Building skills for an automated, AI-driven world

A strategic overview

Advancements in artificial intelligence (AI) have triggered a major paradigm shift in business transformation. The average lifespan of a skill is now less than 5 years in some technology fields, and as low as two and a half ¹.  As a result, the skill sets of today’s knowledge workforce are rapidly becoming obsolete. Roles are being redefined, and new capabilities are emerging to support these technological changes.

Half of all current employees will require reskilling to keep pace with the rapid rise of new technologies and the emergence of generative AI (GenAI).² HR and talent management leaders are increasingly identifying skill gaps as one of the biggest barriers to effective AI adoption. An 85-million-person talent shortage is expected by 2030. This leaves business leaders facing a significant challenge: ensuring their employees are continuously upskilled or reskilled to remain competitive in today’s modern world. Ongoing geopolitical tensions, market shifts, and investor sentiment are also heightening the urgency of such skill requirements.

Business leaders’ challenges

Aligning with business strategy

Aligning reskilling initiatives with the overall business strategy is essential for their success but is often overlooked by organizations. Leaders face the significant challenge of ensuring that training programs directly support broader organizational objectives. Additionally, limited budgets and resource constraints can impact the ability to launch comprehensive and impactful training initiatives. Leaders must carefully balance immediate operational priorities with long-term strategic goals, making informed decisions about reskilling that drive sustained business growth. 

Employee mindset

Employees often resist reskilling initiatives due to fears of job displacement, as well as skepticism regarding the benefits of new technologies. Maintaining employee engagement and motivation throughout reskilling programs can be particularly difficult. To navigate these challenges, leaders must focus on cultivating a growth mindset within their teams. By tailoring training to align with individual career aspirations and offering meaningful incentives, organizations can enhance participation and commitment.

Identifying skill gaps

Many organizations face difficulties in accurately assessing employees’ skills and determining which new skills are required. Further, organizations often lack effective tools or methods to evaluate their workforce’s capabilities, resulting in ineffective training initiatives. This can lead to potential mismatches between training and actual job requirements. The World Economic Forum estimates that effective investments to close the skills gap could boost GDP by US$6.5 trillion by 2030.² These skill gaps are one of the biggest barriers to effective AI adoption.

Learning culture

Fostering a culture of continuous learning is essential for long-term organizational resilience in the current environment; however, this can be challenging due to cultural barriers within an organization. Resistance to change, fear of failure, and differing attitudes towards learning can hinder participation in reskilling programs. Organizations must embed learning into their cultural values, amplify employee voices, and integrate development into daily workflows to unlock full potential. Building a supportive environment that values and rewards learning is crucial for successfully embedding reskilling initiatives. 

Learning effectiveness

Assessing the success of reskilling initiatives presents a complex challenge for leaders. It is crucial to establish clear metrics and feedback mechanisms to assess the impact of training on performance and productivity. Additionally, employees often struggle to balance their current responsibilities with learning new skills, which can compromise overall learning effectiveness. 

Strategic imperatives

Fostering a growth mindset culture

Transforming skills requires shifting mindsets, culture, and processes, not just running a training course.³ A company’s business model must integrate human capabilities with AI and create a “war for talent” mindset. This shift can cultivate a culture that embraces continuous learning and innovation, while promoting a growth mindset by sharing success stories and encouraging experimentation. At the same time, organizational culture should facilitate collaboration across departments to enhance knowledge sharing and allow employees to acquire diverse skills, fostering adaptability in a rapidly changing environment. Instead of asking, ‘’How do we give new learners access to our company?”, a better forward-thinking question would be, “How can we equip ourselves to access new talent?’’.

Leadership development and mentorship programs

“I’m overloaded” is one of the most frequently cited barriers preventing managerial participation in training. To address this problem, organizations must invest in leadership training focused on change management and fostering a learning culture. Establishing mentorship programs that pair experienced employees with those seeking to develop new skills can be very effective. This approach prepares leaders to champion reskilling initiatives while providing personalized guidance to employees navigating their career development. A growing number of leading organizations have already recognized this shift. 

Amazon, for example, offers a variety of mentoring programs for reskilled employees, such as the “Grow Our Own Talent”⁵ program, which the company connects with employees and provides career coaching. 

Skills assessments and leveraging technology 

AI-driven learning management systems can support the assessment of employee capabilities by using digital tools to identify skill gaps and tailor training programs. This creates personalized learning experiences that align with individual career goals and emerging organizational needs, ensuring that training is relevant and effective. Having the right tools empowers people to excel in their craft. Organizations should also emphasize fusion skills, skills at the intersection of human and machine capabilities,1 which go beyond purely technical expertise. These include effectively interacting with AI tools, applying human expertise, and supporting employees to work effectively with AI systems. 

Work-based learning opportunities

The 70:20:10 learning model emphasizes learning on the job through real-life experiences and tasks through problem-solving activities, storytelling workshops, and regular feedback sessions.⁴ Individuals who are curious, emotionally intelligent, and resilient are better equipped to learn and provide value that technology cannot replace. Work-based learning opportunities, such as job rotations and project assignments, reinforce skills in real-world contexts and promote practical application aligned with career paths. Further, cohort-based learning sessions have emerged with higher engagement and completion rates in today’s learning environments. 

Educational collaborations

Building partnerships with universities and educational institutions to design relevant training programs, co-create curriculum that meet industry demands, and offer internships are highly required. These partnerships help ensure a steady pipeline of talent equipped with the skills necessary to succeed in an evolving job market. Cross-company and cross-industry collaboration, supported by ecosystem thinking and partnerships, often proves more effective than siloed efforts.³ The concept of digital academies can further help close digital skills gaps and make a significant contribution to workforce developments.

“AI fluency is key to connecting today’s knowledge to tomorrow’s roles. Using AI as a collaboration tool, individuals boost effectiveness, resolve complex problems faster, and preserve their relevance in an ever-changing digital environment.” - Bhavna Lakhani, Partner, Audit & Assurance - IT, Data & Analytics.

The pathway forward 

AI is a tool based on historical data, but the real future competitive advantage is with the human mind, human critical thinking, and human decision intelligence. As AI becomes increasingly integrated into organizational operations, business leaders must adopt a strategic approach to reskilling and upskilling to ensure their workforce remains competitive in an AI-driven landscape. Prioritizing adaptability, engagement, and alignment with business objectives will be key to success.

While AI is displacing some jobs, it is also creating many new roles that require human skills. Reskilling allows organizations to build competitive advantage ahead of their competitors. Soft skills such as creativity, adaptability, ethical awareness, and change management capability are becoming increasingly valuable, helping humans complement AI rather than compete with it. 

Ultimately, business leaders and individuals must identify the necessary upskilling and reskilling requirements to remain competitive in an increasingly uncertain and fast-paced world.

By Zahi Zeini, Partner and Nandana Kalubowila, Senior Manager, External Audit, Deloitte Middle East

Endnotes:

1. https://www.harvardbusiness.org/insight/march-2025-the-leaders-agenda-the-ai-imperative-strategy-adoption-and-upskilling-for-the-future.
2. https://www.weforum.org/publications/the-future-of-jobs-report-2020/.
3. https://d3.harvard.edu/reskilling-in-the-age-of-ai/.
4. https://www.researchgate.net/publication/316610452_THE_702010_MODEL_FOR_LEARNING_AND_DEVELOPMENT_AN_EFFECTIVE_MODEL_FOR_CAPABILITY_DEVELOPMENT.
5. https://www.amazon.jobs/content/en/teams/amazon-web-services/grow-our-own-talent.