In a rush to adopt AI, the first thing companies often do, is hire a team of data scientists.

Companies often hire data scientists to discover potential AI opportunities without understanding AI or having an AI strategy in place. This bottom-up approach often fails to drive meaningful results, as many projects are better suited for publishing research papers rather than creating value for the business. Additionally, this bottom-up approach is risky.

1. Data scientists tasked with AI problem-solving may have limited understanding of the company’s business challenges, as they lack exposure to daily processes and workflow inefficiencies.
2. Data scientists often struggle to gain upper management’s support for bottom-up AI approaches, often resulting in missed opportunities and a lack of transparency about the true benefits of AI within the organization.
3. Data scientists often lack budget insight, leading to expensive or risky projects being canceled or put on hold by management teams due to lack of cost justification.

Bottom-up approach to AI can lead to poor outcomes for organization and employees, as organizations may not value AI and they may decide not to pursue it further. Additionally the data scientists may be let go or work on unrelated projects.

It doesn’t have to be this way!

Leaders and experts can discover AI opportunities by developing AI skills so as to identify opportunities for the business and involve their technical teams to support and execute their vision, and maximize results by focusing on top-down approaches.