Displacement or demand: The jobs AI could create

Ethics and communication

As AI becomes more involved in decision-making, companies are beginning to realize the need for ethical oversight. In this case, the position of an AI ethics consultant is likely to appear. These specialists would study how AI systems make decisions and comply with accepted specifications and legal norms. Their responsibilities may include identifying bias, ensuring fairness, and providing these recommendations to teams working with AI. They also provide support for communication with regulators, management, and even the courts if required. In turn, AI communicators could help explain AI in a way that is understandable to non-technical staff, helping organizations use such tools more effectively and strategically.

Audit and accountability

Given the growing complexity of AI, many companies may want to employ AI analysts to understand what systems do and why. Analysts would be tasked with evaluating model behavior, monitoring decision-making, and produce documentation useful for audits. This role would help companies to improve transparency and meet the requirements.

In addition, human coordination analysts could become specialists in areas where AI works alongside humans. Coordinators would establish the parameters of algorithmic accountability and decide when human supervision is necessary, which might be crucial in industries like government services or insurance.

Implementation and execution

AI's business potential increases the demand for additional positions in coordination and planning. Companies may be able to identify areas where AI could improve operations with the assistance of AI executive architects. Their tasks could involve infrastructure design, consistency management, and process flow analysis.

In turn, the task of integrating tools into functional systems might fall to AI automation engineers. Connecting artificial models to the IT infrastructure and guaranteeing reliable performance would be the primary responsibility. When combined, such roles would help a business transition from AI exploration to long-term use.

Training and maintenance

To ensure that AI models last over time, they need to be continually refined. AI training managers could take the lead in providing the systems with new, relevant data and aligning their responses with the organization’s organizations. They could also monitor the performance of models and adjust training methods based on error rates or changing conditions.

Additionally, AI diagnosticians will likely focus on systemic issues. When an AI model stops working as expected or produces unexpected results, these specialists will explain the cause of the failure. They may inject internal logic, behavior patterns, or data patterns. These roles together help maintain AI as a constantly improving system rather than a static tool.

Behavior and performance

As AI begins to interact directly with customers and users, its tone and language become part of the company’s brand. AI behavior coordinators could generally engage the AI’s speech behavior, choosing whether it should be very friendly, formal, or expressive. Their work would focus on the creation of a consistent and reliable user experience.

In addition, AI model performance analysts played a role in selecting and maintaining the optimal tools for different use cases. They tested different models, measured their accuracy and efficiency, and identified violations of errors or hallucinations. Based on such an analysis, they might advise companies on which systems to deploy and when.

Earlier, Kazinform reported that one of the practical uses of AI is already being implemented by the Indonesian government.