The current landscape in the United States reveals an imminent challenge: a notable shortage of skills in artificial intelligence (AI) and machine learning that poses a significant threat to productivity and innovation. A recent report titled “How to Solve the Data Science Skills Shortage,” conducted by SAS, a prominent analytics leader, sheds light on this issue. The study involved decision-makers from various sectors, including banking, insurance, government, and retail, outlining the critical need for urgent action to tackle the AI skills crisis.
Projections by Fortune Business Insights anticipate the global AI market to skyrocket from $387 billion in 2022 to almost $1.4 trillion by 2029. The survey indicates that 43% of respondents view AI and machine learning as primary investment priorities over the next one to two years, surpassing other data technology areas like data visualization, data analytics, and big data.
However, amidst these ambitious investment plans, a striking concern emerges: 63% of respondents highlight their most substantial skills gaps in AI and machine learning. This shortage of expertise could potentially render increased investments in AI futile, resulting in financial setbacks and missed opportunities for innovation.
Addressing the Skills Gap: Challenges and Strategies
The report reveals various challenges faced by organizations aiming to bridge this skills gap. While 75% of respondents intend to train and upskill their existing workforce, 64% consider recruiting new talent. Nevertheless, barriers such as time constraints, motivational factors, and concerns about retaining skilled personnel hinder these efforts.
Moreover, escalating salary expectations in the AI field pose a significant challenge for companies, potentially leading to increased costs for recruitment and contracting. The average pay for a data scientist in the US currently stands at around $122,000, creating sustainability concerns for many organizations.
Shifting Focus in Talent Acquisition
An evolving trend among companies involves reconsidering strict educational requirements. The report echoes findings from an April study by Indeed, where 67% of large companies expressed willingness to drop degree prerequisites. Respondents in the SAS survey emphasize the importance of collaborating with academic institutions but acknowledge that solely relying on graduates may not swiftly fill the skills void. Instead, they prioritize factors like case studies, project work, relevant training, industry certifications, hackathons, and problem-solving abilities over traditional degrees when evaluating potential hires.
Recommendations to Bridge the Gap
Dr. Sally Eaves, an AI expert and contributor to the report, emphasizes the necessity of multifaceted approaches to address the skills shortage. The report delineates three recommendations:
- Streamline AI and analytics tools to enhance productivity and encourage end-user engagement while enabling data scientists to focus on core tasks.
- Promote upskilling and cross-skilling within the existing workforce, including individuals from non-technical backgrounds, through diverse certifications and training courses.
- Foster a learning culture that encourages skill development, encompassing online courses, hackathons, and in-house data science academies.
Dr. Eaves emphasizes the importance of a combined strategy involving mid-career training, tool empowerment, and community growth to narrow the skills gap, potentially fostering a more robust talent pool that benefits individuals, organizations, and the broader economy.
Conclusion
The urgency to address the AI skills gap is paramount, as outlined by the SAS report. Employing diverse strategies that combine training, tool enhancement, and cultural shifts within organizations can potentially mitigate the growing shortage of AI and machine learning skills. Such initiatives may pave the way for a more skilled workforce, driving innovation and productivity in an increasingly AI-driven landscape.
For organizations seeking to bolster their analytics capabilities, SAS offers solutions to enhance skills and gain a competitive edge.
Methodology and About SAS
The survey conducted by SAS involved 72 decision-makers from US-based organizations across multiple sectors and was part of a broader global research effort. These organizations typically employed over 1,000 individuals, with some having more than 100,000 employees. The survey targeted individuals in technical roles, including data science and analytics, as well as those in HR and talent management. Coleman Parkes facilitated the survey in the US, UK, and Ireland.
SAS stands as a frontrunner in analytics, empowering customers worldwide to transform data into actionable insights and intelligence, providing them with “THE POWER TO KNOW®.”
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