AI skills gap

There is a greater tech talent shortage across multiple industries at large. Part of the problem is the rapid advancement of artificial intelligence (AI) and the proliferation of new technologies, such as generative AI (gen AI), which are shifting the types of roles and skill requirements companies are hiring for as they continue to automate processes and services.

In 2024, AI spending will grow to over USD 550 billion, and there will be an expected AI talent gap of 50%, according to new research from Reuters.¹

AI has the potential to enhance products and services, optimize business operations and workflows, help with decision-making and automate tedious tasks. It has the potential to change the nature of work and the job market, according to a report by Deloitte. ²

However, even the most advanced AI today cannot operate without humans. Closing the AI skills gap is essential to help organizations prepare for the future of work and accelerate innovation.

Demand for AI roles is growing, as the rate of automation and technological advancements speed up. However, AI adoption remains uneven across companies. Many employees believe that the AI skill gap is an AI training gap.³

According to a 2024 Randstad survey, respondents said that companies adopting AI have been lagging in training or upskilling employees on how to use AI in their jobs. There are also gender and age divides in how well AI training adequately prepares workers.

Respondents on a separate 2024 Skillsoft survey (link resides outside ibm.com)⁵ said that the learning format in existing talent development programs is sometimes not effective, or they struggle to find time or leadership support for completing these programs.

For companies, limits in internal budgets and access to technologies, tools and data can all be impediments to AI upskilling, according to Snaplogic research.⁶

Also, some employers say they are going to use AI but fail to identify the specific ways that AI can be used, making them unsure of the exact skills that are needed to fulfill those tasks.

There exists an ecosystem of high-demand AI and related skillsets.¹ In general, organizations need AI builders and AI translators.² These include people who know how to use and deploy gen AI, predictive analytics, large language models (LLMs), natural language processing (NLP), machine learning (ML), deep learning and reinforcement learning.

Not all skills require extensive knowledge related to deploying AI. Some tasks can include more basic knowledge, for example, how to prompt-tune or fine-tune ChatGPT.

Also, employees are expected to have working knowledge of security, privacy, data science, statistics, software development, coding, models and algorithms.

In addition to AI and programming skills, some workers are expected to take management roles and work with subject experts or user experience designers. It can’t just be filling the gap from the bottom up. Senior leaders in the C-suite also need to be up to speed with the latest AI knowledge to understand what the company is working on and working toward.

Having every employee who interacts with AI-related functions learn how to code AI from end to end is often not necessary. Corporations can also consider implementing ⁷ intuitive tools that are low-code or no-code in AI projects.

The skills shortage can be bridged with investments and initiatives around skills development. Many of the problems causing an AI skills gap are the same problems causing tech talent shortages. Several solutions for closing the AI skill gap overlap with solutions for completing the tech talent shortage.

There are several online platforms that offer teachings on AI skills. For example, IBM’s SkillsBuild and Microsoft⁸ offer free resources that can help anyone start to assess and develop their AI skills.

Fostering a future-ready workforce involves strategic hiring and investing in continuous learning. Most employees are amenable to more training to acclimate them to emerging technologies.

Traditional avenues for learners such as universities, PhD programs, AI camps and online academies, can still be viable for Gen Z workers to acquire skills. Training and exposure to AI technologies and tools in school curriculums, especially for younger students, is necessary. That means that keeping trainers and teachers up to date is vital.

When onboard, internal learning opportunities such as training programs, workshops with peers, office hours or sessions to practice in sandbox environments are what will help retain valuable employees, which can decrease the time needed to vet new applicants.

To streamline hiring and make the learning process efficient, companies must first thoroughly assess the benefits and limitations of AI to their organization (PDF).²

More AI is not always better.⁹ Businesses should carefully evaluate how they have been using it in their operations in the last year, see what’s working and what’s not, and use feedback to roadmap how they want to use AI in the next few years.

Based on this, they can test the AI readiness of their current employees in those AI topics to look for gaps in skill proficiency. Depending on how specialized a company’s AI needs are, they can then choose to either bring in new AI experts to pioneer projects or reskill their available engineers to use and apply AI tools.

To help employees be engaged to reach their personal skill-building goals, employers should consider more interactive and customizable learning programs⁵ that can mix online, on-demand courses with experiential opportunities and live, instructor-led training.

Importantly, companies must help ensure that their AI training approaches and initiatives are offered equitably and are inclusive of workers from different demographics.

It is easier to solve the problem collaboratively rather than having to develop strategies and in-house learning plans from scratch. Businesses can participate in partnerships with educational institutions and other organizations to provide these offerings.