Artificial Intelligence (i.e. intelligence demonstrated by machines rather than humans) is the most
Not a new story, but a news story
AI isn’t all that new: it goes way back to the 1950s when Alan Turing invested in tests based on natural language conversation with machines. AI has been getting smarter and more human-like ever since. It wasn’t until May 11, 1997, that an IBM computer called IBM ® Deep Blue ® beat the world chess champion after a six-game match. Surely, the most impressive moments for AI began in the last few years as the technology has become more democratized; making possible projects like Amelia from IPSOFT. With her Conversational AI capabilities, Amelia continuously learns from human interactions to create the most engaging user experiences and generate business value.
While it may not be shiny new, it is in line to be the next big thing, set to transform every aspect of our lives. Practically every business startup invested in by Silicon Vally investors in 2020 had an AI aspect to its business model. In the next decade, AI is set create enormous economic value, just like electricity once did. No surprise then that AI experts are among the most wanted tech specialists on the market!
Why AI is really useful tech
Artificial Intelligence technologies come with a few characteristics that make it a hugely useful instrument in business workflows:
#1 Data processing transaction volumes and affordability
In the past, computer scientists could not offer business ideas solutions that were affordable due to capacity constraints. AI changes that dynamic. Modern AI algorithms can check through millions of rows of data faster than a human, or many hundreds of humans. This brings greater reach to data processing applications previously constrained by ‘data crunching power.’
#2 24/7 service operation
Computers don’t sleep. It’s one of their endearing qualities. For businesses wanting to serve customers and operate 24/7, and potentially around the globe servicing different timezones, the ability of AI to support data processing around the clock unlocks opportunities for companies to step up their customer service experience.
#3 Attention to detail and interpretive skills
While humans struggle to dig out data variations in a spreadsheet, AI-driven computers can forensically match data across a myriad of data sets.
#4 To not make processing mistakes
Computer algorithms are utterly consistent in the way they operate. When presented with a series of conditions and rules, you can guarantee they will run the same algorithm in the same way. That level of reliability, to act on data in precisely the same way every time, makes AI-driven solutions invaluable in performing roles that would present a challenge for humans because they’re so mundane that boredom or exhaustion might result in manual errors creeping in.
#5 Removing bias
Humans are inherently opinionated. Sometimes, those opinions and perspectives can distort how systems and processes should work. Computers aren’t bias—and the only factor that can install bias into a computer algorithm is another human. Appropriately designed AI systems can overcome problems of bias in processes.
AI’s role in avoiding hiring risks
Within the lifecycle of recruitment and workforce management, there are a series of tasks that are better suited to an AI-driven algorithm than a human. These include:
Running background checks
IC compliance checks are essential to prevent the misclassification of new hires that can result in hefty fines from regulators. The challenge for talent leaders is that running background checks is repetitive, tedious and can place high demands on administrative resources. Fortunately, AI technology can help to take the load from administrators on vetting submitted applicant documents, and compare answers with legislative requirements.
Removing bias from CV screening
As mentioned earlier, AI is useful sometimes to remove bias and emotions from processes. This is particularly appropriate in the exercise of vetting candidates. Without some level of governance, there is a high probability that the wording of job applications, the evaluation of applications, etc., can be distorted by gender bias or other forms of institutionalized discrimination that reduce opportunities for a minority.
Soft-skils candidate vetting
Getting the best out of people means making sure candidates fit in with the culture of the enterprise they work for, and the soft-skills and other qualities needed to perform in the role they are applying for. AI can help to validate factors such as cultural fit and assess ‘what makes a candidate tick by leveraging the best known evaluation models and learning from the results of previous recruitments to shape selection recommendations to hiring managers.
One aspect of workforce management is balancing resourcing needs with talent availability. For some firms, the complexity of shift rotors is made even more complicated by variances in resourcing demands and ‘external environmental impacts’ such as the recent pandemic. Ultimately, the balance between labor demands and resourcing capacity comes down to crude numbers—and when it does, AI driven solutions are helpful in making recommendations to shift coordinators to achieve the optimal shift arrangements.
Setting the right hiring rate
Setting the hiring rate for any given role has a huge impact on the ability of an enterprise to find the talent it needs. Set the price too high, and your business can pay over the odds for its workers, but set too low, it’s unlikely you will find the talent you need. Hiring rates for any given job category are influenced by market conditions (i.e., the demand and supply pressures on labor sources), by the level of experience and skill that’s deemed desirable for the role, by geography, and by the parameters of the candidate search (such as the willingness of hiring managers to consider remote workers).