How to implement Artificial Intelligence in your company?

These 7 Steps Can Help Your Business Implement Artificial Intelligence.
Artificial Intelligence is playing an ever more important role in business. Every year, we see a fresh batch of executives implement AI-based solutions across both products and processes. But do you know how they do it? And if you were to try the same, would you know how to achieve the best results? By the end of this article, you will — you’ll see precisely how you can use AI to benefit your entire operation.

The data proves AI has a role in business
As is crucial with everything AI, let’s start by grounding ourselves in data. According to PwC’s report, Bot.Me: A revolutionary partnership , 67% of executives believe AI will help people and machines work together to improve operations — by combining artificial and human intelligence.
Moreover, PwC’s analysis suggests global GDP will increase by up to 14% by 2030 thanks to the ‘accelerating development and adoption of AI’— that means a $15.7 trillion boost to the economy. But what are the driving forces of such growth?
On the one hand, an increase in business productivity. On the other, an increase in consumer demand, driven by better quality and increasingly personalized AI-enhanced products.
It’s hard to deny, AI is the future of business — and sooner or later, the majority of companies will have to implement it to stay competitive.

Seven key steps to implementing AI in your business
Step 1: Understand the difference between AI and ML
If you think you want to use AI, but you’re not sure where to start, start here: by learning the difference between artificial intelligence and machine learning. The two terms are often used interchangeably, but they have subtly different applications.
Only once you understand this difference can you know which technology to use — so, we’ve given you a little head start below.
Artificial Intelligence (AI): AI refers to the ability of programmed machines (computers or robots) to “think” like people and imitate human behavior. It is often used to describe systems endowed with intellectual processes, such as self-studying and problem-solving. Systems based on AI can assimilate, analyze, and use actual facts and knowledge to obtain further information. For example, speech, voice, and image recognition all use artificial intelligence.
Machine Learning (ML): A 1959 definition coined by Arthur Samuel says, ‘machine learning is a field of study that gives computers the ability to learn without being explicitly programmed’ — and if that sounds like AI, that’s because it is. ML is a field of AI that builds on the idea that systems can learn from data, then make decisions in the absence of human participation.

Want more detail? Check our article on the key differences between AI, Data Science, Machine Learning and Big Data .

Ok… so now you know the difference between artificial intelligence and machine learning — it’s time to answer two related questions before we dive into actual implementation.

How can AI improve business effectiveness?
In truth, the answer depends on your precise needs and expectations. But we’ve summarized the main advantages in the infographic below.

Where is AI ineffective?
While AI has many strengths, it does fall short in certain circumstances. And if you want to avoid any misplaced investments, you must recognize what AI cannot — or should not — do.

Code software: Despite what Hollywood says, machines can’t program themselves. In Fred Brooks’ work, “The Mythical Man-Month” he explains that coding software involves understanding the ‘fundamental complexities of the real world’ — AI cannot do that because AI cannot understand our reality;
Generate creative content: Yes, AI can create content using data. However, it cannot be creative (by which we meanwrite imaginative prose without guidelines);
Make ethical decisions: Machines don’t have feelings. They lack a conscience.