You've just onboarded your newest hire, Camila, a bright and enthusiastic recent graduate with a passion for new technologies, including artificial intelligence (AI) and machine learning.
As a hiring manager, you're excited to bring fresh talent to your team, but there's a slight catch: you’re not well-versed in the world of AI yourself. Like many people, you’ve played around with the new generative AI models like ChatGPT. Beyond that, however, you're in uncharted territory. You realize that this might make it difficult to nurture and upskill Camila and retain her as a valued employee.
Whether you think it’s overhyped or heralds the end of work as we know it, there’s no doubt AI is already changing roles and practices beyond all recognition. This means you need to stay on top of ever-evolving AI requirements to attract and retain talent with AI skills.
In this post, we’ll look at why it's important to get ahead of the AI curve in talent acquisition, including how it can impact business performance. Then we'll examine the AI skills you need to hire for to stay business competitive and attract top talent. We’ll also discuss how to use skills-based hiring to identify the best candidates with these skills and develop them internally.
McKinsey states that tasks accounting for up to 30% of hours currently worked in the US could be automated by 2030. This means that more people are shifting into higher-level, skills-based roles: It's estimated that 12 million AI-related occupational shifts will occur in the US by 2030.
To stay ahead of the curve, it's essential to hire for and develop AI skills to close potential digital skills gaps. This lets you develop an agile team while increasing retention rates. Retention becomes especially important given that more employees will be looking for companies that offer upskilling and growth opportunities.
By preparing employees for the future of work, you can provide improved job security and, therefore, win employee loyalty in an increasingly competitive landscape.
The roles and industries negatively impacted by automation and AI include food services, customer service and sales, production work, and office support.
By contrast, roles on the rise because of AI include science, technology, engineering, and math (STEM) professionals. For example, computer programmers and analysts, business and legal professionals, and health and wellness workers. It's also projected that demand will grow for skilled professionals in green and sustainable energy, transportation services, and healthcare.
As more people leave lower-wage jobs, the economy may readjust as more skilled, higher paying jobs are created. However, this means people will need additional skills to successfully make that transition.
AI has swiftly transitioned from being a novelty to a necessity for various aspects of modern work. This shift has created an unprecedented demand for employees equipped with AI skills across various tasks.
This is because AI saves time, regardless of the task. For example, optimizing supply chain management, enhancing customer experiences through predictive analytics, automating routine tasks, or improving decision-making processes.
This has a positive impact on business performance by allowing you to move faster. It also frees humans up to do more of the high value work they excel at. For example, when you use AI to identify the most valuable prospects on cold emailing lists, salespeople can spend more time crafting engaging emails.
HR professionals should start by gaining a fundamental understanding of AI concepts, which will enable them to talk to tech-savvy talent like Camila on her level. This can also lead to more informed decision-making regarding AI-driven tools. For example, if you’re deciding which generative AI tool to sign up for, it helps to know their capabilities and limitations.
McKinsey predicts that employers and HR teams will need to hire for skills rather than credentials. They’ll also need to recruit from overlooked talent pools like people with disabilities and workers skilled by alternative routes (STARs). Once onboarded, you’ll need to deliver training that keeps pace with employee’s changing needs.
Below, we'll look at which skills you can hire for and develop, as well as how to use skills-based hiring to recruit and retain the best talent.
To win the war for talent and harness the transformative power of AI, you need to hire people with the right skills. Since these are changing all the time, you need to know which AI skills to prioritize when hiring.
Let's take a look at the nine AI skills that should be on your radar, and why they're the building blocks for a future-proof workforce.
Data literate individuals can spot data quality issues and interpret the results of AI models to understand their implications. This might include differentiating between various types of data, collecting and preparing it, or analyzing and visualizing it.
Employees with strong data literacy skills can make better decisions. They can also build more effective AI models and gather accurate insights from data to drive business success.
In AI algorithm development, employees need to identify complex problems and devise innovative solutions. This includes selecting the right algorithms, optimizing them, and troubleshooting issues that arise during development.
To do this, they’ll need soft skills like problem solving and critical thinking. Problem-solving skills come into play when addressing data quality issues or missing data points. Critical thinking helps employees analyze data patterns, recognize anomalies, and draw meaningful conclusions.
Prompt engineering allows AI practitioners to have better control over the output of AI models like ChatGPT. By carefully crafting prompts, you can guide it to produce more specific responses. This is crucial in applications like marketing where output needs to align with specific requirements like brand voice, etc.
Employees who excel in prompt engineering can fine-tune prompts to generate more accurate and contextually relevant responses. This saves time and makes AI even more useful.
Knowing how to handle data is a fundamental AI skill when developing and deploying AI systems. For instance, data cleaning and preprocessing are needed to prepare text data for inputting into AI models. This can enhance the AI’s performance and relevance to your company's needs.
Employees with strong data handling skills can ensure that the data used to train AI models is high quality. This reduces the risk of errors or biases in the models and, therefore, outcomes.
