AI to the Rescue: Overcoming a Global Talent Shortage

With technology advancing at an exponential rate, the need for qualified human resources has never been greater. But what happens when there’s a global talent shortage? Enter artificial intelligence. Artificial Intelligence has rapidly become one of the most versatile tools available, offering businesses a lifeline in times of crisis such as this talent crunch. By implementing Artificial Intelligence into their hiring processes, companies can overcome the obstacles standing in between them and the skilled workers they need.

The vast potential of Artificial Intelligence in modern business is widely recognized, yet many companies struggle to implement effective machine learning systems. The difficulty lies in striking the delicate balance between selecting the right ML model for a specific use case and executing it in a way that maximises its benefits while minimising its weaknesses. This requires a comprehensive understanding of an organisation’s needs, data sets, and goals—something that can be difficult to achieve without the right expertise and resources.

As a result, many business leaders find themselves blocked, unable to fully leverage the power of Artificial Intelligence to improve customer service, streamline administrative tasks, and unlock new insights from massive data sources. But while the path to successful Artificial Intelligence implementation may be challenging, the rewards for those who can surmount these obstacles are immense.

New research by SambaNova Systems suggests that only 18% of organisations are leveraging Artificial Intelligence at an enterprise level. With recent advancements in Artificial Intelligence technology, this number should be much higher, but many organisations are experiencing challenges in deploying Artificial Intelligence initiatives. In the UK, where 59% of IT managers report having the budget to hire additional resources for their Artificial Intelligence teams, a staggering 82% say that hiring into these teams is a significant challenge. The mismatch between budget and staff acquisition highlights the need for organisations to evolve their hiring and retention strategies to ensure they can fully incorporate the benefits of Artificial Intelligence into their business models and gain a competitive edge in their respective industries.

The skills crisis in the tech industry is not a new problem. For years, the lack of talented individuals to fill digital roles has been a matter of concern for CEOs and tech leaders. In fact, as far back as 2011, a PwC study showed that 56% of CEOs were worried about lack of talent to fit digital roles. Fast forward a decade, and it seems nothing has changed. Over 54% of tech leaders still view talent acquisition and retention as the biggest threat to business growth.

The rise of Artificial Intelligence has only compounded this problem, as the pace of change is now faster than ever before. The tech industry must find a way to bridge this skills gap in order to keep up with the demands of the digital world.

The skills crisis is exacerbated by the rapid pace of change in Artificial Intelligence models 

The world of artificial intelligence is constantly evolving, with advancements happening at a breath-taking pace. The challenge for those working in the field is how to keep their skills up to date in such a fast-moving environment. Just when you think you’ve got the hang of a particular technology or method, a new breakthrough emerges, requiring constant vigilance and adaptation. Additionally, as models become bigger and more complex, they become increasingly costly to run. This makes it harder for software engineers to train these models and keep up with the latest advancements, placing further pressure on individuals to stay ahead of the curve. Despite these challenges, the potential benefits of new Artificial Intelligence technologies are undeniable, making it a field well worth investing in.

The hottest topic in Artificial Intelligence is probably large language models (LLMs). The first Generative Pre-trained Transformer (GPT) model was launched by OpenAI in 2018 — which, as a general purpose learner, is not specifically trained to do the tasks it’s good at. The model leverages deep learning and is able to carry out tasks such as summarising text, answering questions, and generating text output — and doing so on a human-like level. The first model came out four years ago, but it only leveraged 150 million parameters (a dataset of less than a million web pages). The breakthrough for GPT and large language models came with GPT-3, which launched in 2020 and had 175 billion parameters, more than a thousand times the number of the first GPT model.

Since this first large language GPT model from OpenAI (which has significant investment from Microsoft), others have been released from Google, Meta and Aleph Alpha. It’s no coincidence that these huge tech companies are behind large LLMs: They require huge amounts of experience to train and run. GPT-3 was trained on 45 terabytes of data and likely cost millions of dollars in computing to create the model. Even the recently-released open-source LLM by BigScience, BLOOM, took the combined efforts of more than 1,000 volunteer researchers and access to the Jean Zay supercomputer near Paris.

Although the concepts are accessible, it’s much more difficult for a typical software engineer to get hands-on experience with the models because of the expense of running them.

