What you need to know
- AI is delivering value, but lack of control is creating risk and slowing progress.
- Many organizations do not fully understand how AI is used across their business.
- Governance is essential to build trust, manage risk, and scale AI effectively.
- Visibility, accountability, and clear guardrails are the first step.
- A structured approach helps you move forward with confidence.
The rapid rise of AI and trust challenge
AI adoption is accelerating across every industry. Moving rapidly from experimentation to everyday business operations. From AI-driven meeting transcripts that reduce admin to predictive maintenance tools that keep systems running smoothly.
BSI’s AI Trust Report shows that for many, the initial driver is cost savings or productivity gains, with 62% expecting to increase AI investment in the next year. 65% of business leaders are already seeing gains in growth, innovation, and efficiency from AI. This confirms that AI value is no longer theoretical, but the challenge has shifted from experimentation to control.
But as AI adoption grows, leaders like you are asking a harder question: how do you build trusted AI that delivers value without increasing risk?
Do you fully trust how AI is used in your organization?
The AI momentum is now matched by growing caution. Adoption has outpaced governance and industry voices are warning that we’ve lost control. Whilst malicious use of AI grabs the headlines, well-intentioned yet poorly controlled use also has significant implications.
Currently, only 28% of leaders understand the data sources used to train or deploy their AI tools, while 24% admit that employee AI use isn’t monitored at all. People are increasingly turning to generative AI to support their work. This means it’s easy to lose sight of where AI is affecting your business and how to manage the risk.
Do you know how AI is being used in your organization?
The risks extend beyond isolated incidents. Concerns about AI quality, ethics, and lawfulness are becoming harder to ignore. A lack of transparency around how AI systems are trained is also fueling distrust.
Uncontrolled adoption is now stalling innovation where it creates distrust. As many as 95% of AI initiatives fail. Often because companies rush implementation, failing to understand risks and limitations. But many of these will not even make it past proof of concept due to the fear of getting it wrong.
One study found that 95% of C-suite and director-level executives have had a negative experience with enterprise AI. This included privacy violations, inaccurate predictions, bias, discrimination, and regulatory noncompliance. Where there were consequences, 39% said the damage was severe. A third of those said it threatened their company’s existence. For many organizations, this is where confidence stalls and AI initiatives fail to scale.
The consequences aren’t theoretical. That’s why governance has become central to successful AI adoption. With the right guardrails in place, you have a clear opportunity to take control of how AI is used.
How do you build trust in your AI?
Put simply, trusted AI starts with visibility and accountability.
You need governance that enables oversight and control, with clear guardrails in place.
Ask yourself:
- Have you determined what AI should and shouldn’t be used for?
- Have you equipped individual employees with the right knowledge and skills to use AI responsibly?
- Can data subjects trust how you collect and use their data?
- Are you applying policies consistently across teams and suppliers?
- And can you demonstrate that you’re meeting evolving regulations?
It’s by taking the first steps towards stronger AI governance that you can prove your AI use is both ethical, lawful, and trustworthy
Where should you begin?
Start by getting visibility into how AI is already being used across your organization. Identify and document your AI use cases, alongside the associated risks, by creating a simple AI inventory and use‑case register. This gives you a clear baseline for decision‑making and helps you prioritize what needs attention first.
As you do this, think about key areas of impact for your organization:
- Your business objectives and values
- The data you rely on and how it’s used
- Your legal and regulatory obligations
You can then clarify what is and isn’t acceptable use of AI, setting accountability for outcomes.
Moving forward with confidence
If you need a structured path to follow, BSI’s AI Foundation Framework can help you take your first steps. It offers clarity on what you need to address and in what order, showing you where to focus, at a pace and level that makes sense for you.
Crucially, it provides independent verification of your AI maturity, based on recognized standards. A clear signal that you’re in control of AI and using it ethically and lawfully.
Find out how you can adopt AI with confidence, by developing your governance and risk management capabilities with BSI’s AI Foundation Framework.
