As organizations lean more into artificial intelligence (AI) and machine learning (ML), they are confronting a significant skills gap among IT professionals. A Skillsoft report, which surveyed over 5,100 global IT decision-makers, highlighted that although AI and ML are highly sought-after skills, they are often lacking within existing teams, which raises concerns among decision-makers eager to rectify this imbalance.

Leadership development is also on the rise, with 58% of companies currently implementing formal programs and 28% planning for future investments in training. Cybersecurity remains a challenging field, with 38% of respondents pointing out difficulties in filling these critical roles. Moreover, nearly two-thirds of decision-makers admit to skill deficiencies within their teams.

In response, 72% of organizations aim to enhance training for their current workforce, and 94% of leaders see tangible benefits from these training initiatives. The primary motivations for IT professionals to upskill include the desire to acquire new knowledge (54%), competitive job positioning (53%), and securing their job roles (46%).

Skillsoft’s CIO, Orla Daly, emphasizes the importance of a well-rounded approach to bridge the AI and ML skills gap, recommending tailored learning paths for specific roles, alongside foundational learning opportunities. She urges that a culture of continuous learning be established within organizations, ensuring that all staff can maximize the new technologies and understand their impact responsibly.

Kayne McGladrey, an IEEE senior member, stresses the critical need for AI ethics skills, which can help organizations navigate biases and maintain public trust in AI applications. Training in AI ethics can guide personnel in developing systems that adhere to ethical societal standards.

To effectively close the AI skills gap, Yaad Oren, managing director of SAP Labs U.S., suggests fostering a culture of continuous learning that integrates technical and soft skills development. This can be achieved through focused training programs and a partnership with research institutions to enhance educational offerings specific to AI.

Daniel Avancini, chief data officer at Indicium, advocates for assessing AI/ML competency across departments to tailor training accordingly, with an emphasis on practical applications through sandbox environments where teams can experiment with AI tools safely.

Scott Wheeler from Asperitas highlights the importance of innovation culture, promoting access to flexible learning platforms and incorporating mentorship into projects to provide real-time, applicable training.

As organizations maneuver through the technological landscape of 2025 and beyond, building a well-rounded talent pool equipped with the necessary AI and ML skills is crucial for maximizing the integration and responsible use of these transformative technologies.

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