Artificial Intelligence (AI) is doing much more than just changing how we do business, it’s redefining it. But while AI opens doors to innovation and growth, it also comes with risks that can’t be ignored. Data bias, cybersecurity vulnerabilities, compliance gaps, these aren’t just technical issues; they are business-critical challenges.

How do you manage these risks without stifling innovation?

The answer lies in taking a deliberate, proactive approach to AI risk management. When done right, it’s not just about avoiding pitfalls, it’s also about creating opportunities, building trust, and future-proofing your business.

1. Assess Risks Before They Become Issues

AI’s complexity makes risk inevitable, but unpreparedness is a choice. Here’s where it starts:

• Define Your Use Cases: Where and how will AI be applied? What’s at stake if it fails?
• Spot Vulnerabilities Early: From biased data to weak cybersecurity protocols, address weak points head-on.
• Plan for the Unexpected: Have contingency plans in place. AI systems are only as strong as the scenarios they’ve been trained for.

When you identify risks upfront, you’re not just protecting your business, you’re building a foundation for trust.

2. Monitor AI as if Your Business Depends on It (Because It Does)

AI systems evolve as they’re exposed to real-world data. That’s both their strength and their vulnerability. Without constant monitoring, you’re flying blind:

• Detect anomalies before they escalate.
• Ensure your AI complies with ethical, legal, and operational standards.
• Create feedback loops for continuous improvement.

Think of it as a health check for your AI, one that keeps your systems resilient and your stakeholders confident.

3. Build a Workforce That Understands AI Risks

AI is powerful, but it’s only as ethical, secure, and effective as the people managing it. Here’s how you empower your teams:

• Train them to recognise and mitigate risks at every stage.
• Foster a culture where AI isn’t feared but embraced responsibly.
• Equip employees with the tools to ask critical questions, like “Is this system fair?” and “What could go wrong?”

Knowledgeable teams are your first line of defence, and your greatest asset in turning risk into opportunity.

4. Stay Ahead of Regulatory Changes

AI governance is evolving faster than many realise. Falling behind isn’t an option. Stay agile by:

• Keeping up with global and regional regulations.
• Adapting processes to meet compliance requirements.
• Engaging with industry groups to influence ethical AI standards.

Compliance isn’t just about ticking boxes; it’s about positioning yourself as a trusted, forward-thinking leader in AI adoption.

5. Embed Trust with AI TRiSM

The AI Trust, Risk, and Security Management (TRiSM) framework is a revolutionary approach to ensuring your AI systems operate securely, ethically, and effectively. It achieves this by:

• Protecting data integrity and maintaining model accuracy.
• Shielding systems from adversarial attacks.
• Ensuring your AI aligns with your ethical and operational values.

By embedding TRiSM principles, you not only safeguard your operations but also build a foundation of trust that resonates with stakeholders and sets your organisation apart as a leader in responsible AI innovation.

6. Make Risk Awareness Part of Your Culture

AI risk management isn’t a one-off task, it’s a mindset. Leaders must lead by example:

• Make risk conversations part of regular strategy discussions.
• Encourage collaboration between technical and non-technical teams.
• Celebrate transparency and accountability, acknowledging risks isn’t a failure; ignoring them is.

A culture that prioritises awareness over avoidance turns AI risks into stepping stones for growth.

Turning Risks Into Rewards
Let’s shift the narrative: AI risk management isn’t about fear. It’s about foresight. When you manage risks effectively:

• Your business earns trust, from customers, stakeholders, and regulators.
• You unlock the full potential of AI, without compromise.
• You gain a competitive edge by showing you can innovate responsibly.

It’s time to stop seeing risk management as a hurdle and start seeing it as a strategic advantage.

The world is moving fast, and AI is at the centre of it. But you can’t afford to sit back and hope for the best.

So, ask yourself:

• Are your AI systems being monitored for vulnerabilities right now?
• Are your teams trained to manage AI risks effectively?
• Do you have a plan for when, not if things go wrong?

Managing AI risks isn’t just about protecting what you’ve built, it’s about creating what comes next. The organisations that get this right will thrive.

Some years ago in my old blog I posed this question. What is the ideal working week around the world.

I was discussing the working hour week with friends that work around the world in different countries, comparing the average and what is now deemed as acceptable or viewed as the new standard, regardless of the contracted hours  so these posts caught my eye.

Some people feel they have to work long hours or stay late at work even when there is nothing to do. Almost like staying late is the norm, to the extent of faking it. Then there is the other side that seem to think there should be some shame associated with working long hours. 
An old survey lists out which countries work the longest hours in Europe the real question though is how does this link to productivity.

Personally I think it’s all about having a balance and scaling up and down as required rather than having a set pattern. However it looks like, due to Covid forcing organizations to make workers remote all this is about to change. There have been a few news reports about burnout and even longer working hours but this time whilst working from home.

Even the WHO has jumped in raising the awareness of increasing deaths from heart disease and stroke. “Working 55 hours or more per week is a serious health hazard,” said Maria Neira, the director of the WHO’s Department of Environment, Climate Change and Health.

There is also talk about reducing the working week to 4 days as seen on CNBC and the 4 Day Week Campaign here

What do you think?

Hello indeed, it has taken a while but I have finally got my blog up and running again. This will be the first of many posts to come.