If your business wants to get ahead and find new, innovative ways to engage with your customers and employees, AI could be a key to successful business transformation.
New businesses are adopting AI systems every year, but they are not always going to be successful – as this all lies in the implementation.
Whether you’re implementing AI, or a new process, setting a clear framework to guide you through the process is an important step if you want the new technology to be embraced by your whole team.
If you want to achieve the best results possible, we’ll take you through some of the most important steps that you should take when implementing AI systems into your business.
1. The differences between AI and ML
AI can be a gray area to many employees and customers, especially if you’re an early adopter in your industry and people aren’t aware of how beneficial AI can be.
There is also a lot of confusion over the difference between AI and ML (machine learning) which can confuse some people who are being introduced to it for the first time.
According to an AI explainability framework, where you educate and support stakeholders through the AI implementation process, you should seek to explain the difference between these two processes.
Machine learning is the process that’s used to describe how a computer develops intelligence whereas artificial intelligence (AI) is the way that a computer thinks like a human and performs tasks by itself – using the machine learning it has developed by performing similar tasks repetitively.
2. The importance of implementing an AI Explainability Framework
Like any new technology or process you’re bringing into your business, you need your employees to buy into the new process if you want it to be successful.
If your employees don’t understand or realise the benefits of new AI systems, it’s unlikely that they will fully embrace the changes and make the most out of the latest technology.
This is why it’s so important to have an AI explainability framework in place; a guide to easing the process of implementation, and making AI more accessible and understandable to everyone who’s interacting with your business.
AI explainability frameworks are different for every business and can be tailored to fit your specific business needs and requirements – regardless of the industry or sector that your business is operating in.
Through this framework, you’ll be able to clearly and succinctly communicate to stakeholders what the new AI systems are, how they are going to work, and how much of an impact they will have on everyday tasks and processes.
3. Defining how AI can benefit your business in your sector
Most people are resistant to change and, when they hear that tasks are going to be taken on by a computer, their initial response may be to push back on proposed changes in fear of losing their job or responsibilities.
In most cases, AI is implemented to aid your employees and customers, not put them out of a job. But, if you don’t communicate this clearly to your employees, they may be distrustful and defensive against these new processes.
When you’re implementing new AI into your business operations, you need to be clear with your staff that the new systems are ultimately going to be beneficial and help them in their daily tasks – not create more problems for them.
Ideally, you want your stakeholders to trust the new AI systems and work together with it to help boost your business’s profits and productivity – which they can only do once they understand the benefits and how they can work together with them.
4. The importance of a Data Protection Officer
All businesses handle a lot of data, and one important part of AI explainability is making sure that you’re compliant with regulations like GDPR.
To be fully compliant, you should ensure that there is one person who is responsible for keeping track of consent, personal information, and filing information in a way that it’s easily accessible and manageable.
A Data Protection Officer is the person who will be given this responsibility and is an important figure in your entire AI transformation process. You can designate this role to someone who is already in your business, alternatively, you could hire a new employee or outsource this work to another business.
5. Ensure there are no learned or programmed biases
One of the benefits of AI is that it has none of the biases that humans unconsciously have. For example, during the hiring process, it can be hard for your HR representative to be completely bias-free during interviews.
But, a machine is not human and can look through processes with an objective view that is completely free of any learned or programmed biases – as long as you implement it properly.