Generative AI and preparing for a shift to skills-based hiring

As gen AI takes hold in the workplace, it’ll no doubt alter workflows, role requirements, and the skills necessary to get work done. The concern isn’t so much whether AI will replace jobs, but what skillsets the technology will replace, and how organizations and leaders can shift human priorities accordingly.

“AI is both a major disruptor and savior, in that gen AI specifically will influence 4.5 times the number of jobs it replaces and, yet, also has the capability to help manage and upskill the very skills it’s upsetting,” says Betsy Summers, an analyst at Forrester.

There’ll be tasks that AI will be able to perform better than humans, tasks that will still benefit from a human touch, and situations where a combination of humans and AI will be the right approach. The key is to take stock of the skills your organization needs to succeed and to identify how those skills might be impacted by gen AI in order to create a reskilling plan for the future.

Because of this, skills-based or skills-first hiring is poised to gain further traction in tomorrow’s enterprise, according to Deloitte AI Institute’s Generative AI and the Future of Work report, which outlines the changes to expect from gen AI and how leaders can embrace such a skills-based approach to prepare workforces for impending changes in roles, responsibilities, and skills.

Traditionally, organizations have structured their hiring approaches around job titles as a way to define the necessary skills and expertise for any role in their hierarchy. According to Deloitte and other skills-first advocates, adhering to this approach can hinder organizational agility and innovation, not to mention diversity, inclusion, and equity. Instead, by viewing roles within the organization as a collection of shifting skillsets, rather than a specific job title, Deloitte and others argue that organizations can be more responsive to industry changes — and to the rise of gen AI in the workplace in particular.

Taking a skills-based approach

In its report, Deloitte points to Ikea, which implemented an AI customer service bot called Billie. According to Ikea, Billie has handled over 47% of customer inquiries during the past two years, freeing up nearly 10,000 call center workers to gain new skills, including those of interior design advisors to help provide consultations for customers. By upskilling and reskilling these workers, Ikea was able to create a new revenue stream, retain trained workers, and cultivate an environment of continuous learning for employees.

For Deloitte, the Swedish home furnishing brand provides the classic example of how gen AI is already impacting the workplace. Skills and tasks are what will face the most change from it, with certain tasks — such as fielding customer inquiries — being more likely to be automated entirely by AI, freeing human workers to focus on more complex projects.

Summers says AI has many use cases to reduce complexity at work, especially in hiring. It can assist recruiters when writing job descriptions, identify competitive skills to list, and evaluate the final posting for any potential bias. It can further simplify the hiring process by guiding or matching candidates to positions they’re best suited for, assisting with candidate outreach, informing interview questions, and helping with scheduling each round of interviews.

“However, just because we can leverage AI for all these use cases doesn’t mean we should,” says Summers. “Each organization must determine their risk readiness and conduct a thoughtful decision process to prioritize and choose AI use cases.”

The key is for organizational leaders to know which tasks and skills can best be automated or supported by gen AI, and which will be the least impacted. This understanding can help guide hiring, training, and upskilling initiatives in the organization, and provide a guide for where to focus on the human aspect, and where to implement gen AI. 

Redefining and recategorizing skills

To start, Deloitte recommends categorizing jobs in your organization into types such as the following:

• Routine cognitive jobs such as data entry, basic coding, and customer service, which will benefit from gen AI by reducing redundancy in daily tasks.
• Non-routine cognitive jobs that require complex problem-solving, strategic thinking, or advanced technical skills that can be supported by gen AI in the form of data-driven insights, pattern recognition, or predictive analysis.
• Social and emotional jobs that require high levels of emotional intelligence, such as therapist, social worker, or salesperson, which may be only lightly impacted by gen AI.
• Creative jobs that could leverage gen AI tools, such as large language and image models, to automate a significant amount of creative work.
• Data analyst jobs that will likely benefit from gen AI automation but may face more disruption than initially anticipated.
• Routine physical jobs such as factory work, housekeeping, and delivery services that will be impacted by automation and AI, but will still require human work for the physical labor.
• Non-routine physical jobs that require high levels of human interaction, problem-solving, and adaptability, meaning there will be a limited impact by gen AI.

