Taking the leap and integrating AI into your business strategy is no small feat.

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The process might be long and progressive.

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After all, it takes a lot of effort and introspection regarding where your brand is headed and what you hope to achieve.

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But it is not a process you need to undergo alone. Actually, you should not be doing it alone.

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Building the right team is essential to making AI incorporation a reality.

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But exactly what roles make up the perfect AI team?

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The data scientist

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Data scientists are the backbone of any AI team. 

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They are responsible for collecting, analyzing, and interpreting complex data to inform decisions. They use statistical methods and algorithms to extract insights from data, 

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It’s these insights that help develop predictive models.

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Data scientists help identify patterns and trends useful to craft solutions and strategies.

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They’re the brains. Experts in data manipulation, statistical analysis, and machine learning algorithms.

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The machine learning engineer

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Machine learning engineers design, build, and deploy machine learning models. 

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They bridge the gap between data scientists and the operational implementation of AI models. They ensure that AI models are scalable and efficient. 

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These engineers are responsible for writing the algorithms and code that allow machines to learn from data. 

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Without their skills, the theoretical models are just theory.

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Programming languages like Python, R, and Java. Machine learning frameworks like TensorFlow and PyTorch. Those are the tools that turn data into practical applications.

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The data engineer

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Data engineers develop, build, test, and maintain databases and large-scale processing systems. They make sure data flows smoothly from source to destination.

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Without clean, organized, and accessible data, even the best AI models fail.

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Data engineers manage and optimize the structures, so that data is available in the right format and quality. 

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They work closely with data scientists to provide the necessary infrastructure and tools. Thanks to them, the data used by AI models is reliable and up-to-date.

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The AI researcher

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AI researchers look for new ways of advancing the field of AI.

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New algorithms. New theories. New models. Pushing the boundaries.

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They search for and come up with innovative approaches and technologies to solve any business issues that arise.

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They look for new avenues to explore, which means they help ensure your company remains competitive and leads the way into the future.

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The DevOps engineer

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DevOps engineers work on maintaining AI systems and providing them with the necessary infrastructure. They make sure the context they’re deployed in can handle all its functions.

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Models need to be integrated into existing systems and monitored. These engineers guarantee that AI solutions are scalable, reliable, and secure.

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Their skills help AI models perform well in real-world scenarios.

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The UX/UI designer

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UX/UI designers create user-friendly interfaces for AI-powered applications. For AI solutions to be effective, they must be accessible and intuitive for users. 

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They make sure that AI applications are designed with the end-user in mind. They recognize that every element a user encounters needs to be easy. Only then is it likely for them to adopt the technology. 

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UX/UI designers’ work enhances the overall usability and user satisfaction of AI products.

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The outsiders

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While they do not form part of the AI team in itself, it is always important to have people from other areas working closely with it.

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Project managers. Business analysts. Marketers. Salespeople. Communicators.

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These outsiders give the tech wizards a business perspective. They bridge the gap between the technical and the business sides of the organization. 

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Translating technical insights into actionable business strategies. Informing the team of specific pain points in their areas. Getting glimpses of what’s coming and anticipating how to integrate any new features into the company’s overall strategy. Ensuring delivery is on time and within budget.

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All these tasks shouldn’t be an afterthought once the AI product is ready. They should guide the AI team’s efforts to smoothen all operations.

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And the list goes on and on

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There’s always space for one more role. There could be as many employees as there are AI functions.

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But a strong AI team is one that has all the bases covered to create the most innovative solutions, develop the necessary technology, guarantee they run smoothly, and push toward the business’ goals.

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As your use of AI evolves, you’ll need more specific talent (such as LLM and NLP experts).

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So stay sharp and sensitive to what your company needs. Before you know it, you’ll be leading the charge into the AI future.

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For more insights into the world of AI and the necessary infrastructure behind it, check out this week’s episode of TOP CEO, featuring Smartling’s CEO!

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Ever thought about creating your own thought leadership content? At TOP Thought Leader, we amplify new and established voices so they can become pioneers of their generation. Get in touch with us and embark on your journey!