Twice as likely to succeed: The case for not building your own AI

Twice as likely to succeed: The case for not building your own AI 

Many leaders believe building AI themselves will be safer, cheaper, and give them more control. In reality, it is one of the fastest ways to waste money, stall progress, and fall behind competitors who move faster. 

According to MIT’s State of AI in Business 2025, companies that partner with specialist providers to deploy AI instead of building are twice as likely to succeed. That is not a small difference. It is the line between being on the winning side of the AI divide or being left behind. 

Myth #1: Building in-house is more secure 

It feels safer to keep everything internal. But most security failures do not come from external partners. They often result from misconfigurations, rushed builds, and inadequate governance. 

When you build AI yourself, you carry the responsibility for: 

• Data privacy, explainability, and bias testing 

• Regulatory compliance in a fast-changing environment; and 

• Continuous security monitoring and patching. 

Specialist AI providers have already built these guardrails in. Replicating that from scratch is costly, complex, and often riskier than the partnership route. What feels “safer” may actually expose you to more reputational and regulatory danger. 

Myth #2: Building in-house is cheaper 

On paper, DIY appears to be a cost-saver, but in reality, it is a cost trap. 

Some leaders also misunderstand what AI actually is. They treat it as another tool to bolt onto the tech stack, underestimating the complexity of integration, compliance, and adoption. The truth is, AI is not a feature that can be simply added. It requires systems that learn, adapt, and fit seamlessly into your operations and expert guidance. 

Hiring AI talent, maintaining infrastructure, and supporting custom models costs millions every year. And internal builds fail twice as often as external partnerships. 

That means half of the money you invest in building will likely be lost to stalled pilots and unfinished projects that never scale. Meanwhile, your competitors will be operationalising AI in months, not years. 

Who this is for 

If you are in: 

• Banks and other financial service providers: Including insurance, super funds, brokers, and financial planners. You face constant pressure to improve complaint handling, meet regulatory requirements, and cut the cost of contact centres. AI can automate complex workflows while protecting compliance. 

• Utilities: Customers want proactive communication and seamless service. AI helps you reduce call volumes, manage outages more effectively, predict customer churn and improve customer satisfaction without exceeding your budget. 

• Hospitals: Patients expect faster, more personalised engagement, but safety and compliance cannot be compromised. AI can streamline patient communication, reduce administrative load, and free staff to focus on care. 

• Common interest groups and peak bodies: Members want responsiveness and personalisation. AI can deliver tailored engagement, freeing up stretched staff to focus on advocacy and value creation. 

• Telcos and ISPs: Churn is high, and customer frustration is higher. AI-powered contact centre automation and outbound engagement can turn that tide by enhancing first-call resolution and fostering customer loyalty. 

In all of these sectors, the benefits are real: 

• Faster complaint resolution 

• Reduced operating costs 

• Stronger compliance and risk management 

• Better customer or member retention 

• More time for staff to focus on what truly matters 

Why you need a guide 

AI is not about owning the most code. It is about deploying the right solution quickly, securely, and with measurable ROI. 

It is easy to become distracted and frustrated by a desire to master AI, when your organisation would be better served with you focussing on its core purpose. In reality you need to be able to master how you will employ AI and the best way to do that is to find a trusted partner who can do the hard work for you by translating the options and the implications, identifying and mitigating the risks and sharing the responsibility of driving success. Much like a builder will employ an architect, there are times when it makes sense to rely on the advice of experts.

At Insync, we guide you through the complexity so you avoid the mistakes others are making. We know what works, what doesn’t, and what will cost you millions if you get it wrong. Learn more here.

The choice in front of you 

You can spend years and millions trying to build something yourself, with no guarantee it will ever work. Alternatively, you can move faster, lower your risk, and actually see results by working with individuals who have already achieved this. 

It’s not really a question of whether you can build your own AI. Many organisations can. The real question is whether you should. 

At Insync, we help you avoid the dead ends and wasted investment. We take the time to understand your requirements and challenges, then guide you to the right solution so you get it right the first time.