The challenge of building a team

New research from SambaNova has highlighted the struggle facing many IT leaders in businesses today. Only one in eight teams have the necessary resources and skilled workers to deliver on what the C-suite is asking for. This leaves a shocking one in three IT leaders struggling to meet the demands placed upon them, causing much anxiety.

Meanwhile, over half of all businesses are unable to properly deliver on the C-suite’s vision with the staff they have in place. These statistics herald the need for businesses to pay more attention to staffing their IT departments in order to deliver against expectations.

IT leaders have the budget to hire, but recruitment and retention can often prove to be a hugely complex and difficult process. Technology companies aren’t in a race for hardware or resources so much as they’re in a race for the best minds. As a consequence, those minds have become a valuable resource in and of themselves.

The education landscape in the field of Artificial Intelligence is facing a predicament. Despite the growing interest in academia among researchers, universities are finding it challenging to hire faculty staff with adequate experience and training in both theory and practice of Artificial Intelligence. This is in part due to the demand for courses and the relatively short history of graduates in this new discipline, thus constricting the talent pipeline. Unfortunately, the struggle is not only faced by universities but also by individuals seeking to obtain an education in Artificial Intelligence to acquire these critical skills. The result is organisations unable to hire the AI skills they require and potential students unable to pursue their aspirations. It is now ever more crucial for organisations to seek alternative paths to achieving their AI/ML goals.

When is outstaffing the right option?

In the absence of an in-house team to develop AI solutions, companies can use outstaffing services to build and deploy their own applications. Outstaffing provides access to a curated pool of talent that already has experience working in AI, ML, and data science. By outsourcing projects or tasks, businesses don’t need to hire full-time employees, giving them the flexibility to scale up or down as needed.

Furthermore, outstaffing companies have already established a recruitment process that covers screening and interviewing candidates, ensuring that the talent hired meets the requirements of the project. This saves businesses time and resources from having to recruit and hire their own AI developers. Furthermore, since outstaffing companies are experienced in providing AI services, they can also provide valuable guidance and advice on the project.

Smaller enterprises often dream of developing top-notch AI initiatives like Google and Meta, but recognize the tremendous costs associated with such ventures. For companies looking to fast-track their own development, outsourcing has become an increasingly popular approach. By bringing in outside expertise, SMEs can implement high-quality AI models without the large up-front costs that might otherwise be required.

Outsourcing options offer an assurance of return on investment, allowing companies to focus on their core competencies while AI professionals handle the rest. Just as a freelancer can transform a start-up’s website or financials, outsourcing AI development can be the key to unlocking a company’s potential.

Ultimately, given a historic shortage of AI talent, enterprises and team leaders need to make the decisions that are right for them. The costs of going in-house and constructing your own team from the ground up, at a time when Big Tech firms like Google, Meta, and others are engaged in a tug-of-war for experienced employees, may be hugely costly and inefficient. But no two projects, or companies, are made equal, and only those with the data at their fingertips can say whether they need outside help or not.

Partner With 9NEXUS For Outstaffing Your Artificial Intelligence Needs

At 9NEXUS, we specialise in providing Artificial Intelligence and ML outstaffing services for companies of all sizes. Our experienced team is made up of experts from the fields of engineering, data science, machine learning, computer vision, natural language processing (NLP), and many others. We carefully curate our developers and match their skills to your project needs, ensuring that you get the best possible results.

Our cost-effective services are designed to accelerate your AI projects without breaking the bank. With our outstaffing services, you can access a team of highly-skilled professionals without the added expenses of onboarding and training. We understand the importance of balancing cost and efficiency, and that’s why we’re committed to helping you achieve success with your projects. Don’t let resources hold you back from realising your Artificial Intelligence goals. Contact us today to learn more about how our services can help you stay ahead of the competition.

Conclusion:

For businesses seeking to increase their focus on AI/ML initiatives, outstaffing offers a viable solution. By leveraging the expertise of an experienced team of professionals, companies can develop applications faster and with more confidence than if they were to go it alone. 9NEXUS provides access to a pool of highly-skilled developers who are ready to take on any project. Contact us today to learn more about how our outstaffing services can help you stay ahead of the competition.