We know that even the right idea in the wrong hands can seem like the wrong one. Although most companies plan to implement AI, only 20% of them truly understand how to get ready for it. This huge gap only highlights how complex it is to adopt new, rapidly evolving technology that has not been fully researched or widely experienced successfully. And this is especially significant for startups, which may lack the expertise to implement new technology successfully but need to compete by constantly showing innovation and broadcasting their value to the market. 

So, in this piece I want to draw attention to some of the key tips that startup founders should consider when thinking of AI integration into the business. 

Act now. The perfect time may never come

Many startups out there are hesitating to adopt AI technology, preferring to wait until it becomes more mature or until universal solutions emerge for smoother implementation. They are looking for wide adoption and standardised options before making a commitment. 

Well, I believe this is a huge mistake that could result in competitive loss. You got to strike while the iron is hot. Your fear can really damage you and your business. While you wait for ready-made solutions, you risk falling behind competitors and more proactive market players. They are not afraid to make crucial decisions and are already developing and implementing their own AI solutions, gaining valuable experience and market advantages.

Pay close attention to costs and profitability of implementation

Another major mistake businesses often make is neglecting to consider the costs of AI integration and having too high expectations for its potential benefits. The primary reason for incorporating AI is to improve operational efficiency and increase profitability, necessitating a thorough and often expensive analysis.

If a start-up is ready to invest significant resources into AI implementation, I advise founders to assess the necessary computing power so the AI can effectively perform the required tasks. This will help determine if AI implementation will indeed result in notable cost savings and enhanced operational efficiency.

If the startup is not sure about  the evaluation it may indicate that AI is not essential for their business's operations. Adopting AI merely just to follow trends shouldn’t be a panacea. And  failing to understand this can lead to investments in technology that fail to provide substantial improvements.

Avoid a blurred focus on AI utilisation

Building on my earlier point, adopting AI without clearly understanding its benefits is pointless.

Many companies really struggle to identify which parts of their operations would benefit most from AI upgrades. Oversized initiatives can lead to employee scepticism if they fail, while overly small projects may not garner enough support to succeed.

This ambiguity and lack of clear priorities significantly hinder AI adoption. In my view, the most valuable applications of AI are in automating routine tasks, such as client support, automated management, and compliance in banking and financial services. Although enhancing internal processes with AI might not immediately boost profits like customer-facing services, it offers substantial long-term benefits. 

Keep a close eye on AI regulations

Integrating AI is not only about the technical side of the question; it also requires adherence to regulatory standards. As a growing industry, AI faces constant regulatory changes, with new rules and norms continually being proposed, making future changes hard to predict.

AI is now on the agenda of global regulators, including the UK, EU, and the United States. Each country has different standards and timelines for AI implementation, so it's essential to constantly monitor all regulatory changes. Navigating this complex landscape is crucial, as non-compliance can hinder AI adoption and result in hefty fines and damage to the company's image.