How AI will affect Food & Drink sector recruitment

Artificial Intelligence may be a much used buzz word but it's application is penetrating many facets of our lives, including how Food & Drink companies go about recruiting personnel. With 96 percent of senior HR professionals believing AI has the potential to enhance talent acquisition, it’s widespread adoption in recruitment seems inevitable.

However, a major barrier to the mass adoption of AI within recruitment is undoubtably the data privacy and data protection challenges that exists, as artificial intelligence when used in a recruitment context often needs the input of an abudance of data to make meaningful predictions and forecasts about job applications and candidates.

With legislators and consumers increasingly calling for stronger data protection, recruiters and employers are having to enusure they give back control of data to the owners. Failure to follow best-practice with regard to data privacy can cause a major fall out and the reputational damage to an employers brand can be catastrophic, potentially bringing about the demise of the orgainisation, as happeded with Cambridge Analytica who harvested Facebook user data for political influence. 

Subject to the data privacy challenges being overcome, Food Careers makes the following predictions on how AI will change recruitment practices for Food & Drink business over the next five years.

Shortlisting of Candidates: When a candidate sends their CV to a company through their website, an AI algorithm will scan the CV and automatically shortlist the candidate to the most suitable job/s and provide a ranking as to their suitability.

Virtual Assistant: Particularly for large Food companies with in-house recruitment teams, who will be able to give voice instruction to a virtual assistant such as: “Find the Technical Manager I spoke to a few months ago, the one who lived near Birmingham and had a lot of experience within HPP Processing.”

Ultra-Targeted Job Ads: Rather than placing an advert on your website and hoping, capture cookie data of an ideal candidate for a particular job, find lookalike cookie data sets, put the job advert in front of a relevant candidate at the right time. For example, if you wanted to recruit a Production Manager, you would target candidates who have been browsing similar positions, and target them at a time when they are most likely to make an application based on cookie history.  

Advanced Chatbots: Many Food companies already use Bots to answer basic questions, but advanced Bots will guide Candidates through the online job application process, decode a candidate’s responses through Natural Language Processing to spot certain skills, then use this information to make suggestions as to which jobs they should apply for.

Advanced Screening for Values & Culture Fit: Natural Language Processing will also be used to identify candidates that share the same values and fit the company culture. Once a prospective employer completes an online application, the company can benchmark the values and beliefs stated against the values and beliefs of the business, or benchmark the values and beliefs stated by the prospective employer against existing employees. Not only keywords could be screened for, but also for the meaning, so if someone has used a different term to describe what they believe in, the advanced screening will decode and interpret it.

Advanced Speech Analysis: The use of speech analysis may be beneficial for Food businesses to utilise for vacancies that are customer-facing. For example, most companies would want a sales person to come across as engaging and trustworthy, and language processing speech analysis allows a candidates speech pattern to be analysed for fluency, pronunciation, vocabulary, progression of ideas and how engaging or trustworthy they sound.

Gamification of Competency Tests: Many roles within the Food & Drink industry require a standard set of competencies. Advanced competency tests allow potential employees to demonstrate their emotional and cognitive abilities through the medium of fun games, which reduces candidate stress allowing them to perform better in the test resulting in a more natural test result. Neuroscience games are fun to complete and enable an employer to work out a number of emotional and cognitive traits that the candidate has, and how this will help or hinder them in the job they are applying for.

Modelling Ideal Employees: With advanced algorithms it is now possible to gather information on high-performing staff, such as their CV, ethics, values, beliefs, the way they work, educational background, professional background, work patterns, career trajectory, performance results, personality traits etc. Then plug all this information into an algorithm to model what the company should be looking for in new employees.