It's an absolute truism to say that AI is rapidly reshaping the job market, with the tech industry at the forefront of this shake-up. But while news media like to concentrate on the fear-mongering aspects of this change, the reality on the ground is more nuanced.
Yes, many repetitive and basic tasks previously performed by people are being automated and run by AI – but AI is also a job creation machine. Take for instance the software industry. Many junior-level coding and testing roles are disappearing thanks to AI – but new jobs are being created too: machine learning specialists, hybrid engineering roles, and in particular, data scientists.
In fact, the software engineer's job itself is changing. Technical skills are now only one part of the equation. Today, the role increasingly requires critical qualities such as judgement and verification – for instance, the ability to analyse AI-generated code and understand whether nor not it does what it's meant to do. There's also a need for systemic thinking plus good communication skills. AI makes it cheap to generate options, but expensive to decide between them. Software engineers who can articulate issues to non-technical stakeholders are becoming increasingly valuable.
The problem is, there aren't enough people out there with the requisite inter-personal skills and hard qualifications to slot neatly into this new world. Yet is this apparent 'talent crisis' actually the product of firms looking at the employment market in an overly simplistic fashion while being unable to measure and assess the people they already employ?
Most HR departments are still using systems designed for a pre-AI world, predominantly based on screening CVs for relevant credentials and prior experience. And ironically, a flood of AI-generated applications has pushed HR even further towards the bluntest of filters: degrees, job titles, years worked etc. But these criteria fail to identify the best candidates when new roles require not just specific technical skills, but also less easily identified qualities such as judgement, intuition and insight.
HR also struggles to understand its existing workforce beyond the most basic criteria of an employee's current role and their performance within that role's parameters. Job history only shows what someone has done, not whether they have the underlying reasoning, motivation and adaptability to do something different. In other words, there's a severe lack of insight into what the worker is like as an individual, and what they might be capable of in the future.
Companies are laying off experienced people whose specific tasks are being automated, while simultaneously struggling to fill new roles. But is a fundamental failure to embrace 'whole-person measurement' – where values, personal traits and skills are assessed together – leading to the needless sacking of employees who actually already have the qualities required to pivot to new AI-augmented roles?
Today, most firms lack any reliable mechanism for identifying who within their workforce has the underlying capabilities to transition to a new role versus who will struggle and stall. Yet at the same time, with the supply of external candidates for AI-augmented roles extremely pinched, internal redeployment of talent remains an important way to address this issue.
This situation has got to change. Those firms that invest in measuring their employees' cognitive ability, learning agility, and motivation to grow into new domains, will be the ones that thrive in this new world of AI. Once HR departments properly understand the people they have, the build-versus-buy decision becomes more informed: they can retrain and redeploy internal candidates whose potential they can now see, and hire externally only when there's genuinely no other option.
A failure to recognise the potential flexibility of internal candidates has helped create an artificial talent crisis within the tech industry, with AI-driven lay-offs hurriedly pushed through without a proper appreciation of workforces' ability to adapt and pivot. The key to escaping this relentless cycle of fire-and-hire is through seeing each employee as a fully-rounded person and not just a set of outdated credentials.