You don’t need an AI strategy because you want to use AI.
You need an AI strategy because AI is already being used.
Over a year ago, we wrote about the growing risk of BYOAI (Bring Your Own AI). The concern was simple. Employees had discovered tools like ChatGPT and Claude, recognised the productivity benefits, and started using them without the knowledge or approval of their employer.
For many businesses, that remains a very real concern. But the conversation has evolved.
Today, AI isn’t something employees are bringing into the workplace. AI is increasingly being built directly into the software businesses already use every day.
Microsoft 365 has Copilot. Google Search now includes AI-generated responses. Security platforms are introducing AI-powered analysis and recommendations. CRM systems, accounting packages, marketing tools and collaboration platforms are all racing to add AI functionality.
In many cases, organisations are adopting AI whether they’ve consciously decided to or not. And that leads to a much bigger question. Who is governing it?
AI Is Already In Your Business
Many business owners still think of AI as something separate. They imagine an employee opening ChatGPT and asking it to write an email or summarise a document. While that certainly happens, modern AI goes much further.
AI is increasingly embedded into everyday business processes. It can summarise meetings, analyse emails, create content, suggest actions, generate reports and surface business insights automatically.
- Sometimes these features are enabled by default.
- Occasionally users can enable them themselves.
- Frequently, organisations don’t even realise they’re using AI until someone points it out.
The reality is simple. Whether you love AI or hate it, there’s a very good chance it’s already influencing decisions, content and workflows inside your organisation.
The question is no longer whether AI is present. The question is whether it’s being managed.
Productivity Is The Easy Conversation
Most discussions around AI focus on productivity. That’s understandable. The benefits are obvious:
- Faster document creation
- Meeting summaries
- Research assistance
- Data analysis
- Process automation
- Improved efficiency
We’ve seen these benefits firsthand. Used correctly, AI can genuinely save time and help teams work more effectively. But productivity isn’t the difficult conversation. Governance is.
Business owners need to think about questions such as:
- What AI tools are staff allowed to use?
- What information can be entered into those tools?
- How is sensitive data protected?
- How do employees verify AI-generated outputs?
- Who is accountable when AI gets something wrong?
- How do you demonstrate appropriate controls if a regulator asks?
Those questions are far less exciting than asking AI to write a proposal in ten seconds. Unfortunately, they’re also the questions that matter most when something goes wrong.
Not All AI Is Equal
One of the challenges businesses face is assuming all AI platforms work the same way. They don’t.
Some enterprise AI platforms, such as Microsoft 365 Copilot, have been designed to operate within existing security, compliance and permission boundaries. This allows organisations to apply governance controls more easily within their existing environment.
At the other end of the scale are public AI services where users may be working through personal accounts, free subscriptions or tools that the business has little visibility over.
Then there are countless applications sitting somewhere in the middle.
The risk isn’t necessarily the AI itself.
The risk is not understanding what data is being used, where it is going, who can access it and what protections exist around it.
AI Governance Is Becoming A Compliance Conversation
This is where things get interesting. Governance frameworks for AI are rapidly emerging.
One example is the NIST AI Risk Management Framework (AI RMF), which was created to help organisations identify, measure, manage and govern AI-related risks. NIST describes the framework as a voluntary approach to improving trustworthiness, accountability, privacy, security and risk management within AI systems.
Now, we’re not suggesting every SME needs a team of AI compliance specialists. Far from it. But the direction of travel is clear.
As AI becomes increasingly embedded in business operations, organisations will be expected to demonstrate that they understand the risks and have appropriate controls in place.
For risk-conscious business owners, this starts to sound very familiar. It’s exactly the journey we saw with cyber security.
Ten years ago, security was largely an IT conversation. Today it’s a boardroom conversation.
AI governance appears to be heading in the same direction.
The Businesses That Will Benefit Most
The organisations likely to gain the greatest value from AI won’t necessarily be the ones that deploy it fastest. They’ll be the ones that adopt it responsibly.
That means:
- Understanding where AI is being used
- Defining acceptable use
- Protecting sensitive information
- Training employees
- Monitoring risk
- Creating accountability
Rather than slowing innovation down, governance provides a framework that allows businesses to adopt AI with confidence.
Key Takeways
AI is no longer arriving at your front door. It’s already sitting in your office.
AI is built into the applications your staff use every day – it’s influencing decisions, creating content, analysing information and changing the way work gets done.
Most organisations now accept they need a cyber security strategy.
The next question may be whether they also need an AI governance strategy. We certainly think it’s a conversation worth having.
If you haven’t already read it, our previous article explores the risks of uncontrolled AI adoption and BYOAI within the workplace: 👉 The Risk of BYOAI
As AI continues to become part of everyday business operations, one thing is becoming increasingly clear.
Ignoring AI is no longer a strategy.
Ignoring AI governance definitely isn’t.
