AI is transforming the workforce. The following paper focuses on the impacts to talent development and recaps the research and innovative approaches companies are using to increase the new and necessary skills and competencies required.
The demand and supply gap for AI talent
As we know, AI and machine learning skills are among the most in-demand skills across industries, but the supply of qualified professionals is extremely limited. This creates a talent crunch and a competitive advantage for organizations that can attract and retain AI talent.
The conundrum of build, buy, and borrow (or partner as McKinsey puts it) is not a new one to HR. There are several models and recommendations for HR in closing the demand and supply gap. Below is one example of a build/buy/borrow decision making model for illustrative purposes.
However, with the AI talent gap, the speed of recruiting, developing, or identifying partners has been rapidly accelerated and is parallel to the speed of technology change itself. Ultimately, a hybrid approach that combines the benefits of retaining and developing current talent with the infusion of new skills and perspectives from external hires may be the most effective. This approach allows for the most balanced and strategic implementation of AI capabilities within the company.
The key competencies and strategies for AI talent development
AI talent development requires a mix of technical, soft, and business skills to fulfill the future needs of an organization looking to compete in the AI space.
It’s crucial for organizations to assess their investment in development strategies while simultaneously identifying the necessary skills and jobs. This approach enables the integration of specific skills into predetermined development strategies, thus avoiding unnecessary delays. Below are three solutions which are effective, fast, and right sized for F5.
Solution 1: Identify employees with adjacent skills and develop a reskilling learning program
Beginning with a skills inventory of current employees, which can be accomplished in Workday, identification, and selection of employees to enroll in a reskilling program through Coursera or Pluralsight which F5 currently has unused licenses to consider distributing (not managed by HR).
Sample Reskilling Program – 6 months in length
Solution 2: Create an AI boot camp to build our own talent pipeline
To attract and develop a diverse pool of talent for AI roles, F5 would design and launch an AI boot camp that offers intensive training with no programming experience required. The boot camp would aim to equip the participants with the foundational skills and knowledge needed to pursue a career in AI at F5 specifically, such as programming, data science, machine learning, and AI ethics combined with an introduction to our current products. The bootcamp would conclude with a capstone project which could feasibly provide F5 with usable work products and use of the applied learning to determine candidates’ employment prospects at F5.
Sample AI Bootcamp Curriculum
The AI boot camp curriculum consists of four modules, each lasting six weeks and covering a different aspect of AI. The modules are as follows:
The boot camp concludes with a capstone project, in which participants work in teams to design and develop an AI solution for a specific business challenge or opportunity at F5. The project involves applying the skills and knowledge acquired throughout the boot camp, as well as conducting research, prototyping, testing, and presenting the solution. The project serves as both a showcase of the participants’ abilities and a potential source of innovation and value for F5.
Solution 3: Social Learning
One of the benefits of social learning is that it can help the company to easily upskill its employees in practical ways, without requiring a lot of resources or formal training. Social learning can include mentoring, group projects such as hackathons, and other collaborative activities that allow employees to share their knowledge, experience, and insights with each other. Social learning can also foster a culture of innovation, curiosity, and community, which are essential for AI adoption and implementation.
Example: Redhat Uses mentoring to close the skills gap
In 2018, Red Hat standardized its existing mentoring initiatives and made its programs more inclusive and accessible to everyone in the organization and focused on upskilling employees.
People were matched based on the competencies they wanted to develop and utilizing the matching feature from withing their mentoring management software. Their mentoring cycles ran for 6 months with specific upskilling goal to be accomplished.
Results
Red Hat enjoyed the fruit of its thoughtful labors across multiple areas, including retention, employee development, program satisfaction, and program ROI.
- After expanding its mentoring program beyond the pilot, the company experienced a 63% decrease in employee turnover among program participants. This equates to a 96% retention rate for this group.
- After parsing its program data, the company discovered that 40% of its program participants had some type of intra-company job movement. Amazingly, 60% of those movements were promotions. The promotion rate for participants was 2x that of the non-participants within the company.
- Red Hat examined its program and relationship satisfaction, revealing a 92% satisfaction rating among mentors and mentees.
- Red Hat followed a cohort of mentoring program participants for just over 28 months to gather data on ROI. The result? A retention benefit of $6,000,000 with a 107x ROI compared to the cost of creating and operating its mentoring programs.
Red Hat’s results speak specifically to how social learning and upskilling work in tandem. Employees who engage in mentoring relationships that matter to them and learn directly from internal experts grow personally and professionally. This helps maintain and expand company culture and boost productivity, even within companies like Red Hat that continue to champion remote and hybrid work flexibility.