Knowing how to handle data involves the ability to check its accuracy. Fact-checking helps make sure AI-driven content or recommendations are based on accurate and up-to-date information. This is essential to maintain credibility for businesses that use AI to generate content or make decisions. Sites like Upwork and Fiverr are awash with offers for skilled fact-checkers and demand is only likely to grow.
Employees with strong fact-checking skills contribute to the integrity and trustworthiness of AI systems and their outputs. This helps your organization make more informed decisions.
To incorporate AI capabilities into your existing apps or processes, you often need to use application programming interfaces (APIs), such as the one provided by OpenAI to integrate ChatGPT into business tools.
Employees skilled in API integration can connect AI systems to a wide range of data sources, including databases, web services, and cloud platforms. This makes it easier to design AI-optimized workflows and streamline existing processes.
Skilled talent can also facilitate data retrieval, which is crucial for training AI models and making data-driven decisions.
Knowing how to handle AI data is one thing, but you also need to know how to translate AI findings so the complexity and tone is suitable for the intended audience.
It's crucial to hire talent with strong communication skills to convey AI-related insights to clients, stakeholders, and cross-functional teams. To do this, they’ll need to be skilled at conveying complex ideas in simple, easy-to-understand terms.
AI changes fast, so employees need to be adaptable and have a growth mindset to stay ahead.
Understanding employee motivation and personality type can help you recruit talent that's eager to actively seek opportunities to learn and grow. This will ensure they can leverage the full potential of current and future AI tools.
Generative predictive text (GPT) AI models can create text, images, and music, among other applications. Employees can leverage this as a starting point for more complex creative work. For example, by creating content that speaks to a specific audience while ensuring high quality.
Now you know what to look for, let’s look at how to hire for these skills.
Below, you'll learn how to hire for and develop AI skills in your workforce, including key talent assessments you can use to hire and upskill the right people.
Skills-based hiring lets you test candidates on hard, soft, and transferable skills, which gives you a clearer picture of their ability to thrive in the role.
"Instead of focusing on specific experience in AI, which is currently a rapidly evolving field with few established benchmarks, HR teams should focus on identifying transferable skills in candidates. Given the limited availability of formal certifications and standards, assessing a candidate's potential becomes more important than ticking off a checklist of experience." - Geoff Newman, founder at Starget.
According to our 2023 State of Skills-Based Hiring report, 77% of hiring managers, recruiters, and senior executives agree that skills-based hiring is more effective than resumes. Moreover, 88% of employees agree that they're more likely to secure their dream job when the hiring process involves talent assessments.
For the millions of people projected to change jobs in the near future, skills-based hiring can, therefore, help improve candidate-position alignment. It can also significantly reduce mis-hires and improve ROI on hiring by getting people into jobs they love, which means they’ll stick around in longer.
Some talent assessments you can use include:
Working with generative AI
And many, many more related to data science, engineering, and development.
Additionally, you can test for:
Skills mapping is a structured approach to identifying, categorizing, and organizing the skills required within an organization or industry. It involves creating a hierarchical taxonomy or framework that classifies skills into various categories and subcategories based on company needs.
By matching the skills required for a job with an individual's skills, you can make more informed decisions about hiring, skills development, and promotion.
Skills mapping is also crucial for conducting a skills gap analysis. This helps you identify gaps in an individual's skill set when compared to the skills they need for their current or desired roles. This is valuable for creating tailored training and development plans.
To help employees do their best work – and stay engaged – you need to provide them with access to learning resources tailored to skills development needs. This might include creating opportunities for cross-departmental knowledge sharing or peer-to-peer learning.
To get the best results, tailor learning paths to each employee. Not everyone has the same training needs or learning style. This means that providing personalized learning experiences based on individual goals and skill gaps is more effective than a one-size-fits-all approach.
For example, some employees might prefer microlearning modules, while others might learn better in workshops and webinars. Talent assessments can help you determine skills development progress, spot any gaps, and determine the right training material.
Pro tip: Leadership should set an example by engaging in their own continuous learning and skill development. This can also help get everyone on board with skills-based hiring and growth and development programs.
AI continues to reshape the world of work, so you need to adapt and stay ahead of the curve by hiring talent with the right AI skills. When you do this, you can harness the full potential of AI – and retain top talent through continuous upskilling, reskilling, and learning.
When hiring, as well as hard skills related to development and engineering, you should look for the nine AI skills we've highlighted. For example, data literacy and handling, working with generative AI, fact-checking, and communicating AI concepts, among others. These help future-proof your workforce and organization.
Use skills-based hiring to hire for hard, soft, and transferable skills and to align candidates with your open roles. Skills mapping and continuous upskilling will help them stay adaptable and effective as the AI landscape evolves.
When you know which skills you need and how to test them, you can better support and develop employees – and improve job satisfaction and retention.
Hire and retain workers with key AI skills.
Skills-based hiring lets you find skilled talent that will stick around longer.
1. "Generative AI and the future of work in America." (2023). McKinsey Global Institute. Retrieved October 13, 2023. https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america
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