Companies are being forced to make tough hiring choices due to AI.

• With the growth of artificial intelligence capabilities, executives are faced with a significant choice: Should they invest in training their current teams or hire external experts to kick-start their AI projects?
• Hakan Kardes, chief experience officer at Alignment Health, asserts that there are significant benefits to utilizing external consultants during the early stages of AI implementation.
• Despite 90% of technology leaders planning to implement AI initiatives this year, 41% of them are hindered by a shortage of staff with AI skills and expertise.

With the growth of artificial intelligence capabilities, executives are faced with a significant choice: Should they invest in training their current teams or hire external experts to kick-start their AI projects?

The global AI consulting market is projected to reach $72.5 billion by 2025, with a compound annual growth rate of 40.3% from 2020 to 2027, and 63% of enterprises planning to increase their AI investments in the coming year. However, Hakan Kardes, chief experience officer at Alignment Health, emphasizes that there isn't a one-size-fits-all solution.

External consultants can provide immediate access to specialized skills and knowledge, which are crucial for accelerating critical projects and exploring new technologies, according to him.

Kardes argues that the challenge is to integrate external expertise with the internal team to prevent long-term dependency. Although upskilling can embed AI expertise within an organization for the long term, it requires a significant investment of time, resources, and commitment, which not all companies can afford.

Stephen Boyer, co-founder and chief innovation officer at cyber risk management firm Bitsight, remarks that while it may be tempting to hire PwC due to their experience in the field, in this specific case, no one has been working on generative AI for a decade. Although machine learning and other aspects of AI have been around for a long time, generative AI is relatively new.

"Addressing the lack of experience in the market was crucial," he said. "We needed to hire talent, but it was too expensive. Unless you were an AI expert at Meta or Google, you weren't considered for the foundational work. However, we knew we had to find a solution."

Instead of seeking external AI consultants, he established an internal "tiger team" to explore AI possibilities.

"Boyer stated that the team aimed to achieve a "quick win" by recognizing their lack of necessary skills but committing to investing in the development of those skills. To achieve this, they assigned two engineers to the task and utilized Boyer's time, with the goal of learning, building relationships, and conducting experiments to determine if they could deliver the desired outcome."

Gen AI results

Bitsight's AI experiment aimed to automate a labor-intensive task by leveraging generative AI to process vast amounts of cybersecurity articles produced daily across multiple languages. The team was able to teach AI to read, analyze, and identify key details from articles with accuracy. According to Boyer, the approach yielded impressive results, with the AI being highly reliable and agreeing with what a human would say about 90% of the time. Although only a year in, Boyer says the team learned what worked, what didn't, and what they could rely on. Now, he's pushing that capability out to the rest of the organization by embedding the people who are doing the experiments into the teams that are doing the development. Boyer says this experiment has made the company more confident and better equipped to develop a roadmap for future AI initiatives.

Boyer emphasized the enthusiasm his team felt while exploring AI technology. "Our engineers were thrilled by the challenge," he stated. "Watching them develop new skills and apply their creativity to the project was as fulfilling as achieving the desired results."

Boyer emphasized that governance and risk management are essential components of the strategy to maintain control over data and AI models. He stated, "We wanted to ensure we had the right access controls, prevent data leaks, and avoid unintentionally exposing ourselves to risk."

To prevent inaccurate information from appearing as correct, we employed a cautious approach when managing risks such as hallucinations with AI.

Alignment Health, like Boyer and Kardes, invested in its internal expertise to develop its AI capabilities. The health insurance company has been committed to building its AI capabilities over the years, starting with the development of a proprietary data technology platform, AVA, a decade ago. Today, the company has more than 200 AI models embedded in various applications and workflows, driving innovations in senior care.

A hybrid work approach

Not all companies have the resources to develop a strong internal technical foundation like Bitsight and Alignment Health.

A survey conducted by Robert Half's technology practice director, Ryan Sutton, revealed that 90% of technology leaders plan to implement AI initiatives this year, but 41% of them cited a shortage of staff with AI skills and expertise.

Sutton advised companies to adopt a hybrid approach to address the skills gaps identified in AI, machine learning, data science, and technology process automation. He emphasized the importance of ensuring that consultants not only provide the specific skills or experience required but also enhance and support the overall health of the workflow.