Ready to implement AI into your business?

Written with love on by Ionela Bărbuță

Make sure your employees are also prepared

The idea of a machine that can display “intelligence” just like a human has been around for quite some time. The concept of artificial intelligence became known on a larger scale starting with the 50’s and, since then, it has had a few ups and downs. But the real progress is happening now. Nowadays, almost all areas of our lives could be enhanced with the help of AI technology and researchers never stop to amaze us with new use cases.

Disruption is inevitable and tech companies are not missing the opportunity to capitalize on what artificial intelligence has to offer. A crucial aspect in adopting AI and developing successful AI products is to have employees that understand and are prepared to address all the challenges such a change might bring.

An Accenture survey on the future workforce reveals that more than 60% of workers have a positive view regarding the impact of AI on their work. Furthermore, two-thirds acknowledge that they must develop their own skills to work with intelligent machines.

On the other hand, business leaders from larger corporations mentioned that only about one-quarter of their workforce is prepared for AI adoption. However, only 3% of business leaders are actually planning significant increases in their training budgets to meet the skills challenge posed by AI.

“Business leaders don’t think their workers are ready for AI, yet only 3 percent are reinvesting in training. ” - Accenture

Let's have a look at some of the things companies can do to prepare their employees to work with AI or build AI projects.

Shift their mindset

Even if we have gone so far with technological breakthroughs, we still don't have any idea how this will evolve in the next decades. At this point, everything related to artificial intelligence amazes us and terrifies us. We fear losing our jobs, our sense of what it means to be an individual, and we expect to wake one day and realize we need to fight the 'machine' because it wants to rule the world.

But what if we were to shift our mindset? Think of a future in which humans and machines don't try to replace each other, but work together and complement each other. With a positive perspective on the future, employees will be more willing to embrace the change and look for ways in which machine learning might improve their performance at work.

And if this idea is reinforced by the fact that you do not prioritize the AI hype over them, they will feel confident and appreciated and will work with you on making the AI integration as smooth as possible.

Photo source: Flickr

Invest in their education

Another important step in preparing your employees for the change is to invest in them. You need to identify the new skills or tools they will need to learn and give them the opportunity to pursue learning and training programs. According to the World Economic Forum, the average worker will need an extra 101 days of learning by 2022 to prepare for the introduction of AI. There should also be a skill strategy in place for how the employees will need to work with AI-powered systems.

Moreover, apart from making sure your people have the necessary qualification to understand and be able to work on an AI project, you need to consider investing in new software and technologies as well. For a successful project, you need skilled employees, but also technologies to support the implementation.

Design a strategy to include new and existing processes

Working with AI-based projects means more than software development as we know it. You might need to create new processes and redefine the existing ones. Introducing different algorithmic approaches, new data sources or any other cognitive technologies can turn out to be quite challenging if you do not have a strategy in place.

You also need to choose the direction in which you're going, what roles and which employees will be involved. In addition, it is important to make sure everyone is clear about the use cases and the value you want to achieve by applying AI.

Preparing data is as important

Although it is key that you remember people are the ones building, measuring, consuming, and determining the success of an AI product, data is the requisite asset.

“Data is the new oil.” - Clive Humb, Chief Data Scientist and Executive Director, Starcount

So, before moving on to implementing an AI project, make sure you have the answer to these questions:

  1. What kind of data are you planning to use?  It is also good to remember that the quality of data is usually more important than the quantity. Yet, depending on what your objectives are, maybe it would be better to check if it is as relevant as you need it to be. Insufficient data might lead to biased outcomes.
  2. Do you own the data? Now, this is important because it allows you to adjust it the way you need to and you can always have access to it.
  3. How do you collect and store the data?
  4. Do you have a clear process on how to prepare your business data for artificial intelligence?

Preparing data for AI is a critical component for ensuring that the accumulated data transforms into a value-added reality. Furthermore, it provides your employees with the necessary measures to tackle this new phase of their work.


Artificial intelligence is reshaping the workplace environment as well as the way we actually do our work. The adoption rate of AI technology by businesses is increasing rapidly as its use cases to improve processes and get ahead of competitors continue to unfold. Yet, as we move into the age of AI and machine learning, there are significant aspects that businesses need to consider. Defining a clear strategy, preparing the data and providing learning opportunities to employees are just a few of the things that come with adopting AI.

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Ionela Bărbuță

Written with love by Ionela Bărbuță

Ionela is an enthusiastic professional, with a proven experience in the payments and fintech industry. She likes working with people, creating things, and writing about AI, security and fraud.