Why thinking like a tech company is essential for your business’s survival

To thrive in today’s business environment, companies must align their technological and cultural foundations with their ultimate goals. This requires reflecting on the fundamental question: Why does your business exist? The answer informs how you integrate innovation into your operations and balance competing priorities to drive long-term success. 

At Brown & Brown, we constantly focus on articulating the value of technology in terms of business outcomes. If we don’t ground ourselves in that, we risk losing sight of what really matters. 

For us, that means remembering our core mission: providing risk management and insurance solutions to our customers in a way that helps them protect their businesses and families. It doesn’t matter what desk we sit at or what department we work in—every decision we make and every technology we adopt has to align with that purpose. 

The phrase “every company is a tech company” gets thrown around a lot, but what does that actually mean? To us, it’s not just about using technology — it’s about thinking like a tech company. The most successful tech companies don’t just refine what they already do; they reinvent themselves in anticipation of what’s next. They place bets. They ask: Where do we need to be in five or 10 years? And then, they start moving in that direction while staying flexible enough to adapt as the market evolves. 

A great example of this is the semiconductor industry. Companies like Qualcomm have to plan and commit well in advance, estimating chip production cycles while simultaneously innovating at breakneck speed. They don’t just react to change; they engineer it. That’s the mindset we need to bring into every business, whether we’re selling insurance, financial services, or something else entirely. 

That’s why we view technology through three interconnected lenses: 

1. Protect the house – Keep our technology and data secure. 

2. Keep the lights on – Ensure the systems we rely on every day continue to function smoothly. 

3. Innovate and explore – Use technology to drive better outcomes and future-proof our business. 

The real challenge is balancing all three while ensuring innovation leads the way. And right now, there’s no greater test of that than AI. 

Preparing for what’s next (AI) 

AI is already here, and it’s reshaping the way businesses operate. But we’re still in the early days of figuring out what it really means for our industry. We’ve taken a structured approach to prepare for AI — one that balances risk, opportunity and education. 

1. Establishing AI guidelines and policies 

One of the first things we asked ourselves was: What does AI mean for us? If we didn’t define it, our teams would — and that could lead to inconsistency, risk or even legal exposure. 

We developed clear governance policies that outlined: 

• How we define AI and generative AI in our business 
• Principles for responsible AI use 
• A structured governance process 
• Compliance standards across different regions (because AI regulations vary significantly between Europe and U.S. states) 

The reality is that if you don’t actively shape your approach to AI, the market will shape it for you. Having clear AI policies isn’t just about risk mitigation; it’s about controlling our own destiny in this rapidly evolving space. 

2. Educating and training our team 

With generative AI, for example, its adoption has surged from 50% to 72% in the past year, according to research by McKinsey. By early 2024, according to a report from Microsoft, 75% of employees reported using AI at work, with 80% of that population using tools not sanctioned by their employers. 

Those stats made us realize we needed to educate our teams, not just regulate them. So, we developed training that: 

• Defines AI and generative AI 
• Explains both the benefits and risks 
• Uses real-world examples to reinforce responsible use 

One of the biggest drivers of unsanctioned AI usage is workplace pressure. People feel overwhelmed; they need solutions fast, and if we don’t give them the right tools, they’ll find their own. So, our goal is to meet them where they are — providing guidance that’s both practical and easy to follow. 

3. Expanding our approach to risk management 

Risk management is part of our DNA, but AI presents new types of risks that businesses haven’t dealt with before. Instead of reinventing the wheel, we asked: How can we incorporate AI risk management into our existing processes? 

For example, when we evaluate third-party vendors, we now ask: 

• Does this vendor comply with AI-related data protections? 
• Are they using our proprietary data to train their AI models? 
• Does their contract language reflect responsible AI use? 

These questions didn’t exist a few years ago, but they’re essential now. We’ve seen contracts from different partners with wildly varying AI clauses, and we’ve recognized the need to have our own standardized language to protect ourselves. 

AI risk will only become more common, and companies that don’t adapt now will find themselves playing catch-up later. 

4. Providing opportunities for AI engagement 

We don’t just want to control AI — we want to help our organization use it effectively. We’ve created pilot programs, starting with tools like Microsoft 365 Copilot, to experiment with AI in a structured, low-risk environment. 

We also launched an internal AI user community where employees can: 

• Share best practices 
• Build prompt libraries 
• Discuss real-world applications 

Some companies have completely blocked AI, fearing security risks. But the problem is, when AI adoption inevitably becomes a business necessity, they’ll have to spend enormous resources catching up. We’d rather stay ahead of the curve. 

Hiring the right people for the future 

No matter how good our technology is, our success ultimately comes down to people. And we’ve learned that mindset matters more than skill set. 

When we launched an AI proof-of-concept project for our interns, we didn’t recruit based on technical acumen. Instead, we looked for curious, self-starting individuals willing to experiment and learn. 

What we found was eye-opening—these interns thrived despite having little prior experience with AI. Why? Because they asked great questions, adapted quickly, and weren’t afraid to explore. It reinforced something we already believed: 

• Adaptability is more valuable than technical skills 
• Curiosity drives better outcomes than expertise alone 
• Empathy is essential—we’re solving business problems, not just implementing technology 

Our industry is changing fast, and the only way to keep up is by hiring people who are willing to learn, try and grow. 

Investing in the future 

Now is the time to dedicate the necessary resources to prepare your business for what lies ahead. The pace of change isn’t slowing down, and neither are we. Aligning your culture, processes and technology strategy ensures you can adapt to a rapidly changing landscape while staying true to your core purpose. By fostering a culture of innovation, embracing emerging technologies like AI, and assembling a forward-thinking team, your organization will be well-positioned to lead, adapt and thrive. The future is coming fast — make sure you’re ready to meet it head-on. 

Mike Vaughan serves as Chief Data Officer for Brown & Brown Insurance. In this role, he strategically partners with business leaders, analytics leaders, data scientists, data analysts, data engineers and technology teammates to provide solutions that address real business challenges and opportunities in a meaningful and scalable way and is a champion for the creation of a data-driven and innovation-focused culture to enable the organization to effectively use data in decision-making and product development.

Arti Deshpande is a Senior Technology Solutions Business Partner for Brown & Brown Insurance. In this role, she empowers and enables the adoption of data, analytics and AI across the enterprise to achieve business outcomes and drive growth. She also serves as a consultant and partner to embedded data delivery, analytics, data science and business teams, leading the strategic development and implementation of AI-powered technology solutions.