Three pieces of advice
1. Start with the business problem – not the technology
What specific challenge facing your customers or your company are you trying to solve? AI does not solve anything on its own. It can help address the particular challenges to which it is applied. Always start with the problem, not the tool.
2. Establish clear principles for data, accountability and use
Once you start applying AI, you need clear principles governing which data is used, who is accountable and which guidelines employees should follow. It is equally important to agree on where the company is comfortable using AI – and where it should not yet be used. Without this framework, adoption becomes fragmented and risks become more difficult to identify.
3. Measure the impact before scaling
Many AI projects begin as small pilots – promising, but not yet proven. They should be scaled only once you know that they create real value. From the outset, be clear about how that value will be measured. Track the results and make sure the solution delivers a meaningful impact before committing to scaling it.