Should AI Be A Part Of Your Product? 5 Crucial Questions To Ask
Be Intentional, Not Reactive
There is no question that one of the greatest impacts of generative AI will be on the health sector.
Many new startups have appeared solving a range of long-standing problems and inefficiencies the health sector has struggled with.
This leaves existing organisations with a dilemma. Do you stick with your core solution, double down on what makes you strong, or do you understand and deploy AI into your solution in a careful and effective way?
The same goes for startups looking to build solutions to problems within the industry. Does your product need generative AI to be more successful? Will you be made obsolete by a competitor using AI to enhance their service?
These are the five core questions you have to consider.
Do Our Customers Want It?
This has to be the first question you ask and be extremely confident in the answer.
Generative AI comes in a variety of forms including chat interfaces and imaging. You need to assess how significant demand is for your existing customers. What features do you have the capacity to create and how effective will they be in solving new challenges or enhancing your existing product?
Assess how important the AI feature will be to their daily use of your product. Implementing AI is likely to be a costly and influential part of your product. Making AI a small and insignificant part of your product may not be worth the trouble of implementing it.
Find out existing user behaviours around generative AI. Understand their issues with AI that could be solved more effectively in line with your system. Then consider where AI can quantifiably enhance your existing systems.
Can We Deploy AI Safely And Reliably?
An important ethical consideration is to understand how reliable the outputs from your new AI interface will be. You need to work with a partner (such as OpenAI, Google or Nividia) who has deployed AI and conducted effective research to verify their accuracy and reliability.
Depending on the scale of your deployment and the depth of interaction with patients or customers you need to conduct your own tests that also work within your existing product structure. This is where most failures occur and the reliability declines.
Ensuring security responsibilities and regulatory compliance will also be crucial to an effective deployment. You need clarity on how customer data is being managed within the foundational models you adopt.
Have We Got The Expertise?
There are two ways to answer this question. The first is to consider the depth of AI implementation you are seeking to achieve. If you are looking for small AI-driven product solutions then the expertise should already exist in your organisation or it will be easy to acquire. If you are looking for a more complex integration of AI into your core solution then think carefully about the time and cost associated with deep implementation of AI. You will need to build out entire teams and integrate them into the existing team structure.
Does This Create Or Improve Our Moat?
Adding useful AI must result in unique features that cannot be replicated easily by competitors. You need to consider what will make your AI integration successful in the context of your existing solution and how the two will combine to create a unique feature set. This creates the moat you need to entice customers with a better product and then keep them by delivering on your promises.
There’s no point in building an AI tool if it’s not used or not understood. Luckily, natural language chat interfaces make this less of a sticking point in most cases but there are points you can slip up. If your AI features require additional training then it becomes more time-consuming and expensive to add the features effectively.
What Does Success Look Like?
You need to quantify what a successful launch will look like. Are you focusing on retention and existing customer satisfaction or are you looking to secure more customers? What are realistic near-term goals and what are the long-term goals you are looking to achieve by integrating AI across your solution?
What does failure look like? What might go wrong in this process that will result in you going backwards because of your focus on AI?
Put Your AI Strategy To The Test
Making a decision on whether to integrate AI into your solution requires a comprehensive investigation of these core considerations and those more relevant to your business.
Animus AI has a dedicated strategy app that is designed to help make these decisions more effectively. The strategy app has been trained on multiple datasets that include strategy pivoting, AI integration and commercial decision-making.
By asking these questions to Animus AI you are able to gain a more useful understanding of your organisation's need to implement AI into your product and how to do it effectively.
You can access the Animus AI strategy app here — Home | Animus Health (animus-health.com)
