Preparing the Workforce for an AI-Native Future

As AI becomes more prevalent within the workplace, businesses are seeking to invest in greater talent and training initiatives to stay ahead.

However, whilst remaining competitive is important, adopting AI technologies too hastily can lead to risks such as cybersecurity data breaches, higher costs and growing skills gap among staff.

AI Magazine speaks with Clyde Seepersad, SVP and General Manager, Training & Certification, at the Linux Foundation, about business AI adoption. He explains his “purposeful but patient” AI ethos - how taking the time to understand AI and best practices for the technology will create more sustainable, effective and responsible AI in the long-term.

Please tell us about your role at the Linux Foundation and the work you do with AI.

At the Linux Foundation, I oversee the Training and Certification program. My team and I are dedicated to helping individuals discover, train on, and achieve certification in collaboratively developed technologies, typically those under an open-source licence. 

For AI, our focus is on establishing a foundational understanding of AI's capabilities and limitations, particularly in the realm of Generative AI (Gen AI).

Our AI and Machine Learning training programs span from fundamentals to advanced applications. We cover essential topics such as deep learning, neural networks, and data science, ensuring learners can implement AI solutions in their respective fields. Our approach combines theoretical knowledge with practical, hands-on labs to provide a thorough understanding and application of the concepts taught. 

These programs are designed for a wide range of skill levels, from beginners to advanced practitioners, and include certifications that validate their expertise. 

What are the most significant AI trends currently, and how are they impacting businesses?

The current AI landscape is marked by a strong push across industries to integrate AI technologies, even in sectors that have traditionally been slow to adopt new technologies.

The pressure is intense and is driven by AI's potential to revolutionise various business processes, such as paralegal research or summarising market news, which have proven to be strong use cases. However, the technology still faces significant challenges in more complex applications like self-driving vehicles and critical health and safety scenarios.

Companies face difficult choices about where to place their AI bets and how fast they should move. They must balance the potential benefits against the limitations and current state of AI technology to make informed decisions about AI implementation and investment. Part of the challenge of evaluating and implementing AI solutions is ensuring that talent is available in your organisation. 

Our 2024 State of Tech Talent survey shows that AI/ML is a priority skill for 48% of organisations. Additionally, 98% of organisations consider upskilling a critical strategy, with 48% prioritising upskilling or cross-skilling existing staff over hiring new employees or consultants. Organisations like Linux Foundation Training and Certification play a role in providing trusted training and certification programs.

Concerning AI, how do you see the technology impacting hiring and staffing?

Our research shows that nearly half of technical employers are prioritising hiring employees with AI/ML skills. Businesses implementing AI/ML solutions need talent to make it possible. This comes from both hiring and upskilling/cross-skilling. I don’t see the demand for these skills slowing down any time soon. 

At the same time, some positions might be reduced as AI systems become more capable of handling these tasks. The net effect will depend on how quickly and effectively AI technologies can be integrated into existing workflows and processes. The jury is still out on whether the hallucination problems can be sufficiently mitigated to allow staffing efficiencies in areas where AI has promise, like security monitoring, network configuration, and cloud cost management.

Another angle is how it will change what our jobs look like. Work will change. New tasks will be automated which will free up professionals to devote time to developing new skills and to pursue creativity and innovation. As this evolves, we will see new jobs we can’t envision now. 

How do you see technology certifications becoming more important in the future AI business landscape?

As with previous waves of technological adoption, having core skills in-house will continue to be a critical factor for success in the AI business landscape. AI will require decisions on data usage, model selection, and the appropriate mix of human judgement and AI-driven decision-making. As these new roles emerge, the need for validated skills will become more pronounced.

The Linux Foundation’s 2024 State of Tech Talent report shows that technical certifications are now more important than college degrees in demonstrating skills to employers. Most of the AI skills needed today are not taught in school. Certifications ensure that professionals remain up-to-date with AI advancements and best practices, enabling organisations to maintain a competitive edge in this rapidly evolving field.

How is the Linux Foundation fostering responsible AI collaboration?

The Linux Foundation, through initiatives like LF AI & Data and open-source, vendor-neutral projects like PyTorch, is at the forefront of fostering responsible AI collaboration. 

LF AI & Data is dedicated to building and supporting an open AI community, promoting collaboration, and developing AI standards and best practices. By offering a wide range of training programs and fostering an open-source ecosystem, the Linux Foundation ensures that AI technologies are developed and used responsibly.

PyTorch, a popular deep-learning framework, is a key part of our portfolio. It enables developers to quickly prototype and deploy AI applications, emphasising practical applications like computer vision and natural language processing. It is open source and housed at the Linux Foundation, so it is vendor-neutral. 

This collaboration helps promote the ethical use of AI by providing robust tools and frameworks for responsible AI development.

How can businesses best prepare for the future of AI development?

The pressure to adopt AI quickly should not overshadow the importance of making informed decisions about where AI can provide the most value and how best to integrate it into existing operations. 

Businesses should approach AI development strategically, prioritising readiness and careful planning over a hasty implementation. They should focus on high-level strategic decisions about their AI goals and interests, ensuring they clearly understand the potential risks and rewards.

A systematic approach emphasising readiness, careful planning, and strategic alignment will help businesses navigate the complexities of AI development and avoid the pitfalls of a "move fast and break things" mindset. 

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