Across the world, organisations are grappling with a growing skills gap as the ever-present pandemic continues to reshape the workforce and redefine people’s priorities. Unless AI bots take up the slack, companies risk leaving millions of pounds of business on the table – because there aren’t enough team members to identify leads, process invoices or attend to customer queries.
Where once increased use of AI automation was perceived as a threat to people’s jobs, today it offers a solution to rising staff gaps as more employees reassess what’s important and how they want to live and work. Today, across all kinds of organisations around the world, millions of pounds/euros/dollars-worth of business are being left on the table because teams don’t have the capacity to identify or follow up on new opportunities, chase unpaid invoices or nurture customer relationships.
It’s a crisis that can’t be resolved easily at a human level, as the Great Resignation has highlighted. However, Covid-19’s practical impact continues to be felt in 2022, a return to working patterns of old is unlikely. Urban-rural migration and trials of four-day weeks are among the current trends that will ensure this. In its Labour Market Outlook Survey in late 2021, the UK Chartered Institute of Personnel & Development (CIPD) saw the proportion of employers with hard-to-fill vacancies jump from 39% to 47% in the third quarter, while the median number of applicants for low-skilled vacancies dropped from 20 to 16.
Even if organisations could find people qualified or willing to fill the vacant positions, many can ill afford to offer the salaries that would now be needed. Skilled employees have realised their worth and increased their demands. Many low-skilled workers have returned to their home countries, meanwhile, fearing border closures or – in the UK – the fallout of Brexit.
AI picks up the slack
It’s in this context that AI offers a powerful solution, assuming more of a proactive and informed role in processing documents and data.
The shift to smart automation can be seen already in the large-scale switch to self-service portals, for everything from registering and managing insurance or warranty claims, to reviewing tax/pension details, viewing and updating HR records, tracking orders, settling bills and downloading invoices and receipts.
Internally, meanwhile, we’re seeing more business functions using intelligent ‘bots’ to extract, identify and process the contents of documents attached to emails. A trained AI bot can readily sort out contracts from invoices from letters of complaint, extract key information and decide and action next steps.
Taking care of critical essentials
As knowledge workers and information processors become harder to recruit, AI bots will fill in – providing greater levels of support to fewer people. Those skilled individuals that remain will become more like senior surgeons – called upon only once a patient has been prepped and even opened up on the operating table. With everything they need in place, they apply their skills, then move on to where they are needed next, while the supporting team (in this case trained AI bots) close and clean up.
This isn’t a futuristic vision, either. In the financial sector, high-frequency trading algorithms have been active for years, identifying and exploiting real-time opportunities in capital markets – work that was once done by humans, but can be done so much more efficiently by bots trained in what to look for (and much less likely to miss anything).
As companies struggle to replace sales team members, it makes sense that they would engage AI bots to mine existing intelligence from across the business, to generate a pipeline with an equivalent sales value. Equally, if the legal or risk department lacks the capacity to monitor contracts or other obligations for an upcoming review, to maintain compliance or minimise financial exposure, why wouldn’t AI be considered to fill that gap?
Capitalising on the huge leaps in AI potential
Gartner notes that, through the use of natural language processing (NLP) and emerging technologies such as generative AI, knowledge graphs and composite AI, organisations are increasingly using AI solutions to create new products, improve existing products and grow their customer base. And it’s a trend that will only accelerate, as necessity dictates.
That’s not to say that AI bots don’t have their limitations: among the challenges is increasing transparency so that it’s clearer how algorithms are reaching their conclusions. But in a great many everyday tasks, especially linked to data and content management, these tools can lighten the load significantly.
As managers’ trust in the technology grows through repeated use and AI training, the scope for process transformation will only grow. Ultimately, we can expect to see multiple AI bots working together, drawing on the same knowledge resources across an organisation to fulfil different workloads in different contexts, rather than being confined to individual departmental systems.
The cloud has democratised deep learning
While AI skills are themselves may be in short supply, there’s no need for enterprises to develop their own AI solutions. Deep learning engines, next-generation statistical analysis tools, natural language processing and image analysis capabilities are readily available via the cloud, and there are plenty of application vendors that should be able to apply and use these techniques in a relevant software layer – for instance, as part of process-specific content services.
Exploring the market to see what’s out there, and trialling new capabilities with a suitable software partner are logical next steps as companies look to AI bots to plug gaps in human teams. To drive real benefit, though, it will be important to seek out the quick wins aligned with current business priorities rather than try to apply AI as a blanket capability across the organisation.
