Want a Career in AI? Domain Expertise Is Key to Success

While skills in artificial intelligence and data analytics are in high demand, they alone won’t guarantee business success. Domain expertise—deep knowledge in a specific industry or subject matter—is increasingly crucial for professionals aspiring to succeed in AI-related careers. This is the message from Tendü Yogurtçu, PhD, Chief Technology Officer at Precisely, who advocates for a balanced skill set that combines AI with industry-specific knowledge.

The Role of Domain Expertise in AI

In a recent interview, Yogurtçu emphasized that while AI is a powerful tool, it requires domain experts to ensure its trustworthiness and accuracy. She explained that AI models, whether large or small, must be paired with deep industry knowledge to provide meaningful and reliable results. For example, in the insurance industry, understanding property boundaries and location data is essential to accurately assessing risk and pricing policies. In healthcare, AI must be complemented by medical expertise to deliver valuable insights and support clinical decision-making.

Combining AI with Business and Technical Skills

Yogurtçu’s insights align with those of other industry leaders, such as Junaid Saiyed, CTO at Alation. Saiyed highlighted the importance of having humans in the loop to verify AI-generated outputs, preventing biased results or misunderstandings. He advocates for a “Machine Suggested, Human Verified” approach, where domain experts oversee and adjust AI decisions as needed.

This blend of AI skills and domain-specific knowledge is not only vital for AI’s effectiveness but also for ensuring transparency and accountability within organizations. According to Saiyed, AI governance processes should allow for continuous improvement and offer mechanisms for employees to raise concerns about AI-driven decisions.

Preparing for AI-Driven Reinvention

Consulting firm Accenture recently underscored the importance of domain expertise in AI-driven business transformation. Their analysis emphasized the need for organizations to adopt a domain-centric approach to data modernization, where data governance is centralized and employees understand how to work with data effectively. Accenture recommends building dynamic project teams that can rotate between projects as strategic needs evolve, allowing for greater flexibility and innovation.

Accenture also highlights the importance of reshaping the workforce to align with evolving business needs in the age of AI. This includes offering comprehensive training to help workers maximize the benefits of generative AI and implementing AI systems that support both customers and employees.

What This Means for AI Careers

For professionals looking to work with AI, developing domain-specific expertise alongside technical skills is becoming a key differentiator in the job market. Whether in healthcare, finance, manufacturing, or any other field, businesses are seeking individuals who can blend business knowledge with AI capabilities to drive meaningful outcomes. As AI continues to shape industries, a holistic approach that combines technical proficiency with deep industry understanding will be essential to delivering trusted AI solutions.