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From AI-based chatbots to automatic tools that analyze user behavior and maximize engagement — the 2023 business outlook establishes AI as an enterprise necessity in the current business environment.

Soon, companies will be looking to eliminate the dependency on data scientists as middlemen by adopting technologies that incorporate low-code extensibility, and intuitive user experiences, lowering the bar for people with no technical background, said Omri Orgad, Chief Customer Officer at Bright Data.

In order to train emerging AI models on larger datasets, enterprises must have access to the world’s largest up-to-date database in the history of mankind, the internet, as public web data is vital for AI models to be trained on diverse sets of frequently updated information and examples. OpenAI’s ChatGPT’s success, for instance, derives from being fed a large public dataset of text scraped from online websites, blogs, articles and forums.

While businesses can attempt to scrape public web data independently, it is a time-consuming and tedious endeavor requiring a large amount of resources. On average, companies spend 78% of data collection budgets on data specialists who spend most of their time developing the necessary architecture. Once collected, the data still needs to be structured and then analyzed, as missing or inaccurate data could affect the performance and accuracy of AI models.

With the new advancements in web data collection technology that simplifies collecting and structuring public web data, any company big or small can get their hands on qualified data to train their machines without having a full-blown data operation in place, according to

Prepared to dive into the world of futuristic technology? Attend INNOTECH 2023, the international convention and exhibition for cyber, HLS and innovation at Expo, Tel Aviv, on March 29th-30th

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