What to look out for when integrating AI into your existing solution
By Ynze Sipkema, Chief AI Officer Blinqx
BIy integrating AI functionality into an existing SaaS solution, people sometimes overlook making sure your customer not only understands the technology, but is actually ready for it. As consumers, we now use AI – consciously and unconsciously – every day, but as a business service provider, you have a responsibility to your customer that often entails a different level of adoption.
At Blinqx, we’re passionate about developing AI solutions that deliver real value for our customers (we’ve been doing it for years). But how do you make sure your AI solution not only works technically, but actually has the impact you promise? In this blog, I’d like to share some insights, practical tips on what to look out for when launching AI innovations and Agentic AI into your existing solution.
1 Define added value for your customer
When you add AI functionality to your SaaS solution, you should always make it clear what value it adds for your customer. It’s easy to get excited about the technological possibilities of AI, but at the end of the day it’s all about the question: what does it benefit the customer?
The latest developments in agentic AI show that these systems cannot just automate tasks, but can actually make strategic decisions. For example, in the insurance industry, we use AI to automatically evaluate claims, where AI not only checks the request in a database, but can independently determine whether a claim has merit or not. This saves an enormous amount of time for claims handlers, while increasing the accuracy of evaluations. But in doing so, it is essential that your client remains the human-in-the-loop.
2 Work together
Work closely with your customers to better understand the problems they experience. Whether it’s automating repetitive tasks or improving customer interactions via chatbots, AI should always add tangible value. It helps to identify your customers’ specific pain points and see how AI can alleviate them. Continuing with the case I just cited, for example, AI can also increase our customer’s efficiency by automatically creating follow-up tasks for a claim, directly contributing to the success of their organization.
3 Think carefully about your data
AI is all about the rightdata. If you want to use AI to increase predictability or automate tasks, for example, you need to make sure that the data you use is representative and of high quality. This is even more true when using agentic AI – systems that can act independently and make decisions based on the data they process.
A good example of agentic AI in the B2B SaaS world is an AI-based chatbot that can handle customer requests independently. These systems are designed to learn from previous interactions and can therefore significantly improve the customer experience. But this requires that the data the AI receives be accurate and representative, so that the system can make informed decisions without human intervention. The knowledge you give your chatbot about your product, your customers and the industry makes all the difference in providing valuable support. (Shit in = shit out).
4 Timing is everything
The right time to bring your AI solution to market is crucial. While the technology needs to work, you also need to consider your customer’s willingness to embrace this innovation. What we often see in business and financial services – and especially our Insurance & Mortgage, Accountancy and Legal sectors – is that (often larger) clients are technically ready for AI solutions, but adoption depends on other factors, such as laws and regulations or internal processes.
5 Compliance and other ‘obstacles’
In business and financial services, one of the challenges in implementing AI is the need for strict compliance with laws and regulations. While AI systems are becoming increasingly powerful, clients may not always be ready to integrate that technology into their operational processes without first ensuring they meet all legal/compliance requirements. This is a situation where timing and education are critical. Customers must not only understand how AI works, but also have confidence in the security and compliance of the technology.
6 Dare to let go of the hype, the hype
Develop for your customer, not for the buhne. Broad adoption of your solution is the best starting point. Therefore, organize regular workshops to help customers understand how to apply AI and the implications of autonomous systems such as agentic AI. These sessions help evaluate the customer’s current data infrastructure and guide them through the process of AI integration. Sometimes it turns out that the customer does not yet have the necessary confidence in the technology, or that additional steps are needed to prepare them for adoption. Be mindful of that.
Conclusion
AI is changing the way business and financial services companies work, thanks in part to your solutions. But to make it successful, you need to be well prepared. From the data you use to defining the added value and finding the right time for launch, each of these steps plays a key role in the success of your AI solution. With the speed of AI developments, it becomes even more important to make sure you prioritize quality data, responsible implementation and user interaction.
At Blinqx, we make sure that we always put the customer first so that we develop AI innovations that really make an impact. It takes not only technical knowledge, but also a deep understanding of market demand and customer needs to ensure that AI is not a technological gadget, but delivers real, added value.
Check out the latest Blinqx developments around AI here.
