YOUR A.I. DESIGN MADE
YOUR A.I. DESIGN MADE
Book the ULTIMATE consultation for your business today!
1 - The more you tell us, the cheaper the development will be:
- Loose specification = £expensive
- Prescriptive specification = £thrifty
-
1 - The more you tell us, the cheaper the development will be:
- Loose specification = £expensive
- Prescriptive specification = £thrifty
-

Book the ULTIMATE consultation for your business today!


Book the ULTIMATE consultation for your business today!

To understand what AI can do for a product, AI must be defined:
‘AI bolstered hardware (AIBH) products enhance end user experience because they sense the world as people do and make more informed decisions from a full sensor data set rather than single measurements.’
This is best explained by example. Imagine a car with collision protection. A traditional solution might measure the distance between the vehicle and the object and velocity, the first being low enough and the second high enough to cause brakes to automatically be applied.
To understand what AI can do for a product, AI must be defined:
‘AI bolstered hardware (AIBH) products enhance end user experience because they sense the world as people do and make more informed decisions from a full sensor data set rather than single measurements.’
This is best explained by example. Imagine a car with collision protection. A traditional solution might measure the distance between the vehicle and the object and velocity, the first being low enough and the second high enough to cause brakes to automatically be applied.

Book the ULTIMATE consultation for your business today!
Statistics suggest that there is a 20% greater ROI from products with AI compared to similar ones without it, so there is surely an ROI from AI.
Achieving ROI from AI requires careful balancing of development costs, market needs and the enhanced performance expected from AI. Only the simplest of applications will be able to use the much vaunted plug-in AI models. It will be necessary to build a model, assimilate model data, learn and implement. This is not a lightweight exercise, and it is very easy to lose focus and become locked in an analysis loop that isn’t leading to satisfaction of market need.


The key points are:
- Before anything else – know your market. If the need is improperly understood, AI could become a millstone.
- AI’s performance is problematic. There should be desired outcomes, but you should always be ready for revelations with AI – measuring what you didn’t know you could. This is difficult to balance – beware of paralysis by analysis but be ready to exploit exciting discoveries when it makes commercial sense to do so.
- Know what your budgets are and weigh them in the balance with the foregoing bullets.
Developments that find the ‘sweet spot’ between AI performance, market need and budget are setting themselves up for success.