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In 2025, the adoption of generative AI (GenAI) has accelerated from exploratory pilots to enterprise-wide deployments. Yet, as the technology matures, one truth has become non-negotiable for CIOs: AI security is not optional.
Generative AI promises unprecedented productivity and innovation. But without the right guardrails, it can expose sensitive data, introduce legal and reputational risks, and destabilise trust with clients, regulators, and employees. For CIOs operating in sectors where confidentiality and compliance are foundational—such as legal, finance, healthcare, and education—the risks are acute, and the time to act is now.
The Business Risks Are Real: From Samsung to Shadow AI
Serious incidents have underscored the dangers of unsecured GenAI adoption. In one high-profile case, Samsung engineers inadvertently leaked proprietary source code into ChatGPT, prompting a company-wide ban on GenAI tools until security policies could be implemented. Major banks, including Bank of America and Deutsche Bank, quickly followed suit with similar restrictions to prevent potential customer data leaks.
These episodes are not outliers—they’re early warning signs. Shadow AI, where employees use unauthorised AI tools without IT oversight, has become a widespread problem. Often well-intentioned, these acts still pose significant threats. Sensitive client data may be uploaded to external systems with unknown training processes, leaving organisations exposed to intellectual property loss and regulatory violations.
78% of AI users are bringing their own AI tools to work (BYOAI)—it’s even more common at small and medium-sized companies (80%).
CIOs must now contend with a new category of digital risk: unsanctioned AI use that creates invisible backdoors for data to escape. As Gartner notes, failure to implement robust GenAI governance could erode ROI and delay enterprise-wide AI strategies.
AI Compliance Is Now Business-Critical
In 2025, compliance is no longer a future consideration—it’s a present-day obligation. Governments and regulators across the globe have introduced or updated legal frameworks to address the risks associated with generative AI, focusing on issues such as transparency, data protection, accountability, and safety.
While regulatory details vary by country and industry, several themes are consistent:
- Transparency: Organisations must be able to explain how AI systems function, what data they use, and how decisions are made—especially for high-stakes applications.
- Privacy and data protection: Feeding personal or client data into GenAI tools without appropriate controls can breach data privacy laws such as GDPR in Europe, HIPAA in the US, or sector-specific frameworks in healthcare, finance, and legal services.
- Risk classification: Many jurisdictions now expect organisations to assess and document the risks associated with AI systems, particularly when they are used for decision-making, public-facing services, or sensitive data processing.
- Human oversight: Across most sectors, AI outputs must be reviewed by accountable humans—particularly when used in regulated environments such as financial services, education, legal advice, or medical support.
- Cross-border obligations: Even if your business is local, your AI use may be subject to international laws if it involves clients, data, or services in other jurisdictions.
For CIOs, this means embedding compliance from the outset—not just to avoid fines, but to maintain stakeholder trust, secure partnerships, and ensure long-term scalability. Whether operating in healthcare, finance, education, or professional services, your organisation must be able to demonstrate that AI systems are deployed responsibly, with clear governance, strong safeguards, and alignment to applicable laws.
Secure AI Starts with Governance, Not Code
Technical controls alone aren’t enough. A secure GenAI programme starts with clear organisational policies and leadership accountability.
Progressive CIOs are:
- Establishing enterprise-wide AI policies that govern which platforms can be used, what data can be processed, and what constitutes acceptable use.
- Banning unsanctioned tools and deploying monitoring systems to detect policy violations.
- Creating AI governance boards with cross-functional representation—from IT, Legal, Risk, HR, and Operations.
For instance, at AAA (Auto Club Group), CIO Shohreh Abedi implemented a policy forbidding the use of company data in unauthorised AI tools. Internal monitoring enforces this in real-time. Discover Financial Services takes it further with a dedicated Technology Academy that trains staff on AI risks and mandates human review of all AI-generated outputs.
The goal isn’t to restrict usage, but to enable safe and productive adoption by setting boundaries and building awareness.
Invest in Secure, Scalable Platforms Built for Enterprise Use
To deploy GenAI safely at scale, CIOs must prioritise platforms that are both secure by design and capable of supporting complex, enterprise-grade use cases. Public or consumer-grade AI tools may offer convenience, but they often lack the governance, integration, and data protection capabilities required in professional environments.
Platforms like Kalisa are built specifically for industries where security, compliance, and operational scale are non-negotiable:
- No-train guarantee – Your data is never used to train models, protecting confidentiality and IP.
- Enterprise-grade security – Aligned with UK and EEA regulations, including role-based access and encryption.
- Reliable outputs – Grounding and guardrails deliver accurate, compliant responses that match your organisation’s tone.
- Scalable use cases – From chat agents and internal AI workspaces to client portals and workflow automation.
- Easy integration – Secure APIs connect Kalisa with your existing systems and processes.
- Fully supported – No technical expertise required; Kalisa is maintained and updated for you.
For CIOs, platforms like Kalisa reduce risk, eliminate operational overhead, and allow AI to be deployed safely and efficiently at scale.
Train the Workforce
Even the most secure architecture can be undermined by poorly trained users. CIOs must lead a cultural shift in how teams approach AI.
Key steps include:
- Providing hands-on training on prompt writing, data sensitivity, and ethical usage.
- Emphasising AI as augmentation, not automation—reminding employees that responsibility for outputs remains with humans.
- Embedding AI literacy into onboarding, compliance training, and role-based upskilling programmes.
This builds a culture of caution and confidence—where employees are empowered to innovate, but know when to pause, escalate, or seek review.
From Cost Centre to Competitive Advantage
It’s tempting to view AI security as a tax on innovation. But in reality, secure GenAI is a differentiator. For organisations in professional services, client trust is paramount. A single AI-related breach can unravel years of reputation building.
Conversely, orgnisations that demonstrate strong AI governance—transparent policies, observable systems, compliant use—position themselves as safe, forward-looking partners. They can experiment confidently, scale faster, and maintain trust in regulated environments.
As CIOs look to digitise client experiences, automate internal workflows, or monetise institutional knowledge, secure AI becomes a core enabler.
Competitive, but Compliant
The future of GenAI in enterprise is not a question of “if,” but “how securely.” For CIOs, this means:
- Implementing policy-led AI governance.
- Choosing secure-by-design platforms.
- Training employees on safe usage.
- Building observability into every GenAI system.
Done right, these measures won’t hold your organisation back—they’ll propel it forward with fewer risks, greater resilience, and stronger returns.
In a world where AI will increasingly power client interactions, employee tools, and business models, security is not a constraint—it’s the key to long-term success.
Powering the next generation of professional services
Kalisa offers everything you need to deliver valuable GenAI experiences to your clients and team.
- Chat agents with subject-matter expertise
- AI Workflows to automate business processes
- AI workspaces for your team
- Self-serve client portals and dashboards
- Subscriptions and monetisation
- Securely combine public and private data
- API for systems integration
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