Perspectives

Becoming an AI-enabled, skills-based organization

The potential of AI in the workforce

Today, every leader is searching for proven AI solutions that deliver value. In talent and workforce experience, AI is emerging as a catalyst to becoming a skills-based organization. Learn how combining AI and skills-based approaches can revolutionize your talent acquisition strategy, boost worker satisfaction and build a future-ready organization.

The growth of the skills-based organization

Traditionally organizations have been structured around jobs, but with workplace flexibility growing in importance, a paradigm shift is underway. Organizations are moving away from job-centric structures towards a skills-focused approach, which allows them to tap into the full range of workers’ capabilities to achieve desired outcomes. The skills-based organization: A new operating model for work and the workforce found that skills-based organizations are 79% more likely to provide a positive workforce experience and 63% more likely to achieve results. More specifically, a skills-based focus improves talent placement, retains high performers, and reduces the number of mis-hires.

Becoming an AI-enabled, skills-based organization

AI-enabled + skills-based = exponential results

In using AI to transform talent acquisition and support a skills-based approach, organizations can expect time savings and productivity boosts. However, organizations that integrate both AI and skills-based approaches stand to gain even more. They'll be able to predict talent gaps, align talent with skills more effectively, and uncover new opportunities in the talent market. This includes the ability to quickly adjust to organizational and talent changes, reduce bias in recruiting and matching, and increase worker retention and satisfaction.

Visualizing the skills-based organization

To operationalize the shift to a skills-based approach, it is helpful to visualize a hub-and-spoke model. The “skills hub”—the engine powering the model—contains the following components:

  • Talent philosophy: A shared approach across the organization regarding the value and prioritization of skills as the “red thread” of talent management—and how they will inform key talent decisions.
  • Skills framework and common language: A common language and framework for skills— including human and specialized skills—across the organization.
  • Data and technology enablers: A single source of truth regarding skills data—and a common integrated suite of tools that identify evolving skill needs, evaluate skill levels, match skill supply and demand, and develop and grow abilities.
  • Governance: A clear understanding of skills “ownership” across the enterprise, along with the structures and processes to enable a skills-based approach and drive change management efforts.

After the skills hub is established, those skills are then integrated into “spoke” components such as talent acquisition, learning and development, and workforce planning to predict and inform business decisions.

 

How AI enables a skills-based transformation

Triangle in a dotted circle

From: Sourcing talent to meet minimum qualifications for a role (e.g., education, relevant job experience).

To: AI-enabled, intelligent sourcing of talent focused on human capabilities, functional and technical skills, and behaviors.

Outcome: Recruiters have deep insights on applicant quality and diversity to expedite hiring and widen the candidate pool.

Dotted circluar maze

From: Forecasting the required headcount needed for the future.

To: AI has the ability to specifically predict the skills and work that will be needed in the future.

Outcome: HR and leaders across the organization are empowered to make more strategic decisions around talent.

Security lock

From: A mismatch of talent supply and organizational business demand.

To: AI allows the organization to dynamically match skills with work, ensuring a balance of talent supply and demand.

Outcome: Enhanced opportunities for employees to explore open projects, full-time positions, and new experiences.

Dotted circles

From: Learning based on jobs, tracking through a learning management system, and disconnected career growth opportunities.

To: AI recommends targeted learning, development, and reskilling opportunities based on skills.

Outcome: Employees are able to identify future roles or opportunities and access a learning ecosystem of training, projects, and mentors to get there.

Circuit in a circle

From: A singular, linear career path.

To: AI-powered suggestions of career paths and opportunities anywhere in the organization.

Outcome: Flexibility for employees to enable a culture of internal mobility.

Creating AI-enabled, human-friendly processes

In most cases, determining where humans should fit within AI-driven business processes is not a simple plug-and-play. The most successful organizations adopt a human-centered approach, seamlessly integrating AI in the workforce and delivering value by embedding technology into their core business processes.

However, AI should not replace human involvement in the talent process. Instead, organizations can focus on building an integrated technology landscape with AI capabilities. This allows them to harness skills data effectively, informing talent transformation and enhancing worker experience. This leaves humans free to focus on areas where they excel, such as critical thinking and creative problem-solving.

The AI-fueled roadmap to transformation

Organizations embarking on an AI-enabled, skills-based transformation should take an experience-led approach. By first understanding the practices, routines, and challenges of their current employees, organizations can then make informed decisions that enhance rather than limit experiences.

To get started, organizations should:

  • Apply a human-centered approach to integrating AI in the workforce: Thoroughly understand current talent experiences and identify opportunities for automation and AI.
  • Thoughtfully plan and design the end-to-end process, making strategic decisions about human involvement at each stage.
  • Define a skills taxonomy: This will be foundational to implementing AI-fueled, skills-based processes.
  • Identify the capabilities needed to enhance workforce experiences and processes, then evaluate existing or new technological solutions that can meet these needs.
  • Select a pilot process or workforce segment to implement changes, using worker experience to measure the success of changes and gather employee feedback for iteration and scaling.
  • Garner leadership buy-in: Leveraging AI in talent acquisition and retention is an enterprise-wide opportunity. Strong leadership alignment and support can significantly impact the success of your transformation journey.

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Get in touch

Amelia Dunlop

Chief Experience Officer

Deloitte Digital

amdunlop@deloitte.com

Kristin Starodub

Principal

Deloitte Consulting LLP

kstarodub@deloitte.com

Roni Gottesdlener

Senior Manager

Deloitte Consulting LLP

rogrant@deloitte.com

Andrea Wilp

Manager

Deloitte Consulting LLP

awilp@deloitte.com

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