Recommendations to avoid failing in the implementation of AI in the management of your business

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There are numerous AI applications in many spheres of our lives, including healthcare services. However, proper implementation of AI is necessary when dealing with health clinics. Around 78% of large corporations in Latin America already have AI programs. The problem is, 70% of adoptions and implementations of AI do not achieve the expected benefits. Let's take a look at some of the best ways and recommendations to avoid failing in the implementation of AI in the management of your business or a health clinic.

What are the main reasons for the failure of implementation of AI technologies?

When looking at some of the companies and businesses that have not properly implemented AI systems, we should take a look at the main factors that have contributed to the overall failure of the implementation of AI. So, what were the main reasons exactly? Forgetting the initial business needs and objectives, many have simply made projects merely focused on technology. This has led to poor implementation of AI.

Another problem is not enough development and very little involvement of user areas in design and testing. Furthermore, excessively large investments that are not agile and have frequent progress controls, have brought failure in the implementation of AI.

An extremely important factor is ethical and legal aspects which must be followed and respected. This is especially the case when implementing new AI technologies. When using artificial intelligence in any kind of sector, but especially healthcare, teams behind it must be particularly vigilant when it comes to sensitive topics such as hiring, evaluating, and making decisions. In short, the key reasons for the failure of implementation of AI in businesses can be:

• Forgetting the initial objective

• Not enough development

• Not following ethical and legal aspects

Which technological trends of AI are having the largest impact on companies?

Now that we have covered some of the main reasons for the failure of the implementation of AI, let's see some of the successful trends. McKinsey firm has done extensive research and found that there are some emerging trends when it comes to AI technologies. One of the most widespread trends is applied AI. According to their research, it has generated the most interest since 2018 and is the most innovative. This is mainly due to its incredible versatility and also ability to take many forms. Machine learning, natural language processing, data analytics, and pattern-based prediction capabilities make applied AI the most preferred technology.

Setting up a succesful AI pilot

To begin with, each implementation of AI needs to start with a simple question. What exactly is the business problem? Namely, for many health clinics around the world, some of the ever-lasting problems come in form of maintaining and establishing proper patient communication, waiting times, scheduling, delivery of services in remote areas, no-show patients, and also an increase in patients. Many of these issues can be tackled in different ways and with different strategies. Coming up with a proper AI implementation means focusing on the main issues at hand and seeing whether the results end up being improved or not.

In order for an AI to be scaled into a full project, the first pilot needs to perform a few basic functions related to tackling these issues and also prove statistically that it can perform in accordance with all of the ethical, moral, and legal guidelines. A team of dedicated experts who specialize in AI technology is always going to be needed when implementing AI in healthcare. Only then can this AI be properly trained and developed and in the final stages incorporated into the work ethic of a particular health clinic in this example. Since AI projects rely very heavily on data, it is essential that you ensure the right speed, volume, and variety of data when building an AI pilot.

Constant testing, improvements, and overall review is always needed before the final implementation of AI into a healthcare system. After all, the main goal of AI in health is to help both patients and health clinics but it can only be implemented properly if all of the rules and guidelines are followed and extensive research is done by the team of dedicated experts behind the AI. Once the pilot AI is ready to be tested, there are numerous ways of determining whether or not it is successful in performing its given tasks. However, a pilot must deliver the perceived measure of success in order to be given the green light for further implementation.

When the results and data show progress, showcase the capabilities of the project once it's fully implemented to customers, partners, etc. In addition to this, always integrate AI into your upstream and downstream workflows.

The value and benefit of incorporating and implementing AI into health

As mentioned several times already, AI can be extremely beneficial when implemented properly. Some of the biggest issues that the healthcare world of today faces can be significantly decreased and sometimes even completely solved with the use of new and innovative AI technologies such as machine learning and natural language processing.

It is safe to say that these two AI technologies are the most beneficial for health clinics. When combined, machine learning and natural language processing create an AI capable of performing various administrative tasks while also being able to communicate with patients in a meaningful way. Furthermore, health clinics can reach patients living in remote areas fairly easily and also not only reach them but maintain communication and deliver healthcare services to them.

As you can see, there are many ways of avoiding mistakes and failing to implement AI technologies properly. However, a certain path must be followed when dealing with AI. A team of dedicated workers who specialize in AI is always needed. Do not forget to gather all of the right data when testing your pilot AI. Development, testing, and analyzing results before final implementation is very important. Finally, always make sure that all of the moral, ethical, and legal aspects are covered.