• Written by Muhammed Abdulla NC, CEO

A chief operating officer sits at her desk, staring at a spreadsheet that is supposed to inform her decisions, but is instead a jumbled mess of numbers and unclear categories, and she wonders how AI could help her make sense of it all, but she knows that before she can even think about implementing such a system, she needs to get her data in order, which is why she is considering creating an AI checklist for executive leadership.

Connected data is crucial

The data that must be connected includes all relevant sources that executive leadership uses to inform their decisions, such as financial reports, customer feedback, and operational metrics, and without this connected data, the AI system will not be able to provide accurate or helpful insights, and will likely lead to more confusion and misinformation, which is why it is so important to have all data sources integrated and compatible before implementing an AI system.

For example, a chief financial officer checks the latest financial reports, but the data is scattered across different systems and departments, making it difficult to get a clear picture of the company's financial health, and this is where an AI system could help, by connecting all the relevant data sources and providing a unified view of the company's financial situation, but only if the data is properly connected and integrated.

Definitions must be agreed upon

Before implementing an AI system, it is essential to agree on definitions for key terms and concepts, such as what constitutes a "customer" or a "sale", and this must be done in writing, to avoid any confusion or misunderstandings down the line, and to ensure that everyone is on the same page, and this is especially important for executive leadership, who need to be able to trust the insights and recommendations provided by the AI system.

This may seem like a trivial matter, but it is surprising how often different departments and teams within an organization have different understandings of the same terms, and this can lead to confusion and errors, which can have serious consequences, and this is why it is so important to take the time to agree on definitions and ensure that everyone is using the same language.

Permissions must be decided in advance

Another crucial aspect of preparing for an AI system is deciding on permissions and access controls, to ensure that sensitive data is only accessible to authorized personnel, and this must be done before anyone starts using the system, to avoid any potential security breaches or data leaks, and this is especially important for executive leadership, who have access to sensitive and confidential information.

Most people get wrong the idea that permissions and access controls can be decided on the fly, as needed, but this is a mistake, as it can lead to confusion and errors, and potentially even security breaches, and it is much better to take the time to decide on permissions and access controls in advance, and to ensure that everyone understands their role and responsibilities.

A first question worth answering

A good first question to ask an AI system is one that executive leadership already waits on, such as "what are the key drivers of our revenue growth" or "which customers are most at risk of churn", and this will help to build trust and confidence in the system, and to demonstrate its value and potential, and it will also help to identify areas where the system needs to be improved or refined, and for more information on how AI can support executive leadership, see our page on executive and strategic leadership.

For example, a category manager compares two suppliers, and wants to know which one is more likely to meet the company's needs, and this is a question that an AI system could help to answer, by analyzing data on the suppliers' past performance, and providing a recommendation based on that analysis, and this could save the category manager a significant amount of time and effort, and help to ensure that the company is getting the best possible value from its suppliers.

When AI is not the answer

Finally, it is worth recognizing that AI is not always the answer, and there are times when it is the wrong choice, such as when the problem is too complex or nuanced, or when the data is too limited or unreliable, and in these cases, it is better to rely on human judgment and expertise, rather than trying to force an AI system to provide a solution, and for help in determining whether AI is right for your organization, see our page on contact us.

This is a mistake that many organizations make, trying to use AI to solve every problem, without stopping to consider whether it is the right tool for the job, and this can lead to wasted time and resources, and potentially even to errors or mistakes, and it is much better to take a more nuanced and thoughtful approach, and to consider carefully whether AI is the right solution for the problem at hand.