”; modern programs start with “what are the critical business processes, data and models that drive value?” and then map risks to those.
- From manual assessment to automated, AI-augmented evaluation: Instead of spreadsheets and point-in-time penetration tests, organizations are increasingly using platforms that continuously ingest signals from cloud environments, endpoints, identities and code pipelines, then score control effectiveness and business impact in near real time.
- From separate innovation and security workflows to shared, integrated governance: Product, data, AI and security leaders are beginning to share risk dashboards and definitions of “acceptable risk,” aligning innovation roadmaps with risk appetite and regulatory constraints from the outset.
Modern governance, risk and compliance (GRC) and IT risk platforms, combined with continuous vulnerability management and automation, are an important part of this shift because they translate technical risk into business-level narratives and decisions. These tools help connect cyber posture to revenue, uptime, regulatory exposure and reputational risk.
Real Risks, Real Solutions
Today’s tech innovations have introduced new threats, but also new opportunities for managing cyber risk. Ultimately, it is up to organizations to ensure that their approach to cybersecurity continues to evolve alongside the tools they use to optimize their business.
With a security-minded approach to tech innovation, enterprises can maximize their potential growth and efficiency without exposing themselves to undue risk.