Human-machine learning loop ensures human feedback and judgement
According to Gartner, building an AI-driven finance organization for the future requires a combination of technical and business skills that many finance teams currently lack. During the Gartner CFO & Finance Executive Conference, analysts discussed the importance of incorporating new AI-focused roles and skill sets into finance teams and highlighted best practices for using AI in finance.
Gartner predicts that finance and accounting teams will resemble software development organizations in the future, and finance leaders should start embracing this shift. They identified three high-priority roles that will be crucial in future finance teams:
- Citizen Data Scientists: These are current finance and accounting staff who will acquire basic data science skills to automate tasks and make better decisions. However, they may require assistance in building more complex solutions beyond their immediate scope of work.
- Centre of Excellence: This role is new to the organization and consists of technical professionals who can develop and maintain technically robust AI solutions. It includes professional data scientists, software engineers, data engineers, statisticians, and other non-traditional finance roles. The Centre of Excellence often starts with a single data scientist and grows as demand increases.
- Company Leadership: Building the finance teams of the future requires leaders who can balance introducing new skills and processes while ensuring ongoing support for daily business operations.
To effectively leverage AI, Gartner suggests establishing a human-machine learning loop where people and AI technology work collaboratively. This partnership capitalizes on the strengths of both parties and avoids over-reliance on machines or delegating human responsibilities to AI. The human-machine learning loop ensures that human feedback and judgment remain central to decision-making processes.
Gartner advises using AI to automate manual tasks while being cautious about allowing machines to take actions solely based on their own advice. By leveraging the strengths of both humans and AI, organizations can achieve increased productivity and value while minimizing risks.
