Learning by doing is a great thing unless it’s costing you money, then it may not seem worth it. In the business world when new technologies come around it may be tempting to take a “wait and see” approach to them, watching your competitors’ successes and failures before taking the time to implement new technologies. Unfortunately when it comes to artificial intelligence (AI), the potential payoff is too big to ignore, and waiting to see how your competitors do implementing this technology could leave your business in the dust.
Taking the right steps toward implementing AI is crucial. Some companies know that they need to hire a data scientist but they don’t know what they expect the person to do and they will try to hire someone with no framework or plan in place.
The first step toward integrating artificial intelligence into your business strategy is to take it seriously and make a plan for how it will work. Start with an end goal in mind and work your way back from there. Next, figure out exactly what AI application will help you achieve that goal. With that in mind, start a pilot program with a targeted goal, keeping in mind that it could take a year or more to see any results from such a program.
While going through the growing pains of implementing an enterprise-wide system of AI, it may seem as though this technology is a huge waste of time and money. Learning by doing is a valuable way to understand the ins and outs of any new technology, and even if your company’s experiment fails you can still gain valuable insights from failures. These insights can help you find a better focus for your next artificial intelligence experiment.
Currently, fewer than a third of AI pilots progress past the exploratory state to be fully implemented. This does not mean failure, though, it simply means the hypothesis needs to be adjusted before the experiment is altered and started again from the beginning. As with any new technology, there are going to be growing pains and opportunities to learn more.
Artificial intelligence can be used in many different ways. Some people use AI algorithms to parse an actionable conclusion from massive amounts of data in a way that humans aren’t able to do without computer help. Others use machine learning to control tedious processes that human operators can easily tune out over time.
This can translate to many different outcomes. AI algorithms can be used to reduce waste and improve quality by removing unnecessary variables. It can help meet rising demand and cut variable costs through analysis. It can make adjustments and predict when the market will shift. Some examples from real businesses:
Today, more than 60% of business leaders urgently need to find and implement a strategy for using artificial intelligence in their businesses, but less than half of those actually have a plan. Learn more about implementing AI in your business below.
Read next: The Future Of Artificial Intelligence In Retail
Taking the right steps toward implementing AI is crucial. Some companies know that they need to hire a data scientist but they don’t know what they expect the person to do and they will try to hire someone with no framework or plan in place.
The first step toward integrating artificial intelligence into your business strategy is to take it seriously and make a plan for how it will work. Start with an end goal in mind and work your way back from there. Next, figure out exactly what AI application will help you achieve that goal. With that in mind, start a pilot program with a targeted goal, keeping in mind that it could take a year or more to see any results from such a program.
While going through the growing pains of implementing an enterprise-wide system of AI, it may seem as though this technology is a huge waste of time and money. Learning by doing is a valuable way to understand the ins and outs of any new technology, and even if your company’s experiment fails you can still gain valuable insights from failures. These insights can help you find a better focus for your next artificial intelligence experiment.
Currently, fewer than a third of AI pilots progress past the exploratory state to be fully implemented. This does not mean failure, though, it simply means the hypothesis needs to be adjusted before the experiment is altered and started again from the beginning. As with any new technology, there are going to be growing pains and opportunities to learn more.
Artificial intelligence can be used in many different ways. Some people use AI algorithms to parse an actionable conclusion from massive amounts of data in a way that humans aren’t able to do without computer help. Others use machine learning to control tedious processes that human operators can easily tune out over time.
This can translate to many different outcomes. AI algorithms can be used to reduce waste and improve quality by removing unnecessary variables. It can help meet rising demand and cut variable costs through analysis. It can make adjustments and predict when the market will shift. Some examples from real businesses:
- One automotive supplier reduced scrap by 50% using AI to monitor work quality
- Big River Steel uses AI to produce precision products, maximizing production
- Transplace used AI to make market predictions and saved $21 million in 3 years
Today, more than 60% of business leaders urgently need to find and implement a strategy for using artificial intelligence in their businesses, but less than half of those actually have a plan. Learn more about implementing AI in your business below.
Read next: The Future Of Artificial Intelligence In Retail