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December 12, 2023

Closing the skills gap: How to build an AI strategy that works for your startup

Adoption of AI is spreading, but without the right workplace learning strategies, companies run the risk of wasting their money

Tom Ritchie

4 min read

As artificial intelligence (AI) continues to proliferate, companies of all sizes will need to acquire key competencies and skills to develop their own products — and leverage new applications to increase efficiency. 

However, new research into the sentiment of business leaders and senior IT professionals based in the US and UK, conducted by technology skills development leader Pluralsight, shows that many organisations aren’t ready to benefit from AI. 

While the vast majority of IT professionals feel they have the right competencies to leverage AI in their day-to-day jobs (81%), very few have regular experience of using the technology (12%). This is leading to a skills gap within organisations. 

You're almost starting from ground zero. Startups that can invest quickly in the right training programme will benefit greatly.

“The AI skills gap is definitely the biggest challenge for organisations,” says Aaron Skonnard, CEO and cofounder of Pluralsight. “This happens when technology moves faster than people can actually acquire the skills. AI is probably moving faster than any technology we’ve ever seen.” 

Typically, startups would address such an issue through hiring, says Skonnard. However, with so much demand for experienced AI talent across all sectors, fledgling companies likely won’t have the budgets to attract the best candidates. 

“There just aren't that many people out there that actually have these skills. It's so new and created by such a small number of people, there just aren’t many options,” he says. “You're almost starting from ground zero. Startups that can invest quickly in the right training programme will benefit greatly.”

Closing the skills gap through learning

Michelle Keim, Pluralsight’s vice president for data science and machine learning, says upskilling over hiring is always desirable practice for lots of good reasons, whether it's in AI or otherwise.

“Internal mobility creates more engaged employees. It also results in quicker time to value, and lower costs when compared to hiring,” she says. 

Where early-stage startups may feel at a disadvantage in terms of budget and access to the large datasets they’ll need to leverage AI to its full potential, they can set themselves up for future success through implementation of skills strategy. Just two in five organisations have implemented an AI-specific learning programme, according to Pluralsight’s data. 

“Even with a small number of resources, you can’t turn a blind eye to it,” says Keim. “In small organisations with a limited number of humans with the ability to take advantage of AI, being nimble can actually be pretty tractable.”


There are certain fundamental competencies that all startups should look to gain when it comes to AI. 

You need what I call an AI IQ. That’s the ability to know what to choose to solve the problem that you have at hand

Skonnard says a base level of aptitude in prompt creation and engineering for GenAI, general AI fluency and a knowledge of the different benefits and downsides of disparate large language models (LLMs) for different business use cases should be present throughout all levels of an organisation. 

“Even the CEO should be leveraging GenAI in their role, all the executives, every team member,” he says. 


Keim stresses the importance of basic data literacy, an understanding of key principles of AI and machine learning (ML), and the development of soft skills like problem-solving. 

“It's helpful for really anyone in this day and age to just have foundational data knowledge skills. At a minimum, you should have the ability to evaluate the types of opportunities that are out there,” she says. “You need what I call an AI IQ. That’s the ability to know what to choose to solve the problem that you have at hand.”

The need to develop soft skills reinforces the need to view learning as a key element of a startup’s AI journey. 

“There's a tremendous need, no matter what our roles are, to be operating with a learner's mindset,” says Keim. “Organisations that are embracing that and reinforcing that culture or even with above and beyond the intention are going to get that return on investment.” 

This should act as a warning for many business leaders out there, as Pluralsight’s data shows that 80% of executives report spending on new technology without considering the training needed to maximise its usage. 

Where to start

While the opportunity is there, many startups won’t necessarily know where to begin. 

Skonnard says the breadth of learning content available today on technology skills greatly exceeds that of 10 years ago, which can lead to paralysis and no guarantee of quality learning outcomes. Not only that, the technology is moving at a pace that can leave recently produced playbooks obsolete. 

To combat this, Pluralsight offers customers the ability to tailor their learning programmes to the specific needs of their staff. It also measures staff proficiency in key areas of learning, making sure that programmes are delivering on the business’s key outcomes. 

This measurement is achieved through learners obtaining industry-recognised certifications and typical platform engagement metrics. Skonnard says Pluralsight works closely with clients to establish and track key KPIs that marry learning opportunities with the business’s goals.

“We have purpose-built content and we have this measurement and guidance capability to measure the result,” says Skonnard. “If you can't measure if the learning is actually working, you’re just running in circles.”