5 rules of thumb for successful AI projects" or "5 aspects of all successful AI projects
Artificial intelligence has come to the forefront in recent years as many businesses have started to recognise its value and unrivalled potential for innovation. Rapid advances in artificial intelligence are already having a profound impact on our everyday lives in the form of automation that lends itself to taking care of mundane tasks to predictive analytics that has changed the healthcare, fintech and retail industry to name just a few. Accepting and adapting to the future of artificial intelligence is imperative for the continuous growth and development of innovation in almost every industry so in light of this we have put together a list of ‘5 Rules of AI’ for companies to consider that are looking to explore and implement artificial intelligence into their business processes.
1) Always start with a well-defined objective
Because of the current nature of AI or ‘Narrow AI’ as it's called, it is important to set a well-defined objective. Narrow AI pulls information from a specific data set meaning they perform the single task they are designed to perform . For this reason, a well-established objective is vital to ensure your successful deployment of artificial intelligence. A good place to start is to consider your business current challenges and opportunities. This information will then be useful to inform your business priorities with greater clarity. The outcome of this research stage should leave you with a clearly defined scope of the business objectives. This stage of the process should not be overlooked and is in fact one of the key stages in deploying AI. Lack of clarity or absence of a clear business challenge or objective can result in project failure later down the line.
2) The importance of data
Data is one of the key factors in implementing any artificial intelligence project. Without sufficient, well-defined data the scope of what AI can achieve is limited. For this reason, it is imperative for companies to have a data infrastructure in place to ensure that their data is coherent, useful and makes sense. This may require companies to build in data aggregation and consolidation into their implementation process. AI needs full visibility of data in order to recognise the bigger picture and make data driven recommendations and predictions, with this being said the importance of ensuring your business data is readily available and accurate should not be overlooked. Failure to recognise the importance of data early on could be detrimental to the overall outcome as accurate predictions rely on accurate data.
3) Consider off-the-shelf solutions vs. building bespoke
Not all companies are at the stage where they can just automatically decide to implement artificial intelligence into their business process at the drop of a hat. Deploying artificial intelligence requires a lot of consideration and planning and big changes usually need to take place internally with regards to data infrastructure. Some businesses just don't have the capacity to facilitate these changes. For this reason, I would recommend companies to consider building a bespoke artificial intelligence solution rather than buying an off-the-shelf one, which often take just as much or even more work to adopt. Building a bespoke AI system allows your company to work closely with data scientists to create a product that works with your current infrastructure.
4) Assess and accept risk as part of the AI journey
It goes without saying that with any sizable investment comes risk. Implementing artificial intelligence is no mean feat and requires dedicated leadership that accurately assess the risks involved. It is necessary to critically evaluate results during every stage of the implementation process which is what Brainpool’s scoping programme is designed to do. Starting with smaller initiative's and projects will help you understand your risk factors and enable you to make better decisions going forward based on the data set that each trial will emit. Accepting early on that this is just part of the journey will make it easier to manage expectations and stick with it even when results may be slower than expected.
5) Understand and adapt to the changes of AI on people
This point is particularly important for business leaders as being able to understand and adapt to the changes that AI will have on your workforce will also be a crucial aspect of the testing and evaluation stage. Understanding the organisational changes that need to take place will allow your business to run more efficiently. For example, implementing AI to take over mundane tasks will free up time for your workforce to complete more importance duties and take over a more creative role. Or perhaps your company needs to invest in some training and development for your employees to ensure that they are well versed on the new technology? Whatever the case may be is it important not to forget about the impact this new technology may have on your workforce so that you can plan in advance for any initiative's that may need to take place for this transition to be a smooth process for everyone.
As more and more companies are seeking out and deploying AI initiative's there is no better time to consider the benefits it would offer yours! If you are interested in learning more about AI and how it could benefit you feel free to reach out to us here at Brainpool for a free consultation about its potential to transform your business.
Written by Alana Finnerty
 Medium. (2018). "Distinguishing between Narrow AI, General AI and Super AI" Retrieved from: https://medium.com/mapping-out-2050/distinguishing-between-narrow-ai-general-ai-and-super-ai-a4bc44172e22