With the 2023 Future of Jobs Report outlining that 43 percent of work tasks are expected to be automated by 2027, industry discussions have been flamed around the subsequent impact on the global workforce, says Markus Bertl.
Similar discussions also being held around emerging tech skills and knowledge gaps across a variety of industries. The proposed solutions are focused on improving hiring strategies, putting tech at the heart of institution-led education programmes, and upskilling existing workers.
While these are valuable tactics organisations should be considering, there is another crucial area that is contributing significantly to these issues and yet is going relatively unaddressed: how to mitigate the loss of existing skills and knowledge from a system.
Whether retiring outright, taking parental leave, or heading to another organisation, people leaving their jobs take with them a wealth of experience and know-how that is often not fully appreciated until it is gone.
These may not be tech-specific skills either – they may range from a company’s particular on-boarding process to running specific financial reports for a client each month or even how to fix the microwave door when it jams. From menial to highly technical, this is knowledge of value within the system, and time-consuming to replace.
Plugging the gaps with AI
A key solution to this will be AI, no matter what sector or industry a company works in. This does not mean the deployment of advanced, headline-grabbing AI that will require a suitably savvy team or costly infrastructure to oversee and try to keep in check. Rather, it is an efficient way of assessing an organisation’s operations and identifying the lesser-known areas within them – mapping the white space within the existing processes, the areas where the dots are joined by the human currently in the system but who may someday leave it.
By using AI to automatically list the documented knowledge, organisations can then more easily identify the existing gaps and look to fill them before the relevant personnel leave and take that knowledge and ability with them. The benefit is this can be automated, removing human error from the system – an intelligent assistant or equivalent can proactively engage with employees and their systems to track accordingly and map gaps. This will then mean that knowledge is shared and remains within the system – leaving organisations less vulnerable to skills and knowledge losses through natural churn and retirements.
When we talk more generally about skills and knowledge gaps, too often we look at the potential solutions and not at the causes. A major one is personnel departing without passing on their knowledge of how to do the job. This kind of white space knowledge mapping with AI tackles that cause directly and should help reduce it – not just minimising the impact of departures but ensuring those that remain or come in are as well-equipped as possible.
Of course, AI can do far more than just map these gaps or prepare for the absence or departures of valuable employees – it can assist all workers in their roles and help make them more efficient, in turn allowing their focus to be on higher value tasks than the time-consuming menial duties that constrain us all.
This can range from automatically answering questions and queries based on existing knowledge and documents to the intelligent management of emails and documents. Additionally, the smart summarising of documents, the identification and analysis of key information within systems and processes, all of this is a readily available benefit of AI and applicable to many organisations.
Once AI is being used, there are many advantages to be gained. In turn, by easing workloads, it will help workers put their energy to the things they most need to or most enjoy in their work, and in some cases lower the barrier to entry for certain jobs where a lack of digital skills might currently prove challenging – in turn potentially attracting more people to these roles.
Cloud provides the silver lining.
Additionally, there is the cost consideration for companies – investing in new technology is an outlay that is weighed against the amount and speed of return on that investment.
While we have foregrounded the timesaving benefits of AI here – in itself a cost saving in the human hours that would otherwise be needed, and in the retention of valuable knowledge within organisations’ systems – there are additional cost benefits to be found from allying it with cloud infrastructure.
Cloud is a fast, cheap and lightweight way to maximise the benefit organisations feel from using AI, and one which is often missing – AI solutions and aides exist but do not get the widespread deployment they ought to. A great example of this is ChatGPT. Its ubiquity came from its ease of access and the fact that millions of people could so quickly enjoy the chance to engage with an AI-based technology. That is a combination of its functionality but also the supporting cloud technology.
At enterprise level, the engagement with AI should go hand in hand with cloud – it allows deployment at scale and quicker and richer benefits. Organisations shouldn’t do this in isolation but work with knowledgeable partners to ensure the combination of technologies they deploy is optimised.
A smart solution
In recent years, we have gone through the Great Resignation, a retirement boom, plus times of economic hardship which might necessitate redundancies – even periods of furlough during the pandemic. AI should be used smartly as a tool to help companies prepare for departures – not in the sense of AI replacing these workers, but rather as a way of ensuring that as much knowledge and ability as possible can stay within an organisation.
Alongside this, it can be used to try to prevent these departures – and to open up a wider pool of potential replacements by helping roles, and the skills required, evolve.
By Markus Bertl, Data, Principal Architect for Data, AI & Automation