10 Key Data Points You Must Know Before Embarking on an Automation and AI Project

11 May 2023 · 3 min read

An automation or AI project promises improved efficiency, higher productivity and real cost saving, but it is not without its challenges, and understanding the right information up front is what makes the difference to the outcome. These are the ten pieces of data to have in hand before you begin.

1. Project objectives. Be clear on why you are doing this and what you hope to achieve, with goals that are specific, measurable, achievable, relevant and time-bound.
2. Current process. To automate a process or apply AI to it, you need to understand it thoroughly: what tasks are done, how, by whom and how often, documented so it can be seen.
3. Data availability and quality. AI thrives on data, so know what you have, where it is stored, how it is formatted, and whether there are privacy or security concerns attached.
4. Technological infrastructure. Assess whether the current systems can integrate new technology, and whether hardware, software or connectivity need upgrading.
5. Business readiness. These technologies change how a business operates, so gauge the team's proficiency, their attitude to the change and the organisation's ability to adapt.
6. Budget. Know the constraints, including the technology, any infrastructure upgrades, training, and ongoing maintenance and support.
7. Potential risks. Identify them early, from data-privacy breaches and technology failure to employee resistance and cost overruns, so they can be mitigated.
8. Regulatory compliance. Depending on the industry, specific rules may apply, from data protection to the ethics of AI use, and knowing them early prevents costly issues later.
9. Project timeline. Build a realistic schedule that accounts for implementation, training and integration, and for the learning curve these projects carry.
10. Expected return. Understand the return you expect in cost saving, productivity and efficiency, taking both the direct and indirect costs and benefits into account.

An automation or AI project is a significant investment, and understanding these data points is what equips you to launch one that actually delivers. Start with clear objectives, understand your current processes and readiness, secure the data and infrastructure, stay mindful of budget, timeline, risk and compliance, and keep the expected return as the measure of success.