Technology, Media & Entertainment

AI/Machine Learning

Machine Learning and AI technology have become a part of our daily lives very quickly through smart assistants like Google Assistant, Apple’s Siri and Amazon’s Alexa that are present in televisions, speakers, phones, watches and cars.

Industry Challenges

This is driving demand for UX and natural language processing talent to allow this ML and AI systems to interact with users effectively.

There is a big gap between companies doing AI / ML, and companies wanting to do ML / AI work and developing this capability. Experienced candidates are needed to set up and establish ML / AI capabilities, but they are in very high demand. They want to be involved in pioneering and challenging work, but this is mostly being done in the companies that are already ahead of the curve in AI / ML, so companies trying to hire experienced talent to catch up struggle to attract the best candidates.

Elements of AI are already being used in the recruitment process to assess the suitability of candidates with the main short-term goal of reducing unconscious bias, however, data can be problematic. Most companies use past selection criteria, or human assessment of candidate profiles to feed into AI which introduces bias into the technology as a starting point. AI in Talent Acquisition and HR is in very early stages but has the potential to drive significant change as with all functions.

ai machine learning

Our Experience

Talent research specialists in AI and machine learning.

From establishing new talent pools and supporting business growth to identifying leadership teams who can help the company meet new customer demands, our insights will give your talent acquisition strategy an unparalleled advantage.

The Armstrong Craven team are experts in talent research and are always ready to support companies as they grow with the industry.

According to a recent report, global spending for AI will reach $97.9 billion in 2023, up almost 3 times (261% increase) from $37.5 billion in 2019. By 2022, more than 3/4 of companies will use deep Neural Networks, rather than the classical machine learning

Client Partner

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