Artificial intelligence, machine learning, and natural language processing have changed work and, along with it, the focus of recruiting. Over the past twenty years at least recruiters have focused on finding and hiring technical talent – experts in a field – practitioners of best practice who are highly skills and experienced. This has led to our current talent shortage and the increased emphasis on STEM education.
However, I believe that focus is misplaced and that there is a shift happening where the most sought-after people and the hardest to fill positions will not be STEM, but those that require a broader and less technical background.
I believe that by rethinking the types of positions we recruit for based on the need for innovation, creativity and teamwork will result in a better appreciation of where recruiting effort should be applied and more focus on where artificial intelligence could augment the recruitment process.
One of the challenges of leadership is how to allocate recruiter resources and budget between positions. Today most budget and time are spent hiring people who do routine work (Transactors) and technical people (Experts).
Transactional work is performed by people doing routine jobs that are largely governed by rules and procedures that need to be learned and followed with some rigor. These are secretaries, receptionists, bookkeepers, legal clerks, and machine operators, for example. There is not a lot of room for interpretation, innovation or teamwork. Individuals perform these jobs and are rewarded by how well they do individually. Some of these positions require specific skills, but these skills, can be learned fairly quickly and once learned, can be applied without any significant modification for long periods.
A.I. is likely to take over many or even most of these functions within the next few years. There are currently tools available to answer your phone with feedback and engagement. There are automated bookkeeping systems. Receptionists have been largely replaced with automated sign-in features and in some cases chatbots. Legal research has been automated to the point that a lawyer can ask a system for the precedents on a particular case without any human intervention. Robots have eliminated or simplified manual machine operation and replaced manufacturing skills. And in every area A.I. and robotics are getting more capable and efficient.
To spend much time or effort recruiting for these jobs is becoming unnecessary and even wasteful of recruiting resources. Recruiting leadership should be focused on finding automated tools to make hiring for these positions fast, effective and inexpensive.
These are the current “darlings” of the recruitment and work world. Filling these positions is the focus of most recruiters and the area where they spend the most time. There are major talent shortages in specific areas and the challenges in finding talented people are the largest. This box includes all technical, engineering, software and hardware positions and positions where deep expertise is valued and where advanced degrees are often required, including functions such as legal, human resources, financial, and leadership. These positions require people who follow rules but also apply judgement, often augmented by mathematics or statistics, to make decisions. Being innovative is not critical but using best practices and acting in a predictable manner are. Everything is aimed at not making mistakes. These positions are sustaining and provide continuity and predictability, traits that are necessary but not ones that lead to growth or innovation.
Over the next decade many of these positions will be affected by A.I. Artificial intelligence will begin to replace some of these, provide answers to technical questions, even write code and reduce the amount and depth of knowledge individuals need to be effective. Some of these positions may be augmented significantly enough to allow a junior person to be effective. I envision more focus on how intelligent software could take over many of the routine parts of these positions with job requirements being pared back for the people who remain, thus eliminating any talent shortages.
Collaborators and Networkers
The skills that are emerging as critical for success in an A.I. augmented world are not the ones you might expect. As we noted above, technical and STEM skills will be gradually replaced or hugely augmented with A.I. The remaining skills will involve working with other people, influencing, challenging, coordinating, and connecting with a global team. We will need people with the ability to work across cultures, built strong relationships, and encourage creative decision making in the face of unknown and unknowable challenges.
A.I. may offer some help to those in these positions, but that help will be technical and will provide a basis for decisions and interactions that are based on emotion and relationship. These positions require people comfortable working in teams, sharing intellectual property, exchanging and debating ideas, and coming to mutually acceptable decisions. Some of these people may straddle the border with the experts and, when this happens, we will have the best of both worlds.
For recruiters and hiring managers, this is the category to focus on and nurturing skills at creating and hiring for these positions. Influencing hiring managers to think outside the technical requirements box and begin to choose people that may lack strong technical backgrounds but have team and collaboration skills will be important.
Innovators are complex and do not conform to the usual ways of recruiting or work.
Imagine the job description for Elon Musk, Steve Jobs, Richard Branson, or Albert Einstein. Where and how would anyone find people with their eclectic and non-traditional skills. What skills have made them exceptional? What tests or behavior patterns would you use?
Yet, these are positions that will create and build future organizations and keep current ones profitable. We have all seen innovative startups lose their creativity and innovation as they mature. We’ve seen the decline of organizations that were considered the best and that were the most profitable because they were not able to hire, develop or promote the mavericks and innovators that might have kept them booming.
We need to focus both A.I. and our recruiting research on how we can find or develop more people with innovation skills, willing to experiment and fail, willing to pick up the pieces and try again. These people need to have a combination of skills that are not normally found or encouraged, and we will need recruiters with same sort of unconventional approach to find and hire them.
While these breakdowns form a simplistic model and do not take in all the shades of gray that exist, it may provide a useful starting point for thinking differently about positions and what we expect from them. It will, hopefully, begin to help change the narrow mindsets both recruiters and hiring manages have on who their most important hires are and where they should spend the most time and money.