Artificial intelligence (AI) is the most transformative tool in our fast-changing technology landscape. By now, many managers understand the importance of this cutting-edge technology, but the road to a successful implementation often proves harder than expected. To succeed, you need to know what you’re in for. So here are three crucial reality checks, shedding light on the challenges before taking the plunge into the AI sea.
Reality check #1: It takes research
Your artificial intelligence implementation doesn’t start with the push of a button. It begins way before any sensor camera, computer and software is installed or database is connected. It actually begins when you first google ‘artificial intelligence’ and look up more information about the technology.
To make your AI implementation a success, you need to know the lay of the land. What is it, how does it work, how can it help your company, how do you get started, who can help you get started…. There are a lot of questions that need answers before you can even think of installing anything AI-related. Be careful: the internet is a big place with a lot of opinions and ‘expert’ advice. Be sure to look for valuable opinions and correct advice.
This might sound like a lot of work, but the research is worth it. It will prepare you for your implementation project. You’ll have a better understanding of the technology, and you’ll be ready to push through the hard parts.
Reality check #2: It takes time
AI takes time. Don’t expect it to be up and running within one month. You need quality data, people, experimentation, you need to stop and start over and you need some more experimentation. AI is a big, long-term project. It can’t give you what you need right away — like all good things in life, it requires patience.
Take it one step at a time. Divide your project into smaller goals. Go for the quick wins first, then tackle the bigger stuff. It takes time, but in the end, you’ll make up for it in efficiency thanks to your smooth-running AI system.
Reality check #3: It takes people
You can’t just leave it up to the tech guy. You’ll need to break through the silo mentality in your organisation and get everyone involved. From legal to production: AI is the ultimate game of cooperation.
Why? Well, firstly AI needs data. And that data is everywhere in your company: marketing has some, sales has some and production has some. And they all need to share their data to feed the AI model. Secondly, AI requires different kinds of knowledge. Production management, data science, strategy, and technological skills: gather people from multiple teams for the best results. Diversity is key.
Even though it’s not easy to get people from different departments to work together, your AI system will work better thanks to their input. Their cooperation is vital to fine-tuning the AI model. It will help to better align the technology with your company’s needs.