Leveraging Generative AI to Efficiently Utilize Skills Data: McKinsey & Company’s Yelena Mammadova, Ed.D

Yelena Mammadova, Ed.D, the Associate Director of Learning at McKinsey, focuses on accelerating talent development through a unique approach. She discusses the integration of generative AI into their skills initiatives, using it to effectively gather and utilize skills data. Discover more about their innovative use of AI in this conversation.

According to Yelena Mammadova, Ed.D—the Associate Director of Learning, Skills Transformation Initiative at McKinsey—McKinsey seeks to bring impact to clients and create an organization where they attract, excite, and retain exceptional people. 

The primary goal of her department is to accelerate talent development. Yelena strives to connect human development and technology in her role. She is one our first guests who’s talked about generative AI and how it’s embedded into their skills effort. They’re using AI to connect and map skills information. 

Secondly, they’re integrating skills with their people analytics teams. They’re starting small and experimenting. Most organizations build skills models around the job architecture currently in place. McKinsey is taking a different approach. They’re developing assessments for skills so they know how to organize the people around the work they have. 

Learn more about their unique approach and their utilization of generative AI to father and efficiently utilize skills data in this conversation. 

What is a skills-based organization?

Yelena aligns with the World Economic Forum’s definition of a skills-based organization: It is a new talent management approach that emphasizes a person’s skills and competencies. It’s an approach that moves away from the emphasis on degrees, job histories, and job titles. 

McKinsey’s firm values individual distinctiveness. So their talent management practices are built to support a culture of development. By doing this, they’re creating a personalized growth journey where development happens in different forms. Skills are the anchor of the journey. 

Yelena believes the pivot to a skills-first organization will unlock opportunities from access, equity, and development & growth standpoints. Focusing on skills creates equity in an organization. 

How McKinsey gathers and assesses skills data

Yelena notes that data can come from a variety of sources but the challenge is making the data truly usable. In the context of recruiting, they seek to unlock hidden talent pools. So they look at the skills data necessary to achieve a goal. They prioritize capturing declared and inferred skills from resumes and utilize technology to do so. 

Why? Because skills can be matched with job requirements to extend beyond the positions a candidate may have initially applied to. When they can gather relevant skills data, they can map candidates to the right roles, reducing talent leakage long-term.

Skills data also helps them enhance how their individuals and teams impact their clients. They assign individuals to the right projects to optimize impact. Doing this properly relies heavily on skills data, which requires a comprehensive data set. A comprehensive skill profile of an individual tackles this use case. 

What’s different about what they’re doing now? According to Yelena, it’s their decision framework. They use three groups of defined skills data. The application depends on the nature of the decisions and the skill. For high-stakes decisions such as hiring, their primary focus is whether or not the candidate possesses the necessary skills for the job. 

When it comes to staffing, they’ll evaluate whether or not the individual has sufficient expertise in the relevant area to be effective. They can rely on observed, declared, or inferred skills. It’s expanding the understanding and categorization of skill data and how to apply it to certain use cases with a different decision-making framework. 

Using generative AI to generate skills assessments

Assessing skills is a difficult task. That’s why McKinsey is using generative AI capabilities to augment and accelerate their internal skills development process. They use generative AI to create skill assessments that will give the expert a starting point to validate that the assessment questions are correct. 

They’re using internal knowledge to create the skill assessment quizzes (using AI models trained on those knowledge sources). Their system also gives the candidate access to the data to understand where they’re at in their skills development journey. Personalized content can then be offered to bridge any gap. 

Generative AI is something that offers better, faster, and cheaper solutions to the same problems we’ve had. AI automates work to free up time for people to apply in areas where AI can’t be utilized. Yelena emphasizes that technology is an enabler but they will always remain people-driven. 

Resources & People Mentioned

• Become part of the RedThread community
• Putting Skills First: A Framework for Action
• The Good Enough Job: Reclaiming Life from Work

Connect with Yelena Mammadova

• McKinsey & Company
• Connect on LinkedIn

Want full access to the episode's transcript? Join our RTR membership. Listen to our top episodes, explore cutting-edge research, attend exclusive member-only events, and share with a top-notch cohort community of industry leaders and peers. Take it for a spin!