AI in Business: Lessons from Industry Leaders

AI is no longer something businesses are preparing for, it is already embedded in how people work. The challenge now is understanding what it really means in practice.

Following our most recent roundtable, which brought together leaders from legal, finance, housing and professional services, one theme came through clearly:

The AI landscape is moving quickly, but not always in a structured or consistent way. 

There is a strong sense of opportunity. The general consensus around the room was that businesses are seeing genuine gains in productivity, efficiency and innovation. At the same time, there is an equally strong awareness of risk, particularly around data security, governance and control – and most organisations are navigating both at the same time.

What stood out most from our roundtable was the gap between adoption and oversight. AI tools are already being used across organisations, often informally, while policies, governance and security frameworks are still catching up. The result is a landscape that feels both advanced, yet uncertain and fraught with risk at the same time.

The Current Landscape: Widespread Use but Limited Structure 

AI adoption is happening from the ground up.

Employees are already using tools to summarise information, write content, automate tasks and solve problems faster. In many cases, this is happening without formal approval or guidance. It is not driven by risk taking behaviour; it is driven by practicality. The tools are accessible, and the benefits are immediate. The difficulty for organisations is maintaining control without limiting progress.

A consistent theme from our roundtable was the lack of clear guardrails. Without defined policies and approved tools, businesses risk sensitive data being shared unintentionally. At the same time, restricting access entirely can push usage outside the organisation, where there is even less visibility in what is being shared, and with which platform.

There is also a noticeable lag in governance. Businesses are assessing risks while adoption is already underway. AI is not something that can be paused while strategies are developed, it is already part of day-to-day operations.

Leadership teams are feeling this shift as well. In many cases, employees are more ready to adopt AI than the organisations themselves. Bridging that gap between curiosity and control is becoming a key challenge.

The Opportunity: Practical, Measurable Value 

Despite the uncertainty, the value AI can deliver is clear and already being realised.

At its simplest, AI removes friction. It reduces the time spent on repetitive tasks, improves consistency, and allows people to focus on more valuable work. Across different sectors, this is translating into real operational improvements.

Processes that once relied on manual input can now be automated and scaled. High volume tasks such as categorising requests or processing information can be completed in seconds, often with greater accuracy than manual methods. In more technical environments, development workflows are being transformed, with tasks reduced from weeks to minutes.

This is why AI is increasingly being viewed through a commercial lens. It is not about adopting technology for its own sake, it is about improving efficiency, reducing cost and delivering better outcomes.

There is also a clear benefit in access to knowledge. In organisations with large volumes of information, AI can surface the right answers instantly, without requiring employees to search through multiple systems or documents.

For many businesses, the question is no longer whether AI can help, but where it can make the biggest difference.

The Risks: Data, Security and Responsibility 

Alongside the opportunity, there are risks that need to be actively managed.

Data governance is one of the most significant. AI tools rely on access to information, and without the right controls in place, there is a real possibility of exposing sensitive data. Something as simple as incorrect permissions can result in information being surfaced that should never have been accessible.

There are also considerations around intellectual property, regulatory compliance and ethical use. These are not theoretical concerns; they are practical issues businesses must address as part of everyday operations.

Cybersecurity adds another layer of complexity. AI is accelerating both sides of the landscape. It can strengthen defence, but it can also enable faster identification and exploitation of vulnerabilities. The window between a weakness being discovered and used is shrinking.

“Shadow AI” remains an ongoing challenge. If employees do not have access to approved tools, they will find alternatives. Without visibility, organisations cannot manage risk effectively. This reinforces the need for structured, practical approaches rather than blanket restrictions.

Ultimately, many of these risks come back to people. Human error remains a key factor in security incidents, and without the right awareness and training, the introduction of AI can amplify that risk.

What Businesses Need to Focus On 

The most effective AI strategies are not built around tools, they are built around outcomes.

A common starting point is to identify where AI can simplify processes, reduce inefficiencies or improve service delivery. From there, the focus shifts to building the right foundations to support it.

That includes:

• Understanding your data, where it sits, who can access it, and how it is structured
• Putting guardrails in place, with clear policies that define how AI can and should be used
• Strengthening security controls, protecting sensitive information from being shared inappropriately
• Investing in education, ensuring employees understand both the benefits and the risks

Culture plays a critical role. Businesses that encourage openness and learning are better positioned to manage risk. When people feel comfortable reporting issues quickly, problems can be contained. When they do not, small mistakes can escalate.

There is also a need to allow controlled experimentation. Innovation comes from using the technology, not avoiding it. Giving people the space to explore within clear boundaries creates a more sustainable approach.

The Future: From Experimentation to Standard Practice 

AI is moving towards becoming a standard part of business operations.

The current phase, characterised by experimentation and rapid change, will evolve into more structured and integrated use. Over time, tools will become more embedded and use cases more refined.

However, the pace of development is unlikely to slow. New capabilities will continue to emerge, and businesses will need to stay informed to understand what is relevant and what is simply noise.

There is also a growing focus on trust. As AI becomes more embedded in business processes, organisations will increasingly prioritise platforms that offer strong governance, security and compliance.

In many ways, this mirrors the early adoption of the internet. What once felt complex and uncertain has become essential. AI is following a similar path.

How razorblue Supports the Journey 

At razorblue, the focus is on making AI work in a practical, secure and sustainable way.

Through ongoing research, development and real-world implementation, the team has built experience across a wide range of use cases. This includes everything from quick productivity improvements through tools like Microsoft Copilot, to more advanced integrations within core business systems.

A key part of this approach is ensuring that security and governance are considered from the outset. AI should enhance business operations, not introduce unnecessary risk.

Every organisation is different. The priority is understanding how each business operates, where the challenges are, and how AI can be applied in a way that delivers meaningful results, supported by the right controls and structure.

Moving Forward 

The AI landscape is not settled, but it is established.

Businesses are already using these tools, already seeing the benefits, and already facing the challenges. The focus now is on how to bring structure to that adoption.

The organisations that will see the most success will not be the ones that move fastest, but the ones that move with clarity. Those that balance opportunity with control, and innovation with responsibility.

AI is not something to wait for. It is something to understand, shape and use with purpose.

How Businesses Can Secure Growth Through Governance 

At razorblue, we believe should accelerate business growth, but never at the cost of security or control. Our AI Framework is designed to help organisations innovate safely, with governance at its core.

A practical approach should include:

• Discovering sensitive information such as intellectual property, customer data and confidential business information, and understanding where AI may have access to it.
• Classifying data appropriately using labels such as Public, Internal, Confidential and Restricted to ensure information is handled correctly.
• Implementing controls to prevent sensitive data from being entered into, processed by, or exposed through AI systems.
• Monitoring and governing AI usage, including identifying unsanctioned or “Shadow AI” tools being used across the organisation.
• Maintaining audit trails of AI interactions and data access to support compliance, investigations and governance requirements.
• Detecting risky behaviour involving AI and sensitive information, enabling organisations to respond before incidents occur.
• Educating users on the safe and responsible use of AI, ensuring innovation happens within clear guardrails.

By combining governance, security and user awareness, businesses can confidently adopt AI technologies whilst maintaining control of their data and reducing organisational risk.

Talk to our team for more information on how we can support your business in remaining cyber secure whilst you implement your AI supported growth plan.