Hurdles to artificial intelligence implementation are not insurmountable but it’s useful to outline the key problems holding the technology back. TechGenix has produced a list that’s worth thinking through:
- not enough computing power: : the next level of AI requires more data analysis, and more complex algorithms. Naturally, the computing demands are massive.
- not enough clean data: For many organizations, data governance is a new and novel idea, and they’re only starting to find their feet in this playground.
- not enough skilled workforce: there’s a clear demand-supply gap in the AI jobs market.
- there’s a lot of skepticism: because end users have no way to understand how AI made a particular decision for them, they are bound to be skeptical, anxious, and even angry.
- severe regulatory risks: As AI begins to pervade all aspects of human life, it’s certain that governments will want a practical level of control. Legislation, until now, has been badly out of tune with tech innovation. In the times to come, regulators have a large ground to cover.