The AI Talent War

AI is now a massive competitive advantage and not merely one of many new intelligence tools. The main obstacle blocking the adoption of AI is talent, not technology. According to McKinsey & Company, approximately 50 per cent of businesses use AI, but only a small fraction have been able to scale their usage due to a lack of qualified talent. LinkedIn reports that individuals working in AI have some of the fastest growth rates worldwide and that these positions are seeing significant growth.

This gap between job openings for those who possess AI knowledge and the number of individuals possessing that knowledge has created an AI talent war and forced companies to decide which option is best for them when it comes to developing AI resources through three routes for acquiring talent: building talent internally, buying talent through external hiring, or borrowing talent through consulting firms.

The overall complexity of the situation prevents companies from analytically determining whether to build, buy, or borrow AI talent. When organisations use a strict either-or methodology, they increase their risk of failing or falling behind in the competitive landscape. The real opportunity for success will be for organisations to leverage all three avenues of talent acquisition into a cohesive, combined strategy.

Build: The Only Sustainable Advantage

Sustainable advantages can only be achieved through the establishment of internal AI talent pipelines. Upskilling to build AI talent internally is the first and best strategy for achieving long-term success. As current employees have already acquired domain expertise and familiarity with the organisation’s mission, culture, and objectives, they possess the critical pieces needed to turn AI from a concept into an impactful reality.

Companies such as Amazon and AT&T have taken note and invested heavily in their employees’ upskilling. For example, Amazon has committed over $1.2 billion to reskilling efforts, and AT&T has made significant investments in workforce transformation programmes. They both recognise that building internal capabilities to develop an organisation’s AI capabilities, rather than laterally sourcing them, is critical; their focus on employee development will lead to long-term retention of reskilled employees, thereby contributing to the organisation’s long-term value.

Developing new AI talent is a time-consuming process. For example, developing an individual to be an accomplished machine-learning practitioner or data engineer is not a quick process, and not every individual will be capable of making that transition. In a rapidly changing, competitive environment, you may miss opportunities if you wait until you have developed enough internal talent before leveraging it. While building your own internal talent pipeline is critical, the need to move quickly creates an urgency that cannot be ignored.

Buy: Speed with Structural Risk

Bringing on board AI talent from a talent pool can yield immediate returns by enabling the organisation to add established professionals quickly, which is important in sectors where time to market is a competitive advantage.

Companies such as Microsoft and Google have pursued this option aggressively, offering lucrative compensation packages to attract and retain high-quality employees. In India, salaries for data scientists are rising sharply due to high demand for employees with that expertise, highlighting the shortage of qualified talent in the market.

This talent acquisition strategy has its own risks. For example, acquiring talent may be expensive due to high salaries and/or high turnover rates, which may result in limited long-term returns; frequent turnover of employees means the organisation continually experiences difficulty in integrating new hires into a team; and reliance on external hires results in placing knowledge with one employee as opposed to within the organisation, which increases risk. Organisations that rely heavily on talent procurement may find themselves in a revolving door of inflated salary costs, without building sustainable capability.

Borrow: Agility without Ownership

Companies get agility by accessing talent through consulting firms, technology platforms, and partnerships. This means companies can test different ideas, build quickly, and get expert input without a long-term commitment.

For example, companies use partners such as Accenture or platforms such as Amazon Web Services to build AI-based solutions quickly and cost-effectively. This allows companies new to building AI solutions to get to market more quickly and spend less money upfront.

However, by borrowing talent, companies give up some of their control. Reliance on external partners reduces companies’ ability to build internal capacity and creates other risks, such as vendor dependency and data security issues. Companies that lack internal expertise may find it difficult to evaluate or modify solutions they have borrowed and will likely lose their competitive advantage.

Competing in the AI Talent War: Orchestrate, Don’t Choose

One mistake many organisations make when following a technology sourcing strategy is treating the three options — build, buy, and borrow — as alternatives when, in fact, they should be viewed as complementary. Each option provides different solutions to the same problem: capacity, speed, and flexibility.

To develop an effective sourcing strategy, each option should be clearly defined:

Build: Develop the company’s fundamental, enterprise-level AI capacity.

Buy: Acquire or attract the capabilities, expertise, and acceleration for the company.

Borrow: Prototype, grow, and access niche skills.

Organisations that leverage all three options in a coordinated manner achieve greater success than organisations that use only one of the options. Netflix demonstrates a balanced approach to sourcing by leveraging a strong internal data science team and augmenting its capabilities through selective hiring and cloud vendor partnerships to improve the performance of its recommendation engine, which is critical to both user engagement and retention.

The Winning Combination

The AI talent war is not about merely accessing talent; it’s about controlling capability. Building ensures sustainability, buying speeds up processes, and borrowing offers flexibility. However, none of these approaches alone is enough.

Firms that will excel in the AI-driven economy will move beyond “build, buy, or borrow”. They will master integrating all three approaches. In a landscape marked by talent scarcity, the true competitive edge will not go to the organisation that hires the most talent but to the one that combines it most effectively.

The main obstacle blocking the adoption of AI is talent, not technology

The real opportunity for success will be for organisations to leverage all three avenues of talent acquisition into a cohesive strategy