Once you’ve categorized the jobs in your organization, you can move on to identify the skills that will be most impacted. This is important for planning upskilling strategies, educating workers on how to leverage AI in their daily work, and guiding the organization through the transformation. You’ll also need to understand what skills will be automated, which employees will be the most freed up from redundant work, and how to upskill and reskill the workers who are most impacted by automation.

Deloitte offers the following categories to identify skills that will be impacted by gen AI:

• Automated tasks that will be entirely undertaken, with minimal or no human interaction necessary. Examples include image and content generation, data sorting and categorization, forecasting, language translation, simple graphic design, and basic trend spotting.
• Augmented skills that are “fundamentally human,” but can be enhanced by gen AI tools. Examples include analytical thinking, problem solving, creativity, research, data visualization, strategic planning, predictive analysis, and rapid prototyping.
• New skills that will emerge such as AI ethics and regulation, AI-human task management, and gen AI output customization.
• Limited impact tasks that require a human touch, such as complex judgment or nuanced decision-making, that gen AI can’t accomplish. Examples include persuasion and negotiation, motivational leadership, ethical judgment and integrity, compassion, building human relationships, and physical dexterity.

Defining, and redefining, the skills in your organization can help give you a better idea of where you need to look at hiring new people versus where you can upskill and reskill internally. Understanding where and how gen AI will impact skills in the organization can also help inform internal training and upskilling programs. Organizations will need to ensure they’re focused on skills-development more than ever, keeping an eye on emerging and new skills.

Ryan Sutton, a technology hiring and consulting expert at Robert Half, says IT leaders need to understand that developing the skills of their tech workforce is crucial to help futureproof operations against technological disruption. Businesses must also invest in the right skills and ensure their workforce has the necessary tools to gain new skills if they want to remain ahead of the wave of digital transformation.

“While companies should consider hiring new employees to address certain skills gaps, they should also acknowledge the value of leveraging the strengths and potential of their existing employees and teams,” says Sutton. “Not only does it uncover more solutions to business needs, it also highlights a commitment to professional growth, which is often a contributing factor to attract and retain talent.”

Shifting metrics to measure success

While it’s important to recognize tech’s potential to enhance productivity, the Deloitte report points out how it’s equally important to reassess the definition of productivity in your organization. There’ll be a shift in measuring performance metrics, and traditional metrics, such as hours worked or revenue per employee, will no longer be relevant. Instead, it’ll become important to “measure human performance, emphasizing both business and human outcomes,” according to Deloitte.

Deloitte calls this “human sustainability,” referring to the goals and objectives that’ll enable an organization’s workforce to “thrive physically, emotionally, financially, and professionally.” These metrics include well-being, job satisfaction, personal growth, and skills development. Rather than evaluating short-term productivity metrics, the focus will be on “tangible outputs and intangible contributions, such as innovative solutions, interpersonal relationships, and organizational culture impact.”

Eventually, employees may even have a skills profile that follows them from each job or organization, says Summers. This will give employees better insight into their own skills and career paths, and give managers more data to help employees develop their careers. It can also be a valuable tool for recruiters, making it easier to narrow down the most qualified candidates for a role. 

But when it comes to talent management, Summers says that when speaking to IT leaders, she notices many aren’t aware of the technology available to help them transition to a skills-based mindset. Typically, it’s HR and recruiters who use these tools, while CIOs are still trying to manage team skills on spreadsheets.

Embracing skills-based talent management tools can help with the monumental task of identifying and categorizing skills in your organization, which can go a long way to smoothing the transition. These tools can offer a bigger picture of the organization’s skills stack, identifying skills and expertise across the entire company, while also providing useful metrics and feedback. Plus, it enables employers to generate a “dynamic and evolving graph of knowledge and skills,” says Summers, allowing organizations to use AI to keep pace with humans as their skills evolve.

It’ll be important to embrace new attitudes toward employee success and grow performance metrics along with gen AI technology. As job skills and expectations shift around automation, leaders will have to reassess how they interpret overall employee performance amid the changes.