Par Brendon CHAMANY
Europe Head
Wipro HOLMES (Artificial Intelligence Platform)
Par Tapati Bandopadhyay
Practice Head, Wipro HOLMES Artificial Intelligence Platform
WIPRO LIMITED
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Common challenges in AI adoption
Enterprises across industries face a few key challenges in adoption of AI:
Significance of selecting the right business case
Cost take-out is definitely a big win for any automation project, be it simple industrial automation or AI-based, intelligent or smart automation involving machine learning and reasoning. Also, people-costs typically being the most visible parameter, it often over-shadows the benefits of AI in other aspects and therefore business problems where AI could make a far bigger impact in terms of top-line, e.g. QoS improvements, gains in productivity, agility, TTM etc. get deprioritized and put on the back-burner.
That’s why- there is a need to put a simple lens in place that will help both clients and their AI solution partners to drive the due diligence in choosing the right business cases.
A framework for guidance
AI techniques work best if the business cases depict the following filtering criteria, briefly presented in figure 1 below and explained further:
Figure 1
This is not an exhaustive list; there can be various other specific criteria of the problem state-spaces that can be best addressed by AI techniques. These represent a basic set of criteria and attributes that are most commonly seen as the principal factors that determine suitability of AI and can leverage the strengths of AI techniques to overcome certain human limitations, beyond just cost considerations.
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