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AI/ML product manager on how small businesses can implement artificial intelligence without huge expenses

Anastasiia Prydius: "Adapting ready-made AI models reduces startup investments by two to three times"

byAytun Çelebi
December 15, 2024
in Conversations

According to a survey conducted by the leading international technology consulting company Accenture, approximately 53% of small and medium-sized enterprises found that the initial cost of implementing AI was much higher than expected. Working with complex AI algorithms requires not only the software itself but also compatible hardware, including high-performance servers, powerful processors, and data storage updates.

AI/ML product manager on how small businesses can implement artificial intelligence without huge expenses

However, with the development of technology, businesses can find an optimal solution for streamlining their workflows without huge costs, believes AI/ML product manager Anastasiia Prydius. The expert has successfully implemented business process automation projects using artificial intelligence in the USA, Europe, and Ukraine. Among other achievements, Anastasiia worked at Vertamedia, a company that was listed in the Inc. 5000 and Deloitte 500 rankings for its success in developing and implementing SaaS solutions. She also developed a unique AI solution for Socket Mobile. Drawing on her years of experience, she believes that implementing AI in business can be affordable if existing solutions are adapted rather than creating a unique product from scratch. Her project, Excelinsight, helps save money while still scaling up operations.

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In an interview with expert Anastasiia Prydius, we explored the question of how to optimize processes with artificial intelligence without going bankrupt.

Anastasiia, is it true that the costs of implementing AI in business are expensive for entrepreneurs? Or is it possible to optimize processes without spending too much?

Implementing AI can be costly. For example, building a complex model from scratch can cost hundreds of thousands of dollars due to the need for highly skilled specialists and powerful computing resources.

However, there are alternatives. One of the key ways to optimize costs is by adapting already existing AI models. This can reduce initial investments by two to three times, as it doesn’t require lengthy research and development stages. Moreover, choosing ready-made solutions that can be customized for the specific needs of a business allows for quicker results.

For instance, our work with leading mobile scanner manufacturer Socket Mobile showed that adapting existing algorithms and integrating them into the company’s existing ecosystem significantly reduced both time and costs. This confirms that AI can be implemented effectively even without huge capital investments.

In collaboration with Socket Mobile, a leading global provider of data capture and transmission solutions, you were able to set up an intelligent customer support system and provide real-time assistance. Could you tell us more about the results achieved in this project?

We developed a tool with a powerful server and client-side component that utilizes advanced AI algorithms and natural language processing (NLP) technologies. It provides relevant recommendations, guides, and automated responses, specifically tailored to support software developers.

Additionally, we ensured seamless integration with Socket Mobile’s existing technological infrastructure and support platform. This allowed the AI system to operate smoothly within the established workflows. The integration also gave the tool access to data and resources from Socket Mobile’s systems, enhancing its ability to provide contextual assistance and predictive analytics. As a result, we created a highly efficient and adaptive support system that anticipates developers’ needs and helps resolve technical issues more quickly.

 This company is a major player in the market, but let’s go back to small and medium-sized businesses. Is it possible to save money by implementing AI in processes through SaaS solutions like your Excelinsight project? How does this work in practice?

SaaS solutions provide companies with access to powerful tools that were once only available to large corporations. For example, Excelinsight offers businesses the ability to integrate data, analyze it, and generate insights using cloud technologies. In practice, this looks like us working with clients to tailor our solution to their unique needs. The configuration process minimizes implementation time, and support during the setup phase allows them to quickly start using AI for strategic planning and process optimization.

For small businesses, this is especially beneficial, as it allows them to use only the necessary features and scale them as they grow. For example, for the financial sector, we helped automate the processing of reports and contracts, and for marketing, we optimized the marketing budget management process. In both cases, implementing SaaS delivered results faster and cheaper than building from scratch.

According to feedback from your clients, your Excelinsight project gives companies 30-40% more time for strategic planning and helps save money in the long run. What about the initial investments?

Excelinsight was specifically developed with a focus on minimizing initial costs. These costs primarily involve the initial configuration of the platform to address a company’s specific needs. This is significantly cheaper than building a custom solution. Clients have mentioned that the money spent on setup pays off within the first few months of use. Moreover, it gives them a competitive edge because they can focus on strategic tasks rather than getting bogged down in routine work.

In addition to your professional solutions that help businesses optimize processes with AI, you are also a member of Women in Technology and Women in Product, supporting women in IT. What is it like to be a leader in the field of technology and artificial intelligence, inspiring women to participate in this industry?

Gender inequality in the IT industry remains a serious issue. For example, in the US, less than 23% of women work in technology, and their salaries are about 3.5 times lower than those of men. The situation in Ukraine is similar, with a lack of transparency regarding salaries and career opportunities.

As a member of communities like Women in Technology and Women in Product, I strive to support women, share my experience, and create a space where they can grow and develop. This is important not only to help women in their careers but also for the entire tech sector, as diversity and inclusivity lead to greater innovation. We not only inspire each other but also actively work on creating equal opportunities that will help women reach leadership positions in IT and AI.


Featured image credit: Freepik

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