Cognitive and social/emotional skills matter
Within the AI industry, soft skills hold significant value. Yet, these qualities are difficult to quantify due to a lack of unified definitions and consistent terms. The following is a meta-analysis from ten recognized sources that have discussed the relevance of soft skills in the current AI landscape and the prevalence of specific skills cited.
Areas not explored in this paper are the AI-related skills needed by functions such as sales, services, marketing, etc.
Learning Solutions Available at F5 beginning Q4FY24
The culture and talent development team identified key areas to focus on for the needed transformation within F5, taking into consideration the afore-referenced soft skills specifically. In FY24, we laid the groundwork by seeking out partners and programs that will contribute to shaping the future of learning and cultural involvement at F5. The endeavors included rebalancing resources by removing dependencies on vendors and processes that served us in the past, and to utilize funding for efforts in alignment with the future. All without compromising any existing programs and offerings. The below represents the additional offerings to be made available in the coming months and supports the development of F5 into a company with AI capabilities at its core.
– Skills Coach: This is a feature in Culture Amp that helps employees identify their strengths and areas for improvement in various soft skills, such as communication, teamwork, leadership, and creativity. The coach provides personalized feedback, tips, and recommendations based on the employee’s responses to surveys and quizzes.
– eLearning courses: Available through the Culture Amp partnership, these training courses cover a wide range of topics related to soft skills, such as innovation, emotional intelligence, inclusion, and problem-solving. The courses are interactive and engaging, and they allow employees to learn at their own pace and convenience.
– Training templates: This enables us to create and share customized training modules for soft skills. We have used the templates feature to design training that matches our specific needs and goals. These training modules are made available through the Cornerstone LMS (LearnF5) where reporting on individual progress is recorded.
– Simulations Based training: This simulates real-world situations and challenges that require the application of soft skills. The process includes giving feedback and guidance to the learners as they navigate the scenarios and interact with virtual characters, thus helping the learners to practice and improve their soft skills in a safe and realistic environment.
– 360 and team effectiveness assessments: Included in the Culture Amp partnership are tools that enable us to collect and review feedback from multiple sources, such as peers, managers, customers, and self. The surveys help us to gain a comprehensive and balanced view of our soft skills and how they affect our work outcomes and relationships. They also help us identify and address any gaps or issues in our team dynamics and collaboration.
– Mentoring tool: This is a program platform that facilitates connections with other employees who can provide personalized advice and guidance to accelerate and support development. The newly implemented tool has improved usability from what was utilized in the past, including enhanced matching capabilities. In addition to helping us grow, the program also helps us to expand our network and gain valuable insights and feedback from different perspectives.
Skills inventorying as a needed component
Skills inventorying is the process of identifying and documenting the current and desired levels of skills needed for each role and employee. While this can help us to align our learning objectives and strategies, it can also be time-consuming and subjective.
But without skills inventorying, how will we know our skills gaps? One approach would be to model your skills inventorying practices after proven methods such as inventory management in retail.
In retail, inventory management is the process of ensuring that there is enough supply to meet customer demand, while minimizing costs and waste. Inventory management best practices include forecasting demand, optimizing inventory levels, tracking inventory performance, and managing inventory turnover.
Similarly, skills inventorying can help us to align our skills supply with our skills demand, while avoiding skills shortages or surpluses. Skills inventorying best practices include:
– Forecasting skills demand: We need to anticipate the future skills needs of our organization, and plan accordingly. We can use data and insights from skills committees comprised of internal employees who are experts in the jobs. We can also utilize external research in partnerships like Aon and i4CP to identify the skills that will be in high demand in the near and long term. This work should include the identification of lesser needed or obsolete skills.
– Optimizing skills levels: We need to ensure that we have the right level of skills for each role and employee, based on their current and expected tasks and responsibilities. It’s incumbent upon us to triangulate this information rather than use one source of truth (such as self-evaluation) to ensure accuracy. Examples of sources to be considered are skills assessments, 360 feedback assessments, and past projects.
– Managing skills turnover: We need to maintain and update our skills inventory regularly, as skills change and evolve over time. Utilizing recognition, rewards, and incentives is a great way to motivate employees to participate in keeping the skills inventory up to date.
Skills inventorying is a necessary component of a skills identification and development program but would need to balance long term scalability with utility and resources required.
Next steps
We are in good company as other organizations are working toward innovative solutions to identify and obtain the necessary skills in a highly competitive market. F5 has begun the necessary foundational components to shift focus to becoming an AI and SaaS led organization but will require continued focus and commitment to fully transform the organization. As 2018 McKinsey report on AI concluded: “Our most important takeaway is that companies need to act quickly. Those that make big bets now and overhaul their traditional strategies will emerge as the winners.”
Sources:
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Microsoft copilot was used in the refinement and design of this paper
