Sharing best practices, thoughts and trends about technology & innovation:
Most of our articles have an international outlook – with a few focusing on Malta – our homebase.
We’re lucky to live in an era where we can supercharge our businesses with the power of AI.
However, onboarding or building generative AI, chatbots, robots and other AI-based solutions brings a fresh set of challenges.
Best practices are the best way to deal with such challenges. This article is a list of 10 best practices gathered through our own experience in AI projects.
Documents such as application forms are a big chunk of the data that many organisations have to process every day. And even nowadays a lot of this processing is done manually.
AI & RPA can help an organisation process its documents promptly and accurately – removing mundane, repetitive, manual-heavy tasks – thus proving a faster, cheaper, better service.
Nowadays with the availability of better and cheaper hardware, lots of data, computer vision algorithms that have evolved and matured over the last 40 years and more AI engineers we can have AI object detection models that are trained to quickly and accurately identify and locate objects in images and videos.
Totally eliminating paper might sound impossible but technology nowadays has provided us with all the tools necessary to have a paperless business.
AI is talked about a lot these days. And this risks downplaying its potential as just another buzzword. In the last few years its adoption exploded. And there are clear good reasons for that. AI in business is used in many ways. We can classify the uses as follows.
For every business challenge, for every pain point, for every need there are always critical decisions to be made. Do you build a solution yourself with your in-house team? Do you commission a custom-built solution from a provider? Or do you find an off-the-shelf solution that is already in the market.
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