TJ interviews: Visier's Ian Cook
Ian Cook looks at the way forward for AI in business.
Has the increase in remote working affected how much AI is going to change our work life?
The rise of AI has required the world to adapt and realign to a new reality more rapidly than ever before - and the COVID-19 pandemic has only accelerated that growth and heightened the need for digital transformation.
To keep front-line workers and their customers safe amid the pandemic, many organisations opted to replace services and manufacturing positions with robotics and automation much quicker than they would have otherwise.
Knowledge workers across all industries found workflow automation and AI-enabled workplace tools becoming more common in their day-to-days to handle the increasing workload and shift to cloud-based technologies.
While these were all instances that were bound to happen eventually due to the evolution of AI and other emerging technologies, the pandemic escalated that growth and forced companies and their employees to adapt much quicker than they would have otherwise.
Is reskilling required to help workers understand and deal with new technology such as AI?
Reskilling is essential to ensuring workers understand and adapt to new technology like AI. Artificial intelligence is poised to eliminate millions of jobs - but will create millions more new ones in its wake, leaving many employers facing an imminent skills gap in their workforce.
Rather than just throwing money into training, thoroughly investigate the source of every success and failure so you can make meaningful improvements.
But, as with past technological revolutions like the Industrial Revolution, humans have already begun to evolve.
Just as the advent of ATMs didn’t put an end to bank teller jobs - in fact, the positions grew in number as banking transactions became more frequent, requiring enhanced customer service –– AI won’t completely eliminate work. Instead, new jobs have emerged to provide critical checks and balances on the technology and fill in gaps that come with the use of AI.
For example, fast food companies like McDonald’s are transitioning cashiers into table-service roles after introducing self-service kiosks into their restaurants. Similarly, Amazon warehouse workers are transitioning from stacking 25-pound bins to supervising robots. Reskilling is critical to all of these instances to ensure employees transitioning to new roles are equipped with the right skills to succeed.
What are the steps organisations can take to reskill workers for new roles?
A data-driven approach to reskilling ensures HR invests resources into training initiatives that will actually pay off. Using data as a foundation, the following steps provide a framework to reskill and upskill workers for new roles:
Step 1: Align people to business goals
Hopefully, your organisation has strategic goals for implementing new tools. When you understand how technologies like AI and automation solve a particular business problem, you can align the people skills that need to be prioritised moving forward.
Step 2: Identify skills gaps
Once people and business goals are aligned, take a look at your existing workforce to determine skills gaps. In this step, HR can use predictive analytics technology to identify employees who already have the skills you need, and those who could be trained to fill gaps where critical skills are missing. Making these identifications early on helps protect HR’s time and budget.
Step 3: Deploy and evolve training programs
Now it’s time for HR to roll out training initiatives to address the skills gaps they’ve identified. It’s critical for organisations to continuously analyze the effectiveness of these initiatives and make optimizations to ensure success. Rather than just throwing money into training, thoroughly investigate the source of every success and failure so you can make meaningful improvements.
Step 4: Create a talent pipeline
If organisations wait until there’s an urgent need to fill a new role, chances are they’ll be hard-pressed to find qualified candidates. One way to create a talent pipeline is through partnerships with educational institutions. This sets a foundation for a healthy stream of new talent as employees naturally turn over or age out of the workforce.
How can organisations use data to uncover the uneven impact of automation?
The pandemic is accelerating automation across multiple industries, and with automation on the rise, employers need to be cognizant of how new technologies disproportionately affect members of their workforce, especially racial minorities and employees in low-paying jobs.
For example, a 2019 McKinsey study shows that automation trends may be widening the racial wealth gap, and “African Americans could experience the disruptive forces of automation from a distinctly disadvantaged position.” COVID-19 has only exacerbated these concerns.
To ensure minority and low-wage workers don’t get left behind due to automation, HR leaders can proactively analyze their workforce data to determine who will most likely be affected by automation and how these individuals could benefit from reskilling.
By identifying individuals who are likely to be displaced, they can deploy targeted training efforts based on the steps above to help remedy this uneven impact.
About the author
Ian Cook is VP of People Analytics at Visier
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