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Skills needed for successful AI deployment

Kiara Miller by Kiara Miller
May 17, 2022
in Technology
Reading Time: 5 mins read
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Skills needed for successful AI deployment

Artificial intelligence has evolved into one of the most awe-inspiring technologies in recent years. Gradually, this powerful technology has made an enormous place in the business world. Majority of the leading businesses have investments in AI technologies. But, less deploy AI capabilities in their work. This is because AI deployment is a huge challenge. The demand for professionals possessing enormous AI capabilities and suitable professional degrees is much higher than the availability.

Even those who have studied AI in their college, don’t always possess mastery in this area. The lack of resources and suitable infrastructure are two prominent reasons for the same. However, sometimes those who self-learn from resources such as books, online courses, etc. develop better AI capabilities than their college-educated counterparts. This gives rise to the very important question, “How to determine whether a candidate possesses the skills required to become a true AI deployment asset?”

Here are the crucial skills that are needed for successful AI deployment.

1. Abilities to learn, adapt and match strides with the advancements happening in the field of AI

Technology is ever-evolving and AI is no exception. The secret to being competitive in this highly technological and evolving world is to upgrade yourself consistently. Similarly, if your organization aspires to excel in the field of AI deployment, it should be equipped with AI professionals who possess the ability to learn, adapt and match strides with the advancements happening in the field of AI. New algorithms, tools, strategies keep emerging in the field of Artificial Intelligence.

If your competitors use the latest algorithms but your AI team doesn’t possess the caliber to learn and use them, obviously you’ll lag behind. Having said that, you should examine whether a new hire or the members of your AI team possess self-improvement and consistent learning skills. Now, the question that arises here is how to examine the learning abilities of a candidate? The following are some pointers to help you with that.

a. Determine the additional certifications a candidate has achieved

One of the clearest indicators of a candidate’s learning abilities is the additional certifications he has achieved. Only those who are passionate about learning to undertake the journey of learning additional skills. A majority of individuals only learn what is taught to them in college and expect to get hired on that basis. But, passionate learners don’t stop at college learning, they expand their skills and obtain a clear edge over their competitors.

b. Examine their willingness to accept others’ opinions

Those who possess good learning abilities are open to accepting others’ opinions. They don’t get fixated on their opinions and beliefs. They stay open to new ideas, perspectives and are willing to change their opinions if they learn something new. To evaluate the willingness of a candidate to consider others’ opinions, you can ask him some questions.

One example of such a question is, “Have you ever had a disagreement with a team member? If yes, what did you do or how did you deal with it?” Further, when it comes to your existing AI team, you can determine the willingness of your employees to learn by carefully watching how they deal with disagreements or how they respond when you try to teach them something new.

c. Ask about future endeavors

This is one of the best ways to determine someone’s passion for learning. Ask about his future endeavors. If those consist of something to learn or gain expertise at, the candidate or team member is definitely dedicated to the expansion of his knowledge.

2. Industry expertise with domain and sector knowledge

Along with excellent knowledge of AI operations, algorithms and tools, there is something else that your AI deployment team will need to succeed. It is- industry expertise with domain and sector knowledge. It is only when your AI experts have significant knowledge of your industry and domain that they can devise accurate algorithms to bolster your business. Without proper knowledge of your domain and sector, their algorithms might be more complex than required.

Insensitive sectors such as healthcare, these complexities can even be dangerous. Errors and misinterpretations can put people’s lives at risk. Given that, it is best to hire those AI experts who know your industry and the intricacies involved in your domain properly. Even if they don’t, it will come down to their learning ability when it comes to being a great fit for your AI deployment team. A good learner possesses the capabilities to learn effectively and excel under any circumstances.

3. Governance skills

AI bias is one of the major issues that need to be addressed when it comes to AI deployment. For example, it is crucial that the identity verification processes work well without any discrepancies for everyone without any bias based on gender, race, religion, ethnicity, etc. If AI biases exist in your products, services, or other machine tools, it is obviously unfortunate and may take your organization downhill rather than uphill.

To minimize AI bias, it is important for AI teams to possess governance skills. Also, AI teams can use governance framework tools to enhance their decision-making skills and get rid of all biasing tendencies. The success of AI in the future depends on to what extent discriminatory and biasing tendencies can be eradicated. Given that, your AI deployment team should be well versed with AI bias and possess governance skills.

4. Communication skills

AI deployment teams should possess excellent communication skills. Why is that so? Good communication is what helps team members interact effectively and produce the desired results together. Imagine, if your AI team lacks effective communication, can it’s functioning ever be smooth? The answer is obviously a big no.

Strategic planning, discussion, and nearly everything require good communication skills. Moreover, everyone doesn’t possess technical expertise in AI. Given that, when interacting with your clients or non-technical members of the team, AI engineers should be able to explain things to them in a non-technical yet well-understandable manner.

That is why your AI deployment team should possess excellent communication skills. You should definitely analyze a candidate’s communication skills before recruiting him. Even if they doesn’t possess good communication skills, but have good knowledge of AI and an ability to learn quickly, you can work on enhancing their communication skills after hiring them.

5. Thorough knowledge of compliance practices

Artificial intelligence is a tremendous technology. It has a vast wingspan with immense possibilities. If the usage of AI is not bound by certain rules and regulations it can pose a huge risk to individuals, groups, and even society. AI can even violate the basic rights of individuals. For example, resume screening based on AI tools that are biased towards certain backgrounds and religions may definitely pose a threat to individuals from minority groups.

Given that, it is essential to bind the usage of AI with certain rules. Authoritative rules come in multiple forms. There are international laws, country laws, and regulations set by companies on their own. Your AI deployment team should possess thorough technical knowledge of compliance practices. It is with this knowledge that they can help you stay secure legally when it comes to the usage of AI.

Conclusion

Artificial intelligence has become one of the trending technologies in the business world today. To make the most of this awe-inspiring technology, it is crucial for you to build a skillful AI deployment team. For this, you should know exactly what skills do AI deployment engineers need to possess to function effectively. This article contains the most important skills required for successful AI deployment. Don’t forget to consider them when hiring AI engineers. 

Tags: AI
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