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According to the International Data Corporation (IDC) Worldwide Artificial Intelligence Systems Spending Guide, spending on AI enterprise technology will reach $97.9 billion in 2023. That’s more than double the $37.5 billion spent in 2019. There has never been a better time to adopt and implement these new technologies. Here’s why.
According to Deloitte’s State of AI and Intelligent Automation in Business Survey, the early-adopter advantage has all but fizzled out. While the main goal for AI adopters has been to improve efficiency; mature adopters are now seeking to use AI technologies to enhance differentiation. AI for automation and optimization provides substantial and clear benefits, but AI can also be leveraged to create new ways of working and develop stronger, more future-proof workforces. Most adopters believe that AI will “substantially transform” their industry and organization over the next three years.
AI has four aspects that can each be harnessed individually or in tandem to drive progress and productivity across functions.
Machine learning (ML) technologies can teach computers to analyze and classify data in order to identify hidden patterns and predict future outcomes. The Deloitte survey revealed that 67% of respondents were already using machine learning, and 97% were using or planning to use ML within the next year. In HR, ML can be used to predict things like employee churn, performance and trajectory.
A subset of machine learning known as “deep learning” is based upon a conceptual model of the human brain, made up of neural networks with multiple interconnecting layers. This type of model was already in use by 54% of respondents, while 95% said they were using or planning to use deep learning within the next year. Deep learning can be used to identify future skills required by your workforce.
The ability to extract or generate meaning and intent from text and deliver it in a readable form is known as natural language processing, or NLP. 58% percent of global respondents had already adopted natural language processing, and 94% were using or planning to use NLP within the next year. NLP can help identify strong candidates by “reading between the lines” of resumes.
The ability to extract meaning and intent from images (such as characters for automated document digitization), or categorize image-based content has been labeled computer vision. While 56% of respondents said they were already using computer vision; 94% were using or planning to use this technology within the next year. Computer vision can make scanning and extracting data from applications or resumes faster and more efficient.
In a 2019 PwC survey, 92% of respondents said they had experienced poor recruitment practices. Nearly half (49%) said they had turned down an offer due to a bad recruiting experience, and more than half (56%) said they would discourage others from applying to a job due to a bad experience. Two out of three complained about businesses that drew out the recruiting process for longer than a month, and 61% said they had been “ghosted” by a recruiter even after the interview stage, with no explanation or feedback.
Two out of five HR functions in international companies are currently using AI-applications, according to PwC. AI can streamline recruitment processes, helping identify top-matched talent for needed skills, speed time to hire, and manage the entire onboarding process for higher satisfaction. Feedback can be integrated for candidates that just missed the position, positioning them to be approached again in case of a similar opening.
Censia analyzes and sorts data to reveal subtle advantages from one candidate to the next, even in seemingly identical on the surface bios. You can easily compare careers and rank talent by their ability to work well as a team member, or by their competitive edge in negotiations. Instant Applicant Ranking (enabled when you integrate Censia with your company’s ATS) can surface applicants best suited for long-term retention based on analysis of your organization’s current and future skills needs. It’s time to embrace AI in recruiting and talent management as strongly as in every other aspect of your business.