Blog Post Strengthening AI Security, Due Diligence & Smart Standards

Years of monitoring of AI and cybersecurity legislators, and the same cycle repeats — endless concerns about data storage and sharing, ranging from cautious “we don’t know how the information is stored and shared” or “share it carefully” to a “total ban on sharing and using AI.” But where’s the real action?

This article offers practical advice on implementing AI while maintaining security and regulatory trust (10 min to read). We stand with legal experts who support AI adoption, innovation, and competition while ensuring security and due diligence rather than stifling progress with fear.

The AI Security Debate: Fear or Progress?

The key concerns flagged are AI model training data retention and corporate leaks. But how much of this is real, and how much is just uncertainty? No one knows exactly how AI developers manage security, yet the conversation remains stuck on potential threats without concrete solutions.

So, what’s next? Some countries and companies block AI models outright, thinking it ensures safety. But IS ISOLATING YOURSELF REALLY THE ANSWER while the rest of the world moves forward?

Let’s face the facts — most markets and governments actively encourage AI growth, not restrict it. So, it’s time to focus on smart solutions instead of fear-driven stagnation!

AI Investments: Full Speed Ahead

Governments and major corporations pour billions into AI development, prioritising innovation over fear: [2]

• U.S. Leadership: Stargate, a $100B+ AI venture backed by OpenAI, SoftBank, and Nvidia, could reach $500B in four years. 
• EU’s Response: The InvestAI initiative aims to mobilise €200B, including €20B for AI gigafactories. 
• France’s Push: Private sector commits €109B to AI projects, French President Emmanuel Macron said.
• Mistral AI: Barcelona-French AI startup (a thriving competitor to tech rivals) raised over $1B, proving investor confidence.

Thus, despite ongoing concerns about data leaks, global leaders are betting big on AI’s future — without hitting pause. 

AI Cost Savings: Too Good to Ignore

AI-driven coding tools are revolutionising efficiency, slashing costs, and accelerating innovation:

• Massive Efficiency Gains: GitHub Copilot, used by 77,000+ organisations, boosts coding speed by 10-20%. [3]
• Infrastructure Savings: AI adoption could cut costs by 40-60%, especially in high-end computing. [1]
• Open-Source AI Growth: Nearly 50% of IT leaders plan to expand AI use in 2025 for faster development. [1]

Using generative AI tools significantly reduces costs, especially fixed ones, while boosting production capacity. 

With AI reducing expenses and increasing productivity, who would willingly forgo such an advantage? Security concerns exist, but they are not stopping investments.

What’s Next? Balance Innovation & Security

AI’s cost-effectiveness makes it a tempting risk, but businesses must balance adoption with cybersecurity measures. The key? Implementing technical standards, running early-stage due diligence, and following compliance to safeguard sensitive data.

Here’s how to move forward…

1. Boosting Competition and Innovation

AI tools are driving fierce competition, which fuels innovation. As more players enter the generative AI space, the race for breakthroughs intensifies, benefiting the entire industry.

Investing in AI technology and supporting startups will create new market participants, even if they are built on existing technologies from current industry giants. Many startups are making their models publicly available, and this open-source approach enables smaller companies to learn from each other and compete with more prominent, better-funded players. [1]

Take Mistral AI, a Barcelona-based startup, which plans to release models that could rival DeepSeek’s latest version. By embracing open source, they aim to develop powerful AI without spending billions of dollars in investment. As one expert points out, “An AI startup can hold the top spot only for so long before another company releases a more advanced model.” [2]

In essence, a diverse range of solutions will prevent a small group of tech giants from monopolising the market, leading to more innovation and opportunity for all.

2. Increasing Cybersecurity Awareness

When budgeting, it’s essential to prioritise a robust cybersecurity strategy, even if securing the necessary funds can be challenging. Imagine the immediate response from the CEO or CFO, which may often be: “Who cares? We’re not that big size company as XYZ!”

Yet cybersecurity is an unavoidable expense; moreover, it is essential. Hackers exploit vulnerabilities quickly, and a data breach can cost millions — $4.9 million on average in the U.S. in 2024 [4]. 

Companies often hesitate to spend on security, but failing to do so can lead to significant losses. Therefore, it’s critical to understand the actual disruption costs when allocating your budget. 

Instead of focusing solely on reducing cybersecurity spending, aim to minimise technical fixed costs (e.g., using AI) while setting aside adequate funds for cybersecurity risks, which could easily surpass your initial budget.

Plan ahead and allocate funds early for cybersecurity to standardise safety protocols, protect data, increase client trust, and avoid costly breaches and compliance issues.

3. Legal and Security Due Diligence

Conduct technical audits and compliance checks early on to ensure secure AI usage and data sharing. This includes vulnerability assessments, legal compliance, and certifications, which build a solid foundation and enhance client trust.

When developing AI tools, involve testing auditing firms to ensure secure internal deployment, assess legal risks, and check the quality and accuracy of results. 

Undergo standardisation processes and obtain globally recognised certifications (like ISO or local government programs).

Reassure clients that data is secure, corporate information is protected, sensitive data isn’t used for AI training, and measures are in place to minimise data leaks, ensuring the solution is safe for deployment!

AI Usage: When Innovation Meets Security

AI fuels business growth, innovation, and competition with significant government and company investments.  

While cybersecurity and data privacy remain concerns, businesses must prioritise security, allocate protection budgets, and undergo audits to mitigate the risks of costly breaches. Embracing AI responsibly — with proper due diligence and certifications — strengthens credibility and reduces potential vulnerabilities.

Legal professionals should avoid bluster and buzzwords but suggest ready-to-deploy solutions and offer clients comprehensive due diligence at the early stage. This helps ensure security measures and compliance with laws and enhances client loyalty and trust.

Sources:

1. Firms in Singapore eye DeepSeek benefits, but cautious about data security risks, AI biases, Osmond Chia & Sheila Chiang, Straits Times, February 11, 2025
2. Mistral AI Bets on Open-Source Development to Overtake DeepSeek, CEO Says, Mauro Orru, Najat Kantouar, March 7, 2025
3. How AI Tools Are Reshaping the Coding Workforce, Isabelle Bousquette, March 4, 2025
4. Cybersecurity Budgets Should Reflect Business Risks, Corporate Leaders Say, Oliver Staley, February 26, 2025